MACD Volume S2 By Gammaprod>> How to use this indicator :
1. Set your teadingview theme to dark theme.
2. My indicator is valid for forex, stock and but more valid for crypto.
3. Use three timeframe for more validation (choose between those, that fit to your trading style) :
- Timeframe 1m, 5m, and 15m for Scalping
- Timeframe 30m, 1h and 4h for Intraday
- Timeframe 4h, 1D and 1W for Swing Trading
4 . Always use THREE INDICATORS FROM GAMMAPROD, those three indicators is back to back each other, by the way, I only made those three indicators only (for now) :
- Trendlines Boll Ichi Crypto by Gammaprod
- Stoch RSI Divs Zone Crypto by Gammaprod
- MACD Volume Crypto by Gammaprod
>> How to setting :
1. Trendlines Boll Ichi Crypto by Gammaprod
A. Support and Resistence
- Well if you familiar with this indicator you can add it, but recommended for Timeframe 30m or more
B. Trendlines Primary or Trendlines Secondary
- Timeframe 1m you DON'T NEED Trendlines Primary or Trendlines Secondary
- Timeframe 5m you DON'T NEED Trendlines Secondary, but you CAN ADD Trendlines Primary if you fell it helpful (for me, it is helpful to find where the candles start or the end trend or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 15m you DON'T NEED Trendlines Secondary, DEFENITELY add Trendlines Primary it will help to find where the candles stop or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 30m or more, DEFENITELY NEED BOTH Trendlines Primary and Secondary Trendlines, it will help to find where the candle stop or consolidation or where the candle will surpass a resistance or support).
C. Bolinger, Ichimoku Cloud and Lagging Span
- Please DON'T CHANGE IT at all, it's really helpful to know when and where to make an entry decesion or a trend or a consolidation, if you don't understand how to read it, you better to learn it first (on "how to read" section and "How to OPEN position" the section below)
2. Stoch RSI Divs Zone Crypto by Gammaprod (DON'T CHANGE IT)
3. MACD Volume Crypto by Gammaprod (DON'T CHANGE IT)
>> How to read :
1. Sell or Buy Priority :
A. Buy Priority
- Color background on macd and stoch rsi is pink or purple sell is the priority, (if you're not sure to buy, just wait until the best moment to sell)
B. Buy Priority
- Color background on macd and stoch rsi Teal or light green buy is the priority, (if you're not sure to sell, just wait until the best moment to buy)
C. Indecision / Golden Moment
- Color background on stoch rsi yellow is indecision / golden moment of reversal pattern (wait until it formed background only on Stoch RSI), please becareful at this moment.
2. Trend / Consolidation :
A. BULLISH trend
- When Stoch RSI and MACD have teal or light green background that's means BULLISH trend, better to confirm by the candle is above green cloud and lagging span (red line) is also above the candle.
B. BEARISH trend
- When Stoch RSI and MACD have the Pink or purple background that's means BEARISH trend, better to confirm by the candle is above purple cloud and lagging span (red line) is also below the candle.
C. CONSOLIDATION
- When Stoch RSI have the mix background that's means CONSOLIDATION, better to confirm by the candle is in or near to green / purple cloud and lagging span (red line) is also on the candle.
3. Special Mark
A. Ideal Bullish :
- Near line 20 and green / teal background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for buy
B. Not an Ideal Bullish :
- Near line 80 and green / teal background = if this happens make sure you know what happen, it could be a false signal or bullish continual pattern
C. Ideal Bearish :
- Near line 80 and pink / purple background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for sell position.
D. Not an Ideal Bearish:
- Near line 20 and pink / purple background = if this happens make sure you know what happen, it could be a false signal or bearish continual pattern
E. The Beginning of Reversal (from BEARISH to BULLISH) :
- When Stoch RSI line shaping GREEN position is near 20.
- MACD lines still PINK, position lines is UNDER the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL PINK (light pink) and the BACKGROUND still PINK / PURPLE.
- Position CANDLES NEAR BLUE line, NEAR PURPLE CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
F. The Beginning of Reversal (from BULLISH to BEARISH) :
- When Stoch RSI line shaping PINK position is near 80.
- MACD lines still GREEN, position lines is ABOVE the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL GREEN (light green) and the BACKGROUND still TEAL / GREEN.
- Position CANDLES NEAR WHITE line, NEAR TEAL CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
G. False Signals, or It could be a Golden Moment (better to see it on TF 15 or bigger):
- Near line 20 or 80 and yellow background = When Stoch RSI have the char R / H on color label, that's means divergence or hidden divergence for buy / sell position, if you not see this label that's means just a standard confirmation for buy / sell depends on where the Stoch RSI line if near 20 that's means buy, near 80 means sell
>> How to OPEN position:
A. Bullish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles above the green cloud.
- Lagging span (red line) above the candles.
- then open buy near yellow line (the first option) / blue line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Teal or Green background.
- The lines is shaping green.
- Better if on the bottom (at a range 20).
3. MACD Volume Crypto by Gammaprod
- Teal or Green background.
- The lines is shaped or shaping green.
- Better if at the green histogram.
B. Bearish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles below the purple cloud.
- Lagging span (red line) below the candles.
- then open buy near yellow line (the first option) / white line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Pink or purple background.
- The lines are shaping pink.
- Better if the line on the top (at a range 80).
3. MACD Volume Crypto by Gammaprod
- Pink or purple background.
- The lines are shaped or shaping green.
- Better if at the pink histogram.
C. Consolidation
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles on the cloud (green or purple).
- Lagging span (red line) on the candles.
- then open buy near the white or blue line (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Mix background specially on a timeframe 15m or more.
- The line move fast up and down.
- Better if on the bottom or the top of the lines (at a range 20 or 80).
3. MACD Volume Crypto by Gammaprod
- Changing the background.
- The line is near the middle line.
- Have small Histogram.
>> The secret ingridient is comparing the timeframe :
The example scalping (Timeframe 1m, 5m and 15m)
- TF 1m is for making an open position.
- TF 5m is for making a judgement of the trend market.
- TF 15m is to confirm that judgement from TF 5m, be careful if it not similar then it used to be a consolidation or the beginning of the reversal.
There's a lot a way to open the position than above information that i gave it to you, but consider there are a limit char on this column, I hope it will help your trading and make a more profit on it.
Recherche dans les scripts pour "股价在8元左右净利润为正市值小于80亿的热门股票有哪些"
Stoch RSI, Div, Zone S3 by Gammaprod>> How to use this indicator :
1. Set your teadingview theme to dark theme.
2. My indicator is valid for forex, stock and but more valid for crypto.
3. Use three timeframe for more validation (choose between those, that fit to your trading style) :
- Timeframe 1m, 5m, and 15m for Scalping
- Timeframe 30m, 1h and 4h for Intraday
- Timeframe 4h, 1D and 1W for Swing Trading
4 . Always use THREE INDICATORS FROM GAMMAPROD, those three indicators is back to back each other, by the way, I only made those three indicators only (for now) :
- Trendlines Boll Ichi Crypto by Gammaprod
- Stoch RSI Divs Zone Crypto by Gammaprod
- MACD Volume Crypto by Gammaprod
>> How to setting :
1. Trendlines Boll Ichi Crypto by Gammaprod
A. Support and Resistence
- Well if you familiar with this indicator you can add it, but recommended for Timeframe 30m or more
B. Trendlines Primary or Trendlines Secondary
- Timeframe 1m you DON'T NEED Trendlines Primary or Trendlines Secondary
- Timeframe 5m you DON'T NEED Trendlines Secondary, but you CAN ADD Trendlines Primary if you fell it helpful (for me, it is helpful to find where the candles start or the end trend or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 15m you DON'T NEED Trendlines Secondary, DEFENITELY add Trendlines Primary it will help to find where the candles stop or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 30m or more, DEFENITELY NEED BOTH Trendlines Primary and Secondary Trendlines, it will help to find where the candle stop or consolidation or where the candle will surpass a resistance or support).
C. Bolinger, Ichimoku Cloud and Lagging Span
- Please DON'T CHANGE IT at all, it's really helpful to know when and where to make an entry decesion or a trend or a consolidation, if you don't understand how to read it, you better to learn it first (on "how to read" section and "How to OPEN position" the section below)
2. Stoch RSI Divs Zone Crypto by Gammaprod (DON'T CHANGE IT)
3. MACD Volume Crypto by Gammaprod (DON'T CHANGE IT)
>> How to read :
1. Sell or Buy Priority :
A. Buy Priority
- Color background on macd and stoch rsi is pink or purple sell is the priority, (if you're not sure to buy, just wait until the best moment to sell)
B. Buy Priority
- Color background on macd and stoch rsi Teal or light green buy is the priority, (if you're not sure to sell, just wait until the best moment to buy)
C. Indecision / Golden Moment
- Color background on stoch rsi yellow is indecision / golden moment of reversal pattern (wait until it formed background only on Stoch RSI), please becareful at this moment.
2. Trend / Consolidation :
A. BULLISH trend
- When Stoch RSI and MACD have teal or light green background that's means BULLISH trend, better to confirm by the candle is above green cloud and lagging span (red line) is also above the candle.
B. BEARISH trend
- When Stoch RSI and MACD have the Pink or purple background that's means BEARISH trend, better to confirm by the candle is above purple cloud and lagging span (red line) is also below the candle.
C. CONSOLIDATION
- When Stoch RSI have the mix background that's means CONSOLIDATION, better to confirm by the candle is in or near to green / purple cloud and lagging span (red line) is also on the candle.
3. Special Mark
A. Ideal Bullish :
- Near line 20 and green / teal background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for buy
B. Not an Ideal Bullish :
- Near line 80 and green / teal background = if this happens make sure you know what happen, it could be a false signal or bullish continual pattern
C. Ideal Bearish :
- Near line 80 and pink / purple background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for sell position.
D. Not an Ideal Bearish:
- Near line 20 and pink / purple background = if this happens make sure you know what happen, it could be a false signal or bearish continual pattern
E. The Beginning of Reversal (from BEARISH to BULLISH) :
- When Stoch RSI line shaping GREEN position is near 20.
- MACD lines still PINK, position lines is UNDER the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL PINK (light pink) and the BACKGROUND still PINK / PURPLE.
- Position CANDLES NEAR BLUE line, NEAR PURPLE CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
F. The Beginning of Reversal (from BULLISH to BEARISH) :
- When Stoch RSI line shaping PINK position is near 80.
- MACD lines still GREEN, position lines is ABOVE the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL GREEN (light green) and the BACKGROUND still TEAL / GREEN.
- Position CANDLES NEAR WHITE line, NEAR TEAL CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
G. False Signals, or It could be a Golden Moment (better to see it on TF 15 or bigger):
- Near line 20 or 80 and yellow background = When Stoch RSI have the char R / H on color label, that's means divergence or hidden divergence for buy / sell position, if you not see this label that's means just a standard confirmation for buy / sell depends on where the Stoch RSI line if near 20 that's means buy, near 80 means sell
>> How to OPEN position:
A. Bullish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles above the green cloud.
- Lagging span (red line) above the candles.
- then open buy near yellow line (the first option) / blue line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Teal or Green background.
- The lines is shaping green.
- Better if on the bottom (at a range 20).
3. MACD Volume Crypto by Gammaprod
- Teal or Green background.
- The lines is shaped or shaping green.
- Better if at the green histogram.
B. Bearish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles below the purple cloud.
- Lagging span (red line) below the candles.
- then open buy near yellow line (the first option) / white line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Pink or purple background.
- The lines are shaping pink.
- Better if the line on the top (at a range 80).
3. MACD Volume Crypto by Gammaprod
- Pink or purple background.
- The lines are shaped or shaping green.
- Better if at the pink histogram.
C. Consolidation
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles on the cloud (green or purple).
- Lagging span (red line) on the candles.
- then open buy near the white or blue line (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Mix background specially on a timeframe 15m or more.
- The line move fast up and down.
- Better if on the bottom or the top of the lines (at a range 20 or 80).
3. MACD Volume Crypto by Gammaprod
- Changing the background.
- The line is near the middle line.
- Have small Histogram.
>> The secret ingridient is comparing the timeframe :
The example scalping (Timeframe 1m, 5m and 15m)
- TF 1m is for making an open position.
- TF 5m is for making a judgement of the trend market.
- TF 15m is to confirm that judgement from TF 5m, be careful if it not similar then it used to be a consolidation or the beginning of the reversal.
There's a lot a way to open the position than above information that i gave it to you, but consider there are a limit char on this column, I hope it will help your trading and make a more profit on it.
Multi-TF Trend Table (Configurable)1) What this tool does (in one minute)
A compact, multi‑timeframe dashboard that stacks eight timeframes and tells you:
Trend (fast MA vs slow MA)
Where price sits relative to those MAs
How far price is from the fast MA in ATR terms
MA slope (rising, falling, flat)
Stochastic %K (with overbought/oversold heat)
MACD momentum (up or down)
A single score (0%–100%) per timeframe
Alignment tick when trend, structure, slope and momentum all agree
Use it to:
Frame bias top‑down (M→W→D→…→15m)
Time entries on your execution timeframe when the higher‑TF stack is aligned
Avoid counter‑trend traps when the table is mixed
2) Table anatomy (each column explained)
The table renders 9 columns × 8 rows (one row per timeframe label you define).
TF — The label you chose for that row (e.g., Month, Week, 4H). Cosmetic; helps you read the stack.
Trend — Arrow from fast MA vs slow MA: ↑ if fastMA > slowMA (up‑trend), ↓ otherwise (down‑trend). Cell is green for up, red for down.
Price Pos — One‑character structure cue:
🔼 if price is above both fast and slow MAs (bullish structure)
🔽 if price is below both (bearish structure)
– otherwise (between MAs / mixed)
MA Dist — Distance of price from the fast MA measured in ATR multiples:
XS < S < M < L < XL according to your thresholds (see §3.3). Useful for judging stretch/mean‑reversion risk and stop sizing.
MA Slope — The fast MA one‑bar slope:
↑ if fastMA - fastMA > 0
↓ if < 0
→ if = 0
Stoch %K — Rounded %K value (default 14‑1‑3). Background highlights when it aligns with the trend:
Green heat when trend up and %K ≤ oversold
Red heat when trend down and %K ≥ overbought Tooltip shows K and D values precisely.
Trend % — Composite score (0–100%), the dashboard’s confidence for that timeframe:
+20 if trendUp (fast>slow)
+20 if fast MA slope > 0
+20 if MACD up (signal definition in §2.8)
+20 if price above fast MA
+20 if price above slow MA
Background colours:
≥80 lime (strong alignment)
≥60 green (good)
≥40 orange (mixed)
<40 grey (weak/contrary)
MACD — 🟢 if EMA(12)−EMA(26) > its EMA(9), else 🔴. It’s a simple “momentum up/down” proxy.
Align — ✔ when everything is in gear for that trend direction:
For up: trendUp and price above both MAs and slope>0 and MACD up
For down: trendDown and price below both MAs and slope<0 and MACD down Tooltip spells this out.
3) Settings & how to tune them
3.1 Timeframes (TF1–TF8)
Inputs: TF1..TF8 hold the resolution strings used by request.security().
Defaults: M, W, D, 720, 480, 240, 60, 15 with display labels Month, Week, Day, 12H, 8H, 4H, 1H, 15m.
Tips
Keep a top‑down funnel (e.g., Month→Week→Day→H4→H1→M15) so you can cascade bias into entries.
If you scalp, consider D, 240, 120, 60, 30, 15, 5, 1.
Crypto weekends: consider 2D in place of W to reflect continuous trading.
3.2 Moving Average (MA) group
Type: EMA, SMA, WMA, RMA, HMA. Changes both fast & slow MA computations everywhere.
Fast Length: default 20. Shorten for snappier trend/slope & tighter “price above fast” signals.
Slow Length: default 200. Controls the structural trend and part of the score.
When to change
Swing FX/equities: EMA 20/200 is a solid baseline.
Mean‑reversion style: consider SMA 20/100 so trend flips slower.
Crypto/indices momentum: HMA 21 / EMA 200 will read slope more responsively.
3.3 ATR / Distance group
ATR Length: default 14; longer makes distance less jumpy.
XS/S/M/L thresholds: define the labels in column MA Dist. They are compared to |close − fastMA| / ATR.
Defaults: XS 0.25×, S 0.75×, M 1.5×, L 2.5×; anything ≥L is XL.
Usage
Entries late in a move often occur at L/XL; consider waiting for a pullback unless you are trading breakouts.
For stops, an initial SL around 0.75–1.5 ATR from fast MA often sits behind nearby noise; use your plan.
3.4 Stochastic group
%K Length / Smoothing / %D Smoothing: defaults 14 / 1 / 3.
Overbought / Oversold: defaults 70 / 30 (adjust to 80/20 for trendier assets).
Heat logic (column Stoch %K): highlights when a pullback aligns with the dominant trend (oversold in an uptrend, overbought in a downtrend).
3.5 View
Full Screen Table Mode: centers and enlarges the table (position.middle_center). Great for clean screenshots or multi‑monitor setups.
4) Signal logic (how each datapoint is computed)
Per‑TF data (via a single request.security()):
fastMA, slowMA → based on your MA Type and lengths
%K, %D → Stoch(High,Low,Close,kLen) smoothed by kSmooth, then %D smoothed by dSmooth
close, ATR(atrLen) → for structure and distance
MACD up → (EMA12−EMA26) > EMA9(EMA12−EMA26)
fastMA_prev → yesterday/previous‑bar fast MA for slope
TrendUp → fastMA > slowMA
Price Position → compares close to both MAs
MA Distance Label → thresholds on abs(close − fastMA)/ATR
Slope → fastMA − fastMA
Score (0–100) → sum of the five 20‑point checks listed in §2.7
Align tick → conjunction of trend, price vs both MAs, slope and MACD (see §2.9)
Important behaviour
HTF values are sampled at the execution chart’s bar close using Pine v6 defaults (no lookahead). So the daily row updates only when a daily bar actually closes.
5) How to trade with it (playbooks)
The table is a framework. Entries/exits still follow your plan (e.g., S/D zones, price action, risk rules). Use the table to know when to be aggressive vs patient.
Playbook A — Trend continuation (pullback entry)
Look for Align ✔ on your anchor TFs (e.g., Week+Day both ≥80 and green, Trend ↑, MACD 🟢).
On your execution TF (e.g., H1/H4), wait for Stoch heat with the trend (oversold in uptrend or overbought in downtrend), and MA Dist not at XL.
Enter on your trigger (break of pullback high/low, engulfing, retest of fast MA, or S/D first touch per your plan).
Risk: consider ATR‑based SL beyond structure; size so 0.25–0.5% account risk fits your rules.
Trail or scale at M/L distances or when score deteriorates (<60).
Playbook B — Breakout with confirmation
Mixed stack turns into broad green: Trend % jumps to ≥80 on Day and H4; MACD flips 🟢.
Price Pos shows 🔼 across H4/H1 (above both MAs). Slope arrows ↑.
Enter on the first clean base‑break with volume/impulse; avoid if MA Dist already XL.
Playbook C — Mean‑reversion fade (advanced)
Use only when higher TFs are not aligned and the row you trade shows XL distance against the higher‑TF context. Take quick targets back to fast MA. Lower win‑rate, faster management.
Playbook D — Top‑down filter for Supply/Demand strategy
Trade first retests only in the direction where anchor TFs (Week/Day) have Align ✔ and Trend % ≥60. Skip counter‑trend zones when the stack is red/green against you.
6) Reading examples
Strong bullish stack
Week: ↑, 🔼, S/M, slope ↑, %K=32 (green heat), Trend 100%, MACD 🟢, Align ✔
Day: ↑, 🔼, XS/S, slope ↑, %K=45, Trend 80%, MACD 🟢, Align ✔
Action: Look for H4/H1 pullback into demand or fast MA; buy continuation.
Late‑stage thrust
H1: ↑, 🔼, XL, slope ↑, %K=88
Day/H4: only 60–80%
Action: Likely overextended on H1; wait for mean reversion or multi‑TF alignment before chasing.
Bearish transition
Day flips from 60%→40%, Trend ↓, MACD turns 🔴, Price Pos “–” (between MAs)
Action: Stand aside for longs; watch for lower‑high + Align ✔ on H4/H1 to join shorts.
7) Practical tips & pitfalls
HTF closure: Don’t assume a daily row changed mid‑day; it won’t settle until the daily bar closes. For intraday anticipation, watch H4/H1 rows.
MA Type consistency: Changing MA Type changes slope/structure everywhere. If you compare screenshots, keep the same type.
ATR thresholds: Calibrate per asset class. FX may suit defaults; indices/crypto might need wider S/M/L.
Score ≠ signal: 100% does not mean “must buy now.” It means the environment is favourable. Still execute your trigger.
Mixed stacks: When rows disagree, reduce size or skip. The tool is telling you the market lacks consensus.
8) Customisation ideas
Timeframe presets: Save layouts (e.g., Swing, Intraday, Scalper) as indicator templates in TradingView.
Alternative momentum: Replace the MACD condition with RSI(>50/<50) if desired (would require code edit).
Alerts: You can add alert conditions for (a) Align ✔ changes, (b) Trend % crossing 60/80, (c) Stoch heat events. (Not shipped in this script, but easy to add.)
9) FAQ
Q: Why do I sometimes see a dash in Price Pos? A: Price is between fast and slow MAs. Structure is mixed; seek clarity before acting.
Q: Does it repaint? A: No, higher‑TF values update on the close of their own bars (standard request.security behaviour without lookahead). Intra‑bar they can fluctuate; decisions should be made at your bar close per your plan.
Q: Which columns matter most? A: For trend‑following: Trend, Price Pos, Slope, MACD, then Stoch heat for entries. The Score summarises, and Align enforces discipline.
Q: How do I integrate with ATR‑based risk? A: Use the MA Dist label to avoid chasing at extremes and to size stops in ATR terms (e.g., SL behind structure at ~1–1.5 ATR).
Candle Breakout Oscillator [LuxAlgo]The Candle Breakout Oscillator tool allows traders to identify the strength and weakness of the three main market states: bullish, bearish, and choppy.
Know who controls the market at any given moment with an oscillator display with values ranging from 0 to 100 for the three main plots and upper and lower thresholds of 80 and 20 by default.
🔶 USAGE
The Candle Breakout Oscillator represents the three main market states, with values ranging from 0 to 100. By default, the upper and lower thresholds are set at 80 and 20, and when a value exceeds these thresholds, a colored area is displayed for the trader's convenience.
This tool is based on pure price action breakouts. In this context, we understand a breakout as a close above the last candle's high or low, which is representative of market strength. All other close positions in relation to the last candle's limits are considered weakness.
So, when the bullish plot (in green) is at the top of the oscillator (values above 80), it means that the bullish breakouts (close below the last candle low) are at their maximum value over the calculation window, indicating an uptrend. The same interpretation can be made for the bearish plot (in red), indicating a downtrend when high.
On the other hand, weakness is indicated when values are below the lower threshold (20), indicating that breakouts are at their minimum over the last 100 candles. Below are some examples of the possible main interpretations:
There are three main things to look for in this oscillator:
Value reaches extreme
Value leaves extreme
Bullish/Bearish crossovers
As we can see on the chart, before the first crossover happens the bears come out of strength (top) and the bulls come out of weakness (bottom), then after the crossover the bulls reach strength (top) and the bears weakness (bottom), this process is repeated in reverse for the second crossover.
The other main feature of the oscillator is its ability to identify periods of sideways trends when the sideways values have upper readings above 80, and trending behavior when the sideways values have lower readings below 20. As we just saw in the case of bullish vs. bearish, sideways values signal a change in behavior when reaching or leaving the extremes of the oscillator.
🔶 DETAILS
🔹 Data Smoothing
The tool offers up to 10 different smoothing methods. In the chart above, we can see the raw data (smoothing: None) and the RMA, TEMA, or Hull moving averages.
🔹 Data Weighting
Users can add different weighting methods to the data. As we can see in the image above, users can choose between None, Volume, or Price (as in Price Delta for each breakout).
🔶 SETTINGS
Window: Execution window, 100 candles by default
🔹 Data
Smoothing Method: Choose between none or ten moving averages
Smoothing Length: Length for the moving average
Weighting Method: Choose between None, Volume, or Price
🔹 Thresholds
Top: 80 by default
Bottom: 20 by default
ATM Option Selling StrategyATM Option Selling Strategy – Explained
This strategy is designed for intraday option selling based on the 9/15 EMA crossover, 50/80 MA trend filter, and RSI 50 level. It ensures that all trades are exited before market close (3:24 PM IST).
. Indicators Used:
9 EMA & 15 EMA → For short-term trend identification.
50 MA & 80 MA → To determine the overall trend.
RSI (14) → To confirm momentum (above or below 50 level).
2. Entry Conditions:
🔴 Sell ATM Call (CE) when:
Price is below 50 & 80 MA (Bearish trend).
9 EMA crosses below 15 EMA (Short-term trend turns bearish).
RSI is below 50 (Momentum confirms weakness).
🟢 Sell ATM Put (PE) when:
Price is above 50 & 80 MA (Bullish trend).
9 EMA crosses above 15 EMA (Short-term trend turns bullish).
RSI is above 50 (Momentum confirms strength).
3. Position Sizing & Risk Management:
Sell 375 quantity per trade (Lot size).
50-Point Stop Loss → If option premium moves against us by 50 points, exit.
50-Point Take Profit → If option premium moves in our favor by 50 points, book profit.
Exit all trades at 3:24 PM IST → No overnight positions.
4. Exit Conditions:
✅ Stop Loss or Take Profit Hits → Automatically exits based on a 50-point move.
✅ Time-Based Exit at 3:24 PM → Ensures no open positions at market close.
Why This Works?
✔ Trend Confirmation → 50/80 MA ensures we only sell options in the direction of the market trend.
✔ Momentum Confirmation → RSI prevents entering weak trades.
✔ Controlled Risk → SL and TP protect against large losses.
✔ No Overnight Risk → All trades close before market close.
Money Flow ExtendedMoney Flow Extended (MF)
Definition
The Money Flow Extended (MF) indicator brings together the functionality of the Money Flow Index indicator (MFI) , a tool created by Gene Quong and Avrum Soudack and used in technical analysis for measuring buying and selling pressure, and The Relative Strength Index (RSI) , a well versed momentum based oscillator created by J.Welles Wilder Jr., which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements.
History
As the Money Flow Index (MFI) is quite similar to The Relative Strength Index (RSI), essentially the RSI with the added aspect of volume, adding a Moving Average, divergence calculation, oversold and overbought gradients, facilitates the transition from RSI, making the use of MFI pretty similar.
What to look for
Overbought/Oversold
When momentum and price rise fast enough, at a high enough level, eventual the security will be considered overbought. The opposite is also true. When price and momentum fall far enough, they can be considered oversold. Traditional overbought territory starts above 80 and oversold territory starts below 20. These values are subjective however, and a technical analyst can set whichever thresholds they choose.
Divergence
MF Divergence occurs when there is a difference between what the price action is indicating and what MF is indicating. These differences can be interpreted as an impending reversal. Specifically, there are two types of divergences, bearish and bullish.
Bullish MFI Divergence – When price makes a new low but MF makes a higher low.
Bearish MFI Divergence – When price makes a new high but MF makes a lower high.
Failure Swings
Failure swings are another occurrence which can lead to a price reversal. One thing to keep in mind about failure swings is that they are completely independent of price and rely solely on MF. Failure swings consist of four steps and are considered to be either Bullish (buying opportunity) or Bearish (selling opportunity).
Bullish Failure Swing
MF drops below 20 (considered oversold).
MF bounces back above 20.
MF pulls back but remains above 20 (remains above oversold)
MF breaks out above its previous high.
Bearish Failure Swing
MF rises above 80 (considered overbought)
MF drops back below 80
MF rises slightly but remains below 80 (remains below overbought)
MF drops lower than its previous low.
Summary
The Money Flow Extended (MF) can be a very valuable technical analysis tool. Of course, MF should not be used alone as the sole source for a trader’s signals or setups. MF can be combined with additional indicators or chart pattern analysis to increase its effectiveness.
Inputs
Length
The time period to be used in calculating the MF. 14 is the default.
Pivot Loopback
After how many bars you want the divergence to show, on the scale of 1-5. 5 is the default.
Calculate Divergence
Calculating divergences is needed in order for divergence alerts to fire.
Moving Average section
You can learn more about the inputs in the "Moving Average" section in this Help Center article .
Style
MF
Can toggle the visibility of the MF as well as the visibility of a price line showing the actual current value of the MF. Can also select the MF Line's color, line thickness and visual style.
MF-based MA
Can toggle the visibility of the MF-based MA as well as the visibility of a price line showing the actual current MA value. Can also select its color, line thickness and line style.
MF Upper Band
Can toggle the visibility of the Upper Band as well as sets the boundary, on the scale of 1-100, for the Upper Band (80 is the default). The color, line thickness and line style can also be determined.
MF Middle Band
Can toggle the visibility of the Middle Band as well as sets the boundary, on the scale of 1-100, for the Middle Band (50 is the default). The color, line thickness and line style can also be determined.
MF Lower Band
Can toggle the visibility of the Lower Band as well as sets the boundary, on the scale of 1-100, for the Lower Band (20 is the default). The color, line thickness and line style can also be determined.
MF Background Fill
Toggles the visibility of a Background color within the MF's boundaries. Can also change the Color itself as well as the opacity.
Overbought Gradient Fill
Can toggle the visibility of the Overbought Gradient Fill. Can also select its colors combination.
Oversold Gradient Fill
Can toggle the visibility of the Oversold Gradient Fill. Can also select its colors combination.
Precision
Sets the number of decimal places to be left on the indicator's value before rounding up. The higher this number, the more decimal points will be on the indicator's value.
Multi-Timeframe Stochastic Alert [tradeviZion]# Multi-Timeframe Stochastic Alert : Complete User Guide
## 1. Introduction
### What is the Multi-Timeframe Stochastic Alert?
The Multi-Timeframe Stochastic Alert is an advanced technical analysis tool that helps traders identify potential trading opportunities by analyzing momentum across multiple timeframes. It combines the power of the stochastic oscillator with multi-timeframe analysis to provide more reliable trading signals.
### Key Features and Benefits
- Simultaneous analysis of 6 different timeframes
- Advanced alert system with customizable conditions
- Real-time visual feedback with color-coded signals
- Comprehensive data table with instant market insights
- Motivational trading messages for psychological support
- Flexible theme support for comfortable viewing
### How it Can Help Your Trading
- Identify stronger trends by confirming momentum across multiple timeframes
- Reduce false signals through multi-timeframe confirmation
- Stay informed of market changes with customizable alerts
- Make more informed decisions with comprehensive market data
- Maintain trading discipline with clear visual signals
## 2. Understanding the Display
### The Stochastic Chart
The main chart displays three key components:
1. ** K-Line (Fast) **: The primary stochastic line (default color: green)
2. ** D-Line (Slow) **: The signal line (default color: red)
3. ** Reference Lines **:
- Overbought Level (80): Upper dashed line
- Middle Line (50): Center dashed line
- Oversold Level (20): Lower dashed line
### The Information Table
The table provides a comprehensive view of stochastic readings across all timeframes. Here's what each column means:
#### Column Explanations:
1. ** Timeframe **
- Shows the time period for each row
- Example: "5" = 5 minutes, "15" = 15 minutes, etc.
2. ** K Value **
- The fast stochastic line value (0-100)
- Higher values indicate stronger upward momentum
- Lower values indicate stronger downward momentum
3. ** D Value **
- The slow stochastic line value (0-100)
- Helps confirm momentum direction
- Crossovers with K-line can signal potential trades
4. ** Status **
- Shows current momentum with symbols:
- ▲ = Increasing (bullish)
- ▼ = Decreasing (bearish)
- Color matches the trend direction
5. ** Trend **
- Shows the current market condition:
- "Overbought" (above 80)
- "Bullish" (above 50)
- "Bearish" (below 50)
- "Oversold" (below 20)
#### Row Explanations:
1. ** Title Row **
- Shows "🎯 Multi-Timeframe Stochastic"
- Indicates the indicator is active
2. ** Header Row **
- Contains column titles
- Dark blue background for easy reading
3. ** Timeframe Rows **
- Six rows showing different timeframe analyses
- Each row updates independently
- Color-coded for easy trend identification
4. **Message Row**
- Shows rotating motivational messages
- Updates every 5 bars
- Helps maintain trading discipline
### Visual Indicators and Colors
- ** Green Background **: Indicates bullish conditions
- ** Red Background **: Indicates bearish conditions
- ** Color Intensity **: Shows strength of the signal
- ** Background Highlights **: Appear when alert conditions are met
## 3. Core Settings Groups
### Stochastic Settings
These settings control the core calculation of the stochastic oscillator.
1. ** Length (Default: 14) **
- What it does: Determines the lookback period for calculations
- Higher values (e.g., 21): More stable, fewer signals
- Lower values (e.g., 8): More sensitive, more signals
- Recommended:
* Day Trading: 8-14
* Swing Trading: 14-21
* Position Trading: 21-30
2. ** Smooth K (Default: 3) **
- What it does: Smooths the main stochastic line
- Higher values: Smoother line, fewer false signals
- Lower values: More responsive, but more noise
- Recommended:
* Day Trading: 2-3
* Swing Trading: 3-5
* Position Trading: 5-7
3. ** Smooth D (Default: 3) **
- What it does: Smooths the signal line
- Works in conjunction with Smooth K
- Usually kept equal to or slightly higher than Smooth K
- Recommended: Keep same as Smooth K for consistency
4. ** Source (Default: Close) **
- What it does: Determines price data for calculations
- Options: Close, Open, High, Low, HL2, HLC3, OHLC4
- Recommended: Stick with Close for most reliable signals
### Timeframe Settings
Controls the multiple timeframes analyzed by the indicator.
1. ** Main Timeframes (TF1-TF6) **
- TF1 (Default: 10): Shortest timeframe for quick signals
- TF2 (Default: 15): Short-term trend confirmation
- TF3 (Default: 30): Medium-term trend analysis
- TF4 (Default: 30): Additional medium-term confirmation
- TF5 (Default: 60): Longer-term trend analysis
- TF6 (Default: 240): Major trend confirmation
Recommended Combinations:
* Scalping: 1, 3, 5, 15, 30, 60
* Day Trading: 5, 15, 30, 60, 240, D
* Swing Trading: 15, 60, 240, D, W, M
2. ** Wait for Bar Close (Default: true) **
- What it does: Controls when calculations update
- True: More reliable but slightly delayed signals
- False: Faster signals but may change before bar closes
- Recommended: Keep True for more reliable signals
### Alert Settings
#### Main Alert Settings
1. ** Enable Alerts (Default: true) **
- Master switch for all alert notifications
- Toggle this off when you don't want any alerts
- Useful during testing or when you want to focus on visual signals only
2. ** Alert Condition (Options) **
- "Above Middle": Bullish momentum alerts only
- "Below Middle": Bearish momentum alerts only
- "Both": Alerts for both directions
- Recommended:
* Trending Markets: Choose direction matching the trend
* Ranging Markets: Use "Both" to catch reversals
* New Traders: Start with "Both" until you develop a specific strategy
3. ** Alert Frequency **
- "Once Per Bar": Immediate alerts during the bar
- "Once Per Bar Close": Alerts only after bar closes
- Recommended:
* Day Trading: "Once Per Bar" for quick reactions
* Swing Trading: "Once Per Bar Close" for confirmed signals
* Beginners: "Once Per Bar Close" to reduce false signals
#### Timeframe Check Settings
1. ** First Check (TF1) **
- Purpose: Confirms basic trend direction
- Alert Triggers When:
* For Bullish: Stochastic is above middle line (50)
* For Bearish: Stochastic is below middle line (50)
* For Both: Triggers in either direction based on position relative to middle line
- Settings:
* Enable/Disable: Turn first check on/off
* Timeframe: Default 5 minutes
- Best Used For:
* Quick trend confirmation
* Entry timing
* Scalping setups
2. ** Second Check (TF2) **
- Purpose: Confirms both position and momentum
- Alert Triggers When:
* For Bullish: Stochastic is above middle line AND both K&D lines are increasing
* For Bearish: Stochastic is below middle line AND both K&D lines are decreasing
* For Both: Triggers based on position and direction matching current condition
- Settings:
* Enable/Disable: Turn second check on/off
* Timeframe: Default 15 minutes
- Best Used For:
* Trend strength confirmation
* Avoiding false breakouts
* Day trading setups
3. ** Third Check (TF3) **
- Purpose: Confirms overall momentum direction
- Alert Triggers When:
* For Bullish: Both K&D lines are increasing (momentum confirmation)
* For Bearish: Both K&D lines are decreasing (momentum confirmation)
* For Both: Triggers based on matching momentum direction
- Settings:
* Enable/Disable: Turn third check on/off
* Timeframe: Default 30 minutes
- Best Used For:
* Major trend confirmation
* Swing trading setups
* Avoiding trades against the main trend
Note: All three conditions must be met simultaneously for the alert to trigger. This multi-timeframe confirmation helps reduce false signals and provides stronger trade setups.
#### Alert Combinations Examples
1. ** Conservative Setup **
- Enable all three checks
- Use "Once Per Bar Close"
- Timeframe Selection Example:
* First Check: 15 minutes
* Second Check: 1 hour (60 minutes)
* Third Check: 4 hours (240 minutes)
- Wider gaps between timeframes reduce noise and false signals
- Best for: Swing trading, beginners
2. ** Aggressive Setup **
- Enable first two checks only
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
- Closer timeframes for quicker signals
- Best for: Day trading, experienced traders
3. ** Balanced Setup **
- Enable all checks
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
* Third Check: 1 hour (60 minutes)
- Balanced spacing between timeframes
- Best for: All-around trading
### Visual Settings
#### Alert Visual Settings
1. ** Show Background Color (Default: true) **
- What it does: Highlights chart background when alerts trigger
- Benefits:
* Makes signals more visible
* Helps spot opportunities quickly
* Provides visual confirmation of alerts
- When to disable:
* If using multiple indicators
* When preferring a cleaner chart
* During manual backtesting
2. ** Background Transparency (Default: 90) **
- Range: 0 (solid) to 100 (invisible)
- Recommended Settings:
* Clean Charts: 90-95
* Multiple Indicators: 85-90
* Single Indicator: 80-85
- Tip: Adjust based on your chart's overall visibility
3. ** Background Colors **
- Bullish Background:
* Default: Green
* Indicates upward momentum
* Customizable to match your theme
- Bearish Background:
* Default: Red
* Indicates downward momentum
* Customizable to match your theme
#### Level Settings
1. ** Oversold Level (Default: 20) **
- Traditional Setting: 20
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 10): More conservative
* Higher values (e.g., 30): More aggressive
- Trading Applications:
* Potential bullish reversal zone
* Support level in uptrends
* Entry point for long positions
2. ** Overbought Level (Default: 80) **
- Traditional Setting: 80
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 70): More aggressive
* Higher values (e.g., 90): More conservative
- Trading Applications:
* Potential bearish reversal zone
* Resistance level in downtrends
* Exit point for long positions
3. ** Middle Line (Default: 50) **
- Purpose: Trend direction separator
- Applications:
* Above 50: Bullish territory
* Below 50: Bearish territory
* Crossing 50: Potential trend change
- Trading Uses:
* Trend confirmation
* Entry/exit trigger
* Risk management level
#### Color Settings
1. ** Bullish Color (Default: Green) **
- Used for:
* K-Line (Main stochastic line)
* Status symbols when trending up
* Trend labels for bullish conditions
- Customization:
* Choose colors that stand out
* Match your trading platform theme
* Consider color blindness accessibility
2. ** Bearish Color (Default: Red) **
- Used for:
* D-Line (Signal line)
* Status symbols when trending down
* Trend labels for bearish conditions
- Customization:
* Choose contrasting colors
* Ensure visibility on your chart
* Consider monitor settings
3. ** Neutral Color (Default: Gray) **
- Used for:
* Middle line (50 level)
- Customization:
* Should be less prominent
* Easy on the eyes
* Good background contrast
### Theme Settings
1. **Color Theme Options**
- Dark Theme (Default):
* Dark background with white text
* Optimized for dark chart backgrounds
* Reduces eye strain in low light
- Light Theme:
* Light background with black text
* Better visibility in bright conditions
- Custom Theme:
* Use your own color preferences
2. ** Available Theme Colors **
- Table Background
- Table Text
- Table Headers
Note: The theme affects only the table display colors. The stochastic lines and alert backgrounds use their own color settings.
### Table Settings
#### Position and Size
1. ** Table Position **
- Options:
* Top Right (Default)
* Middle Right
* Bottom Right
* Top Left
* Middle Left
* Bottom Left
- Considerations:
* Chart space utilization
* Personal preference
* Multiple monitor setups
2. ** Text Sizes **
- Title Size Options:
* Tiny: Minimal space usage
* Small: Compact but readable
* Normal (Default): Standard visibility
* Large: Enhanced readability
* Huge: Maximum visibility
- Data Size Options:
* Recommended: One size smaller than title
* Adjust based on screen resolution
* Consider viewing distance
3. ** Empowering Messages **
- Purpose:
* Maintain trading discipline
* Provide psychological support
* Remind of best practices
- Rotation:
* Changes every 5 bars
* Categories include:
- Market Wisdom
- Strategy & Discipline
- Mindset & Growth
- Technical Mastery
- Market Philosophy
## 4. Setting Up for Different Trading Styles
### Day Trading Setup
1. **Timeframes**
- Primary: 5, 15, 30 minutes
- Secondary: 1H, 4H
- Alert Settings: "Once Per Bar"
2. ** Stochastic Settings **
- Length: 8-14
- Smooth K/D: 2-3
- Alert Condition: Match market trend
3. ** Visual Settings **
- Background: Enabled
- Transparency: 85-90
- Theme: Based on trading hours
### Swing Trading Setup
1. ** Timeframes **
- Primary: 1H, 4H, Daily
- Secondary: Weekly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 14-21
- Smooth K/D: 3-5
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Optional
- Transparency: 90-95
- Theme: Personal preference
### Position Trading Setup
1. ** Timeframes **
- Primary: Daily, Weekly
- Secondary: Monthly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 21-30
- Smooth K/D: 5-7
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Disabled
- Focus on table data
- Theme: High contrast
## 5. Troubleshooting Guide
### Common Issues and Solutions
1. ** Too Many Alerts **
- Cause: Settings too sensitive
- Solutions:
* Increase timeframe intervals
* Use "Once Per Bar Close"
* Enable fewer timeframe checks
* Adjust stochastic length higher
2. ** Missed Signals **
- Cause: Settings too conservative
- Solutions:
* Decrease timeframe intervals
* Use "Once Per Bar"
* Enable more timeframe checks
* Adjust stochastic length lower
3. ** False Signals **
- Cause: Insufficient confirmation
- Solutions:
* Enable all three timeframe checks
* Use larger timeframe gaps
* Wait for bar close
* Confirm with price action
4. ** Visual Clarity Issues **
- Cause: Poor contrast or overlap
- Solutions:
* Adjust transparency
* Change theme settings
* Reposition table
* Modify color scheme
### Best Practices
1. ** Getting Started **
- Start with default settings
- Use "Both" alert condition
- Enable all timeframe checks
- Wait for bar close
- Monitor for a few days
2. ** Fine-Tuning **
- Adjust one setting at a time
- Document changes and results
- Test in different market conditions
- Find your optimal timeframe combination
- Balance sensitivity with reliability
3. ** Risk Management **
- Don't trade against major trends
- Confirm signals with price action
- Use appropriate position sizing
- Set clear stop losses
- Follow your trading plan
4. ** Regular Maintenance **
- Review settings weekly
- Adjust for market conditions
- Update color scheme for visibility
- Clean up chart regularly
- Maintain trading journal
## 6. Tips for Success
1. ** Entry Strategies **
- Wait for all timeframes to align
- Confirm with price action
- Use proper position sizing
- Consider market conditions
2. ** Exit Strategies **
- Trail stops using indicator levels
- Take partial profits at targets
- Honor your stop losses
- Don't fight the trend
3. ** Psychology **
- Stay disciplined with settings
- Don't override system signals
- Keep emotions in check
- Learn from each trade
4. ** Continuous Improvement **
- Record your trades
- Review performance regularly
- Adjust settings gradually
- Stay educated on markets
Moving Average Dispersion Index w/ Z-Score (Adjusted MADI-Z)Overview
The Adjusted MADI-Z indicator is a custom indicator that looks to decipher trends and consolidations based on the clustering and dispersion of Moving Averages. It calculates a z-score based on the dispersion of various exponentially weighted moving averages to identify trends and consolidation. The z-score is then adjusted using a logistic function to map it between 0-100.
How can it be used?
- Identify trends and consolidation - Values above 80 indicate a strong trend while values below 20 show consolidation
- Gauge trend strength - Higher positive values suggest a stronger uptrend while lower negative values indicate a stronger downtrend
- Generate trading signals - Crossovers of key levels can act as entry/exit triggers
- Smooth noise in price action - The adjusted z-score filters out market noise
Default Values
- ma5_len = 5
- ma10_len = 10
- ma50_len = 50
- ma200_len = 200
- lookback_period = 100
Strategies
The Adjusted MADI-Z can be used for trend-following strategies across various timeframes. Specific strategies include:
- Trend trading - Enter long on crossover above 80, exit on crossover below 80. Reverse for short trades.
- Range trading - Enter short on crossover below 20, exit on crossover above 20. Reverse for long trades.
- Identifying pullbacks - Temporary moves below 80 during uptrends and above 20 during downtrends can act as retracement entry points.
Rationale
By adjusting the z-score output of the standard MADI using a logistic function, the indicator becomes bounded and easier to interpret for trading purposes. The customized moving average lengths also allow tuning the indicator to particular assets and timeframes.
Interpretation
- Above 80 - Strong uptrend
- 70 to 80 - Moderate uptrend
- 50 to 70 - Weak uptrend
- 30 to 50 - Range-bound consolidation
- 20 to 30 - Weak downtrend
- Below 20 - Strong downtrend
Values below 15 or above 85 represent extremes outside two standard deviations.
Hull Suite Oscillator - Normalized | IkkeOmarThis script is based off the Hull Suite by @InSilico.
I made this script to provide and calculate the Hull Moving Average (HMA) based on the chosen variation (HMA, TMA, or EMA) and length to then normalize the HMA values to a range of 0 to 100. The normalized values are further smoothed using an exponential moving average (EMA).
The smoothed oscillator is plotted as a line, where values above 80 are colored red, values below 20 are colored green, and values between 20 and 80 are colored blue. Additionally, there are horizontal dashed lines at the levels of 20 and 80 to serve as reference points.
Explanation for the code:
The script uses the close price of the asset as the source for calculations. The modeSwitch parameter allows selecting the type of Hull variation: Hma, Thma, or Ehma. The length parameter determines the calculation period for the Hull moving averages. The lengthMult parameter is used to adjust the length for higher timeframes. The oscSmooth parameter determines the lookback period for smoothing the oscillator.
There are three functions defined for calculating different types of Hull moving averages: HMA, EHMA, and THMA. These functions take the source and length as inputs and return the corresponding Hull moving average.
The Mode function acts as a switch and selects the appropriate Hull variation based on the modeSwitch parameter. It returns the chosen Hull moving average.
The script calculates the Hull moving averages using the selected mode, source, and length. The main Hull moving average is stored in the _hull variable, and aliases are created for the main Hull moving average (HULL), the main Hull value (MHULL), and the secondary Hull value (SHULL).
To create the normalized oscillator values, the script finds the highest and lowest values of the Hull moving average within the specified length. It then normalizes the Hull values to a range of 0 to 100 using a formula. This normalized oscillator represents the strength of the trend.
To smooth out the oscillator values, an exponential moving average is applied using the oscSmooth parameter.
The smoothed oscillator is plotted as a line chart. The line color is determined based on the oscillator value using conditional statements. If the oscillator value is above or equal to 80, the line color is set to red. If it is below or equal to 20, the color is green. Otherwise, it is blue. The linewidth is set to 2.
Additionally, two horizontal reference lines are plotted at levels 20 and 80 for visual reference. They are displayed in gray and dashed style.
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Volume Delta Volume Signals by Claudio [hapharmonic]// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © hapharmonic
//@version=6
FV = format.volume
FP = format.percent
indicator('Volume Delta Volume Signals by Claudio ', format = FV, max_bars_back = 4999, max_labels_count = 500)
//------------------------------------------
// Settings |
//------------------------------------------
bool usecandle = input.bool(true, title = 'Volume on Candles',display=display.none)
color C_Up = input.color(#12cef8, title = 'Volume Buy', inline = ' ', group = 'Style')
color C_Down = input.color(#fe3f00, title = 'Volume Sell', inline = ' ', group = 'Style')
// ✅ Nueva entrada para colores de señales
color buySignalColor = input.color(color.new(color.green, 0), "Buy Signal Color", group = "Signals")
color sellSignalColor = input.color(color.new(color.red, 0), "Sell Signal Color", group = "Signals")
string P_ = input.string(position.top_right,"Position",options = ,
group = "Style",display=display.none)
string sL = input.string(size.small , 'Size Label', options = , group = 'Style',display=display.none)
string sT = input.string(size.normal, 'Size Table', options = , group = 'Style',display=display.none)
bool Label = input.bool(false, inline = 'l')
History = input.bool(true, inline = 'l')
// Inputs for EMA lengths and volume confirmation
bool MAV = input.bool(true, title = 'EMA', group = 'EMA')
string volumeOption = input.string('Use Volume Confirmation', title = 'Volume Option', options = , group = 'EMA',display=display.none)
bool useVolumeConfirmation = volumeOption == 'none' ? false : true
int emaFastLength = input(12, title = 'Fast EMA Length', group = 'EMA',display=display.none)
int emaSlowLength = input(26, title = 'Slow EMA Length', group = 'EMA',display=display.none)
int volumeConfirmationLength = input(6, title = 'Volume Confirmation Length', group = 'EMA',display=display.none)
string alert_freq = input.string(alert.freq_once_per_bar_close, title="Alert Frequency",
options= ,group = "EMA",
tooltip="If you choose once_per_bar, you will receive immediate notifications (but this may cause interference or indicator repainting).
\n However, if you choose once_per_bar_close, it will wait for the candle to confirm the signal before notifying.",display=display.none)
//------------------------------------------
// UDT_identifier |
//------------------------------------------
type OHLCV
float O = open
float H = high
float L = low
float C = close
float V = volume
type VolumeData
float buyVol
float sellVol
float pcBuy
float pcSell
bool isBuyGreater
float higherVol
float lowerVol
color higherCol
color lowerCol
//------------------------------------------
// Calculate volumes and percentages |
//------------------------------------------
calcVolumes(OHLCV ohlcv) =>
var VolumeData data = VolumeData.new()
data.buyVol := ohlcv.V * (ohlcv.C - ohlcv.L) / (ohlcv.H - ohlcv.L)
data.sellVol := ohlcv.V - data.buyVol
data.pcBuy := data.buyVol / ohlcv.V * 100
data.pcSell := 100 - data.pcBuy
data.isBuyGreater := data.buyVol > data.sellVol
data.higherVol := data.isBuyGreater ? data.buyVol : data.sellVol
data.lowerVol := data.isBuyGreater ? data.sellVol : data.buyVol
data.higherCol := data.isBuyGreater ? C_Up : C_Down
data.lowerCol := data.isBuyGreater ? C_Down : C_Up
data
//------------------------------------------
// Get volume data |
//------------------------------------------
ohlcv = OHLCV.new()
volData = calcVolumes(ohlcv)
// Plot volumes and create labels
plot(ohlcv.V, color=color.new(volData.higherCol, 90), style=plot.style_columns, title='Total',display = display.all - display.status_line)
plot(ohlcv.V, color=volData.higherCol, style=plot.style_stepline_diamond, title='Total2', linewidth = 2,display = display.pane)
plot(volData.higherVol, color=volData.higherCol, style=plot.style_columns, title='Higher Volume', display = display.all - display.status_line)
plot(volData.lowerVol , color=volData.lowerCol , style=plot.style_columns, title='Lower Volume',display = display.all - display.status_line)
S(D,F)=>str.tostring(D,F)
volStr = S(math.sign(ta.change(ohlcv.C)) * ohlcv.V, FV)
buyVolStr = S(volData.buyVol , FV )
sellVolStr = S(volData.sellVol , FV )
// ✅ MODIFICACIÓN: Porcentaje sin decimales
buyPercentStr = str.tostring(math.round(volData.pcBuy)) + " %"
sellPercentStr = str.tostring(math.round(volData.pcSell)) + " %"
totalbuyPercentC_ = volData.buyVol / (volData.buyVol + volData.sellVol) * 100
sup = not na(ohlcv.V)
if sup
TC = text.align_center
CW = color.white
var table tb = table.new(P_, 6, 6, bgcolor = na, frame_width = 2, frame_color = chart.fg_color, border_width = 1, border_color = CW)
tb.cell(0, 0, text = 'Volume Candles', text_color = #FFBF00, bgcolor = #0E2841, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 0, 5, 0)
tb.cell(0, 1, text = 'Current Volume', text_color = CW, bgcolor = #0B3040, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 1, 1, 1)
tb.cell(0, 2, text = 'Buy', text_color = #000000, bgcolor = #92D050, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 2, text = 'Sell', text_color = #000000, bgcolor = #FF0000, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(0, 3, text = buyVolStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 3, text = sellVolStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(0, 5, text = 'Net: ' + volStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 5, 1, 5)
tb.cell(0, 4, text = buyPercentStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 4, text = sellPercentStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
cellCount = 20
filledCells = 0
for r = 5 to 1 by 1
for c = 2 to 5 by 1
if filledCells < cellCount * (totalbuyPercentC_ / 100)
tb.cell(c, r, text = '', bgcolor = C_Up)
else
tb.cell(c, r, text = '', bgcolor = C_Down)
filledCells := filledCells + 1
filledCells
if Label
sp = ' '
l = label.new(bar_index, ohlcv.V,
text=str.format('Net: {0}\nBuy: {1} ({2})\nSell: {3} ({4})\n{5}/\\\n {5}l\n {5}l',
volStr, buyVolStr, buyPercentStr, sellVolStr, sellPercentStr, sp),
style=label.style_none, textcolor=volData.higherCol, size=sL, textalign=text.align_left)
if not History
(l ).delete()
//------------------------------------------
// Draw volume levels on the candlesticks |
//------------------------------------------
float base = na,float value = na
bool uc = usecandle and sup
if volData.isBuyGreater
base := math.min(ohlcv.O, ohlcv.C)
value := base + math.abs(ohlcv.O - ohlcv.C) * (volData.pcBuy / 100)
else
base := math.max(ohlcv.O, ohlcv.C)
value := base - math.abs(ohlcv.O - ohlcv.C) * (volData.pcSell / 100)
barcolor(sup ? color.new(na, na) : ohlcv.C < ohlcv.O ? color.red : color.green,display = usecandle? display.all:display.none)
UseC = uc ? volData.higherCol:color.new(na, na)
plotcandle(uc?base:na, uc?base:na, uc?value:na, uc?value:na,
title='Body', color=UseC, bordercolor=na, wickcolor=UseC,
display = usecandle ? display.all - display.status_line : display.none, force_overlay=true,editable=false)
plotcandle(uc?ohlcv.O:na, uc?ohlcv.H:na, uc?ohlcv.L:na, uc?ohlcv.C:na,
title='Fill', color=color.new(UseC,80), bordercolor=UseC, wickcolor=UseC,
display = usecandle ? display.all - display.status_line : display.none, force_overlay=true,editable=false)
//------------------------------------------------------------
// Plot the EMA and filter out the noise with volume control. |
//------------------------------------------------------------
float emaFast = ta.ema(ohlcv.C, emaFastLength)
float emaSlow = ta.ema(ohlcv.C, emaSlowLength)
bool signal = emaFast > emaSlow
color c_signal = signal ? C_Up : C_Down
float volumeMA = ta.sma(ohlcv.V, volumeConfirmationLength)
bool crossover = ta.crossover(emaFast, emaSlow)
bool crossunder = ta.crossunder(emaFast, emaSlow)
isVolumeConfirmed(source, length, ma) =>
math.sum(source > ma ? source : 0, length) >= math.sum(source < ma ? source : 0, length)
bool ISV = isVolumeConfirmed(ohlcv.V, volumeConfirmationLength, volumeMA)
bool crossoverConfirmed = crossover and (not useVolumeConfirmation or ISV)
bool crossunderConfirmed = crossunder and (not useVolumeConfirmation or ISV)
PF = MAV ? emaFast : na
PS = MAV ? emaSlow : na
p1 = plot(PF, color = c_signal, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 80), linewidth = 10, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 90), linewidth = 20, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 95), linewidth = 30, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 98), linewidth = 45, editable = false, force_overlay = true, display = display.pane)
p2 = plot(PS, color = c_signal, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 80), linewidth = 10, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 90), linewidth = 20, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 95), linewidth = 30, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 98), linewidth = 45, editable = false, force_overlay = true, display = display.pane)
fill(p1, p2, top_value=crossover ? emaFast : emaSlow,
bottom_value =crossover ? emaSlow : emaFast,
top_color =color.new(c_signal, 80),
bottom_color =color.new(c_signal, 95)
)
// ✅ Usar colores configurables para señales
plotshape(crossoverConfirmed and MAV, style=shape.triangleup , location=location.belowbar, color=buySignalColor , size=size.small, force_overlay=true,display =display.pane)
plotshape(crossunderConfirmed and MAV, style=shape.triangledown, location=location.abovebar, color=sellSignalColor, size=size.small, force_overlay=true,display =display.pane)
string msg = '---------\n'+"Buy volume ="+buyVolStr+"\nBuy Percent = "+buyPercentStr+"\nSell volume = "+sellVolStr+"\nSell Percent = "+sellPercentStr+"\nNet = "+volStr+'\n---------'
if crossoverConfirmed
alert("Price (" + str.tostring(close) + ") Crossed over MA\n" + msg, alert_freq)
if crossunderConfirmed
alert("Price (" + str.tostring(close) + ") Crossed under MA\n" + msg, alert_freq)
Small Business Economic Conditions - Statistical Analysis ModelThe Small Business Economic Conditions Statistical Analysis Model (SBO-SAM) represents an econometric approach to measuring and analyzing the economic health of small business enterprises through multi-dimensional factor analysis and statistical methodologies. This indicator synthesizes eight fundamental economic components into a composite index that provides real-time assessment of small business operating conditions with statistical rigor. The model employs Z-score standardization, variance-weighted aggregation, higher-order moment analysis, and regime-switching detection to deliver comprehensive insights into small business economic conditions with statistical confidence intervals and multi-language accessibility.
1. Introduction and Theoretical Foundation
The development of quantitative models for assessing small business economic conditions has gained significant importance in contemporary financial analysis, particularly given the critical role small enterprises play in economic development and employment generation. Small businesses, typically defined as enterprises with fewer than 500 employees according to the U.S. Small Business Administration, constitute approximately 99.9% of all businesses in the United States and employ nearly half of the private workforce (U.S. Small Business Administration, 2024).
The theoretical framework underlying the SBO-SAM model draws extensively from established academic research in small business economics and quantitative finance. The foundational understanding of key drivers affecting small business performance builds upon the seminal work of Dunkelberg and Wade (2023) in their analysis of small business economic trends through the National Federation of Independent Business (NFIB) Small Business Economic Trends survey. Their research established the critical importance of optimism, hiring plans, capital expenditure intentions, and credit availability as primary determinants of small business performance.
The model incorporates insights from Federal Reserve Board research, particularly the Senior Loan Officer Opinion Survey (Federal Reserve Board, 2024), which demonstrates the critical importance of credit market conditions in small business operations. This research consistently shows that small businesses face disproportionate challenges during periods of credit tightening, as they typically lack access to capital markets and rely heavily on bank financing.
The statistical methodology employed in this model follows the econometric principles established by Hamilton (1989) in his work on regime-switching models and time series analysis. Hamilton's framework provides the theoretical foundation for identifying different economic regimes and understanding how economic relationships may vary across different market conditions. The variance-weighted aggregation technique draws from modern portfolio theory as developed by Markowitz (1952) and later refined by Sharpe (1964), applying these concepts to economic indicator construction rather than traditional asset allocation.
Additional theoretical support comes from the work of Engle and Granger (1987) on cointegration analysis, which provides the statistical framework for combining multiple time series while maintaining long-term equilibrium relationships. The model also incorporates insights from behavioral economics research by Kahneman and Tversky (1979) on prospect theory, recognizing that small business decision-making may exhibit systematic biases that affect economic outcomes.
2. Model Architecture and Component Structure
The SBO-SAM model employs eight orthogonalized economic factors that collectively capture the multifaceted nature of small business operating conditions. Each component is normalized using Z-score standardization with a rolling 252-day window, representing approximately one business year of trading data. This approach ensures statistical consistency across different market regimes and economic cycles, following the methodology established by Tsay (2010) in his treatment of financial time series analysis.
2.1 Small Cap Relative Performance Component
The first component measures the performance of the Russell 2000 index relative to the S&P 500, capturing the market-based assessment of small business equity valuations. This component reflects investor sentiment toward smaller enterprises and provides a forward-looking perspective on small business prospects. The theoretical justification for this component stems from the efficient market hypothesis as formulated by Fama (1970), which suggests that stock prices incorporate all available information about future prospects.
The calculation employs a 20-day rate of change with exponential smoothing to reduce noise while preserving signal integrity. The mathematical formulation is:
Small_Cap_Performance = (Russell_2000_t / S&P_500_t) / (Russell_2000_{t-20} / S&P_500_{t-20}) - 1
This relative performance measure eliminates market-wide effects and isolates the specific performance differential between small and large capitalization stocks, providing a pure measure of small business market sentiment.
2.2 Credit Market Conditions Component
Credit Market Conditions constitute the second component, incorporating commercial lending volumes and credit spread dynamics. This factor recognizes that small businesses are particularly sensitive to credit availability and borrowing costs, as established in numerous Federal Reserve studies (Bernanke and Gertler, 1995). Small businesses typically face higher borrowing costs and more stringent lending standards compared to larger enterprises, making credit conditions a critical determinant of their operating environment.
The model calculates credit spreads using high-yield bond ETFs relative to Treasury securities, providing a market-based measure of credit risk premiums that directly affect small business borrowing costs. The component also incorporates commercial and industrial loan growth data from the Federal Reserve's H.8 statistical release, which provides direct evidence of lending activity to businesses.
The mathematical specification combines these elements as:
Credit_Conditions = α₁ × (HYG_t / TLT_t) + α₂ × C&I_Loan_Growth_t
where HYG represents high-yield corporate bond ETF prices, TLT represents long-term Treasury ETF prices, and C&I_Loan_Growth represents the rate of change in commercial and industrial loans outstanding.
2.3 Labor Market Dynamics Component
The Labor Market Dynamics component captures employment cost pressures and labor availability metrics through the relationship between job openings and unemployment claims. This factor acknowledges that labor market tightness significantly impacts small business operations, as these enterprises typically have less flexibility in wage negotiations and face greater challenges in attracting and retaining talent during periods of low unemployment.
The theoretical foundation for this component draws from search and matching theory as developed by Mortensen and Pissarides (1994), which explains how labor market frictions affect employment dynamics. Small businesses often face higher search costs and longer hiring processes, making them particularly sensitive to labor market conditions.
The component is calculated as:
Labor_Tightness = Job_Openings_t / (Unemployment_Claims_t × 52)
This ratio provides a measure of labor market tightness, with higher values indicating greater difficulty in finding workers and potential wage pressures.
2.4 Consumer Demand Strength Component
Consumer Demand Strength represents the fourth component, combining consumer sentiment data with retail sales growth rates. Small businesses are disproportionately affected by consumer spending patterns, making this component crucial for assessing their operating environment. The theoretical justification comes from the permanent income hypothesis developed by Friedman (1957), which explains how consumer spending responds to both current conditions and future expectations.
The model weights consumer confidence and actual spending data to provide both forward-looking sentiment and contemporaneous demand indicators. The specification is:
Demand_Strength = β₁ × Consumer_Sentiment_t + β₂ × Retail_Sales_Growth_t
where β₁ and β₂ are determined through principal component analysis to maximize the explanatory power of the combined measure.
2.5 Input Cost Pressures Component
Input Cost Pressures form the fifth component, utilizing producer price index data to capture inflationary pressures on small business operations. This component is inversely weighted, recognizing that rising input costs negatively impact small business profitability and operating conditions. Small businesses typically have limited pricing power and face challenges in passing through cost increases to customers, making them particularly vulnerable to input cost inflation.
The theoretical foundation draws from cost-push inflation theory as described by Gordon (1988), which explains how supply-side price pressures affect business operations. The model employs a 90-day rate of change to capture medium-term cost trends while filtering out short-term volatility:
Cost_Pressure = -1 × (PPI_t / PPI_{t-90} - 1)
The negative weighting reflects the inverse relationship between input costs and business conditions.
2.6 Monetary Policy Impact Component
Monetary Policy Impact represents the sixth component, incorporating federal funds rates and yield curve dynamics. Small businesses are particularly sensitive to interest rate changes due to their higher reliance on variable-rate financing and limited access to capital markets. The theoretical foundation comes from monetary transmission mechanism theory as developed by Bernanke and Blinder (1992), which explains how monetary policy affects different segments of the economy.
The model calculates the absolute deviation of federal funds rates from a neutral 2% level, recognizing that both extremely low and high rates can create operational challenges for small enterprises. The yield curve component captures the shape of the term structure, which affects both borrowing costs and economic expectations:
Monetary_Impact = γ₁ × |Fed_Funds_Rate_t - 2.0| + γ₂ × (10Y_Yield_t - 2Y_Yield_t)
2.7 Currency Valuation Effects Component
Currency Valuation Effects constitute the seventh component, measuring the impact of US Dollar strength on small business competitiveness. A stronger dollar can benefit businesses with significant import components while disadvantaging exporters. The model employs Dollar Index volatility as a proxy for currency-related uncertainty that affects small business planning and operations.
The theoretical foundation draws from international trade theory and the work of Krugman (1987) on exchange rate effects on different business segments. Small businesses often lack hedging capabilities, making them more vulnerable to currency fluctuations:
Currency_Impact = -1 × DXY_Volatility_t
2.8 Regional Banking Health Component
The eighth and final component, Regional Banking Health, assesses the relative performance of regional banks compared to large financial institutions. Regional banks traditionally serve as primary lenders to small businesses, making their health a critical factor in small business credit availability and overall operating conditions.
This component draws from the literature on relationship banking as developed by Boot (2000), which demonstrates the importance of bank-borrower relationships, particularly for small enterprises. The calculation compares regional bank performance to large financial institutions:
Banking_Health = (Regional_Banks_Index_t / Large_Banks_Index_t) - 1
3. Statistical Methodology and Advanced Analytics
The model employs statistical techniques to ensure robustness and reliability. Z-score normalization is applied to each component using rolling 252-day windows, providing standardized measures that remain consistent across different time periods and market conditions. This approach follows the methodology established by Engle and Granger (1987) in their cointegration analysis framework.
3.1 Variance-Weighted Aggregation
The composite index calculation utilizes variance-weighted aggregation, where component weights are determined by the inverse of their historical variance. This approach, derived from modern portfolio theory, ensures that more stable components receive higher weights while reducing the impact of highly volatile factors. The mathematical formulation follows the principle that optimal weights are inversely proportional to variance, maximizing the signal-to-noise ratio of the composite indicator.
The weight for component i is calculated as:
w_i = (1/σᵢ²) / Σⱼ(1/σⱼ²)
where σᵢ² represents the variance of component i over the lookback period.
3.2 Higher-Order Moment Analysis
Higher-order moment analysis extends beyond traditional mean and variance calculations to include skewness and kurtosis measurements. Skewness provides insight into the asymmetry of the sentiment distribution, while kurtosis measures the tail behavior and potential for extreme events. These metrics offer valuable information about the underlying distribution characteristics and potential regime changes.
Skewness is calculated as:
Skewness = E / σ³
Kurtosis is calculated as:
Kurtosis = E / σ⁴ - 3
where μ represents the mean and σ represents the standard deviation of the distribution.
3.3 Regime-Switching Detection
The model incorporates regime-switching detection capabilities based on the Hamilton (1989) framework. This allows for identification of different economic regimes characterized by distinct statistical properties. The regime classification employs percentile-based thresholds:
- Regime 3 (Very High): Percentile rank > 80
- Regime 2 (High): Percentile rank 60-80
- Regime 1 (Moderate High): Percentile rank 50-60
- Regime 0 (Neutral): Percentile rank 40-50
- Regime -1 (Moderate Low): Percentile rank 30-40
- Regime -2 (Low): Percentile rank 20-30
- Regime -3 (Very Low): Percentile rank < 20
3.4 Information Theory Applications
The model incorporates information theory concepts, specifically Shannon entropy measurement, to assess the information content of the sentiment distribution. Shannon entropy, as developed by Shannon (1948), provides a measure of the uncertainty or information content in a probability distribution:
H(X) = -Σᵢ p(xᵢ) log₂ p(xᵢ)
Higher entropy values indicate greater unpredictability and information content in the sentiment series.
3.5 Long-Term Memory Analysis
The Hurst exponent calculation provides insight into the long-term memory characteristics of the sentiment series. Originally developed by Hurst (1951) for analyzing Nile River flow patterns, this measure has found extensive application in financial time series analysis. The Hurst exponent H is calculated using the rescaled range statistic:
H = log(R/S) / log(T)
where R/S represents the rescaled range and T represents the time period. Values of H > 0.5 indicate long-term positive autocorrelation (persistence), while H < 0.5 indicates mean-reverting behavior.
3.6 Structural Break Detection
The model employs Chow test approximation for structural break detection, based on the methodology developed by Chow (1960). This technique identifies potential structural changes in the underlying relationships by comparing the stability of regression parameters across different time periods:
Chow_Statistic = (RSS_restricted - RSS_unrestricted) / RSS_unrestricted × (n-2k)/k
where RSS represents residual sum of squares, n represents sample size, and k represents the number of parameters.
4. Implementation Parameters and Configuration
4.1 Language Selection Parameters
The model provides comprehensive multi-language support across five languages: English, German (Deutsch), Spanish (Español), French (Français), and Japanese (日本語). This feature enhances accessibility for international users and ensures cultural appropriateness in terminology usage. The language selection affects all internal displays, statistical classifications, and alert messages while maintaining consistency in underlying calculations.
4.2 Model Configuration Parameters
Calculation Method: Users can select from four aggregation methodologies:
- Equal-Weighted: All components receive identical weights
- Variance-Weighted: Components weighted inversely to their historical variance
- Principal Component: Weights determined through principal component analysis
- Dynamic: Adaptive weighting based on recent performance
Sector Specification: The model allows for sector-specific calibration:
- General: Broad-based small business assessment
- Retail: Emphasis on consumer demand and seasonal factors
- Manufacturing: Enhanced weighting of input costs and currency effects
- Services: Focus on labor market dynamics and consumer demand
- Construction: Emphasis on credit conditions and monetary policy
Lookback Period: Statistical analysis window ranging from 126 to 504 trading days, with 252 days (one business year) as the optimal default based on academic research.
Smoothing Period: Exponential moving average period from 1 to 21 days, with 5 days providing optimal noise reduction while preserving signal integrity.
4.3 Statistical Threshold Parameters
Upper Statistical Boundary: Configurable threshold between 60-80 (default 70) representing the upper significance level for regime classification.
Lower Statistical Boundary: Configurable threshold between 20-40 (default 30) representing the lower significance level for regime classification.
Statistical Significance Level (α): Alpha level for statistical tests, configurable between 0.01-0.10 with 0.05 as the standard academic default.
4.4 Display and Visualization Parameters
Color Theme Selection: Eight professional color schemes optimized for different user preferences and accessibility requirements:
- Gold: Traditional financial industry colors
- EdgeTools: Professional blue-gray scheme
- Behavioral: Psychology-based color mapping
- Quant: Value-based quantitative color scheme
- Ocean: Blue-green maritime theme
- Fire: Warm red-orange theme
- Matrix: Green-black technology theme
- Arctic: Cool blue-white theme
Dark Mode Optimization: Automatic color adjustment for dark chart backgrounds, ensuring optimal readability across different viewing conditions.
Line Width Configuration: Main index line thickness adjustable from 1-5 pixels for optimal visibility.
Background Intensity: Transparency control for statistical regime backgrounds, adjustable from 90-99% for subtle visual enhancement without distraction.
4.5 Alert System Configuration
Alert Frequency Options: Three frequency settings to match different trading styles:
- Once Per Bar: Single alert per bar formation
- Once Per Bar Close: Alert only on confirmed bar close
- All: Continuous alerts for real-time monitoring
Statistical Extreme Alerts: Notifications when the index reaches 99% confidence levels (Z-score > 2.576 or < -2.576).
Regime Transition Alerts: Notifications when statistical boundaries are crossed, indicating potential regime changes.
5. Practical Application and Interpretation Guidelines
5.1 Index Interpretation Framework
The SBO-SAM index operates on a 0-100 scale with statistical normalization ensuring consistent interpretation across different time periods and market conditions. Values above 70 indicate statistically elevated small business conditions, suggesting favorable operating environment with potential for expansion and growth. Values below 30 indicate statistically reduced conditions, suggesting challenging operating environment with potential constraints on business activity.
The median reference line at 50 represents the long-term equilibrium level, with deviations providing insight into cyclical conditions relative to historical norms. The statistical confidence bands at 95% levels (approximately ±2 standard deviations) help identify when conditions reach statistically significant extremes.
5.2 Regime Classification System
The model employs a seven-level regime classification system based on percentile rankings:
Very High Regime (P80+): Exceptional small business conditions, typically associated with strong economic growth, easy credit availability, and favorable regulatory environment. Historical analysis suggests these periods often precede economic peaks and may warrant caution regarding sustainability.
High Regime (P60-80): Above-average conditions supporting business expansion and investment. These periods typically feature moderate growth, stable credit conditions, and positive consumer sentiment.
Moderate High Regime (P50-60): Slightly above-normal conditions with mixed signals. Careful monitoring of individual components helps identify emerging trends.
Neutral Regime (P40-50): Balanced conditions near long-term equilibrium. These periods often represent transition phases between different economic cycles.
Moderate Low Regime (P30-40): Slightly below-normal conditions with emerging headwinds. Early warning signals may appear in credit conditions or consumer demand.
Low Regime (P20-30): Below-average conditions suggesting challenging operating environment. Businesses may face constraints on growth and expansion.
Very Low Regime (P0-20): Severely constrained conditions, typically associated with economic recessions or financial crises. These periods often present opportunities for contrarian positioning.
5.3 Component Analysis and Diagnostics
Individual component analysis provides valuable diagnostic information about the underlying drivers of overall conditions. Divergences between components can signal emerging trends or structural changes in the economy.
Credit-Labor Divergence: When credit conditions improve while labor markets tighten, this may indicate early-stage economic acceleration with potential wage pressures.
Demand-Cost Divergence: Strong consumer demand coupled with rising input costs suggests inflationary pressures that may constrain small business margins.
Market-Fundamental Divergence: Disconnection between small-cap equity performance and fundamental conditions may indicate market inefficiencies or changing investor sentiment.
5.4 Temporal Analysis and Trend Identification
The model provides multiple temporal perspectives through momentum analysis, rate of change calculations, and trend decomposition. The 20-day momentum indicator helps identify short-term directional changes, while the Hodrick-Prescott filter approximation separates cyclical components from long-term trends.
Acceleration analysis through second-order momentum calculations provides early warning signals for potential trend reversals. Positive acceleration during declining conditions may indicate approaching inflection points, while negative acceleration during improving conditions may suggest momentum loss.
5.5 Statistical Confidence and Uncertainty Quantification
The model provides comprehensive uncertainty quantification through confidence intervals, volatility measures, and regime stability analysis. The 95% confidence bands help users understand the statistical significance of current readings and identify when conditions reach historically extreme levels.
Volatility analysis provides insight into the stability of current conditions, with higher volatility indicating greater uncertainty and potential for rapid changes. The regime stability measure, calculated as the inverse of volatility, helps assess the sustainability of current conditions.
6. Risk Management and Limitations
6.1 Model Limitations and Assumptions
The SBO-SAM model operates under several important assumptions that users must understand for proper interpretation. The model assumes that historical relationships between economic variables remain stable over time, though the regime-switching framework helps accommodate some structural changes. The 252-day lookback period provides reasonable statistical power while maintaining sensitivity to changing conditions, but may not capture longer-term structural shifts.
The model's reliance on publicly available economic data introduces inherent lags in some components, particularly those based on government statistics. Users should consider these timing differences when interpreting real-time conditions. Additionally, the model's focus on quantitative factors may not fully capture qualitative factors such as regulatory changes, geopolitical events, or technological disruptions that could significantly impact small business conditions.
The model's timeframe restrictions ensure statistical validity by preventing application to intraday periods where the underlying economic relationships may be distorted by market microstructure effects, trading noise, and temporal misalignment with the fundamental data sources. Users must utilize daily or longer timeframes to ensure the model's statistical foundations remain valid and interpretable.
6.2 Data Quality and Reliability Considerations
The model's accuracy depends heavily on the quality and availability of underlying economic data. Market-based components such as equity indices and bond prices provide real-time information but may be subject to short-term volatility unrelated to fundamental conditions. Economic statistics provide more stable fundamental information but may be subject to revisions and reporting delays.
Users should be aware that extreme market conditions may temporarily distort some components, particularly those based on financial market data. The model's statistical normalization helps mitigate these effects, but users should exercise additional caution during periods of market stress or unusual volatility.
6.3 Interpretation Caveats and Best Practices
The SBO-SAM model provides statistical analysis and should not be interpreted as investment advice or predictive forecasting. The model's output represents an assessment of current conditions based on historical relationships and may not accurately predict future outcomes. Users should combine the model's insights with other analytical tools and fundamental analysis for comprehensive decision-making.
The model's regime classifications are based on historical percentile rankings and may not fully capture the unique characteristics of current economic conditions. Users should consider the broader economic context and potential structural changes when interpreting regime classifications.
7. Academic References and Bibliography
Bernanke, B. S., & Blinder, A. S. (1992). The Federal Funds Rate and the Channels of Monetary Transmission. American Economic Review, 82(4), 901-921.
Bernanke, B. S., & Gertler, M. (1995). Inside the Black Box: The Credit Channel of Monetary Policy Transmission. Journal of Economic Perspectives, 9(4), 27-48.
Boot, A. W. A. (2000). Relationship Banking: What Do We Know? Journal of Financial Intermediation, 9(1), 7-25.
Chow, G. C. (1960). Tests of Equality Between Sets of Coefficients in Two Linear Regressions. Econometrica, 28(3), 591-605.
Dunkelberg, W. C., & Wade, H. (2023). NFIB Small Business Economic Trends. National Federation of Independent Business Research Foundation, Washington, D.C.
Engle, R. F., & Granger, C. W. J. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 25(2), 383-417.
Federal Reserve Board. (2024). Senior Loan Officer Opinion Survey on Bank Lending Practices. Board of Governors of the Federal Reserve System, Washington, D.C.
Friedman, M. (1957). A Theory of the Consumption Function. Princeton University Press, Princeton, NJ.
Gordon, R. J. (1988). The Role of Wages in the Inflation Process. American Economic Review, 78(2), 276-283.
Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
Hurst, H. E. (1951). Long-term Storage Capacity of Reservoirs. Transactions of the American Society of Civil Engineers, 116(1), 770-799.
Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.
Krugman, P. (1987). Pricing to Market When the Exchange Rate Changes. In S. W. Arndt & J. D. Richardson (Eds.), Real-Financial Linkages among Open Economies (pp. 49-70). MIT Press, Cambridge, MA.
Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1), 77-91.
Mortensen, D. T., & Pissarides, C. A. (1994). Job Creation and Job Destruction in the Theory of Unemployment. Review of Economic Studies, 61(3), 397-415.
Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379-423.
Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance, 19(3), 425-442.
Tsay, R. S. (2010). Analysis of Financial Time Series (3rd ed.). John Wiley & Sons, Hoboken, NJ.
U.S. Small Business Administration. (2024). Small Business Profile. Office of Advocacy, Washington, D.C.
8. Technical Implementation Notes
The SBO-SAM model is implemented in Pine Script version 6 for the TradingView platform, ensuring compatibility with modern charting and analysis tools. The implementation follows best practices for financial indicator development, including proper error handling, data validation, and performance optimization.
The model includes comprehensive timeframe validation to ensure statistical accuracy and reliability. The indicator operates exclusively on daily (1D) timeframes or higher, including weekly (1W), monthly (1M), and longer periods. This restriction ensures that the statistical analysis maintains appropriate temporal resolution for the underlying economic data sources, which are primarily reported on daily or longer intervals.
When users attempt to apply the model to intraday timeframes (such as 1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 2-hour, 4-hour, 6-hour, 8-hour, or 12-hour charts), the system displays a comprehensive error message in the user's selected language and prevents execution. This safeguard protects users from potentially misleading results that could occur when applying daily-based economic analysis to shorter timeframes where the underlying data relationships may not hold.
The model's statistical calculations are performed using vectorized operations where possible to ensure computational efficiency. The multi-language support system employs Unicode character encoding to ensure proper display of international characters across different platforms and devices.
The alert system utilizes TradingView's native alert functionality, providing users with flexible notification options including email, SMS, and webhook integrations. The alert messages include comprehensive statistical information to support informed decision-making.
The model's visualization system employs professional color schemes designed for optimal readability across different chart backgrounds and display devices. The system includes dynamic color transitions based on momentum and volatility, professional glow effects for enhanced line visibility, and transparency controls that allow users to customize the visual intensity to match their preferences and analytical requirements. The clean confidence band implementation provides clear statistical boundaries without visual distractions, maintaining focus on the analytical content.
CCI Stochastic - YOSI
CCI Stochastic (Pro v6) – MTF, Adaptive Bands & Live Label
What it does
This indicator applies a Stochastic calculation on the CCI (K/D lines) to highlight momentum shifts, overbought/oversold zones, and adaptive market regimes. It comes with optional higher-timeframe confirmation, adaptive volatility bands, a live value label, and built-in alerts.
Key Features
Core Signal: Choose between D or K line of the Stoch-CCI.
Extreme Zones: Customizable OB/OS thresholds (default 80/20) and a midline (50), with dynamic background shading.
Adaptive Bands (optional): Mean ± k·standard deviation of the signal, to capture cyclic extremes.
MTF Confirmation (optional): Fetches the same signal from a higher timeframe via request.security.
Arrows/Signals:
Enter – Cross above OS (Buy) / below OB (Sell).
Center – Cross of the 50 midline (momentum shift).
Exit – Exit from extreme zones.
Alerts: All arrow signals + adaptive band crosses.
Live Value Label: Shows the latest signal value near the last bar, customizable decimals/offset/background colors.
Visuals: Red line above OB, green below OS, gray neutral; adaptive band fills.
Use Cases
Momentum / Reversals: Enter with OS/OB crosses confirmed by MTF.
Trend validation: Combine with moving averages (e.g., EMA200) or support/resistance.
Mean Reversion: Fade extreme zones, especially with adaptive band or OB/OS exit alerts.
Inputs
CCI Period, Stoch Period, Smooth K/D – core calculation.
Overbought / Oversold – thresholds (default 80/20).
Line to plot – K or D.
Show Arrows (Enter, Center, Exit) – visual control.
Adaptive Bands – length and k multiplier.
Higher TF – optional confirmation timeframe.
Live Label – decimals, offset, colors.
Quick Tips
For scalping/short-term setups: tighten OB/OS (e.g., 85/15) to filter noise.
In high volatility: increase adaptLen or decrease k to smooth bands.
Reduce false signals: require local + MTF alignment (e.g., only long if MTF > 50).
Disclaimer
This is a technical analysis tool – not a standalone buy/sell signal. Always use with proper risk management, key levels, and confluence from multiple factors.
מה זה עושה?
האינדיקטור מחשב Stochastic על CCI (קו K/D) ומציג אזורי קיצון, חציות ומשטרי שוק. הוא כולל אופציה לאישור מטיימפריים גבוה, בנדים אדפטיביים, תווית ערך חיה והתרעות מוכנות.
יכולות עיקריות
סיגנל מרכזי: בחירה בין קו D או K של Stoch-CCI.
אזורי קיצון: קווים ניתנים להגדרה (ברירת מחדל 80/20) וקו אמצע 50, עם צביעת רקע דינמית כשנכנסים לקיצון.
Adaptive Bands (אופציונלי): ממוצע ± k·סטיית תקן של הסיגנל—מסייע לזהות overheat ומחזוריות.
אישור MTF (אופציונלי): אותו סיגנל מטיימפריים גבוה באמצעות request.security.
חיצים/סיגנלים:
Enter – חציה מלמטה מעל OS (קנייה) / מלמעלה מתחת OB (מכירה).
Center – חציה של 50 (שינוי מומנטום).
Exit – יציאה מאזורים קיצוניים (OS/OB).
Alerts: לכל הסיגנלים לעיל + כניסה/יציאה לבנדים האדפטיביים.
תווית ערך חיה: מציגה את ערך הסיגנל האחרון ליד הנקודה (ספרות ו־offset ניתנים להגדרה).
עיצוב קריא: צבע קו אדום מעל OB, ירוק מתחת OS, אפור ניטרלי; מילוי אזורים.
שימוש מומלץ
מומנטום/היפוכים: כניסה עם חציה מה-OS/OB ואישור מה-MTF.
ממוצע נע/רמות מחיר: חברו לאימות מגמה (למשל EMA200 או תמיכה/התנגדות).
Mean Reversion: חיפוש חזרה מאזורי קיצון, במיוחד כשיש התרעת יציאה מ-OB/OS או נגיעה בבנד אדפטיבי.
קלטים מרכזיים
CCI Period, Stoch Period, Smooth K/D – פרמטרי חישוב.
Overbought / Oversold – ספי קיצון (ברירת מחדל 80/20).
Line to plot – בחירה בין K או D.
Show Arrows/Center/Exit/Enter – שליטה בתצוגת החיצים.
Adaptive Bands (len, k) – חלון ורגישות לבנדים.
Higher TF – טיימפריים לאישור (אופציונלי).
Live Label – ספרות, היסט ברים, צבעי רקע.
טיפים מהירים
בסקלפים/טווחים קצרים: הקשיחו ספי קיצון (למשל 85/15) להפחתת רעש.
בשוק תנודתי: העלו את adaptLen או הורידו את k כדי לקבל בנדים רגישים פחות.
להקטנת אותות שווא: דרשו התאמה בין הסיגנל המקומי ל-MTF (לדוגמה, לונג רק כשה-MTF מעל 50).
הערה חשובה
זהו כלי ניתוח טכני—לא אות קנייה/מכירה בפני עצמו. שלבו אותו עם ניהול סיכונים (SL/TP), בדיקת רמות מפתח ואימות ממספר אינדיקטורים או טיימפריימים.
Cardwell RSI by TQ📌 Cardwell RSI – Enhanced Relative Strength Index
This indicator is based on Andrew Cardwell’s RSI methodology , extending the classic RSI with tools to better identify bullish/bearish ranges and trend dynamics.
In uptrends, RSI tends to hold between 40–80 (Cardwell bullish range).
In downtrends, RSI tends to stay between 20–60 (Cardwell bearish range).
Key Features :
Standard RSI with configurable length & source
Fast (9) & Slow (45) RSI Moving Averages (toggleable)
Cardwell Core Levels (80 / 60 / 40 / 20) – enabled by default
Base Bands (70 / 50 / 30) in dotted style
Optional custom levels (up to 3)
Alerts for MA crosses and level crosses
Data Window metrics: RSI vs Fast/Slow MA differences
How to Use :
Monitor RSI behavior inside Cardwell’s bullish (40–80) and bearish (20–60) ranges
Watch RSI crossovers with Fast (9) and Slow (45) MAs to confirm momentum or trend shifts
Use levels and alerts as confluence with your trading strategy
Default Settings :
RSI Length: 14
MA Type: WMA
Fast MA: 9 (hidden by default)
Slow MA: 45 (hidden by default)
Cardwell Levels (80/60/40/20): ON
Base Bands (70/50/30): ON
Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI
What this is
A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts:
• A sensitivity window that scans several recent bars to capture the strongest up and down impulses.
• A selectable moving average that smooths those impulses before computing RSI.
The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection.
How it works
Impulse extraction
• For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price.
• It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise.
MA-based averaging
• The up and down impulse series are averaged with your chosen MA over rsi_len bars.
• Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA.
Zero-centered RSI transform
• RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) .
• Above 0 implies positive momentum bias. Below 0 implies negative momentum bias.
Optional extra smoothing
• A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”.
Visual encoding
• The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes.
• Static bands mark 80 to 100 and −80 to −100 for extreme conditions.
Key inputs and what they change
• Price Source : input series for momentum.
• Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower.
• Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts.
• Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower.
• Smoothing Type and Length : optional second pass to calm noise on the final output.
• UI toggles : show or hide the oscillator, candle painting, and extreme bands.
Reading the oscillator
• Midline cross up (0) : momentum bias turning positive.
• Midline cross down (0) : momentum bias turning negative.
• Positive territory :
– 0 to 40: constructive but not stretched.
– 40 to 80: strong momentum, continuation more likely.
– Above 80: extreme risk of mean reversion grows.
• Negative territory : mirror the same levels for the downside.
Divergence detection
The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR .
• Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion.
• Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up.
• Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion.
• Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down.
Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish.
Candle coloring
• Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only.
Strengths
• Adaptive sensitivity via a rolling impulse window that responds to genuine bursts.
• Configurable MA core so you can match responsiveness to the instrument.
• Zero-centered scale for simple regime reads with 0 as a clear bias line.
• Built-in regular and hidden divergence mapping.
• Flexible across symbols and timeframes once tuned.
Limitations and cautions
• Trends can remain extended. Treat extremes as context rather than automatic reversal signals.
• Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag.
• Double smoothing can delay zero-line transitions. Balance smoothness and timeliness.
Practical usage ideas
• Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0.
• Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends.
• Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence.
• Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts.
Alerts
• MA-A RSI Long : oscillator crosses above 0.
• MA-A RSI Short : oscillator crosses below 0.
Use these as bias or timing aids, not standalone trade commands.
Settings quick reference
• Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity.
• Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing.
• UI : Show Oscillator, Paint Candles, Show Static High and Low Levels.
• Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences.
Final thoughts
This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.
Aroon ADX/DIUnified trend-strength (ADX/DI) + trend-age (Aroon) with centered scaling, gated signals, regime tints, and a compact readout.
What is different about this script:
- Purpose-built mashup of ADX/DI tells trend strength and side, while Aroon Oscillator tracks trend emergence/aging. Combining them into a scaled chart creates a way to separate “strong-but-late” trends from “newly-emerging” ones.
- Unified scale: Centering the maps into a common +/- 100 range so all lines are directly comparable at a glance (no units mismatch or fumbling with scales).
- Signal quality gating: DI cross signals can be gated by minimum ADX so crosses in chop are filtered out.
- Regime context: Background tints show low-strength chop, developing, and strong regimes using your ADX thresholds.
- Operator-focused UI: Clean fills, color-blind palette, and a two-column table summarizing DI+, DI−, ADX, Aroon, and a plain-English Bias/Trend status.
How it works:
- DI+/DI−/ADX: Wilder’s DI is smoothed; DX → ADX via SMA smoothing.
- Aroon Oscillator: highlights new highs/lows frequency to infer trend
- Centering: Maps DI/ADX from 5-95 and ±100, with your Midpoint controlling where “0” sits in raw mode.
- Signals:
- Bullish/Bearish DI crosses, optionally allowed only when ADX ≥ Min.
- ADX crosses of your Low/High thresholds.
- Aroon crosses of 0, +80, −80 (fresh trend thresholds).
- Display aids: Optional fill between DI+/DI−; thin guides for thresholds; single-pane table summary.
How to use:
- For this to be useful, centering should stay on, modify ADX Low/High and monitor DI crosses with ADX.
- Interpretations:
Bias: DI+ above DI− = bull; below = bear.
Strength level: ADX < Low = chop, Low–High = developing, > High = strong.
Freshness: Aroon > +80 or crossing up 0 suggests new or continued bull push; < −80 or crossing down 0 suggests new or continued bear push.
- Alerts: Use built-ins for DI crosses, ADX regime changes, and Aroon thresholds.
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
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1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
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2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
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3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
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4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
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5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
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6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
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7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
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8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
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9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
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1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
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2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
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3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
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4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
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5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
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6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
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7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
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8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
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9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
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⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
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⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Dual Volume Profiles: Session + Rolling (Range Delineation)Dual Volume Profiles: Session + Rolling (Range Delineation)
INTRO
This is a probability-centric take on volume profile. I treat the volume histogram as an empirical PDF over price, updated in real time, which makes multi-modality (multiple acceptance basins) explicit rather than assumed away. The immediate benefit is operational: if we can read the shape of the distribution, we can infer likely reversion levels (POC), acceptance boundaries (VAH/VAL), and low-friction corridors (LVNs).
My working hypothesis is that what traders often label “fat tails” or “power-law behavior” at short horizons is frequently a tail-conditioned view of a higher-level Gaussian regime. In other words, child distributions (shorter periodicities) sit within parent distributions (longer periodicities); when price operates in the parent’s tail, the child regime looks heavy-tailed without being fundamentally non-Gaussian. This is consistent with a hierarchical/mixture view and with the spirit of the central limit theorem—Gaussian structure emerges at aggregate scales, while local scales can look non-Gaussian due to nesting and conditioning.
This indicator operationalizes that view by plotting two nested empirical PDFs: a rolling (local) profile and a session-anchored profile. Their confluence makes ranges explicit and turns “regime” into something you can see. For additional nesting, run multiple instances with different lookbacks. When using the default settings combined with a separate daily VP, you effectively get three nested distributions (local → session → daily) on the chart.
This indicator plots two nested distributions side-by-side:
Rolling (Local) Profile — short-window, prorated histogram that “breathes” with price and maps the immediate auction.
Session Anchored Profile — cumulative distribution since the current session start (Premkt → RTH → AH anchoring), revealing the parent regime.
Use their confluence to identify range floors/ceilings, mean-reversion magnets, and low-volume “air pockets” for fast traverses.
What it shows
POC (dashed): central tendency / “magnet” (highest-volume bin).
VAH & VAL (solid): acceptance boundaries enclosing an exact Value Area % around each profile’s POC.
Volume histograms:
Rolling can auto-color by buy/sell dominance over the lookback (green = buying ≥ selling, red = selling > buying).
Session uses a fixed style (blue by default).
Session anchoring (exchange timezone):
Premarket → anchors at 00:00 (midnight).
RTH → anchors at 09:30.
After-hours → anchors at 16:00.
Session display span:
Session Max Span (bars) = 0 → draw from session start → now (anchored).
> 0 → draw a rolling window N bars back → now, while still measuring all volume since session start.
Why it’s useful
Think in terms of nested probability distributions: the rolling node is your local Gaussian; the session node is its parent.
VA↔VA overlap ≈ strong range boundary.
POC↔POC alignment ≈ reliable mean-reversion target.
LVNs (gaps) ≈ low-friction corridors—expect quick moves to the next node.
Quick start
Add to chart (great on 5–10s, 15–60s, 1–5m).
Start with: bins = 240, vaPct = 0.68, barsBack = 60.
Watch for:
First test & rejection at overlapping VALs/VAHs → fade back toward POC.
Acceptance beyond VA (several closes + growing outer-bin mass) → traverse to the next node.
Inputs (detailed)
General
Lookback Bars (Rolling)
Count of most-recent bars for the rolling/local histogram. Larger = smoother node that shifts slower; smaller = more reactive, “breathing” profile.
• Typical: 40–80 on 5–10s charts; 60–120 on 1–5m.
• If you increase this but keep Number of Bins fixed, each bin aggregates more volume (coarser bins).
Number of Bins
Vertical resolution (price buckets) for both rolling and session histograms. Higher = finer detail and crisper LVNs, but more line objects (closer to platform limits).
• Typical: 120–240 on 5–10s; 80–160 on 1–5m.
• If you hit performance or object limits, reduce this first.
Value Area %
Exact central coverage for VAH/VAL around POC. Computed empirically from the histogram (no Gaussian assumption): the algorithm expands from POC outward until the chosen % is enclosed.
• Common: 0.68 (≈“1σ-like”), 0.70 for slightly wider core.
• Smaller = tighter VA (more breakout flags). Larger = wider VA (more reversion bias).
Max Local Profile Width (px)
Horizontal length (in pixels) of the rolling bars/lines and its VA/POC overlays. Visual only (does not affect calculations).
Session Settings
RTH Start/End (exchange tz)
Defines the current session anchor (Premkt=00:00, RTH=your start, AH=your end). The session histogram always measures from the most recent session start and resets at each boundary.
Session Max Span (bars, 0 = full session)
Display window for session drawings (POC/VA/Histogram).
• 0 → draw from session start → now (anchored).
• > 0 → draw N bars back → now (rolling look), while still measuring all volume since session start.
This keeps the “parent” distribution measurable while letting the display track current action.
Local (Rolling) — Visibility
Show Local Profile Bars / POC / VAH & VAL
Toggle each overlay independently. If you approach object limits, disable bars first (POC/VA lines are lighter).
Local (Rolling) — Colors & Widths
Color by Buy/Sell Dominance
Fast uptick/downtick proxy over the rolling window (close vs open):
• Buying ≥ Selling → Bullish Color (default lime).
• Selling > Buying → Bearish Color (default red).
This color drives local bars, local POC, and local VA lines.
• Disable to use fixed Bars Color / POC Color / VA Lines Color.
Bars Transparency (0–100) — alpha for the local histogram (higher = lighter).
Bars Line Width (thickness) — draw thin-line profiles or chunky blocks.
POC Line Width / VA Lines Width — overlay thickness. POC is dashed, VAH/VAL solid by design.
Session — Visibility
Show Session Profile Bars / POC / VAH & VAL
Independent toggles for the session layer.
Session — Colors & Widths
Bars/POC/VA Colors & Line Widths
Fixed palette by design (default blue). These do not change with buy/sell dominance.
• Use transparency and width to make the parent profile prominent or subtle.
• Prefer minimal? Hide session bars; keep only session VA/POC.
Reading the signals (detailed playbook)
Core definitions
POC — highest-volume bin (fair price “magnet”).
VAH/VAL — upper/lower bounds enclosing your Value Area % around POC.
Node — contiguous block of high-volume bins (acceptance).
LVN — low-volume gap between nodes (low friction path).
Rejection vs Acceptance (practical rule)
Rejection at VA edge: 0–1 closes beyond VA and no persistent growth in outer bins.
Acceptance beyond VA: ≥3 closes beyond VA and outer-bin mass grows (e.g., added volume beyond the VA edge ≥ 5–10% of node volume over the last N bars). Treat acceptance as regime change.
Confluence scores (make boundary/target quality objective)
VA overlap strength (range boundary):
C_VA = 1 − |VA_edge_local − VA_edge_session| / ATR(n)
Values near 1.0 = tight overlap (stronger boundary).
Use: if C_VA ≥ 0.6–0.8, treat as high-quality fade zone.
POC alignment (magnet quality):
C_POC = 1 − |POC_local − POC_session| / ATR(n)
Higher C_POC = greater chance a rotation completes to that fair price.
(You can estimate these by eye.)
Setups
1) Range Fade at VA Confluence (mean reversion)
Context: Local VAL/VAH near Session VAL/VAH (tight overlap), clear node, local color not screaming trend (or flips to your side).
Entry: First test & rejection at the overlapped band (wick through ok; prefer close back inside).
Stop: A tick/pip beyond the wider of the two VA edges or beyond the nearest LVN, a small buffer zone can be used to judge whether price is truly rejecting a VAL/VAH or simply probing.
Targets: T1 node mid; T2 POC (size up when C_POC is high).
Flip: If acceptance (rule above) prints, flip bias or stand down.
2) LVN Traverse (continuation)
Context: Price exits VA and enters an LVN with acceptance and growing outer-bin volume.
Entry: Aggressive—first close into LVN; Conservative—retest of the VA edge from the far side (“kiss goodbye”).
Stop: Back inside the prior VA.
Targets: Next node’s VA edge or POC (edge = faster exits; POC = fuller rotations).
Note: Flatter VA edge (shallower curvature) tends to breach more easily.
3) POC→POC Magnet Trade (rotation completion)
Context: Local POC ≈ Session POC (high C_POC).
Entry: Fade a VA touch or pullback inside node, aiming toward the shared POC.
Stop: Past the opposite VA edge or LVN beyond.
Target: The shared POC; optional runner to opposite VA if the node is broad and time-of-day is supportive.
4) Failed Break (Reversion Snap-back)
Context: Push beyond VA fails acceptance (re-enters VA, outer-bin growth stalls/shrinks).
Entry: On the re-entry close, back toward POC.
Stop/Target: Stop just beyond the failed VA; target POC, then opposite VA if momentum persists.
How to read color & shape
Local color = most recent sentiment:
Green = buying ≥ selling; Red = selling > buying (over the rolling window). Treat as context, not a standalone signal. A green local node under a blue session VAH can still be a fade if the parent says “over-valued.”
Shape tells friction:
Fat nodes → rotation-friendly (fade edges).
Sharp LVN gaps → traversal-friendly (momentum continuation).
Time-of-day intuition
Right after session anchor (e.g., RTH 09:30): Session profile is young and moves quickly—treat confluence cautiously.
Mid-session: Cleanest behavior for rotations.
Close / news: Expect more traverses and POC migrations; tighten risk or switch playbooks.
Risk & execution guidance
Use tight, mechanical stops at/just beyond VA or LVN. If you need wide stops to survive noise, your entry is late or the node is unstable.
On micro-timeframes, account for fees & slippage—aim for targets paying ≥2–3× average cost.
If acceptance prints, don’t fight it—flip, reduce size, or stand aside.
Suggested presets
Scalp (5–10s): bins 120–240, barsBack 40–80, vaPct 0.68–0.70, local bars thin (small bar width).
Intraday (1–5m): bins 80–160, barsBack 60–120, vaPct 0.68–0.75, session bars more visible for parent context.
Performance & limits
Reuses line objects to stay under TradingView’s max_lines_count.
Very large bins × multiple overlays can still hit limits—use visibility toggles (hide bars first).
Session drawings use time-based coordinates to avoid “bar index too far” errors.
Known nuances
Rolling buy/sell dominance uses a simple uptick/downtick proxy (close vs open). It’s fast and practical, but it’s not a full tape classifier.
VA boundaries are computed from the empirical histogram—no Gaussian assumption.
This script does not calculate the full daily volume profile. Several other tools already provide that, including TradingView’s built-in Volume Profile indicators. Instead, this indicator focuses on pairing a rolling, short-term volume distribution with a session-wide distribution to make ranges more explicit. It is designed to supplement your use of standard or periodic volume profiles, not replace them. Think of it as a magnifying lens that helps you see where local structure aligns with the broader session.
How to trade it (TL;DR)
Fade overlapping VA bands on first rejection → target POC.
Continue through LVN on acceptance beyond VA → target next node’s VA/POC.
Respect acceptance: ≥3 closes beyond VA + growing outer-bin volume = regime change.
FAQ
Q: Why 68% Value Area?
A: It mirrors the “~1σ” idea, but we compute it exactly from empirical volume, not by assuming a normal distribution.
Q: Why are my profiles thin lines?
A: Increase Bars Line Width for chunkier blocks; reduce for fine, thin-line profiles.
Q: Session bars don’t reach session start—why?
A: Set Session Max Span (bars) = 0 for full anchoring; any positive value draws a rolling window while still measuring from session start.
Changelog (v1.0)
Dual profiles: Rolling + Session with independent POC/VA lines.
Session anchoring (Premkt/RTH/AH) with optional rolling display span.
Dynamic coloring for the rolling profile (buying vs selling).
Fully modular toggles + per-feature colors/widths.
Thin-line rendering via bar line width.
Smart Money Proxy IndexOverview
The Smart Money Proxy Index (SMPI) is an educational tool that attempts to identify potential institutional-style behavior patterns using publicly available market data. This comprehensive tool combines multiple institutional analysis techniques into a single, easy-to-read 0-100 oscillator.
Important Disclaimer
This is an educational proxy indicator that analyzes volume and price patterns. It cannot identify actual institutional trading activity and should not be interpreted as tracking real "smart money." Use for educational purposes and combine with other analysis methods.
Inspiration & Methodology
This indicator is inspired by MAPsignals' Big Money Index (BMI) methodology but uses publicly available price and volume data with original calculations. This is an independent educational interpretation designed to teach smart money concepts to retail traders.
What It Analyzes
SMPI tracks potential "smart money" activity by combining:
Block Trading Detection - Identifies unusual volume surges with significant price impact
Money Flow Analysis - Volume-weighted price pressure using Money Flow Index
Accumulation/Distribution Patterns - Modified On-Balance Volume signals
Institutional Control Proxy - End-of-day positioning and control analysis
Key Features
– Multi-Component Analysis - Combines 4 different institutional detection methods
– BMI-Style 0-100 Scale - Familiar oscillator range with clear extreme levels
– Professional Visualization - Dynamic colors, gradient fills, and clean data table
– Comprehensive Alerts - Buy/sell signals plus divergence detection
– Fully Customizable - Adjust all parameters, colors, and display options
– Non-Repainting Signals - All alerts use confirmed data for reliability
– Educational Focus - Designed to teach institutional flow concepts
How to Interpret
Above 80: Potential smart money distribution phase (bearish pressure)
Below 20: Potential smart money accumulation phase (bullish opportunity)
Signal Generation: Buy signals when crossing above 20, sell signals when crossing below 80
Divergences: Price vs SMPI divergences can signal potential trend changes
Volume Confirmation: Higher volume ratios strengthen signal reliability
Best Practices
Timeframes: Works best on higher timeframes for institutional behavior analysis
Confirmation: Combine with other technical analysis tools and market context
Volume: Pay attention to volume confirmation in the data table
Context: Consider overall market conditions and fundamental factors
Risk Management: Not recommended as standalone trading system
Customizable Parameters
Block Volume Threshold: Sensitivity for unusual volume detection (default: 2.5x average)
SMPI Smoothing Period: Index calculation smoothing (default: 25 bars)
Extreme Levels: Overbought/oversold thresholds (default: 80/20)
Money Flow Length: MFI calculation period (default: 14)
Visual Options: Colors, signals, and display preferences
Available Alerts
Buy Signal: SMPI crosses above oversold level (20)
Sell Signal: SMPI crosses below overbought level (80)
Extreme Levels: Alerts when reaching overbought/oversold zones
Divergence Detection: Bullish and bearish price vs SMPI divergences
Educational Purpose & Limitations
This indicator is designed as an educational proxy for understanding institutional flow concepts. It analyzes publicly available price and volume data to identify potential smart money behavior patterns.
Cannot access actual institutional transaction data
Signals may be slower than day-trading indicators (intentionally designed for institutional timeframes)
Should be used in conjunction with other analysis methods
Past performance does not guarantee future results
What Makes This Different
Unlike simple volume or momentum indicators, SMPI combines multiple institutional analysis techniques into one comprehensive tool. The multi-component approach provides a more robust view of potential smart money activity.
MACD Liquidity Tracker Strategy [Quant Trading]MACD Liquidity Tracker Strategy
Overview
The MACD Liquidity Tracker Strategy is an enhanced trading system that transforms the traditional MACD indicator into a comprehensive momentum-based strategy with advanced visual signals and risk management. This strategy builds upon the original MACD Liquidity Tracker System indicator by TheNeWSystemLqtyTrckr , converting it into a fully automated trading strategy with improved parameters and additional features.
What Makes This Strategy Original
This strategy significantly enhances the basic MACD approach by introducing:
Four distinct system types for different market conditions and trading styles
Advanced color-coded histogram visualization with four dynamic colors showing momentum strength and direction
Integrated trend filtering using 9 different moving average types
Comprehensive risk management with customizable stop-loss and take-profit levels
Multiple alert systems for entry signals, exits, and trend conditions
Flexible signal display options with customizable entry markers
How It Works
Core MACD Calculation
The strategy uses a fully customizable MACD configuration with traditional default parameters:
Fast MA : 12 periods (customizable, minimum 1, no maximum limit)
Slow MA : 26 periods (customizable, minimum 1, no maximum limit)
Signal Line : 9 periods (customizable, now properly implemented and used)
Cryptocurrency Optimization : The strategy's flexible parameter system allows for significant optimization across different crypto assets. Traditional MACD settings (12/26/9) often generate excessive noise and false signals in volatile crypto markets. By using slower, more smoothed parameters, traders can capture meaningful momentum shifts while filtering out market noise.
Example - DOGE Optimization (45/80/290 settings) :
• Performance : Optimized parameters yielding exceptional backtesting results with 29,800% PnL
• Why it works : DOGE's high volatility and social sentiment-driven price action benefits from heavily smoothed indicators
• Timeframes : Particularly effective on 30-minute and 4-hour charts for swing trading
• Logic : The very slow parameters filter out noise and capture only the most significant trend changes
Other Optimizable Cryptocurrencies : This parameter flexibility makes the strategy highly effective for major altcoins including SUI, SEI, LINK, Solana (SOL) , and many others. Each crypto asset can benefit from custom parameter tuning based on its unique volatility profile and trading characteristics.
Four Trading System Types
1. Normal System (Default)
Long signals : When MACD line is above the signal line
Short signals : When MACD line is below the signal line
Best for : Swing trading and capturing longer-term trends in stable markets
Logic : Traditional MACD crossover approach using the signal line
2. Fast System
Long signals : Bright Blue OR Dark Magenta (transparent) histogram colors
Short signals : Dark Blue (transparent) OR Bright Magenta histogram colors
Best for : Scalping and high-volatility markets (crypto, forex)
Logic : Leverages early momentum shifts based on histogram color changes
3. Safe System
Long signals : Only Bright Blue histogram color (strongest bullish momentum)
Short signals : All other colors (Dark Blue, Bright Magenta, Dark Magenta)
Best for : Risk-averse traders and choppy markets
Logic : Prioritizes only the strongest bullish signals while treating everything else as bearish
4. Crossover System
Long signals : MACD line crosses above signal line
Short signals : MACD line crosses below signal line
Best for : Precise timing entries with traditional MACD methodology
Logic : Pure crossover signals for more precise entry timing
Color-Coded Histogram Logic
The strategy uses four distinct colors to visualize momentum:
🔹 Bright Blue : MACD > 0 and rising (strong bullish momentum)
🔹 Dark Blue (Transparent) : MACD > 0 but falling (weakening bullish momentum)
🔹 Bright Magenta : MACD < 0 and falling (strong bearish momentum)
🔹 Dark Magenta (Transparent) : MACD < 0 but rising (weakening bearish momentum)
Trend Filter Integration
The strategy includes an advanced trend filter using 9 different moving average types:
SMA (Simple Moving Average)
EMA (Exponential Moving Average) - Default
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
LSMA (Least Squares Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
VIDYA (Variable Index Dynamic Average)
Default Settings : 50-period EMA for trend identification
Visual Signal System
Entry Markers : Blue triangles (▲) below candles for long entries, Magenta triangles (▼) above candles for short entries
Candle Coloring : Price candles change color based on active signals (Blue = Long, Magenta = Short)
Signal Text : Optional "Long" or "Short" text inside entry triangles (toggleable)
Trend MA : Gray line plotted on main chart for trend reference
Parameter Optimization Examples
DOGE Trading Success (Optimized Parameters) :
Using 45/80/290 MACD settings with 50-period EMA trend filter has shown exceptional results on DOGE:
Performance : Backtesting results showing 29,800% PnL demonstrate the power of proper parameter optimization
Reasoning : DOGE's meme-driven volatility and social sentiment spikes create significant noise with traditional MACD settings
Solution : Very slow parameters (45/80/290) filter out social media-driven price spikes while capturing only major momentum shifts
Optimal Timeframes : 30-minute and 4-hour charts for swing trading opportunities
Result : Exceptionally clean signals with minimal false entries during DOGE's characteristic pump-and-dump cycles
Multi-Crypto Adaptability :
The same optimization principles apply to other major cryptocurrencies:
SUI : Benefits from smoothed parameters due to newer coin volatility patterns
SEI : Requires adjustment for its unique DeFi-related price movements
LINK : Oracle news events create price spikes that benefit from noise filtering
Solana (SOL) : Network congestion events and ecosystem developments need smoothed detection
General Rule : Higher volatility coins typically benefit from very slow MACD parameters (40-50 / 70-90 / 250-300 ranges)
Key Input Parameters
System Type : Choose between Fast, Normal, Safe, or Crossover (Default: Normal)
MACD Fast MA : 12 periods default (no maximum limit, consider 40-50 for crypto optimization)
MACD Slow MA : 26 periods default (no maximum limit, consider 70-90 for crypto optimization)
MACD Signal MA : 9 periods default (now properly utilized, consider 250-300 for crypto optimization)
Trend MA Type : EMA default (9 options available)
Trend MA Length : 50 periods default (no maximum limit)
Signal Display : Both, Long Only, Short Only, or None
Show Signal Text : True/False toggle for entry marker text
Trading Applications
Recommended Use Cases
Momentum Trading : Capitalize on strong directional moves using the color-coded system
Trend Following : Combine MACD signals with trend MA filter for higher probability trades
Scalping : Use "Fast" system type for quick entries in volatile markets
Swing Trading : Use "Normal" or "Safe" system types for longer-term positions
Cryptocurrency Trading : Optimize parameters for individual crypto assets (e.g., 45/80/290 for DOGE, custom settings for SUI, SEI, LINK, SOL)
Market Suitability
Volatile Markets : Forex, crypto, indices (recommend "Fast" system or smoothed parameters)
Stable Markets : Stocks, ETFs (recommend "Normal" or "Safe" system)
All Timeframes : Effective from 1-minute charts to daily charts
Crypto Optimization : Each major cryptocurrency (DOGE, SUI, SEI, LINK, SOL, etc.) can benefit from custom parameter tuning. Consider slower MACD parameters for noise reduction in volatile crypto markets
Alert System
The strategy provides comprehensive alerts for:
Entry Signals : Long and short entry triangle appearances
Exit Signals : Position exit notifications
Color Changes : Individual histogram color alerts
Trend Conditions : Price above/below trend MA alerts
Strategy Parameters
Default Settings
Initial Capital : $1,000
Position Size : 100% of equity
Commission : 0.1%
Slippage : 3 points
Date Range : January 1, 2018 to December 31, 2069
Risk Management (Optional)
Stop Loss : Disabled by default (customizable percentage-based)
Take Profit : Disabled by default (customizable percentage-based)
Short Trades : Disabled by default (can be enabled)
Important Notes and Limitations
Backtesting Considerations
Uses realistic commission (0.1%) and slippage (3 points)
Default position sizing uses 100% equity - adjust based on risk tolerance
Stop-loss and take-profit are disabled by default to show raw strategy performance
Strategy does not use lookahead bias or future data
Risk Warnings
Past performance does not guarantee future results
MACD-based strategies may produce false signals in ranging markets
Consider combining with additional confluences like support/resistance levels
Test thoroughly on demo accounts before live trading
Adjust position sizing based on your risk management requirements
Technical Limitations
Strategy does not work on non-standard chart types (Heikin Ashi, Renko, etc.)
Signals are based on close prices and may not reflect intraday price action
Multiple rapid signals in volatile conditions may result in overtrading
Credits and Attribution
This strategy is based on the original "MACD Liquidity Tracker System" indicator created by TheNeWSystemLqtyTrckr . This strategy version includes significant enhancements:
Complete strategy implementation with entry/exit logic
Addition of the "Crossover" system type
Proper implementation and utilization of the MACD signal line
Enhanced risk management features
Improved parameter flexibility with no artificial maximum limits
Additional alert systems for comprehensive trade management
The original indicator's core color logic and visual system have been preserved while expanding functionality for automated trading applications.
Stochastic RSI with MTF TableShort Description of the Script
The provided Pine Script indicator, titled "Stochastic RSI with MTF Table," calculates and displays the Stochastic RSI for the current timeframe and multiple other timeframes (5m, 15m, 30m, 60m, 240m, and daily). The Stochastic RSI is a momentum indicator that blends the Relative Strength Index (RSI) and Stochastic Oscillator to identify overbought and oversold conditions, as well as potential trend reversals via K and D line crossovers.
Key features of the script include:
Inputs: Customizable parameters such as K smoothing (default 3), D smoothing (default 3), RSI length (default 14), Stochastic length (default 14), source price (default close), and overbought/oversold levels (default 80/20).
MTF Table: A table displays the Stochastic RSI status for each timeframe:
"OB" (overbought) if K > 80, "OS" (oversold) if K < 20, or "N" (neutral) otherwise.
Crossovers: "K↑D" for bullish (K crosses above D) and "K↓D" for bearish (K crosses below D).
Visualization: Plots the K and D lines for the current timeframe, with horizontal lines at 80 (overbought), 50 (middle), and 20 (oversold), plus a background fill for clarity.
Table Position: Configurable to appear in one of four chart corners (default: top-right).
This indicator helps traders assess momentum across multiple timeframes simultaneously, aiding in the identification of trend strength and potential entry/exit points.
Trading Strategy with 50EMA and 200EMA for Highest Winning Rate
To create a strategy with the best probability of a high winning rate using the Stochastic RSI MTF indicator alongside the 50-period Exponential Moving Average (50EMA) and 200-period Exponential Moving Average (200EMA), we can combine trend identification with momentum-based entry timing. The 50EMA and 200EMA are widely used to determine medium- and long-term trends, while the Stochastic RSI MTF table provides multi-timeframe momentum signals. Here’s the strategy:
1. Determine the Overall Trend
Bullish Trend: The 50EMA is above the 200EMA on the current timeframe (e.g., daily or 60m chart). This suggests an uptrend, often associated with a "Golden Cross."
Bearish Trend: The 50EMA is below the 200EMA on the current timeframe. This indicates a downtrend, often linked to a "Death Cross."
Implementation: Plot the 50EMA and 200EMA on your chart and visually confirm their relative positions.
2. Identify Entry Signals Using the Stochastic RSI MTF Table
In a Bullish Trend (50EMA > 200EMA):
Look for timeframes in the MTF table showing:
Oversold (OS): K < 20, indicating a potential pullback in the uptrend where price may rebound.
Bullish Crossover (K↑D): K crosses above D, signaling rising momentum and a potential entry point.
Example: If the 60m and 240m timeframes show "OS" or "K↑D," this could be a buy signal.
In a Bearish Trend (50EMA < 200EMA):
Look for timeframes in the MTF table showing:
Overbought (OB): K > 80, suggesting a rally in the downtrend where price may reverse downward.
Bearish Crossover (K↓D): K crosses below D, indicating declining momentum and a potential short entry.
Example: If the 30m and daily timeframes show "OB" or "K↓D," this could be a sell/short signal.
Current Timeframe Check: Use the plotted K and D lines on your trading timeframe for precise entry timing (e.g., confirm a K↑D crossover on a 60m chart for a long trade).
3. Confirm Signals Across Multiple Timeframes
Strengthen the Signal: A higher winning rate is more likely when multiple timeframes align with the trend and signal. For instance:
Bullish trend + "OS" or "K↑D" on 60m, 240m, and daily = strong buy signal.
Bearish trend + "OB" or "K↓D" on 15m, 60m, and 240m = strong sell signal.
Prioritize Higher Timeframes: Signals from the 240m or daily timeframe carry more weight due to their indication of broader trends, increasing reliability.
4. Set Stop-Loss and Take-Profit Levels
Long Trades (Bullish):
Stop-Loss: Place below the most recent swing low or below the 50EMA, whichever is closer, to protect against trend reversals.
Take-Profit: Target a key resistance level or use a risk-reward ratio (e.g., 2:1 or 3:1) based on the stop-loss distance.
Short Trades (Bearish):
Stop-Loss: Place above the most recent swing high or above the 50EMA, whichever is closer.
Take-Profit: Target a key support level or apply a similar risk-reward ratio.
Trailing Stop Option: As the trend progresses, trail the stop below the 50EMA (for longs) or above it (for shorts) to lock in profits.
5. Risk Management
Position Sizing: Risk no more than 1-2% of your trading capital per trade to minimize losses from false signals.
Volatility Consideration: Adjust stop-loss distances and position sizes based on the asset’s volatility (e.g., wider stops for volatile stocks or crypto).
Avoid Overtrading: Wait for clear alignment between the EMA trend and MTF signals to avoid low-probability setups.
Example Scenario
Chart: 60-minute timeframe.
Trend: 50EMA > 200EMA (bullish).
MTF Table: 60m shows "OS," 240m shows "K↑D," and daily is "N."
Action: Enter a long position when the 60m K line crosses above D, confirming the table signal.
Stop-Loss: Below the recent 60m swing low (e.g., 2% below entry).
Take-Profit: At the next resistance level or a 3:1 reward-to-risk ratio.
Outcome: High probability of success due to trend alignment and multi-timeframe confirmation.
Why This Strategy Works
Trend Following: Trading in the direction of the 50EMA/200EMA trend reduces the risk of fighting the market’s momentum.
Momentum Timing: The Stochastic RSI MTF table pinpoints pullbacks or reversals within the trend, improving entry timing.
Multi-Timeframe Confirmation: Alignment across timeframes filters out noise, increasing the win rate.
Risk Control: Defined stop-loss and position sizing protect against inevitable losses.
Caveats
No strategy guarantees a 100% win rate; false signals can occur, especially in choppy markets.
Test this strategy on historical data or a demo account to verify its effectiveness for your asset and timeframe.
This approach leverages the strengths of both trend-following (EMA) and momentum (Stochastic RSI) tools, aiming for a high-probability, disciplined trading system.
Normalized MACD with RSI & Stoch RSI + SignalsNormalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
Here’s a clear and concise description of your updated Pine Script indicator:
⸻
Normalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
⸻
Key Components:
① MACD (Normalized):
• The Moving Average Convergence Divergence (MACD) originally has an unlimited numerical range.
• Normalization Method:
• Uses a custom tanh(x) function implemented directly in Pine Script:
\tanh(x) = \frac{e^{x}-e^{-x}}{e^{x}+e^{-x}}
• MACD values are scaled using this method to a range of 0–100, with the neutral line at exactly 50.
• Interpretation:
• Values above 50 indicate bullish momentum.
• Values below 50 indicate bearish momentum.
② RSI (Relative Strength Index):
• Measures market momentum on a 0–100 scale.
• Traditional RSI interpretation:
• Overbought conditions: RSI > 70–80.
• Oversold conditions: RSI < 30–20.
③ Stochastic RSI:
• Combines RSI and Stochastic Oscillator to give short-term, highly sensitive signals.
• Helps identify immediate market extremes:
• Above 80 → Short-term overbought.
• Below 20 → Short-term oversold.
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How the Indicator Works:
• Visualization:
• All three indicators (Normalized MACD, RSI, Stochastic RSI) share the same 0–100 scale.
• Clear visual lines and reference levels:
• Midline at 50 indicates neutral momentum.
• Dashed lines at 20 and 80 clearly mark oversold/overbought zones.
• Trading Signals (Recommended approach):
• Bullish Signal (Potential Buy):
• Normalized MACD crosses above 50.
• RSI below or approaching oversold zone (below 30–20).
• Stochastic RSI below 20, indicating short-term oversold conditions.
• Bearish Signal (Potential Sell):
• Normalized MACD crosses below 50.
• RSI above or approaching overbought zone (above 70–80).
• Stochastic RSI above 80, indicating short-term overbought conditions.
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Why Use This Indicator?
• Harmonized Signals:
Normalization of MACD significantly improves clarity and comparability with RSI and Stochastic RSI, providing a unified momentum picture.
• Intuitive Analysis:
Traders can rapidly and intuitively identify momentum shifts without needing multiple indicator windows.
• Improved Decision-Making:
Clear visual references and signals help reduce subjective interpretation, potentially improving trading outcomes.
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Suggested Usage:
• Combine with traditional support
Smart Volume S/R Pro [The_lurker]مؤشر "Smart Volume S/R Pro " هو أداة تحليل فني متقدمة مصممة لمساعدة المتداولين في تحديد مستويات الدعم والمقاومة القوية بناءً على حجم التداول، مع إضافة ميزات تحليلية متطورة مثل تصفية الاتجاه ، مناطق الثقة ، تقييم القوة ، حساب احتمالية الاختراق ، قياس السيولة ، تحديد الأهداف السعرية ، ومستويات فيبوناتشي . وايضا تقديم تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوقيهدف هذا المؤشر إلى توفير رؤية شاملة للسوق .
الوظائف الرئيسية للمؤشر
1- تحديد مستويات الدعم والمقاومة بناءً على حجم التداول العالي
يقوم المؤشر بتحليل الأشرطة (Bars) السابقة (حتى 300 شريط افتراضيًا) لتحديد النقاط التي شهدت أعلى مستويات حجم التداول.
يرسم خطوط أفقية تمثل مستويات المقاومة (عند أعلى سعر في تلك الأشرطة) والدعم (عند أدنى سعر)، ويمكن للمستخدم اختيار عدد الخطوط المعروضة (من 1 إلى 6).
2- تصفية الاتجاه باستخدام مؤشر ADX
يستخدم المؤشر مؤشر الاتجاه المتوسط (ADX) لتقييم قوة الاتجاه في السوق.
عندما تكون قوة الاتجاه عالية (تتجاوز عتبة محددة، 25 افتراضيًا)، يقلل المؤشر عدد مستويات الدعم والمقاومة المعروضة للتركيز فقط على المستويات الأكثر أهمية.
3- مناطق الثقة الديناميكية
يضيف المؤشر مناطق حول مستويات الدعم والمقاومة بناءً على متوسط المدى الحقيقي (ATR)، مما يساعد المتداولين على تصور النطاقات التي قد يتفاعل فيها السعر مع هذه المستويات.
يمكن تعديل عرض هذه المناطق باستخدام مضاعف ATR.
4- تقييم قوة المستويات
يحسب المؤشر قوة كل مستوى بناءً على حجم التداول، عدد المرات التي تم اختبار المستوى فيها (Touch Count)، وقرب السعر الحالي من المستوى.
يتم عرض درجة القوة (من 0 إلى 100) بجانب كل مستوى إذا تم تفعيل هذه الخاصية.
5- احتمالية الاختراق
يقدّر المؤشر احتمالية اختراق كل مستوى بناءً على الزخم (ROC)، قوة المستوى، والمسافة بين السعر الحالي والمستوى.
يظهر الاحتمال كنسبة مئوية إذا تم تفعيل الخيار، مما يساعد المتداولين على توقع الحركات المحتملة.
6- تحليل السيولة التاريخية
يقيس المؤشر السيولة حول كل مستوى بناءً على حجم التداول في النطاقات القريبة منه.
يمكن عرض قيم السيولة في التسميات أو استخدامها لتعديل عرض الخطوط (الخطوط الأكثر سيولة تظهر أعرض).
7- الأهداف السعرية
عند تفعيل هذه الخاصية، يحسب المؤشر أهداف سعرية للاختراق (Breakout) والارتداد (Reversal) بناءً على الزخم وقوة المستوى وATR.
يمكن عرض هذه الأهداف كنصوص في التسميات أو كخطوط أفقية على الرسم البياني.
8- مستويات فيبوناتشي
يرسم المؤشر مستويات فيبوناتشي (0.0، 0.236، 0.382، 0.5، 0.618، 0.786، 1.0) بناءً على أعلى وأدنى سعر في فترة النظرة الخلفية.
يمكن للمستخدم اختيار أي من هذه المستويات لعرضها أو إخفائها.
9- تنبيه شامل للاختراق
يوفر المؤشر تنبيهًا واحدًا يشمل جميع المستويات، حيث يُطلق التنبيه عندما يخترق السعر أي مستوى دعم أو مقاومة مع رسالة توضح نوع الاختراق والمستوى المخترق.
كيفية عمل المؤشر
الخطوة الأولى: يحدد المؤشر الأشرطة ذات الحجم العالي خلال فترة النظرة الخلفية المحددة (Lookback Period).
الخطوة الثانية: يرسم مستويات الدعم والمقاومة بناءً على أعلى وأدنى الأسعار في تلك الأشرطة، مع مراعاة عدد الخطوط المختارة من المستخدم.
الخطوة الثالثة: يطبق مرشح الاتجاه (إذا كان مفعلاً) لتقليل عدد المستويات في حالة الاتجاه القوي.
الخطوة الرابعة: يضيف التحليلات الإضافية مثل القوة، السيولة، احتمالية الاختراق، والأهداف السعرية، ويرسم مناطق الثقة ومستويات فيبوناتشي حسب الإعدادات.
الخطوة الخامسة: يراقب السعر ويطلق تنبيهًا عند الاختراق.
الإعدادات القابلة للتخصيص
1- فترة النظرة الخلفية (Lookback Period): عدد الأشرطة التي يتم تحليلها (افتراضيًا 300).
2- عدد الخطوط (Number of Lines): من 1 إلى 6 مستويات دعم ومقاومة.
3- الألوان والأنماط: يمكن تغيير ألوان الخطوط وأنماطها (ممتلئة، متقطعة، منقطة).
4- التسميات: تفعيل/تعطيل التسميات، وحجمها، وموقعها، ولون النص.
5- مرشح الاتجاه: تفعيل/تعطيل ADX، وتعديل طوله وعتبته.
6- مناطق الثقة: تفعيل/تعطيل، وتعديل طول ATR ومضاعفه.
7- القوة واحتمالية الاختراق: تفعيل/تعطيل العرض، وتعديل طول ROC.
8- السيولة: تفعيل/تعطيل تأثير السيولة على عرض الخطوط وقيمها في التسميات.
9- الأهداف السعرية: تفعيل/تعطيل الأهداف وعرضها كخطوط.
10- فيبوناتشي: اختيار المستويات المعروضة ولون الخطوط.
فوائد المؤشر
دقة عالية: يعتمد على حجم التداول لتحديد المستويات، مما يجعله أكثر موثوقية من المستويات العشوائية.
مرونة: يوفر خيارات تخصيص واسعة تتيح للمتداولين تكييفه حسب استراتيجياتهم.
تحليل شامل: يجمع بين الدعم والمقاومة، الاتجاه، السيولة، والأهداف في أداة واحدة.
سهولة الاستخدام: التسميات والتنبيهات تجعل من السهل متابعة السوق دون تعقيد.
==================================================================================تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوق. في هذا الشرح، سنستعرض كل رقم أو قيمة تظهر في التسميات ومعناها العملي.
مكونات التسميات
التسميات تظهر بجانب كل مستوى دعم (Support) ومقاومة (Resistance) وتبدأ بحرف "S" للدعم أو "R" للمقاومة، تليها مجموعة من الأرقام والقيم التي يمكن تفعيلها أو تعطيلها حسب إعدادات المستخدم. إليك تفصيل كل عنصر:
1- عدد اللمسات (Touch Count)
الرمز: يظهر مباشرة بعد "S" أو "R" (مثال: "R: 5" أو "S: 3").
المعنى: يشير إلى عدد المرات التي اختبر فيها السعر هذا المستوى دون اختراقه.
الفائدة: كلما زاد عدد اللمسات، كلما كان المستوى أقوى وأكثر أهمية. على سبيل المثال، إذا كان "R: 5"، فهذا يعني أن السعر ارتد من هذا المستوى 5 مرات، مما يجعله مقاومة قوية محتملة.
2- قوة المستوى (Strength Rating)
الرمز: يظهر بين قوسين مربعين (مثال: " ").
المعنى: قيمة من 0 إلى 100 تعكس قوة المستوى بناءً على عوامل مثل حجم التداول، عدد اللمسات، وقرب السعر الحالي من المستوى.
الفائدة: القيم العالية (مثل 75 أو أكثر) تشير إلى مستوى قوي يصعب اختراقه، بينما القيم المنخفضة (مثل 30 أو أقل) تدل على ضعف المستوى وسهولة اختراقه. يمكن للمتداول استخدام هذا لتحديد المستويات الأكثر موثوقية.
3- احتمالية الاختراق (Breakout Probability)
الرمز: يبدأ بحرف "B" متبوعًا بنسبة مئوية (مثال: "B: 60%").
المعنى: نسبة من 0% إلى 100% تُظهر احتمالية اختراق السعر للمستوى بناءً على الزخم الحالي، قوة المستوى، والمسافة بين السعر والمستوى.
الفائدة: نسبة مرتفعة (مثل 60% أو أكثر) تعني أن السعر قد يخترق المستوى قريبًا، بينما النسب المنخفضة (مثل 20%) تشير إلى احتمال ارتداد السعر. هذا مفيد لتوقع الحركة التالية.
4- قيمة السيولة (Liquidity Value)
الرمز: يبدأ بحرف "L" متبوعًا برقم (مثال: "L: 1200").
المعنى: يمثل متوسط حجم التداول في النطاق القريب من المستوى، مما يعكس السيولة التاريخية حوله.
الفائدة: القيم العالية تدل على وجود سيولة كبيرة، مما يعني أن السعر قد يتفاعل بقوة مع هذا المستوى (إما بالارتداد أو الاختراق). القيم المنخفضة تشير إلى سيولة ضعيفة، مما قد يجعل المستوى أقل تأثيرًا.
5- الأهداف السعرية (Price Targets)
الرمز: يبدأ بـ "BT" (هدف الاختراق) و"RT" (هدف الارتداد) متبوعين بأرقام (مثال: "BT: 150.50 RT: 148.20").
المعنى:
BT (Breakout Target): السعر المحتمل الذي قد يصل إليه السعر بعد اختراق المستوى.
RT (Reversal Target): السعر المحتمل الذي قد يصل إليه السعر إذا ارتد من المستوى.
الفائدة: تساعد المتداولين في تحديد نقاط الخروج المحتملة بعد الاختراق أو الارتداد، مما يسهل وضع خطة تداول دقيقة.
أمثلة عملية
تسمية مقاومة: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
المستوى اختُبر 4 مرات، قوته 80 (قوي جدًا)، احتمالية الاختراق 25% (منخفضة، أي احتمال ارتداد أعلى)، السيولة 1500 (مرتفعة)، هدف الاختراق 155.00، هدف الارتداد 152.00.
الاستنتاج: المستوى قوي ومن المرجح أن يرتد السعر منه، لكن إذا اخترق، فقد يصل إلى 155.00.
تسمية دعم: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
المستوى اختُبر مرتين، قوته 40 (متوسطة إلى ضعيفة)، احتمالية الاختراق 70% (مرتفعة)، السيولة 800 (متوسطة)، هدف الاختراق 145.00، هدف الارتداد 147.50.
الاستنتاج: المستوى ضعيف ومن المحتمل أن يخترقه السعر ليهبط إلى 145.00.
كيفية الاستفادة من التسميات
تحديد القوة والضعف: استخدم قوة المستوى (Strength) لمعرفة ما إذا كان المستوى موثوقًا للارتداد أو عرضة للاختراق.
توقع الحركة: انظر إلى احتمالية الاختراق (Breakout Probability) لتحديد ما إذا كنت ستنتظر اختراقًا أو ترتدًا.
إدارة المخاطر: استخدم الأهداف السعرية (BT وRT) لتحديد نقاط جني الأرباح أو وقف الخسارة.
تقييم السيولة: ركز على المستويات ذات السيولة العالية لأنها غالبًا تكون نقاط تحول رئيسية في السوق.
تأكيد التحليل: ادمج عدد اللمسات مع القوة والسيولة للحصول على صورة كاملة عن أهمية المستوى.
تخصيص التسميات
يمكن للمستخدم تفعيل أو تعطيل أي من هذه القيم (القوة، الاحتمالية، السيولة، الأهداف) من إعدادات المؤشر.
يمكن أيضًا تغيير حجم التسميات (صغير، عادي، كبير)، موقعها (يمين، يسار، أعلى، أسفل)، ولون النص لتناسب احتياجاتك.
التسميات في هذا المؤشر هي بمثابة لوحة تحكم صغيرة بجانب كل مستوى دعم ومقاومة، تقدم لك معلومات فورية عن قوته، احتمالية اختراقه، سيولته، وأهدافه السعرية. بفهم هذه الأرقام، يمكنك تحسين قراراتك في التداول، سواء كنت تبحث عن نقاط دخول، خروج، أو إدارة مخاطر. إذا كنت تريد أداة تجمع بين البساطة والعمق التحليلي .
تنويه:
المؤشر هو أداة مساعدة فقط ويجب استخدامه مع التحليل الفني والأساسي لتحقيق أفضل النتائج.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView.
The Smart Volume S/R Pro indicator is an advanced technical analysis tool designed to help traders identify strong support and resistance levels based on trading volume, with the addition of advanced analytical features such as trend filtering, confidence zones, strength assessment, breakout probability calculation, liquidity measurement, price target identification, and Fibonacci levels. It also provides labels next to each support and resistance level, containing accurate numbers and information that reflect the market condition. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. This indicator aims to provide a comprehensive view of the market.
Main functions of the indicator
1- Identifying support and resistance levels based on high trading volume
The indicator analyzes previous bars (up to 300 bars by default) to identify the points that witnessed the highest levels of trading volume.
It draws horizontal lines representing resistance levels (at the highest price in those bars) and support (at the lowest price), and the user can choose the number of lines displayed (from 1 to 6).
2- Filtering the trend using the ADX indicator
The indicator uses the Average Directional Index (ADX) to assess the strength of a trend in the market.
When the strength of the trend is high (exceeding a specified threshold, 25 by default), the indicator reduces the number of support and resistance levels displayed to focus only on the most important levels.
3- Dynamic Confidence Zones
The indicator adds zones around support and resistance levels based on the Average True Range (ATR), helping traders visualize the ranges in which the price may interact with these levels.
The width of these zones can be adjusted using the ATR multiplier.
4- Assessing the Strength of Levels
The indicator calculates the strength of each level based on trading volume, the number of times the level has been tested (Touch Count), and the proximity of the current price to the level.
A strength score (from 0 to 100) is displayed next to each level if this feature is enabled.
5- Breakout Probability
The indicator estimates the probability of breaking each level based on momentum (ROC), the strength of the level, and the distance between the current price and the level.
The probability is displayed as a percentage if the option is enabled, helping traders anticipate potential moves.
6- Historical Liquidity Analysis
The indicator measures liquidity around each level based on the trading volume in the ranges near it.
The liquidity values can be displayed in the labels or used to adjust the width of the lines (the most liquid lines appear wider).
7- Price Targets
When this feature is enabled, the indicator calculates price targets for breakout and reversal based on momentum, level strength and ATR.
These targets can be displayed as text in the labels or as horizontal lines on the chart.
8- Fibonacci Levels
The indicator plots Fibonacci levels (0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0) based on the highest and lowest price in the lookback period.
The user can choose which of these levels to display or hide.
9- Comprehensive Breakout Alert
The indicator provides a single alert that includes all levels, where the alert is triggered when the price breaks any support or resistance level with a message explaining the type of breakout and the level broken.
How the indicator works
Step 1: The indicator identifies the bars with high volume during the specified Lookback Period.
Step 2: Draws support and resistance levels based on the highest and lowest prices in those bars, taking into account the number of lines selected by the user.
Step 3: Apply the trend filter (if enabled) to reduce the number of levels in case of a strong trend.
Step 4: Adds additional analyses such as strength, liquidity, breakout probability, and price targets, and draws confidence zones and Fibonacci levels according to the settings.
Step 5: Monitors the price and triggers an alert when the breakout occurs.
Customizable Settings
1- Lookback Period: Number of bars to analyze (default 300).
2- Number of Lines: From 1 to 6 support and resistance levels.
3- Colors and Styles: Line colors and styles can be changed (filled, dashed, dotted).
4- Labels: Enable/disable labels, their size, location, and text color.
5- Trend Filter: Enable/disable ADX, and modify its length and threshold.
6- Confidence Zones: Enable/disable, and modify the ATR length and multiplier.
7- Strength and Breakout Probability: Enable/disable the display, and modify the ROC length.
8- Liquidity: Enable/disable the effect of liquidity on the display of the lines and their values in the labels.
9- Price Targets: Enable/disable the targets and display them as lines.
10- Fibonacci: Choose the displayed levels and the color of the lines.
Indicator Benefits
High Accuracy: It relies on trading volume to determine the levels, which makes it more reliable than random levels.
Flexibility: It provides extensive customization options that allow traders to adapt it to their strategies.
Comprehensive Analysis: Combines support and resistance, trend, liquidity, and targets in one tool. Ease of Use: Labels and alerts make it easy to follow the market without complexity.
Labels next to each support and resistance level contain accurate numbers and information that reflect the market situation. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. In this explanation, we will review each number or value that appears in the labels and their practical meaning.
Label Components
Labels appear next to each support and resistance level and begin with the letter "S" for support or "R" for resistance, followed by a set of numbers and values that can be enabled or disabled according to the user's settings. Here is a breakdown of each element:
1- Touch Count
Symbol: Appears immediately after "S" or "R" (example: "R: 5" or "S: 3").
Meaning: Indicates the number of times the price has tested this level without breaking it.
Benefit: The more touches, the stronger and more important the level. For example, if it is "R: 5", it means that the price has bounced off this level 5 times, making it a potentially strong resistance.
2- Strength Rating
Symbol: Appears between square brackets (example: " ").
Meaning: A value from 0 to 100 that reflects the strength of the level based on factors such as trading volume, number of touches, and proximity of the current price to the level.
Benefit: High values (such as 75 or more) indicate a strong level that is difficult to break, while low values (such as 30 or less) indicate a weak level that is easy to break. A trader can use this to determine the most reliable levels.
3- Breakout Probability
Symbol: Starts with the letter "B" followed by a percentage (example: "B: 60%").
Meaning: A percentage from 0% to 100% that shows the probability of the price breaking the level based on the current momentum, the strength of the level, and the distance between the price and the level.
Interest: A high percentage (such as 60% or more) means that the price may soon break through the level, while low percentages (such as 20%) indicate that the price may bounce. This is useful for anticipating the next move.
4- Liquidity Value
Symbol: Starts with the letter "L" followed by a number (example: "L: 1200").
Meaning: Represents the average trading volume in the range near the level, reflecting historical liquidity around it.
Interest: High values indicate high liquidity, meaning that the price may react strongly to this level (either by bouncing or breaking through). Low values indicate low liquidity, which may make the level less influential.
5- Price Targets
Symbol: Starts with "BT" (breakout target) and "RT" (rebound target) followed by numbers (example: "BT: 150.50 RT: 148.20").
Meaning:
BT (Breakout Target): The potential price that the price may reach after breaking the level.
RT (Reversal Target): The potential price that the price may reach if it rebounds from the level.
Utility: Helps traders identify potential exit points after a breakout or rebound, making it easier to develop an accurate trading plan.
Working examples
Resistance label: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
Level tested 4 times, strength 80 (very strong), probability of breakout 25% (low, i.e. higher probability of rebound), liquidity 1500 (high), breakout target 155.00, rebound target 152.00.
Conclusion: The level is strong and the price is likely to rebound from it, but if it breaks, it may reach 155.00.
Support Label: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
Level tested twice, Strength 40 (medium to weak), Breakout Probability 70% (high), Liquidity 800 (medium), Breakout Target 145.00, Rebound Target 147.50.
Conclusion: The level is weak and the price is likely to break it to drop to 145.00.
How to use labels
Determine strength and weakness: Use the level's strength to see if the level is reliable for a bounce or vulnerable to a breakout.
Predict the move: Look at the Breakout Probability to determine whether to wait for a breakout or a bounce.
Risk Management: Use price targets (BT and RT) to set take profit or stop loss points.
Liquidity Evaluation: Focus on levels with high liquidity as they are often key turning points in the market.
Analysis Confirmation: Combine the number of touches with strength and liquidity to get a complete picture of the level’s importance.
Customize Labels
The user can enable or disable any of these values (strength, probability, liquidity, targets) from the indicator settings.
The size of the labels (small, normal, large), their position (right, left, top, bottom), and the color of the text can also be changed to suit your needs.
The labels in this indicator act as a small dashboard next to each support and resistance level, providing you with instant information about its strength, probability of breakout, liquidity, and price targets. By understanding these numbers, you can improve your trading decisions, whether you are looking for entry points, exit points, or risk management. If you want a tool that combines simplicity with analytical depth.
Disclaimer:
The indicator is an auxiliary tool only and should be used in conjunction with technical and fundamental analysis for best results.
Disclaimer
The information and posts are not intended to be, or constitute, any financial, investment, trading or other types of advice or recommendations provided or endorsed by TradingView.
