Market direction and pullback based on S&P 500.A simple indicator based on www.swing-trade-stocks.com The link is also the guide for how to use it.
0 - nothing. If the indicator is showing 0 for a prolonged amount of time, it is likely the market is in "momentum mode" (referred to in the link above).
1 - indicates an uptrend based on SMA and EMA and also a place where a reversal to the upside is likely to occur. You should look only for long trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
-1 - indicates a downtrend based on SMA and EMA and also a place where a reversal to the downside is likely to occur. You should look only for short trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
Recherche dans les scripts pour "做空标普500"
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
Net DASH Margin PositionTotal DASH Longs minus DASH Shorts in order to give you the total outstanding DASH margin debt.
ie: If 500,000 DASH has been longed, and 400,000 DASH has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 DASH (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net NEO Margin PositionTotal NEO Longs minus NEO Shorts in order to give you the total outstanding NEO margin debt.
ie: If 500,000 NEO has been longed, and 400,000 NEO has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 NEO (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project.
Like I wrote the last time - my goal is to create a new strategy everyday
for the rest of 2016 and post it here on TradingView.
I'm a complete beginner so this is my way of learning about coding strategies.
I'll give myself between 15 minutes and 2 hours to complete each creation.
This is basically a repetition of the first strategy I wrote - a Moving Average Crossover,
but I added a tiny thing.
I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time."
(source: )
My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility
and because of this missed one nice bull run and a very nice bear run.
So I added this single line: if time("60", "1000-1600") regarding when to take exits:
if time("60", "1000-1600")
strategy.exit("Close Long", "Long", profit=2000, loss=500)
strategy.exit("Close Short", "Short", profit=2000, loss=500)
Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually.
Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility.
When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily.
On the other hand I'll have to test this on various stocks .
Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs
to read on this topic is very welcome!
Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated!
/pbergden
EMA + SuperTrend Signals (Customized Subham) - FIXED//@version=5
indicator("EMA + SuperTrend Signals (modes + filters) - FIXED firstClose", overlay=true, shorttitle="EMA×ST Modes", max_labels_count=500)
// ====== USER INPUTS ======
useHeikin = input.bool(false, "Use Heikin Ashi price (set true if chart is Heikin Ashi)")
srcType = input.string("Close", "Price source for EMA/SuperTrend", options= )
emaFastLen = input.int(10, "Fast EMA Length", minval=1)
emaSlowLen = input.int(50, "Slow EMA Length", minval=1)
useEMAFilter = input.bool(true, "Require EMA filter for signals (Fast EMA > Slow EMA)")
atrLen = input.int(10, "SuperTrend ATR Length", minval=1)
atrMult = input.float(3.0, "SuperTrend ATR Multiplier", step=0.1)
showArrows = input.bool(true, "Show buy/sell arrows")
showBands = input.bool(true, "Show final upper/lower bands")
showST = input.bool(true, "Show SuperTrend line")
showEMA = input.bool(true, "Plot EMAs")
showBg = input.bool(true, "Color background by ST")
alertsEnabled = input.bool(true, "Enable alertcondition()s")
// ====== SIGNAL MODE / BEHAVIOR ======
signalMode = input.string("Flip only", "Signal Mode", options= )
allowOnTrendNotOnlyFlip = input.bool(true, "Allow signals based on Signal Mode (in addition to flips)")
// ====== SIDEWAYS / NOISE FILTER INPUTS ======
useAdxFilter = input.bool(true, "Use ADX filter (require trend strength)")
adxLen = input.int(14, "ADX length", minval=1)
adxThreshold = input.int(20, "ADX threshold (lower = more signals)")
useVolFilter = input.bool(true, "Use ATR% volatility filter (require sufficient movement)")
volPctThreshold = input.float(0.002, "ATR / Price threshold (e.g. 0.002 = 0.2%)", step=0.0001)
useRsiFilter = input.bool(true, "Use RSI filter")
rsiLen = input.int(14, "RSI length", minval=1)
rsiBuyThreshold = input.int(50, "RSI buy threshold (require RSI > this for buys)", minval=1, maxval=99)
rsiSellThreshold = input.int(50, "RSI sell threshold (require RSI < this for sells)", minval=1, maxval=99)
// ====== HEIKIN ASHI VALUES (optional) ======
var float haOpen = na
var float haClose = na
var float haHigh = na
var float haLow = na
if useHeikin
haClose := (open + high + low + close) / 4.0
haOpen := na(haOpen ) ? (open + close) / 2.0 : (haOpen + haClose ) / 2.0
haHigh := math.max(high, math.max(haOpen, haClose))
haLow := math.min(low, math.min(haOpen, haClose))
// ====== PRICE SOURCE FUNCTION ======
_getSrc(_choice) =>
float _result = na
if useHeikin
if _choice == "Close"
_result := haClose
else if _choice == "HL2"
_result := (haHigh + haLow) * 0.5
else
_result := (haHigh + haLow + haClose) / 3.0
else
if _choice == "Close"
_result := close
else if _choice == "HL2"
_result := (high + low) * 0.5
else
_result := (high + low + close) / 3.0
_result
priceSrc = _getSrc(srcType)
priceHigh = useHeikin ? haHigh : high
priceLow = useHeikin ? haLow : low
priceClose = nz(priceSrc, close)
// ====== EMA CALC ======
emaFast = ta.ema(priceSrc, emaFastLen)
emaSlow = ta.ema(priceSrc, emaSlowLen)
// ====== SUPER TREND CALC (finalUpper / finalLower) ======
hl2_local = (priceHigh + priceLow) * 0.5
atr = ta.atr(atrLen)
upperBasic = hl2_local + atrMult * atr
lowerBasic = hl2_local - atrMult * atr
var float finalUpper = na
var float finalLower = na
finalUpper := nz(finalUpper , upperBasic)
finalLower := nz(finalLower , lowerBasic)
finalUpper := (upperBasic < finalUpper or priceClose > finalUpper) ? upperBasic : finalUpper
finalLower := (lowerBasic > finalLower or priceClose < finalLower) ? lowerBasic : finalLower
var int trend = 1
trend := nz(trend , 1)
if (priceClose > nz(finalUpper , finalUpper))
trend := 1
else if (priceClose < nz(finalLower , finalLower))
trend := -1
superTrend = trend == 1 ? finalLower : finalUpper
isBull = trend == 1
isBear = trend == -1
// ====== SIGNAL RULE BASE (flips) ======
prevTrend = nz(trend , trend)
bullFlip = (trend == 1 and prevTrend == -1)
bearFlip = (trend == -1 and prevTrend == 1)
// EMA crossover signals (series)
emaXoverBuy = ta.crossover(emaFast, emaSlow)
emaXoverSell = ta.crossunder(emaFast, emaSlow)
// price vs superTrend confirmation
priceAboveST = priceClose > superTrend
priceBelowST = priceClose < superTrend
// Basic EMA filters
emaFilterBuy = (emaFast > emaSlow) and (priceClose > emaFast)
emaFilterSell = (emaFast < emaSlow) and (priceClose < emaFast)
// Build raw candidates depending on mode
flipBuy = bullFlip
flipSell = bearFlip
// firstClose: first bar where trend flipped and price confirms on that bar's close
firstCloseBuy = (trend == 1) and (prevTrend == -1) and (priceClose > superTrend)
firstCloseSell = (trend == -1) and (prevTrend == 1) and (priceClose < superTrend)
// emaCrossoverCandidate: EMA cross while trend confirms
emaCandidateBuy = emaXoverBuy and (trend == 1)
emaCandidateSell = emaXoverSell and (trend == -1)
// Compose the raw buy/sell depending on chosen Signal Mode
var bool buySignal_raw = false
var bool sellSignal_raw = false
if signalMode == "Flip only"
buySignal_raw := flipBuy
sellSignal_raw := flipSell
else if signalMode == "First close in trend"
buySignal_raw := firstCloseBuy or (allowOnTrendNotOnlyFlip and flipBuy)
sellSignal_raw := firstCloseSell or (allowOnTrendNotOnlyFlip and flipSell)
else // "EMA crossover in trend"
buySignal_raw := emaCandidateBuy or (allowOnTrendNotOnlyFlip and flipBuy)
sellSignal_raw := emaCandidateSell or (allowOnTrendNotOnlyFlip and flipSell)
// Apply EMA filter option (if enabled)
if useEMAFilter
buySignal_raw := buySignal_raw and emaFilterBuy
sellSignal_raw := sellSignal_raw and emaFilterSell
// ====== SIDEWAYS FILTERS IMPLEMENTATION ======
// Manual ADX implementation (Wilder smoothing)
up = priceHigh - priceHigh
down = priceLow - priceLow
plusDM = (up > down and up > 0) ? up : 0.0
minusDM = (down > up and down > 0) ? down : 0.0
tr1 = priceHigh - priceLow
tr2 = math.abs(priceHigh - nz(priceClose , priceClose))
tr3 = math.abs(priceLow - nz(priceClose , priceClose))
trueRange = math.max(tr1, math.max(tr2, tr3))
smoothedTR = ta.rma(trueRange, adxLen)
smoothedPlusDM = ta.rma(plusDM, adxLen)
smoothedMinusDM = ta.rma(minusDM, adxLen)
plusDI = smoothedTR == 0 ? 0.0 : (100.0 * smoothedPlusDM / smoothedTR)
minusDI = smoothedTR == 0 ? 0.0 : (100.0 * smoothedMinusDM / smoothedTR)
dx = (plusDI + minusDI == 0) ? 0.0 : (100.0 * math.abs(plusDI - minusDI) / (plusDI + minusDI))
adxValue = ta.rma(dx, adxLen)
adxOk = useAdxFilter ? (adxValue > adxThreshold) : true
// ATR% check
safePrice = priceClose == 0.0 ? nz(close) : priceClose
atrPct = atr / math.abs(safePrice)
volOk = useVolFilter ? (atrPct > volPctThreshold) : true
// RSI checks
rsiValue = ta.rsi(priceSrc, rsiLen)
rsiOkBuy = useRsiFilter ? (rsiValue > rsiBuyThreshold) : true
rsiOkSell = useRsiFilter ? (rsiValue < rsiSellThreshold) : true
// Allow signal only when all enabled filters pass (separate for buy/sell)
allowBuy = adxOk and volOk and rsiOkBuy
allowSell = adxOk and volOk and rsiOkSell
// Final gated signals
buySignal = buySignal_raw and allowBuy
sellSignal = sellSignal_raw and allowSell
// Avoid both at once
if (buySignal and sellSignal)
buySignal := false
sellSignal := false
// ====== PLOTTING ======
plot(showEMA ? emaFast : na, title="EMA Fast", linewidth=2)
plot(showEMA ? emaSlow : na, title="EMA Slow", linewidth=2)
pUpper = plot(showBands ? finalUpper : na, title="Final Upper", linewidth=2, style=plot.style_line)
pLower = plot(showBands ? finalLower : na, title="Final Lower", linewidth=2, style=plot.style_line)
plot(showST ? superTrend : na, title="SuperTrend", linewidth=3, style=plot.style_line)
fill(pUpper, pLower, color = color.new(color.blue, 92))
plotshape(series = (showArrows and buySignal), title="Buy Arrow", style=shape.labelup, location=location.belowbar, color=color.green, text="BUY", textcolor=color.white, size=size.tiny)
plotshape(series = (showArrows and sellSignal), title="Sell Arrow", style=shape.labeldown, location=location.abovebar, color=color.red, text="SELL", textcolor=color.white, size=size.tiny)
// ====== BACKGROUND COLOR ======
var color bg_col = na
if showBg
if not (adxOk and volOk)
bg_col := color.new(color.gray, 85)
else
bg_col := isBull ? color.new(color.green, 90) : color.new(color.red, 90)
else
bg_col := na
bgcolor(bg_col)
// ====== ALERTS ======
alertcondition(alertsEnabled and buySignal, title="EMA+ST Buy", message="EMA+ST BUY — signal passed filters.")
alertcondition(alertsEnabled and sellSignal, title="EMA+ST Sell", message="EMA+ST SELL — signal passed filters.")
alertcondition(alertsEnabled and (buySignal or sellSignal), title="EMA+ST Any Signal", message="EMA+ST signal detected.")
// ====== DEBUG / LABELS ======
showDebug = input.bool(false, "Show debug label (mode, ADX, ATR%, RSI)")
if showDebug and barstate.islast
var label dbg = na
label.delete(dbg)
dbgText = "Mode:" + signalMode + " ADX:" + str.tostring(adxValue, "#.0") + " ATR%:" + str.tostring(atrPct*100, "#.2") + "% RSI:" + str.tostring(rsiValue, "#.1")
dbg := label.new(bar_index, high, dbgText, xloc=xloc.bar_index, yloc=yloc.abovebar, style=label.style_label_left, color=color.gray, textcolor=color.white)
var label lastLbl = na
if barstate.islast
label.delete(lastLbl)
lastLbl := label.new(bar_index, high, isBull ? "ST: Bull" : "ST: Bear", xloc=xloc.bar_index, yloc=yloc.abovebar, style=label.style_label_left, color=isBull ? color.green : color.red, textcolor=color.white)
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview
A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals.
Key Features
Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options)
Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional)
Automated Risk Management: 2% stop loss with wick-touch detection
Position Auto-Reversal: Opposite signals automatically close and reverse positions
Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short)
Performance Metrics
NIFTY Futures (15min): 50%+ win rate with ADX filter OFF
Crypto Markets: Requires extensive backtesting before live deployment
Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes)
Strategy Logic
Entry Signals:
LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled)
SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled)
Exit Signals:
Opposite EMA crossover (auto-closes current position)
Stop loss hit at 2% from entry price (tracks candle wicks)
Technical Indicators:
Fast EMA: 9-period (short-term trend)
Slow EMA: 21-period (primary trend)
RSI: 14-period with 55/45 thresholds (momentum confirmation)
ADX: 14-period with 20 threshold (trend strength filter - optional)
Market-Specific Settings
Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options)
Recommended Settings:
ADX Filter: Turn OFF (less choppy, cleaner trends)
Timeframe: 15-minute chart
Win Rate: 50%+ on NIFTY Futures
Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary
Cryptocurrency Markets (BTC, ETH, Altcoins)
Recommended Settings:
ADX Filter: Turn ON (ADX > 20)
Timeframe: 15-minute to 1-hour
Extensive backtesting required before live trading
Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop
Best Practices
✅ Backtest thoroughly on your specific instrument and timeframe
✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward
✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger)
✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto
✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price
✅ Paper trade first - test for 2-4 weeks before risking real capital
Risk Management
Fixed 2% stop loss per trade (adjustable)
Stop loss tracks candle wicks for accurate execution
Positions auto-reverse on opposite signals (no manual intervention needed)
0.075% commission built into backtest (adjust for your broker)
Customization Options
All parameters are adjustable via inputs:
EMA periods (default: 9/21)
RSI length and thresholds (default: 14-period, 55/45 levels)
ADX length and threshold (default: 14-period, 20 threshold)
Stop loss percentage (default: 2%)
Webhook Automation
This strategy includes six distinct alert messages for automated trading:
"Entry Buy" - Long position opened
"Entry Sell" - Short position opened
"Close Long" - Long position closed on opposite crossover
"Close Short" - Short position closed on opposite crossover
"SL Hit Long" - Long stop loss triggered
"SL Hit Short" - Short stop loss triggered
Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms.
Important Notes
⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets
⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals
⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto
⚠️ Not financial advice - always conduct your own research and use proper risk management
⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions
Disclaimer
This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy.
FVG ATRFVG ATR — Fair Value Gap Size Measured in ATR Units
This Pine Script v6 indicator detects Fair Value Gaps and displays their size as a ratio of the Average True Range, providing traders with a normalized measurement of gap significance across different market conditions and timeframes.
Key Features
Automatic FVG Detection
The indicator identifies bullish and bearish Fair Value Gaps using the standard three-candle pattern. Bullish FVGs occur when the current low exceeds the high from two bars ago, while bearish FVGs occur when the current high falls below the low from two bars ago.
ATR Ratio Calculation
Each detected FVG is measured against the current Average True Range at the moment of detection. The ratio is displayed as a compact label next to the gap, showing values like "ATR: 0.75" or "ATR: 1.41". This normalization allows comparison of gap significance across volatile and calm market periods.
Minimal Visual Footprint
Labels are displayed directly on the chart without boxes or lines, using customizable text sizes from tiny to large. The default tiny size ensures the chart remains uncluttered while providing essential information at a glance.
Highly Customizable Display
All visual aspects are configurable through input parameters, including label position (top, middle, or bottom of gap), text size, text color, optional background, and horizontal offset from the detection candle.
Customizable Parameters
Detection Settings
Detect Bullish FVG: Enable or disable detection of bullish gaps. Default is enabled.
Detect Bearish FVG: Enable or disable detection of bearish gaps. Default is enabled.
Min Size (pips): Filter out small gaps below the specified threshold. One pip equals 10 ticks for most Forex pairs. Default is 10 pips.
ATR Calculation
ATR Period: Period length for Average True Range calculation. Default is 14, adjustable to match your trading strategy.
Label Settings
Label Position: Vertical placement of the text label relative to the FVG zone. Options are Top, Middle, or Bottom. Default is Middle.
Label Size: Text size from Tiny (smallest), Small, Normal, to Large. Default is Tiny for minimal chart clutter.
Text Color: Custom color for label text. Default is white for visibility on dark themes.
Show Background: Toggle to display labels with a colored background box or as transparent text only. Default is disabled for cleaner appearance.
Background Color: Custom color for label background when enabled. Default is semi-transparent gray.
Label Offset (bars): Horizontal distance in bars between the detection candle and the label. Set to 0 for labels directly on the candle, or increase for separation. Default is 0.
Recommended Use Cases
Multi-Timeframe Analysis
Compare FVG significance across different timeframes by observing ATR ratios. A 1.5 ATR gap on the 1-hour chart may indicate different significance than the same ratio on the daily chart.
Volatility-Adjusted Trading
Use ATR ratios to filter for only the most significant gaps. For example, only trade FVGs with ratios above 1.0 to focus on gaps larger than typical price movement.
Risk Management
Size positions based on gap magnitude relative to current volatility. Larger ATR ratios may warrant tighter stops or smaller position sizes.
Market Efficiency Analysis
Track how quickly and completely different-sized gaps get filled. Gaps with higher ATR ratios may take longer to fill or act as stronger support and resistance zones.
Technical Details
This indicator is written in Pine Script v6 and follows all recommended coding standards including strict 4-space indentation, lazy boolean evaluation, and proper type declarations. The script uses array-based storage to maintain up to 500 labels simultaneously.
The ATR ratio is calculated at the moment of FVG detection and remains fixed, never repainting. The calculation divides the FVG height (distance between gap boundaries) by the current ATR value using the specified period. Division by zero is protected with conditional logic.
Label positioning uses the xloc.bar_index and yloc.price system for precise placement. The horizontal offset parameter allows traders to adjust label spacing based on chart zoom level and personal preference. Text formatting uses str.tostring with two decimal places for clear ratio display.
Important Notes
The indicator never repaints as all FVG detections and ATR calculations are fixed upon bar confirmation. Labels persist on the chart until the maximum label count is reached, at which point the oldest labels are automatically removed by TradingView.
For optimal performance on charts with many FVGs, consider increasing the minimum pip size filter or using smaller label sizes. The tiny size option provides the smallest possible text for maximum chart clarity.
Installation and Usage
Copy the source code into the TradingView Pine Editor and add the indicator to your chart. The overlay parameter is set to true, allowing labels to display directly on price candles. Configure all parameters through the indicator settings panel to match your trading style and visual preferences.
100% Pine Script v6 indicator — No repaint — Open source
ES VIX on MNQ🧭 ES + VIX Overlay on MNQ
This indicator overlays the ES (S&P 500 futures) and VIX (Volatility Index) directly on the MNQ (Micro Nasdaq Futures) chart, allowing traders to visualize in real time the correlation, divergence, and volatility influence between the three instruments.
⸻
⚙️ How It Works
• The VIX is dynamically rescaled to the MNQ’s daily open, so its moves appear on the same price scale.
• The ES line is projected based on its percentage move relative to the session open (18:00 NY).
• Both are plotted in sync with MNQ to expose relative strength and divergence zones that often precede strong directional moves.
⸻
🧩 Inputs
• VIX Symbol: choose between VIX, CBOE:VIX, TVC:VIX
• Invert VIX Correlation: flips the VIX line for inverse-correlation setups
• VIX Step: controls how sensitively the VIX moves on the MNQ scale
• ES Symbol: defines the ES contract (e.g. ES1!)
• Show Signals: toggles on/off buy & sell markers
• Step (points): minimum distance between MNQ and VIX for a valid signal
• Block Signals: disables signals between 16:15 – 03:15 (illiquid hours)
⸻
💡 Signal Logic
The system tracks crossings between MNQ and the projected VIX line:
• Buy signal → when MNQ crosses above the VIX and expands upward by ≥ X points.
• Sell signal → when MNQ crosses below the VIX and expands downward by ≥ X points.
A time filter avoids noise during low-volume sessions.
⸻
📊 Visual Guide
• Cyan line = VIX on MNQ scale
• Orange line = ES on MNQ scale
• Labels on the right = current VIX / ES values
• BUY/SELL markers = potential volatility-based reversals
⸻
🚀 Practical Use
Perfect for traders who monitor:
• VIX–price divergence
• ES vs MNQ momentum confirmation
• Early volatility expansions before trend moves
⸻
💬 Core Idea:
“Volatility leads — price confirms.”
QQQ TimingThis is a trend-following position trading strategy designed for the QQQ and the leveraged ETF QLD (ProShares Ultra QQQ). The primary goal is to capture multi-month holds for maximal profit.
Key Instruments & Performance
The strategy performs best with QLD, which yields far superior results compared to QQQ.
TQQQ (triple-leveraged) results in higher drawdowns and is not the optimal choice.
Important: The system is not intended for use with other indexes, individual stocks, or investments (like crypto or gold), as performance can vary widely.
Buy Signals
The strategy's signals are rooted in the S&P 500 Index (SPX), as testing showed it provides more reliable triggers than using QQQ itself.
Primary Buy Signal (Credit to IBD/Mike Webster): The SPX triggers a buy when its low closes above the 21-day Exponential Moving Average (EMA) for three consecutive days.
Refinement with Downtrend Lines: During corrective or bear periods, results and drawdowns can be significantly improved by incorporating downtrend lines. These lines connect lower highs. The strategy waits for the price to close above a drawn downtrend line before executing a buy. This refinement can modify the primary signal, either by allowing for an earlier entry or, in some cases, completely nullifying a false signal until the trend change proves itself.
Risk Management & Exit Strategy
Initial Buy Risk: A 3.7% stop loss is applied immediately upon the initial entry.
Initial Exit Rule: An exit is required if the QQQ's low drops below the 50-day Simple Moving Average (SMA).
Note: The 3.7% stop often provides protection when the initial buy occurs below the 50-day SMA. However, if QQQ is already trading above its 50-day SMA at the time of the SPX signal (indicating relative strength), historically, it has been better to use the 50-day SMA rule to give the position more room to run.
Trend Exit (Profit-Taking): To stay in a strong trend for the optimal amount of time, the long position is exited when a moving average crossover to the downside is triggered, based around the 107-day Simple Moving Average (SMA).
Simple FVG - All GapsSimple FVG Indicator - Pure Fair Value Gap Detection
A clean, no-nonsense Fair Value Gap (FVG) script for TradingView. No filters, no overcomplication — just pure FVG detection with optional mitigation and visual control.
Pure FVG Logic : Detects imbalance using only low > high and high < low — the original ICT definition.
No False Filters : Zero reliance on volume, RSI, moving averages, or swing structure.
Accurate Mitigation : Choose between Touch, Mid, or Full fill with correct proximal/distal logic.
Smart Extension : Indefinite (until mitigated) or Fixed Bars (visual only).
Performance Optimized : Uses arrays + max 500 boxes to prevent lag.
Bullish FVG: Green translucent box from high to low
Bearish FVG: Red translucent box from low to high
Mitigated FVGs: Gray (or hidden) with extension stopped
"No fluff. Just gaps."
How to Use:
Add to chart
Enable Bullish/Bearish FVGs
Set Mitigation Type (Mid recommended)
Watch price react at unmitigated zones
ADR levels+// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © notprofessorgreen
//@version=5
indicator("ADR levels", shorttitle = 'ADR', overlay=true, max_bars_back=5000, max_lines_count=500)
// Error catching
if (timeframe.in_seconds() >= timeframe.in_seconds('D'))
runtime.error('Timeframe cannot be greater than Daily')
// Inputs
adr_days = input.int(10, title = 'Days', maxval=250, minval = 1)
std_x = input.float(1.0, "Scale Factor")
width = input.int(1, "Line Width")
// ADR line inputs
adr_color = input.color(color.gray, "ADR Color")
adr_style = input.string("solid", "ADR Style", options= )
// Standard deviation inputs
std_dev_0_5 = input.float(0.5, "Std Dev 1 Multiplier", minval=0.1, maxval=5.0)
std_0_5_show = input.bool(true, "Show Std Dev 1", inline="std1")
std_0_5_color = input.color(color.gray, "Std Dev 1 Color", inline="std1")
std_0_5_style = input.string("dotted", "Std Dev 1 Style", options= , inline="std1")
std_dev_1 = input.float(1.0, "Std Dev 2 Multiplier", minval=0.1, maxval=5.0)
std_1_show = input.bool(true, "Show Std Dev 2", inline="std2")
std_1_color = input.color(color.gray, "Std Dev 2 Color", inline="std2")
std_1_style = input.string("dotted", "Std Dev 2 Style", options= , inline="std2")
std_dev_2 = input.float(2.0, "Std Dev 3 Multiplier", minval=0.1, maxval=5.0)
std_2_show = input.bool(true, "Show Std Dev 3", inline="std3")
std_2_color = input.color(color.gray, "Std Dev 3 Color", inline="std3")
std_2_style = input.string("dotted", "Std Dev 3 Style", options= , inline="std3")
// Fibonacci inputs
fib_1_level = input.float(0.3, "Fib Level 1", minval=0, maxval=2.0)
fib_1_show = input.bool(true, "Show Fib 1", inline="fib1")
fib_1_color = input.color(color.blue, "Fib 1 Color", inline="fib1")
fib_1_style = input.string("dashed", "Fib 1 Style", options= , inline="fib1")
fib_2_level = input.float(0.5, "Fib Level 2", minval=0, maxval=2.0)
fib_2_show = input.bool(true, "Show Fib 2", inline="fib2")
fib_2_color = input.color(color.blue, "Fib 2 Color", inline="fib2")
fib_2_style = input.string("dashed", "Fib 2 Style", options= , inline="fib2")
fib_3_level = input.float(0.7, "Fib Level 3", minval=0, maxval=2.0)
fib_3_show = input.bool(true, "Show Fib 3", inline="fib3")
fib_3_color = input.color(color.blue, "Fib 3 Color", inline="fib3")
fib_3_style = input.string("dashed", "Fib 3 Style", options= , inline="fib3")
show_labels = input.bool(true, "Show Labels")
// Stats table inputs
show_stats = input.bool(true, "Show Table")
sample_size = input.bool(true, "Show Sample Sizes")
tbl_loc = input.string('Bottom Right', "Table", options = )
tbl_size = input.string('Tiny', "", options = )
rch_color = input.color(color.rgb(3, 131, 99, 70), "Reached ")
csd_color = input.color(color.rgb(127, 1, 185, 70), "Closed Through ")
// Function to convert style string to line style
get_line_style(string style) =>
switch style
"solid" => line.style_solid
"dashed" => line.style_dashed
"dotted" => line.style_dotted
// Variables
reset = session.islastbar_regular
var float track_highs = 0.00
var float track_lows = 0.00
var float today_adr = 0.00
var adrs = array.new_float(adr_days, 0.00)
var line adr_pos = na
var line adr_neg = na
var line fib_1_pos = na
var line fib_1_neg = na
var line fib_2_pos = na
var line fib_2_neg = na
var line fib_3_pos = na
var line fib_3_neg = na
var line std_0_5_pos = na
var line std_0_5_neg = na
var line std_1_pos = na
var line std_1_neg = na
var line std_2_pos = na
var line std_2_neg = na
var label fib_1_pos_lbl = na
var label fib_1_neg_lbl = na
var label fib_2_pos_lbl = na
var label fib_2_neg_lbl = na
var label fib_3_pos_lbl = na
var label fib_3_neg_lbl = na
var label adr_pos_lbl = na
var label adr_neg_lbl = na
var label std_0_5_pos_lbl = na
var label std_0_5_neg_lbl = na
var label std_1_pos_lbl = na
var label std_1_neg_lbl = na
var label std_2_pos_lbl = na
var label std_2_neg_lbl = na
// ADR calculation
track_highs := reset ? high : math.max(high, track_highs )
track_lows := reset ? low : math.min(low, track_lows )
if reset
array.unshift(adrs, math.round_to_mintick(track_highs - track_lows ))
if array.size(adrs) > adr_days
array.pop(adrs)
today_adr := math.round_to_mintick(array.avg(adrs))
// Delete previous lines and labels
line.delete(adr_pos )
line.delete(adr_neg )
line.delete(fib_1_pos )
line.delete(fib_1_neg )
line.delete(fib_2_pos )
line.delete(fib_2_neg )
line.delete(fib_3_pos )
line.delete(fib_3_neg )
line.delete(std_0_5_pos )
line.delete(std_0_5_neg )
line.delete(std_1_pos )
line.delete(std_1_neg )
line.delete(std_2_pos )
line.delete(std_2_neg )
label.delete(fib_1_pos_lbl )
label.delete(fib_1_neg_lbl )
label.delete(fib_2_pos_lbl )
label.delete(fib_2_neg_lbl )
label.delete(fib_3_pos_lbl )
label.delete(fib_3_neg_lbl )
label.delete(adr_pos_lbl )
label.delete(adr_neg_lbl )
label.delete(std_0_5_pos_lbl )
label.delete(std_0_5_neg_lbl )
label.delete(std_1_pos_lbl )
label.delete(std_1_neg_lbl )
label.delete(std_2_pos_lbl )
label.delete(std_2_neg_lbl )
// Draw ADR lines
adr_pos := line.new(bar_index, open + today_adr, bar_index+50, open + today_adr,
width=width, color=adr_color, style=get_line_style(adr_style))
adr_neg := line.new(bar_index, open - today_adr, bar_index+50, open - today_adr,
width=width, color=adr_color, style=get_line_style(adr_style))
// Draw ADR labels
if show_labels
adr_pos_lbl := label.new(bar_index+50, open + today_adr, "ADR High (" + str.tostring(adr_days) + "D)",
xloc=xloc.bar_index, textalign=text.align_left, textcolor=adr_color, color=color.new(color.blue, 90), style=label.style_none)
adr_neg_lbl := label.new(bar_index+50, open - today_adr, "ADR Low (" + str.tostring(adr_days) + "D)",
xloc=xloc.bar_index, textalign=text.align_left, textcolor=adr_color, color=color.new(color.red, 90), style=label.style_none)
// Calculate deviations
var float half_dev = na
var float one_dev = na
var float two_dev = na
half_dev := today_adr * std_dev_0_5
one_dev := today_adr * std_dev_1
two_dev := today_adr * std_dev_2
// Draw standard deviation lines (with show/hide options)
if std_0_5_show
std_0_5_pos := line.new(bar_index, (open + today_adr) + half_dev, bar_index+50, (open + today_adr) + half_dev,
width=width, color=std_0_5_color, style=get_line_style(std_0_5_style))
std_0_5_neg := line.new(bar_index, (open - today_adr) - half_dev, bar_index+50, (open - today_adr) - half_dev,
width=width, color=std_0_5_color, style=get_line_style(std_0_5_style))
if show_labels
std_0_5_pos_lbl := label.new(bar_index+50, (open + today_adr) + half_dev, "Std " + str.tostring(std_dev_0_5),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_0_5_color, color=color.new(#000000,100), style=label.style_none)
std_0_5_neg_lbl := label.new(bar_index+50, (open - today_adr) - half_dev, "Std -" + str.tostring(std_dev_0_5),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_0_5_color, color=color.new(#000000,100), style=label.style_none)
if std_1_show
std_1_pos := line.new(bar_index, (open + today_adr) + one_dev, bar_index+50, (open + today_adr) + one_dev,
width=width, color=std_1_color, style=get_line_style(std_1_style))
std_1_neg := line.new(bar_index, (open - today_adr) - one_dev, bar_index+50, (open - today_adr) - one_dev,
width=width, color=std_1_color, style=get_line_style(std_1_style))
if show_labels
std_1_pos_lbl := label.new(bar_index+50, (open + today_adr) + one_dev, "Std " + str.tostring(std_dev_1),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_1_color, color=color.new(#000000,100), style=label.style_none)
std_1_neg_lbl := label.new(bar_index+50, (open - today_adr) - one_dev, "Std -" + str.tostring(std_dev_1),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_1_color, color=color.new(#000000,100), style=label.style_none)
if std_2_show
std_2_pos := line.new(bar_index, (open + today_adr) + two_dev, bar_index+50, (open + today_adr) + two_dev,
width=width, color=std_2_color, style=get_line_style(std_2_style))
std_2_neg := line.new(bar_index, (open - today_adr) - two_dev, bar_index+50, (open - today_adr) - two_dev,
width=width, color=std_2_color, style=get_line_style(std_2_style))
if show_labels
std_2_pos_lbl := label.new(bar_index+50, (open + today_adr) + two_dev, "Std " + str.tostring(std_dev_2),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_2_color, color=color.new(#000000,100), style=label.style_none)
std_2_neg_lbl := label.new(bar_index+50, (open - today_adr) - two_dev, "Std -" + str.tostring(std_dev_2),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=std_2_color, color=color.new(#000000,100), style=label.style_none)
// Draw Fibonacci lines
if fib_1_show
fib_1_pos := line.new(bar_index, open + today_adr * fib_1_level, bar_index+50, open + today_adr * fib_1_level,
width=width, color=fib_1_color, style=get_line_style(fib_1_style))
fib_1_neg := line.new(bar_index, open - today_adr * fib_1_level, bar_index+50, open - today_adr * fib_1_level,
width=width, color=fib_1_color, style=get_line_style(fib_1_style))
if show_labels
fib_1_pos_lbl := label.new(bar_index+50, open + today_adr * fib_1_level, "Fib " + str.tostring(fib_1_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_1_color, color=color.new(#000000,100), style=label.style_none)
fib_1_neg_lbl := label.new(bar_index+50, open - today_adr * fib_1_level, "Fib -" + str.tostring(fib_1_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_1_color, color=color.new(#000000,100), style=label.style_none)
if fib_2_show
fib_2_pos := line.new(bar_index, open + today_adr * fib_2_level, bar_index+50, open + today_adr * fib_2_level,
width=width, color=fib_2_color, style=get_line_style(fib_2_style))
fib_2_neg := line.new(bar_index, open - today_adr * fib_2_level, bar_index+50, open - today_adr * fib_2_level,
width=width, color=fib_2_color, style=get_line_style(fib_2_style))
if show_labels
fib_2_pos_lbl := label.new(bar_index+50, open + today_adr * fib_2_level, "Fib " + str.tostring(fib_2_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_2_color, color=color.new(#000000,100), style=label.style_none)
fib_2_neg_lbl := label.new(bar_index+50, open - today_adr * fib_2_level, "Fib -" + str.tostring(fib_2_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_2_color, color=color.new(#000000,100), style=label.style_none)
if fib_3_show
fib_3_pos := line.new(bar_index, open + today_adr * fib_3_level, bar_index+50, open + today_adr * fib_3_level,
width=width, color=fib_3_color, style=get_line_style(fib_3_style))
fib_3_neg := line.new(bar_index, open - today_adr * fib_3_level, bar_index+50, open - today_adr * fib_3_level,
width=width, color=fib_3_color, style=get_line_style(fib_3_style))
if show_labels
fib_3_pos_lbl := label.new(bar_index+50, open + today_adr * fib_3_level, "Fib " + str.tostring(fib_3_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_3_color, color=color.new(#000000,100), style=label.style_none)
fib_3_neg_lbl := label.new(bar_index+50, open - today_adr * fib_3_level, "Fib -" + str.tostring(fib_3_level),
xloc=xloc.bar_index, textalign=text.align_left, textcolor=fib_3_color, color=color.new(#000000,100), style=label.style_none)
else
today_adr := today_adr
line.set_x2(adr_pos, bar_index+50)
line.set_x2(adr_neg, bar_index+50)
if show_labels
label.set_x(adr_pos_lbl, bar_index+50)
label.set_x(adr_neg_lbl, bar_index+50)
if std_0_5_show
line.set_x2(std_0_5_pos, bar_index+50)
line.set_x2(std_0_5_neg, bar_index+50)
if show_labels
label.set_x(std_0_5_pos_lbl, bar_index+50)
label.set_x(std_0_5_neg_lbl, bar_index+50)
if std_1_show
line.set_x2(std_1_pos, bar_index+50)
line.set_x2(std_1_neg, bar_index+50)
if show_labels
label.set_x(std_1_pos_lbl, bar_index+50)
label.set_x(std_1_neg_lbl, bar_index+50)
if std_2_show
line.set_x2(std_2_pos, bar_index+50)
line.set_x2(std_2_neg, bar_index+50)
if show_labels
label.set_x(std_2_pos_lbl, bar_index+50)
label.set_x(std_2_neg_lbl, bar_index+50)
if fib_1_show
line.set_x2(fib_1_pos, bar_index+50)
line.set_x2(fib_1_neg, bar_index+50)
if show_labels
label.set_x(fib_1_pos_lbl, bar_index+50)
label.set_x(fib_1_neg_lbl, bar_index+50)
if fib_2_show
line.set_x2(fib_2_pos, bar_index+50)
line.set_x2(fib_2_neg, bar_index+50)
if show_labels
label.set_x(fib_2_pos_lbl, bar_index+50)
label.set_x(fib_2_neg_lbl, bar_index+50)
if fib_3_show
line.set_x2(fib_3_pos, bar_index+50)
line.set_x2(fib_3_neg, bar_index+50)
if show_labels
label.set_x(fib_3_pos_lbl, bar_index+50)
label.set_x(fib_3_neg_lbl, bar_index+50)
// Stats calculation
var float d_hi = high
var float d_lo = low
var float d_open = open
var float d_range = array.new_float()
var float adr_val = na
var float d_adr_hi = na
var float d_adr_lo = na
type adr_stats
int hit_adr_hi = 0
int hit_adr_lo = 0
int hit_adr_both = 0
int thru_adr_hi = 0
int thru_adr_lo = 0
int hit_fib_1_hi = 0
int hit_fib_1_lo = 0
int hit_fib_2_hi = 0
int hit_fib_2_lo = 0
int hit_fib_3_hi = 0
int hit_fib_3_lo = 0
int hit_std_0_5_hi = 0
int hit_std_0_5_lo = 0
int hit_std_1_hi = 0
int hit_std_1_lo = 0
int hit_std_2_hi = 0
int hit_std_2_lo = 0
int d_count = 0
var adr_sun = adr_stats.new()
var adr_mon = adr_stats.new()
var adr_tue = adr_stats.new()
var adr_wed = adr_stats.new()
var adr_thu = adr_stats.new()
var adr_fri = adr_stats.new()
var adr_sat = adr_stats.new()
if timeframe.change("D")
x = adr_mon
dow = dayofweek(time , "America/New_York")
if dow == dayofweek.tuesday
x := adr_tue
else if dow == dayofweek.wednesday
x := adr_wed
else if dow == dayofweek.thursday
x := adr_thu
else if dow == dayofweek.friday
x := adr_fri
else if dow == dayofweek.saturday
x := adr_sat
else if dow == dayofweek.sunday
x := adr_sun
if not na(adr_val)
x.d_count += 1
if d_hi > d_adr_hi
x.hit_adr_hi += 1
if d_lo < d_adr_lo
x.hit_adr_lo += 1
if d_hi > d_adr_hi and d_lo < d_adr_lo
x.hit_adr_both += 1
if close > d_adr_hi
x.thru_adr_hi += 1
if close < d_adr_lo
x.thru_adr_lo += 1
if fib_1_show
if d_hi > d_open + (adr_val * fib_1_level)
x.hit_fib_1_hi += 1
if d_lo < d_open - (adr_val * fib_1_level)
x.hit_fib_1_lo += 1
if fib_2_show
if d_hi > d_open + (adr_val * fib_2_level)
x.hit_fib_2_hi += 1
if d_lo < d_open - (adr_val * fib_2_level)
x.hit_fib_2_lo += 1
if fib_3_show
if d_hi > d_open + (adr_val * fib_3_level)
x.hit_fib_3_hi += 1
if d_lo < d_open - (adr_val * fib_3_level)
x.hit_fib_3_lo += 1
if std_0_5_show
if d_hi > d_adr_hi + (adr_val * std_dev_0_5)
x.hit_std_0_5_hi += 1
if d_lo < d_adr_lo - (adr_val * std_dev_0_5)
x.hit_std_0_5_lo += 1
if std_1_show
if d_hi > d_adr_hi + (adr_val * std_dev_1)
x.hit_std_1_hi += 1
if d_lo < d_adr_lo - (adr_val * std_dev_1)
x.hit_std_1_lo += 1
if std_2_show
if d_hi > d_adr_hi + (adr_val * std_dev_2)
x.hit_std_2_hi += 1
if d_lo < d_adr_lo - (adr_val * std_dev_2)
x.hit_std_2_lo += 1
if timeframe.change("D")
d_open := open
array.unshift(d_range, d_hi - d_lo)
if array.size(d_range) > adr_days
array.pop(d_range)
if array.size(d_range) == adr_days
adr_val := array.avg(d_range)
d_adr_hi := open + (adr_val*std_x)/2
d_adr_lo := open - (adr_val*std_x)/2
d_hi := high
d_lo := low
else
d_hi := math.max(high, d_hi)
d_lo := math.min(low, d_lo)
// Table functions
get_table_pos(pos) =>
switch pos
"Bottom Center" => position.bottom_center
"Bottom Left" => position.bottom_left
"Bottom Right" => position.bottom_right
"Middle Center" => position.middle_center
"Middle Left" => position.middle_left
"Middle Right" => position.middle_right
"Top Center" => position.top_center
"Top Left" => position.top_left
"Top Right" => position.top_right
var _loc = get_table_pos(tbl_loc)
get_table_size(size) =>
switch size
'Tiny' => size.tiny
'Small' => size.small
'Normal' => size.normal
'Large' => size.large
'Huge' => size.huge
'Auto' => size.auto
var _size = get_table_size(tbl_size)
fmt_sample(s, float pct, int count) =>
str.format("{0,number,percent}", pct) + (sample_size ? " ("+str.tostring(count)+")" : "")
// Draw table
if barstate.islast and show_stats
var tbl = table.new(_loc, 100, 100, chart.bg_color, chart.fg_color, 2, chart.fg_color, 1)
// Column headers (days + empty first cell)
table.cell(tbl, 0, 0, "Level", text_size = _size)
table.cell(tbl, 1, 0, "Mon", bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, 0, "Tue", bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, 0, "Wed", bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, 0, "Thu", bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, 0, "Fri", bgcolor = rch_color, text_size = _size)
// Row headers and data
var row = 1
table.cell(tbl, 0, row, "ADR High", text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_adr_hi / adr_mon.d_count, adr_mon.hit_adr_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_adr_hi / adr_tue.d_count, adr_tue.hit_adr_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_adr_hi / adr_wed.d_count, adr_wed.hit_adr_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_adr_hi / adr_thu.d_count, adr_thu.hit_adr_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_adr_hi / adr_fri.d_count, adr_fri.hit_adr_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "ADR Low", text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_adr_lo / adr_mon.d_count, adr_mon.hit_adr_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_adr_lo / adr_tue.d_count, adr_tue.hit_adr_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_adr_lo / adr_wed.d_count, adr_wed.hit_adr_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_adr_lo / adr_thu.d_count, adr_thu.hit_adr_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_adr_lo / adr_fri.d_count, adr_fri.hit_adr_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "ADR High (Close)", text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.thru_adr_hi / adr_mon.d_count, adr_mon.thru_adr_hi), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.thru_adr_hi / adr_tue.d_count, adr_tue.thru_adr_hi), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.thru_adr_hi / adr_wed.d_count, adr_wed.thru_adr_hi), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.thru_adr_hi / adr_thu.d_count, adr_thu.thru_adr_hi), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.thru_adr_hi / adr_fri.d_count, adr_fri.thru_adr_hi), bgcolor = csd_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "ADR Low (Close)", text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.thru_adr_lo / adr_mon.d_count, adr_mon.thru_adr_lo), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.thru_adr_lo / adr_tue.d_count, adr_tue.thru_adr_lo), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.thru_adr_lo / adr_wed.d_count, adr_wed.thru_adr_lo), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.thru_adr_lo / adr_thu.d_count, adr_thu.thru_adr_lo), bgcolor = csd_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.thru_adr_lo / adr_fri.d_count, adr_fri.thru_adr_lo), bgcolor = csd_color, text_size = _size)
row := row + 1
if fib_1_show
table.cell(tbl, 0, row, "Fib " + str.tostring(fib_1_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_1_hi / adr_mon.d_count, adr_mon.hit_fib_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_1_hi / adr_tue.d_count, adr_tue.hit_fib_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_1_hi / adr_wed.d_count, adr_wed.hit_fib_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_1_hi / adr_thu.d_count, adr_thu.hit_fib_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_1_hi / adr_fri.d_count, adr_fri.hit_fib_1_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Fib -" + str.tostring(fib_1_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_1_lo / adr_mon.d_count, adr_mon.hit_fib_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_1_lo / adr_tue.d_count, adr_tue.hit_fib_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_1_lo / adr_wed.d_count, adr_wed.hit_fib_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_1_lo / adr_thu.d_count, adr_thu.hit_fib_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_1_lo / adr_fri.d_count, adr_fri.hit_fib_1_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
if fib_2_show
table.cell(tbl, 0, row, "Fib " + str.tostring(fib_2_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_2_hi / adr_mon.d_count, adr_mon.hit_fib_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_2_hi / adr_tue.d_count, adr_tue.hit_fib_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_2_hi / adr_wed.d_count, adr_wed.hit_fib_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_2_hi / adr_thu.d_count, adr_thu.hit_fib_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_2_hi / adr_fri.d_count, adr_fri.hit_fib_2_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Fib -" + str.tostring(fib_2_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_2_lo / adr_mon.d_count, adr_mon.hit_fib_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_2_lo / adr_tue.d_count, adr_tue.hit_fib_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_2_lo / adr_wed.d_count, adr_wed.hit_fib_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_2_lo / adr_thu.d_count, adr_thu.hit_fib_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_2_lo / adr_fri.d_count, adr_fri.hit_fib_2_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
if fib_3_show
table.cell(tbl, 0, row, "Fib " + str.tostring(fib_3_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_3_hi / adr_mon.d_count, adr_mon.hit_fib_3_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_3_hi / adr_tue.d_count, adr_tue.hit_fib_3_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_3_hi / adr_wed.d_count, adr_wed.hit_fib_3_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_3_hi / adr_thu.d_count, adr_thu.hit_fib_3_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_3_hi / adr_fri.d_count, adr_fri.hit_fib_3_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Fib -" + str.tostring(fib_3_level), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_fib_3_lo / adr_mon.d_count, adr_mon.hit_fib_3_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_fib_3_lo / adr_tue.d_count, adr_tue.hit_fib_3_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_fib_3_lo / adr_wed.d_count, adr_wed.hit_fib_3_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_fib_3_lo / adr_thu.d_count, adr_thu.hit_fib_3_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_fib_3_lo / adr_fri.d_count, adr_fri.hit_fib_3_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
if std_0_5_show
table.cell(tbl, 0, row, "Std " + str.tostring(std_dev_0_5), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_0_5_hi / adr_mon.d_count, adr_mon.hit_std_0_5_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_0_5_hi / adr_tue.d_count, adr_tue.hit_std_0_5_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_0_5_hi / adr_wed.d_count, adr_wed.hit_std_0_5_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_0_5_hi / adr_thu.d_count, adr_thu.hit_std_0_5_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_0_5_hi / adr_fri.d_count, adr_fri.hit_std_0_5_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Std -" + str.tostring(std_dev_0_5), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_0_5_lo / adr_mon.d_count, adr_mon.hit_std_0_5_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_0_5_lo / adr_tue.d_count, adr_tue.hit_std_0_5_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_0_5_lo / adr_wed.d_count, adr_wed.hit_std_0_5_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_0_5_lo / adr_thu.d_count, adr_thu.hit_std_0_5_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_0_5_lo / adr_fri.d_count, adr_fri.hit_std_0_5_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
if std_1_show
table.cell(tbl, 0, row, "Std " + str.tostring(std_dev_1), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_1_hi / adr_mon.d_count, adr_mon.hit_std_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_1_hi / adr_tue.d_count, adr_tue.hit_std_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_1_hi / adr_wed.d_count, adr_wed.hit_std_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_1_hi / adr_thu.d_count, adr_thu.hit_std_1_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_1_hi / adr_fri.d_count, adr_fri.hit_std_1_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Std -" + str.tostring(std_dev_1), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_1_lo / adr_mon.d_count, adr_mon.hit_std_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_1_lo / adr_tue.d_count, adr_tue.hit_std_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_1_lo / adr_wed.d_count, adr_wed.hit_std_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_1_lo / adr_thu.d_count, adr_thu.hit_std_1_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_1_lo / adr_fri.d_count, adr_fri.hit_std_1_lo), bgcolor = rch_color, text_size = _size)
row := row + 1
if std_2_show
table.cell(tbl, 0, row, "Std " + str.tostring(std_dev_2), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_2_hi / adr_mon.d_count, adr_mon.hit_std_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_2_hi / adr_tue.d_count, adr_tue.hit_std_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_2_hi / adr_wed.d_count, adr_wed.hit_std_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_2_hi / adr_thu.d_count, adr_thu.hit_std_2_hi), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_2_hi / adr_fri.d_count, adr_fri.hit_std_2_hi), bgcolor = rch_color, text_size = _size)
row := row + 1
table.cell(tbl, 0, row, "Std -" + str.tostring(std_dev_2), text_size = _size)
table.cell(tbl, 1, row, fmt_sample(adr_mon.d_count, adr_mon.hit_std_2_lo / adr_mon.d_count, adr_mon.hit_std_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 2, row, fmt_sample(adr_tue.d_count, adr_tue.hit_std_2_lo / adr_tue.d_count, adr_tue.hit_std_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 3, row, fmt_sample(adr_wed.d_count, adr_wed.hit_std_2_lo / adr_wed.d_count, adr_wed.hit_std_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 4, row, fmt_sample(adr_thu.d_count, adr_thu.hit_std_2_lo / adr_thu.d_count, adr_thu.hit_std_2_lo), bgcolor = rch_color, text_size = _size)
table.cell(tbl, 5, row, fmt_sample(adr_fri.d_count, adr_fri.hit_std_2_lo / adr_fri.d_count, adr_fri.hit_std_2_lo), bgcolor = rch_color, text_size = _size)
Anchored ATH Drawdown LevelsThe Anchored ATH Drawdown Levels plots horizontal lines from a chosen anchor price (ATH), showing potential pullback zones at set percentage drops below it.
This indicator's use lies in its anchored ATH framework, which rapidly visualizes precise drawdown levels as dynamic levels of interest or price targets enabling traders to anticipate pullback depths and potential reversal levels without manual calculations.
Pick "True ATH" for the all-time high or "Period ATH" for anchored highs reset weekly, monthly, or quarterly. Lines stretch right for a cleaner visual.
Key Features
Anchoring: True ATH (lifetime max) or Period ATH (resets on 1W/1M/3M intervals).
Drawdown Levels: 8 adjustable levels (defaults: -5%, -10%, -15%, -20% on; -25% to -50% off). Toggle each, set drop % (0.1-99.9), pick color, style (solid/dashed/dotted), width (1-3).
ATH Line: Optional ATH line with custom color, style, width.
Unified Look: Global overrides for all levels' color, style, width.
Labels: Show % drops (with/without prices) via text boxes or full tags; sizes from tiny to large.
Projection: Lines extend 5-100 bars right (default 20).
Settings
Anchor: Mode and timeframe.
Display: Toggle levels/ATH, set extension.
Labels: Style (text/full/none), size, price display.
Global/ATH/Levels: Colors, styles, widths (per-level or shared).
How to Use
Load on chart (overlays prices; handles up to 500 lines).
Choose anchor for your high.
Tune levels for key pullbacks (e.g., -5% minor, -20% major).
Customize visuals where the lines update on new peaks.
Relative Strength vs Benchmark SPYRelative Strength vs Benchmark (SPY)
This indicator compares the performance of the charted symbol (stock or ETF) against a benchmark index — by default, SPY (S&P 500). It plots a Relative Strength (RS) ratio line (Symbol / SPY) and its EMA(50) to visualize when the asset is outperforming or underperforming the market.
Key Features
📈 RS Line (blue): Shows how the asset performs relative to SPY.
🟠 EMA(50): Smooths the RS trend to highlight sustained leadership.
🟩 Green background: Symbol is outperforming SPY (RS > EMA).
🟥 Red background: Symbol is underperforming SPY (RS < EMA).
🔔 Alerts: Automatic notifications when RS crosses above/below its EMA — signaling new leadership or weakness.
How to Use
Apply to any stock or ETF chart.
Keep benchmark = SPY, or switch to another index (e.g., QQQ, IWM, XLK).
Watch for RS crossovers and trends:
Rising RS → money flowing into the asset.
Falling RS → rotation away from the asset.
Perfect for sector rotation, ETF comparison, and momentum analysis workflows.
BSL / SSL Liquidity Zones + Alerts//@version=5
indicator("BSL / SSL Liquidity Zones + Alerts", overlay=true, max_labels_count=500)
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator
Overview
The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities.
"Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY
### Key Features
✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics
✅ **Dynamic weighting**: Assets weighted by rolling correlation strength
✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro
✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9)
✅ **Visual transparency**: Live correlation panel, fair value bands, statistics
✅ **Non-repainting**: All calculations use confirmed historical data only
### What This Indicator Does
- Builds a **synthetic macro composite** from traditional assets
- Runs a **rolling regression** to predict BTC price from macro
- Calculates **deviation z-score** (how far BTC is from macro fair value)
- Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2)
- Generates **exit signals** when BTC returns to fair value (dev > 0)
### What This Indicator Is NOT
❌ Not a high-frequency trading system (sparse signals by design)
❌ Not optimized for absolute returns (optimized for Sharpe ratio)
❌ Not suitable as standalone trading system (best as overlay/confirmation)
❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks)
---
## Core Concept
### The Premise
Bitcoin doesn't trade in a vacuum. It's influenced by:
- **Risk appetite** (equities: QQQ, SPX)
- **Dollar strength** (DXY - inverse to risk assets)
- **Safe haven flows** (Gold: XAUUSD)
When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower.
### The Innovation
Instead of looking at BTC in isolation, this indicator:
1. **Measures how strongly** BTC currently correlates with each macro asset
2. **Builds a weighted composite** of those macro returns (the "D" driver)
3. **Regresses BTC price on D** to estimate "macro fair value"
4. **Tracks the deviation** between actual price and fair value
5. **Signals mean reversion** when deviation becomes extreme
### The Edge
The validated edge comes from:
- **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars)
- **Monotonic relationship** (more negative dev → higher forward returns)
- **Works out-of-sample** (test Sharpe +83-87% better than training)
- **Low correlation with buy & hold** (provides diversification value)
---
## Methodology
### Step 1: Macro Composite Driver D(t)
The indicator builds a weighted composite of macro asset returns:
**Process:**
1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD)
2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars
3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0
4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships
5. **Z-score normalize** each reference's returns over `fvWindow`
6. **Composite D(t)** = weighted sum of sign-adjusted z-scores
**Formula:**
```
For each reference i:
corr_i = correlation(BTC_returns, ref_i_returns, corrLen)
weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0
sign_i = +1 if corr_i >= 0 else -1
z_i = (ref_i_returns - mean) / std
contrib_i = sign_i * z_i * weight_i
D(t) = sum(contrib_i) / sum(weight_i)
```
**Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way.
---
### Step 2: Fair Value Regression
Uses rolling linear regression to predict BTC price from D(t):
**Model:**
```
BTC_price(t) = α + β * D(t)
```
**Calculation (Pine Script approach):**
```
corr_CD = correlation(BTC_price, D, fvWindow)
sd_price = stdev(BTC_price, fvWindow)
sd_D = stdev(D, fvWindow)
cov = corr_CD * sd_price * sd_D
var_D = variance(D, fvWindow)
β = cov / var_D
α = mean(BTC_price) - β * mean(D)
fair_value(t) = α + β * D(t)
```
**Result:** A time-varying "macro fair value" line that adapts as correlations change.
---
### Step 3: Deviation Oscillator
Measures how far BTC price has deviated from fair value:
**Calculation:**
```
residual(t) = BTC_price(t) - fair_value(t)
residual_std = stdev(residual, normWindow)
deviation(t) = residual(t) / residual_std
```
**Interpretation:**
- `dev = 0` → BTC at fair value
- `dev = -2` → BTC is 2 standard deviations **cheap** vs macro
- `dev = +2` → BTC is 2 standard deviations **rich** vs macro
---
### Step 4: Signal Generation
**Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro)
**Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value)
**No shorting** in default config (risk management choice - crypto volatility)
---
## How It Works
### Visual Components
#### 1. Price Chart (Main Panel)
**Fair Value Line (Orange):**
- The estimated "macro-driven fair value" for BTC
- Calculated from rolling regression on macro composite
**Fair Value Bands:**
- **±1σ** (light): 68% confidence zone
- **±2σ** (medium): 95% confidence zone
- **±3σ** (dark, dots): 99.7% confidence zone
**Entry/Exit Markers:**
- **Green "LONG" label** below bar: Entry signal (dev < -2)
- **Red "EXIT" label** above bar: Exit signal (dev > 0)
#### 2. Deviation Oscillator (Separate Pane)
**Line plot:**
- Shows current deviation z-score
- **Green** when dev < -2 (cheap)
- **Red** when dev > +2 (rich)
- **Gray** when neutral
**Histogram:**
- Visual representation of deviation magnitude
- Green bars = negative deviation (cheap)
- Red bars = positive deviation (rich)
**Threshold lines:**
- **Green dashed at -2.0**: Entry threshold
- **Red dashed at 0.0**: Exit threshold
- **Gray solid at 0**: Fair value line
#### 3. Correlation Panel (Top-Right)
Shows live correlation and weighting for each macro asset:
| Asset | Corr | Weight |
|-------|------|--------|
| QQQ | +0.45 | 0.45 |
| DXY | -0.32 | 0.32 |
| XAUUSD | +0.15 | 0.00 |
| Avg \|Corr\| | 0.31 | 0.77 |
**Reading:**
- **Corr**: Current rolling correlation with BTC (-1 to +1)
- **Weight**: How much this asset contributes to fair value (0 = excluded)
- **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals)
**Colors:**
- Green/Red corr = positive/negative correlation
- White weight = asset included, Gray = excluded (below minCorrAbs)
#### 4. Statistics Label (Bottom-Right)
```
━━━ BTC Macro FV ━━━
Dev: -2.34
Price: $103,192
FV: $110,500
Status: CHEAP ⬇
β: 103.52
```
**Fields:**
- **Dev**: Current deviation z-score
- **Price**: Current BTC close price
- **FV**: Current macro fair value estimate
- **Status**: CHEAP (< -2), RICH (> +2), or FAIR
- **β**: Current regression beta (sensitivity to macro)
---
## Installation & Setup
### TradingView Setup
1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.)
2. Open **Pine Editor** (bottom panel)
3. Click **"+ New"** → **"Blank indicator"**
4. **Delete** all default code
5. **Copy** the entire Pine Script from `GHPT_optimized.pine`
6. **Paste** into the editor
7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator"
8. Click **"Add to Chart"**
### Recommended Chart Settings
**Timeframe:** 4h (validated timeframe)
**Chart Type:** Candlestick or Heikin Ashi
**Overlay:** Yes (indicator plots on price chart + separate pane)
**Alternative Timeframes:**
- Daily: Works but slower signals
- 1h-2h: May work but not validated
- < 1h: Not recommended (too noisy)
### Symbol Requirements
**Primary:** BTC/USD or BTC/USDT on any exchange
**Macro References:** Automatically fetched
- QQQ (Nasdaq 100 ETF)
- DXY (US Dollar Index)
- XAUUSD (Gold spot)
**Data Requirements:**
- At least **90 bars** of history (warmup period)
- Premium TradingView recommended for full historical data
---
## Reading the Indicator
### Identifying Signals
#### Strong Long Signal (High Conviction)
- ✅ Deviation < -2.0 (extreme undervaluation)
- ✅ Avg |Corr| > 0.3 (strong macro relationships)
- ✅ Price touching or below -2σ band
- ✅ "LONG" label appears below bar
**Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe).
#### Moderate Long Signal (Lower Conviction)
- ⚠️ Deviation between -1.5 and -2.0
- ⚠️ Avg |Corr| between 0.2-0.3
- ⚠️ Price approaching -2σ band
**Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals.
#### Exit Signal
- 🔴 Deviation crosses above 0 (returns to fair value)
- 🔴 "EXIT" label appears above bar
**Interpretation:** Mean reversion complete. Close long positions.
#### Strong Short/Avoid Signal
- 🔴 Deviation > +2.0 (extreme overvaluation)
- 🔴 Avg |Corr| > 0.3
- 🔴 Price touching or above +2σ band
**Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure.
### Regime Detection
**Strong Regime (Reliable Signals):**
- Avg |Corr| > 0.3
- Multiple assets weighted > 0
- Fair value line tracking price reasonably well
**Weak Regime (Unreliable Signals):**
- Avg |Corr| < 0.2
- Most weights = 0 (grayed out)
- Fair value line diverging wildly from price
- **Action:** Ignore signals until correlations strengthen
ROC & Momentum FusionROC & Momentum Fusion
(by HabibiTrades ©)
Purpose:
“ROC & Momentum Fusion” combines the Rate of Change (ROC) with a MACD-style signal engine to identify early momentum reversals, confirmed trend shifts, and low-volatility choppy zones.
It’s built for traders who want early momentum detection with the clarity of trend persistence — adaptable to any instrument and timeframe.
⚙️ How It Works
Rate of Change (ROC):
Measures the percentage speed of price change over time, showing the raw momentum strength.
Signal Line (EMA):
A short EMA of the ROC — responds faster to new directional shifts, similar to a MACD signal line.
Histogram:
Displays acceleration and deceleration between the ROC and its signal line.
Persistent Trend States:
When the ROC crosses the signal line or zero, the indicator enters a new momentum regime
(bullish or bearish) and stays in that color until another flip occurs.
Dynamic Choppy Zone:
When ROC momentum fades within the zero buffer zone, the indicator turns orange, signaling a sideways or indecisive market.
🟢 Visual Regimes
Regime Description Color
Bullish Momentum ROC above zero or signal line 🟢 Neon Green
Bearish Momentum ROC below zero or signal line 🔴 Neon Red
Choppy / Neutral ROC hovering within ±threshold range 🟠 Neon Orange
This color system makes it visually effortless to see whether the market is trending, reversing, or consolidating.
🧭 Adaptive Intelligence
The script automatically adjusts to market type and session for consistent accuracy:
Session Adaptive: Adjusts smoothing based on global sessions (Asian, London, New York, Sydney).
Instrument Adaptive: Fine-tunes sensitivity automatically for major assets — NASDAQ (NQ), S&P 500 (ES), Gold (GC), Oil (CL), Bitcoin (BTC).
Volatility Normalization: Optionally divides ROC by its own standard deviation to stabilize noisy assets and maintain consistent scaling.
🔔 Signals & Alerts
Bullish Reversal:
ROC crosses above its signal or zero line — early momentum flip.
Bearish Reversal:
ROC crosses below its signal or zero line — downward momentum flip.
Alerts:
Both reversal conditions include built-in alert triggers for automation and notifications.
🎨 Visual Features
Main ROC Line: Adaptive EMA of ROC, color-coded by trend regime.
Signal Line: Optional white EMA overlay for MACD-style crossovers.
Histogram: Visual burst display of acceleration (green/red).
Reversal Markers: Optional triangles marking exact crossover points.
Threshold Lines: Highlight the zero and buffer zones for visual clarity.
🧩 Best Use Cases
Identify early momentum shifts before price confirms them.
Confirm trend continuation or exhaustion with color persistence.
Detect choppy / low-volatility periods instantly.
Works across all timeframes — from 1-minute scalping to weekly swings.
Combine with structure, EMAs, or volume for confirmation.
⚙️ Recommended Settings
Setting Default Description
ROC Period 6 Core momentum length (lower = faster response).
Signal EMA Length 3 MACD-style responsiveness (lower = more reactive).
Zero Buffer Threshold 0.15 Defines the width of the neutral zone around zero.
Choppy Zone Multiplier 1.0 Expands or tightens the orange zone sensitivity.
These defaults have been optimized through real-market testing to balance responsiveness and smoothness across different asset classes.
⚠️ Notes
The color regime is persistent, meaning once the line turns bullish or bearish, it remains in that state until momentum structurally flips.
The orange zone represents momentum uncertainty and helps avoid false entries in range-bound markets.
Works seamlessly on any timeframe and with any asset.
davidqqq//@version=5
indicator('CD', overlay=false, max_bars_back=500)
// 输入参数
S = input(12, title='Short EMA Period')
P = input(26, title='Long EMA Period')
M = input(9, title='Signal Line Period')
// 计算DIFF, DEA和MACD值
fastEMA = ta.ema(close, S)
slowEMA = ta.ema(close, P)
DIFF = fastEMA - slowEMA
DEA = ta.ema(DIFF, M)
MACD = (DIFF - DEA) * 2
// 计算N1和MM1
N1 = ta.barssince(ta.crossunder(MACD, 0))
MM1 = ta.barssince(ta.crossover(MACD, 0))
// 确保长度参数大于0
N1_safe = na(N1) ? 1 : math.max(N1 + 1, 1)
MM1_safe = na(MM1) ? 1 : math.max(MM1 + 1, 1)
// 计算CC和DIFL系列值
CC1 = ta.lowest(close, N1_safe)
CC2 = nz(CC1 , CC1)
CC3 = nz(CC2 , CC2)
DIFL1 = ta.lowest(DIFF, N1_safe)
DIFL2 = nz(DIFL1 , DIFL1)
DIFL3 = nz(DIFL2 , DIFL2)
// 计算CH和DIFH系列值
CH1 = ta.highest(close, MM1_safe)
CH2 = nz(CH1 , CH1)
CH3 = nz(CH2 , CH2)
DIFH1 = ta.highest(DIFF, MM1_safe)
DIFH2 = nz(DIFH1 , DIFH1)
DIFH3 = nz(DIFH2 , DIFH2)
// 判断买入条件
AAA = CC1 < CC2 and DIFL1 > DIFL2 and MACD < 0 and DIFF < 0
BBB = CC1 < CC3 and DIFL1 < DIFL2 and DIFL1 > DIFL3 and MACD < 0 and DIFF < 0
CCC = (AAA or BBB) and DIFF < 0
LLL = not CCC and CCC
XXX = AAA and DIFL1 <= DIFL2 and DIFF < DEA or BBB and DIFL1 <= DIFL3 and DIFF < DEA
JJJ = CCC and math.abs(DIFF ) >= math.abs(DIFF) * 1.01
BLBL = JJJ and CCC and math.abs(DIFF ) * 1.01 <= math.abs(DIFF)
DXDX = not JJJ and JJJ
DJGXX = (close < CC2 or close < CC1) and (JJJ or JJJ ) and not LLL and math.sum(JJJ ? 1 : 0, 24) >= 1
DJXX = not(math.sum(DJGXX ? 1 : 0, 2) >= 1) and DJGXX
DXX = (XXX or DJXX) and not CCC
// 判断卖出条件
ZJDBL = CH1 > CH2 and DIFH1 < DIFH2 and MACD > 0 and DIFF > 0
GXDBL = CH1 > CH3 and DIFH1 > DIFH2 and DIFH1 < DIFH3 and MACD > 0 and DIFF > 0
DBBL = (ZJDBL or GXDBL) and DIFF > 0
DBL = not DBBL and DBBL and DIFF > DEA
DBLXS = ZJDBL and DIFH1 >= DIFH2 and DIFF > DEA or GXDBL and DIFH1 >= DIFH3 and DIFF > DEA
DBJG = DBBL and DIFF >= DIFF * 1.01
DBJGXC = not DBJG and DBJG
DBJGBL = DBJG and DBBL and DIFF * 1.01 <= DIFF
ZZZZZ = (close > CH2 or close > CH1) and (DBJG or DBJG ) and not DBL and math.sum(DBJG ? 1 : 0, 23) >= 1
YYYYY = not(math.sum(ZZZZZ ? 1 : 0, 2) >= 1) and ZZZZZ
WWWWW = (DBLXS or YYYYY) and not DBBL
// plot买入和卖出信号
if DXDX
label.new(bar_index, low, text='抄底', style=label.style_label_up, color=color.red, textcolor=color.white, size=size.small)
if DBJGXC
label.new(bar_index, high, text='卖出', style=label.style_label_down, color=color.green, textcolor=color.white, size=size.small)
Hindenburg OmenThe Hindenburg Omen highlights periods of internal market stress — when both new 52-week highs and new lows expand while the NYSE remains in an uptrend.
This condition often precedes major corrections or volatility spikes by revealing divergence beneath the surface of an advancing market.
The indicator triggers when four classic breadth rules align: elevated highs and lows, a positive trend, a negative McClellan Oscillator, and a highs-to-lows ratio under 2:1.
Use it on broad indices (NYSE, S&P 500) as an early-warning context tool, NOT a standalone sell signal.
Henry's MA & RSProviding 10 21 50 200 MA and RS rating based on S&P 500, basically for US stocks. Enjoy!
Market Structure Trailing Stop MTF [Inspired by LuxAlgo]# Market Structure Trailing Stop MTF
**OPEN-SOURCE SCRIPT**
*208k+ views on original · Modified for MTF Support*
This indicator is a direct adaptation of the renowned **Market Structure Trailing Stop** by **LuxAlgo** (original script: [Market Structure Trailing Stop ]()). The core logic remains untouched, providing dynamic trailing stops based on market structure breaks (CHoCH/BOS). The **only modification** is the addition of **Multi-Timeframe (MTF) support**, allowing users to apply the trailing stops and structures from **higher timeframes (HTF)** directly on their current chart. This enhances usability for traders analyzing cross-timeframe confluence without switching charts.
**Special thanks to LuxAlgo** for releasing this powerful open-source tool under CC BY-NC-SA 4.0. Your contributions to the TradingView community have inspired countless traders—grateful for the solid foundation!
## 🔶 How the Script Works: A Deep Dive
At its heart, this indicator detects **market structure shifts** (bullish or bearish breaks of swing highs/lows) and uses them to generate **adaptive trailing stops**. These stops trail the price while protecting profits and acting as dynamic support/resistance levels. The MTF enhancement pulls this logic from user-specified higher timeframes, overlaying HTF structures and stops on the lower timeframe chart for seamless multi-timeframe analysis.
### Core Logic (Unchanged from LuxAlgo's Original)
1. **Pivot Detection**:
- Uses `ta.pivothigh()` and `ta.pivotlow()` with a user-defined lookback (`length`) to identify swing highs (PH) and lows (PL).
- Coordinates (price `y` and bar index/time `x`) are stored in persistent variables (`var`) for tracking recent pivots.
2. **Market Structure Detection**:
- **Bullish Structure (BOS/CHoCH)**: Triggers when `close > recent PH` (break above swing high).
- If `resetOn = 'CHoCH'`, resets only on major shifts (Change of Character); otherwise, on all breaks.
- Sets trend state `os = 1` (bullish) and highlights the break with a horizontal line (dashed for CHoCH, dotted for BOS).
- Initializes trailing stop at the local minimum (lowest low since the pivot) using a backward loop: `btm = math.min(low , btm)`.
- **Bearish Structure**: Triggers when `close < recent PL`, mirroring the bullish logic (`os = -1`, local maximum for stop).
- Structure state `ms` tracks the break type (1 for bull, -1 for bear, 0 neutral), resetting based on user settings.
3. **Trailing Stop Calculation**:
- Tracks **trailing max/min**:
- On new bull structure: Reset `max = close`.
- On new bear: Reset `min = close`.
- Otherwise: `max = math.max(close, max)` / `min = math.min(close, min)`.
- **Stop Adjustment** (the "trailing" magic):
- On fresh structure: `ts = btm` (bull) or `top` (bear).
- In ongoing trend: Increment/decrement by a percentage of the max/min change:
- Bull: `ts += (max - max ) * (incr / 100)`
- Bear: `ts += (min - min ) * (incr / 100)`
- This creates a **ratcheting effect**: Stops move favorably with the trend but never against it, converging toward price at a controlled rate.
- **Visuals**:
- Plots `ts` line colored by trend (teal for bull, red for bear).
- Fills area between `close` and `ts` (orange on retracements).
- Draws structure lines from pivot to break point.
4. **Edge Cases**:
- Variables like `ph_cross`/`pl_cross` prevent multiple triggers on the same pivot.
- Neutral state (`ms = 0`) preserves prior `max/min` until a new structure.
### MTF Enhancement (Our Addition)
- **request.security() Integration**:
- Wraps the entire core function `f()` in a security call for each timeframe (`tf1`, `tf2`).
- Returns HTF values (e.g., `ts1`, `os1`, structure times/prices) to the chart's context.
- Uses `lookahead=barmerge.lookahead_off` for accurate historical repainting-free data.
- Structures are drawn using `xloc.bar_time` to align HTF lines precisely on the LTF chart.
- **Multi-Output Handling**:
- Separate plots/fills/lines for each TF (e.g., `plot_ts1`, `plot_ts2`).
- Colors and toggles per TF to distinguish HTF1 (e.g., teal/red) from HTF2 (e.g., blue/maroon).
- **Benefits**: Spot HTF bias on LTF entries, e.g., enter longs only if both TF1 (1H) and TF2 (4H) show bullish `os=1`.
This keeps the script lightweight—**no repainting, max 500 lines**, and fully compatible with LuxAlgo's original behavior when TFs are set to the chart's timeframe.
## 🔶 SETTINGS
### Core Parameters
- **Pivot Lookback** (`length = 14`): Bars left/right for pivot detection. Higher = smoother structures, fewer signals; lower = more noise.
- **Increment Factor %** (`incr = 100`): Speed of stop convergence (0-∞). 100% = full ratchet (mirrors max/min exactly); <100% = slower trail, reduces whipsaws.
- **Reset Stop On** (`'CHoCH'`): `'CHoCH'` = Reset only on major reversals (dashed lines); `'All'` = Reset on every BOS/CHoCH (tighter stops).
### MTF Support
- **Timeframe 1** (`tf1 = ""`): HTF for first set (e.g., "1H"). Empty = current chart.
- **Timeframe 2** (`tf2 = ""`): Second HTF (e.g., "4H"). Enables dual confluence.
### Display Toggles
- **Show Structures** (`true`): Draws horizontal lines for breaks (per TF colors).
- **Show Trailing Stop TF1/TF2** (`true`): Plots the stop line.
- **Show Fill TF1/TF2** (`true`): Area fill between close and stop.
### Candle Coloring (Optional)
- **Color Candles** (`false`): Enables custom `plotcandle` for body/wick/border.
- **Candle Color Based On TF** (`"None"`): `"TF1"`, `"TF2"`, or none. Colors bull trend green, bear red.
- **Candle Colors**: Separate inputs for bull/bear body, wick, border (e.g., solid green body, transparent wick).
### Alerts
- **Enable MS Break Alerts** (`false`): Notifies on structure breaks (bull/bear per TF) **only on bar close** (`barstate.isconfirmed` + `alert.freq_once_per_bar_close`).
- **Enable Stop Hit Alerts** (`false`): Triggers on stop breaches (long/short per TF), using `ta.crossunder/crossover`.
### Colors
- **TF1 Colors**: Bullish (teal), Bearish (red), Retracement (orange).
- **TF2 Colors**: Bullish (blue), Bearish (maroon), Retracement (orange).
- **Area Transparency** (`80`): Fill opacity (0-100).
## 🔶 USAGE
Trailing stops shine in **trend-following strategies**:
- **Entries**: Use structure breaks as signals (e.g., long on bullish BOS from HTF1).
- **Exits**: Trail stops for profit-locking; alert on hits for automation.
- **Confluence**: Overlay HTF1 (e.g., 1H) for bias, HTF2 (e.g., Daily) for major levels—enter LTF only on alignment.
- **Risk Management**: Lower `incr` avoids early stops in chop; reset on `'All'` for aggressive trailing.
! (i.imgur.com)
*HTF1 shows bullish structure (teal line), trailing stop ratchets up—long entry confirmed on LTF pullback.*
! (i.imgur.com)
*TF1 (blue) bearish, TF2 (red) neutral—avoid shorts until alignment.*
! (i.imgur.com)
*Colored based on TF1 trend: Green bodies on bull `os=1`.*
Pro Tip: Test on demo—pair with LuxAlgo's other tools like Smart Money Concepts for full structure ecosystem.
## 🔶 DETAILS: Mathematical Breakdown
On bullish break:
- Local min: `btm = ta.lowest(n - ph_x)` (optimized loop equivalent).
- Stop init: `ts = btm`.
- Update: `Δmax = max - max `, `ts_new = ts + Δmax * (incr/100)`.
Bearish mirrors with `Δmin` (negative, so decrements `ts`).
In MTF: HTF `time` aligns lines via `line.new(htf_time, level, current_time, level, xloc.bar_time)`.
No logs/math libs needed—pure Pine v5 efficiency.
## Disclaimer
This is for educational purposes. Not financial advice. Backtest thoroughly. Original by LuxAlgo—modify at your risk. See TradingView's (www.tradingview.com). Licensed under CC BY-NC-SA 4.0 (attribution to LuxAlgo required).
X Tail that Wagsintraday session-framework and ETH-anchored VWAP tool for TradingView. It draws today’s OVN (ETH) high/mid/low, today’s RTH-day open, previous day open/high/low, and a carried ETH VWAP handle (yesterday’s 4:00 PM NY VWAP, projected forward) to give you a clean, non-repainting scaffold for bias, structure, and execution. All timestamps are New York–local with DST handled explicitly, so historical sessions align correctly across time changes.
Key Capabilities
ETH OVN Range (18:00 → 09:30 NY)
Captures the rolling overnight high/low and computes the mid; at 09:30 NY it locks those levels and extends them to 16:00 NY (same day).
Optional labels (size/color configurable) placed slightly to the right of the 4 PM timestamp for readability.
Daily Handles (Today & Previous Day)
Today’s open line starts at the ETH open (anchor preserved) and extends toward 4 PM NY (or up to the “current bar + 5 bars” cap), with label control.
Previous day open/high/low plotted as discrete reference lines for carry-over structure.
ETH-Anchored VWAP (Live) + Bands
ETH-anchored VWAP runs only during the active ETH session (DST-aware).
Optional VWAP bands (0.5×, 1.0×, 2.0× multipliers) plotted as line-break series.
Carried ETH VWAP Handle (PD 4 PM Snapshot)
At 16:00 NY, the script snapshots the final ETH VWAP value.
On the next ETH open, it projects that value as a static dashed line through the session (non-mutating, non-repainting), with optional label.
Labeling & Styling
Single-toggle label system with color and five sizes.
Per-line color/width controls for quick visual hierarchy.
Internal “tail” logic keeps right endpoints near price (open-anchored lines extend to min(4 PM, now + 5 bars)), avoiding chart-wide overdraw.
Robust Session Logic
All session boundaries computed in NY local time; DST rules applied for historical bars.
Cross-midnight windows handled safely (no gaps or misalignment around day rolls).
Primary Use Cases
Session Bias & Context
Use OVN H/M/L and today’s open to define structural bias zones before RTH begins. A break-and-hold above OVN mid, for example, can filter long ideas; conversely, rejection at OVN high can warn of mean reversion.
Carry-Forward Mean/Value Reference
The carried ETH VWAP (PD 4 PM) acts as a “value memory” line for the next day. Traders can:
Fade tests away from it in balanced conditions,
Use it as a pullback/acceptance gauge during trends,
Track liquidity grabs when price spikes through and reclaims.
Execution Planning & Risk
Anchor stops/targets around PD H/L and OVN H/M/L for well-defined invalidation.
Combine with your entry model (order-flow, momentum, or pattern) to time fades at range extremes or momentum breaks from OVN mid.
Confluence Mapping
Layer the tool with opening range tools, HTF zones, or profile/VWAPs (weekly/daily) to spot high-quality confluence where multiple references cluster.
Regime & Day-Type Read
Quickly see whether RTH accepts/rejects the OVN range or gravitates to PD VWAP handle, helping classify the day (trend, balanced, double-distribution, etc.).
Quick Start
Apply to your intraday chart (any instrument supported by TradingView; best on ≤15m for live intraday context).
In Current Day group, keep Open and OVN HL on; optionally display the mid.
In Previous Day group, enable PD Open/HL for carry-over levels.
Enable AVWAP if you want live ETH-anchored VWAP and its Bands for distance context.
Keep PD VWAP on to project yesterday’s 4 PM ETH VWAP as a static dashed line into today.
Use the Label group to size/color the on-chart tags.
Settings Overview (Plain-English)
Label: Toggle labels on/off; choose label text color and size.
Current Day:
Open (color/width) — daily open line anchored at ETH open.
OVN HL (and Mid) — overnight high/low and midpoint, locked at 09:30 and extended to 16:00.
AVWAP + Bands — ETH-anchored VWAP with optional 0.5×/1×/2× bands.
Previous Day:
PD Open/HL — yesterday’s daily handles.
PD VWAP — the carried snapshot of yesterday’s 4 PM ETH VWAP projected forward (dashed).
Notes & Best Practices
Time Zone: All session logic is hard-coded to America/New_York and DST-robust. No manual DST tweaks required.
Non-Repainting: The carried PD VWAP line is a snapshot; once drawn, it does not back-fill or mutate.
Intraday Use: Designed for intraday execution. It will display on higher TFs, but the session granularity is most informative at ≤15m.
Performance: Script caps lines/labels (500) and uses short “tails” to keep charts responsive.
Compatibility: Uses request.security(..., "D", series, lookahead_on) intentionally to lock daily handles early for planning; this is by design.
Typical Playbook Examples
Fade Extremes in Balance: As RTH opens inside OVN, look for rejection wicks at OVN High with confluence from PD VWAP handle overhead; risk above OVN High.
Trend Continuation: In directional sessions, acceptances above OVN Mid with price pulling back to the live ETH VWAP can offer continuation entries.
Reversion to Value: Sharp extensions away from the carried PD VWAP that quickly stall often revert to that handle; use it as a target or as an acceptance test.
Risk & Position DashboardRisk & Position Dashboard
Overview
The Risk & Position Dashboard is a comprehensive trading tool designed to help traders calculate optimal position sizes, manage risk, and visualize potential profit/loss scenarios before entering trades. This indicator provides real-time calculations for position sizing based on account size, risk percentage, and stop-loss levels, while displaying multiple take-profit targets with customizable risk-reward ratios.
Key Features
Position Sizing & Risk Management:
Automatic position size calculation based on account size and risk percentage
Support for leveraged trading with maximum leverage limits
Fractional shares support for brokers that allow partial share trading
Real-time fee calculation including entry, stop-loss, and take-profit fees
Break-even price calculation including trading fees
Multi-Target Profit Management:
Support for up to 3 take-profit levels with individual portion allocations
Customizable risk-reward ratios for each take-profit target
Visual profit/loss zones displayed as colored boxes on the chart
Individual profit calculations for each take-profit level
Visual Dashboard:
Clean, customizable table display showing all key metrics
Configurable label positioning and styling options
Real-time tracking of whether stop-loss or take-profit levels have been reached
Color-coded visual zones for easy identification of risk and reward areas
Advanced Configuration:
Comprehensive input validation and error handling
Support for different chart timeframes and symbols
Customizable colors, fonts, and display options
Hide/show individual data fields for personalized dashboard views
How to Use
Set Account Parameters: Configure your account size, maximum risk percentage per trade, and trading fees in the "Account Settings" section.
Define Trade Setup: Use the "Entry" time picker to select your entry point on the chart, then input your entry price and stop-loss level.
Configure Take Profits: Set your desired risk-reward ratios and portion allocations for each take-profit level. The script supports 1-3 take-profit targets.
Analyze Results: The dashboard will automatically calculate and display position size, number of shares, potential profits/losses, fees, and break-even levels.
Visual Confirmation: Colored boxes on the chart show profit zones (green) and loss zones (red), with lines extending to current price levels.
Reset Entry and SL:
You can easily reset the entry and stop-loss by clicking the "Reset points..." button from the script's "More" menu.
This is useful if you want to quickly clear your current trade setup and start fresh without manually adjusting the points on the chart.
Calculations
The script performs sophisticated calculations including:
Position size based on risk amount and price difference between entry and stop-loss
Leverage requirements and position amount calculations
Fee-adjusted risk-reward ratios for realistic profit expectations
Break-even price including all trading costs
Individual profit calculations for partial position closures
Detailed Take-Profit Calculation Formula:
The take-profit prices are calculated using the following mathematical formula:
// Core variables:
// risk_amount = account_size * (risk_percentage / 100)
// total_risk_per_share = |entry_price - sl_price| + (entry_price * fee%) + (sl_price * fee%)
// shares = risk_amount / total_risk_per_share
// direction_factor = 1 for long positions, -1 for short positions
// Take-profit calculation:
net_win = total_risk_per_share * shares * RR_ratio
tp_price = (net_win + (direction_factor * entry_price * shares) + (entry_price * fee% * shares)) / (direction_factor * shares - fee% * shares)
Step-by-step example for a long position (based on screenshot):
Account Size: 2,000 USDT, Risk: 2% = 40 USDT
Entry: 102,062.9 USDT, Stop Loss: 102,178.4 USDT, Fee: 0.06%
Risk per share: |102,062.9 - 102,178.4| + (102,062.9 × 0.0006) + (102,178.4 × 0.0006) = 115.5 + 61.24 + 61.31 = 238.05 USDT
Shares: 40 ÷ 238.05 = 0.168 shares (rounded to 0.17 in display)
Position Size: 0.17 × 102,062.9 = 17,350.69 USDT
Position Amount (with 9x leverage): 17,350.69 ÷ 9 = 1,927.85 USDT
For 2:1 RR: Net win = 238.05 × 0.17 × 2 = 80.94 USDT
TP1 price = (80.94 + (1 × 102,062.9 × 0.17) + (102,062.9 × 0.0006 × 0.17)) ÷ (1 × 0.17 - 0.0006 × 0.17) = 101,464.7 USDT
For 3:1 RR: TP2 price = 101,226.7 USDT (following same formula with RR=3)
This ensures that after accounting for all fees, the actual risk-reward ratio matches the specified target ratio.
Risk Management Features
Maximum Trade Amount: Optional setting to limit position size regardless of account size
Leverage Limits: Built-in maximum leverage protection
Fee Integration: All calculations include realistic trading fees for accurate expectations
Validation: Automatic checking that take-profit portions sum to 100%
Historical Tracking: Visual indication when stop-loss or take-profit levels are reached (within last 5000 bars)
Understanding Max Trade Amount - Multiple Simultaneous Trades:
The "Max Trade Amount" feature is designed for traders who want to open multiple positions simultaneously while maintaining proper risk management. Here's how it works:
Key Concept:
- Risk percentage (2%) always applies to your full Account Size
- Max Trade Amount limits the capital allocated per individual trade
- This allows multiple trades with full risk on each trade
Example from Screenshot:
Account Size: 2,000 USDT
Max Trade Amount: 500 USDT
Risk per Trade: 2% × 2,000 = 40 USDT per trade
Stop Loss Distance: 0.11% from entry
Result: Position Size = 17,350.69 USDT with 35x leverage
Total Risk (including fees): 40.46 USDT
Multiple Trades Strategy:
With this setup, you can open:
Trade 1: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 2: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 3: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 4: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Total Portfolio Exposure:
- 4 simultaneous trades = 4 × 495.73 = 1,982.92 USDT position amount
- Total risk exposure = 4 × 40 = 160 USDT (8% of account)
