EvoTrend-X Indicator — Evolutionary Trend Learner ExperimentalEvoTrend-X Indicator — Evolutionary Trend Learner
NOTE: This is an experimental Pine Script v6 port of a Python prototype. Pine wasn’t the original research language, so there may be small quirks—your feedback and bug reports are very welcome. The model is non-repainting, MTF-safe (lookahead_off + gaps_on), and features an adaptive (fitness-based) candidate selector, confidence gating, and a volatility filter.
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What it is
EvoTrend-X is adaptive trend indicator that learns which moving-average length best fits the current market. It maintains a small “population” of fast EMA candidates, rewards those that align with price momentum, and continuously selects the best performer. Signals are gated by a multi-factor Confidence score (fitness, strength vs. ATR, MTF agreement) and a volatility filter (ATR%). You get a clean Fast/Slow pair (for the currently best candidate), optional HTF filter, a fitness ribbon for transparency, and a themed info panel with a one-glance STATUS readout.
Core outputs
• Selected Fast/Slow EMAs (auto-chosen from candidates via fitness learning)
• Spread cross (Fast – Slow) → visual BUY/SELL markers + alert hooks
• Confidence % (0–100): Fitness ⊕ Distance vs. ATR ⊕ MTF agreement
• Gates: Trend regime (Kaufman ER), Volatility (ATR%), MTF filter (optional)
• Candidate Fitness Ribbon: shows which lengths the learner currently prefers
• Export plot: hidden series “EvoTrend-X Export (spread)” for downstream use
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Why it’s different
• Evolutionary learning (on-chart): Each candidate EMA length gets rewarded if its slope matches price change and penalized otherwise, with a gentle decay so the model forgets stale regimes. The best fitness wins the right to define the displayed Fast/Slow pair.
• Confidence gate: Signals don’t light up unless multiple conditions concur: learned fitness, spread strength vs. volatility, and (optionally) higher-timeframe trend.
• Volatility awareness: ATR% filter blocks low-energy environments that cause death-by-a-thousand-whipsaws. Your “why no signal?” answer is always visible in the STATUS.
• Preset discipline, Custom freedom: Presets set reasonable baselines for FX, equities, and crypto; Custom exposes all knobs and honors your inputs one-to-one.
• Non-repainting rigor: All MTF calls use lookahead_off + gaps_on. Decisions use confirmed bars. No forward refs. No conditional ta.* pitfalls.
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Presets (and what they do)
• FX 1H (Conservative): Medium candidates, slightly higher MinConf, modest ATR% floor. Good for macro sessions and cleaner swings.
• FX 15m (Active): Shorter candidates, looser MinConf, higher ATR% floor. Designed for intraday velocity and decisive sessions.
• Equities 1D: Longer candidates, gentler volatility floor. Suits index/large-cap trend waves.
• Crypto 1H: Mid-short candidates, higher ATR% floor for 24/7 chop, stronger MinConf to avoid noise.
• Custom: Your inputs are used directly (no override). Ideal for systematic tuning or bespoke assets.
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How the learning works (at a glance)
1. Candidates: A small set of fast EMA lengths (e.g., 8/12/16/20/26/34). Slow = Fast × multiplier (default ×2.0).
2. Reward/decay: If price change and the candidate’s Fast slope agree (both up or both down), its fitness increases; otherwise decreases. A decay constant slowly forgets the distant past.
3. Selection: The candidate with highest fitness defines the displayed Fast/Slow pair.
4. Signal engine: Crosses of the spread (Fast − Slow) across zero mark potential regime shifts. A Confidence score and gates decide whether to surface them.
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Controls & what they mean
Learning / Regime
• Slow length = Fast ×: scales the Slow EMA relative to each Fast candidate. Larger multiplier = smoother regime detection, fewer whipsaws.
• ER length / threshold: Kaufman Efficiency Ratio; above threshold = “Trending” background.
• Learning step, Decay: Larger step reacts faster to new behavior; decay sets how quickly the past is forgotten.
Confidence / Volatility gate
• Min Confidence (%): Minimum score to show signals (and fire alerts). Raising it filters noise; lowering it increases frequency.
• ATR length: The ATR window for both the ATR% filter and strength normalization. Shorter = faster, but choppier.
• Min ATR% (percent): ATR as a percentage of price. If ATR% < Min ATR% → status shows BLOCK: low vola.
MTF Trend Filter
• Use HTF filter / Timeframe / Fast & Slow: HTF Fast>Slow for longs, Fast threshold; exit when spread flips or Confidence decays below your comfort zone.
2) FX index/majors, 15m (active intraday)
• Preset: FX 15m (Active).
• Gate: MinConf 60–70; Min ATR% 0.15–0.30.
• Flow: Focus on session opens (LDN/NY). The ribbon should heat up on shorter candidates before valid crosses appear—good early warning.
3) SPY / Index futures, 1D (positioning)
• Preset: Equities 1D.
• Gate: MinConf 55–65; Min ATR% 0.05–0.12.
• Flow: Use spread crosses as regime flags; add timing from price structure. For adds, wait for ER to remain trending across several bars.
4) BTCUSD, 1H (24/7)
• Preset: Crypto 1H.
• Gate: MinConf 70–80; Min ATR% 0.20–0.35.
• Flow: Crypto chops—volatility filter is your friend. When ribbon and HTF OK agree, favor continuation entries; otherwise stand down.
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Reading the Info Panel (and fixing “no signals”)
The panel is your self-diagnostic:
• HTF OK? False means the higher-timeframe EMAs disagree with your intended side.
• Regime: If “Chop”, ER < threshold. Consider raising the threshold or waiting.
• Confidence: Heat-colored; if below MinConf, the gate blocks signals.
• ATR% vs. Min ATR%: If ATR% < Min ATR%, status shows BLOCK: low vola.
• STATUS (composite):
• BLOCK: low vola → increase Min ATR% down (i.e., allow lower vol) or wait for expansion.
• BLOCK: HTF filter → disable HTF or align with the HTF tide.
• BLOCK: confidence → lower MinConf slightly or wait for stronger alignment.
• OK → you’ll see markers on valid crosses.
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Alerts
Two static alert hooks:
• BUY cross — spread crosses up and all gates (ER, Vol, MTF, Confidence) are open.
• SELL cross — mirror of the above.
Create them once from “Add Alert” → choose the condition by name.
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Exporting to other scripts
In your other Pine indicators/strategies, add an input.source and select EvoTrend-X → “EvoTrend-X Export (spread)”. Common uses:
• Build a rule: only trade when exported spread > 0 (trend filter).
• Combine with your oscillator: oscillator oversold and spread > 0 → buy bias.
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Best practices
• Let it learn: Keep Learning step moderate (0.4–0.6) and Decay close to 1.0 (e.g., 0.99–0.997) for smooth regime memory.
• Respect volatility: Tune Min ATR% by asset and timeframe. FX 1H ≈ 0.10–0.20; crypto 1H ≈ 0.20–0.35; equities 1D ≈ 0.05–0.12.
• MTF discipline: HTF filter removes lots of “almost” trades. If you prefer aggressive entries, turn it off and rely more on Confidence.
• Confidence as throttle:
• 40–60%: exploratory; expect more signals.
• 60–75%: balanced; good daily driver.
• 75–90%: selective; catch the clean stuff.
• 90–100%: only A-setups; patient mode.
• Watch the ribbon: When shorter candidates heat up before a cross, momentum is forming. If long candidates dominate, you’re in a slower trend cycle.
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Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_on.
• No forward references; decisions rely on confirmed bar data.
• EMA lengths are simple ints (no series-length errors).
• Confidence components are computed every bar (no conditional ta.* traps).
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Limitations & tips
• Chop happens: ER helps, but sideways microstructure can still flicker—use Confidence + Vol filter as brakes.
• Presets ≠ oracle: They’re sensible baselines; always tune MinConf and Min ATR% to your venue and session.
• Theme “Auto”: Pine cannot read chart theme; “Auto” defaults to a Dark-friendly palette.
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Publisher’s Screenshots Checklist
1) FX swing — EURUSD 1H
• Preset: FX 1H (Conservative)
• Params: MinConf=70, ATR Len=14, Min ATR%=0.12, MTF ON (TF=4H, 20/50)
• Show: Clear BUY cross, STATUS=OK, green regime background; Fitness Ribbon visible.
2) FX intraday — GBPUSD 15m
• Preset: FX 15m (Active)
• Params: MinConf=60, ATR Len=14, Min ATR%=0.20, MTF ON (TF=60m)
• Show: SELL cross near London session open. HTF lines enabled (translucent).
• Caption: “GBPUSD 15m • Active session sell with MTF alignment.”
3) Indices — SPY 1D
• Preset: Equities 1D
• Params: MinConf=60, ATR Len=14, Min ATR%=0.08, MTF ON (TF=1W, 20/50)
• Show: Longer trend run after BUY cross; regime shading shows persistence.
• Caption: “SPY 1D • Trend run after BUY cross; weekly filter aligned.”
4) Crypto — BINANCE:BTCUSDT 1H
• Preset: Crypto 1H
• Params: MinConf=75, ATR Len=14, Min ATR%=0.25, MTF ON (TF=4H)
• Show: BUY cross + quick follow-through; Ribbon warming (reds/yellows → greens).
• Caption: “BTCUSDT 1H • Momentum break with high confidence and ribbon turning.”
Recherche dans les scripts pour "mtf"
ATR%指標概要 / Overview
ATR Percentage (MTF)：把 ATR 轉為百分比（ATR%）或保留為絕對值，並在該「波動序列」上套用布林帶。支援多週期（MTF）計算：例如在 5 分圖顯示 4H / D1 的 ATR%。內建白色點狀水平線作為固定門檻（預設 1%）。
ATR Percentage (MTF): Converts ATR to a percentage of price (ATR%) or keeps it as absolute ATR, then applies Bollinger Bands on this volatility series. Supports multi-timeframe (MTF) calculation (e.g., show 4H/D1 ATR% on a 5-min chart). Includes a configurable white dotted horizontal threshold line (default 1%).
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設計目的 / Purpose
• 以 ATR% 衡量相對波動，利於跨品種比較。
Use ATR% for relative volatility to compare across markets.
• 以 布林帶 標示「高/低波動區」，觀察擴張與壓縮。
Use Bollinger Bands on volatility to highlight expansion/squeeze.
• 提供 固定閾值（1%） 作為策略濾網或告警門檻。
Provide a fixed threshold (1%) for filters/alerts.
• 以 MTF 方式，讓低週期策略用高週期波動做濾網。
MTF lets lower-TF strategies filter by higher-TF volatility.
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參數說明 / Inputs
• Use ATR as % of Close：切換 ATR（絕對值）/ ATR%（建議）。
Toggle between absolute ATR and ATR% (recommended).
• ATR Periods：ATR 計算長度（預設 22）。
ATR lookback (default 22).
• Show Bollinger Bands / BB Periods / StdDev：布林帶開關、長度與倍數（預設 20 / 2）。
Bollinger Bands on/off, length, and deviation (default 20 / 2).
• Source Timeframe：計算用週期（如 60、240、D、W；留空/Chart ＝ 跟隨圖表）。
Timeframe used for calculations (e.g., 60, 240, D, W; empty/“Chart” = current).
• Threshold Line (%)：白色點線門檻，預設 1.0（即 1%）。
White dotted threshold line, default 1.0 (1%).
提醒：當 非 ATR% 模式時，Threshold 值代表「價格單位」而非百分比。
Note: In non-ATR% mode, the threshold is in price units, not percent.
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訊號解讀 / How to Read
• ATR% > 上軌：波動顯著擴張（趨勢啟動或加速常見）。
ATR% above upper band: significant expansion; often trend ignition/acceleration.
• ATR% < 下軌：波動明顯壓縮（常見於突破前）。
ATR% below lower band: volatility squeeze; often precedes breakouts.
• ATR% 穿越 Threshold（1%）：達到固定波動標準，可作策略開關或風控分水嶺。
ATR% crossing the 1% threshold: fixed volatility bar for filters/risk gates.
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內建告警 / Built-in Alerts
• Volatility Breakout (MTF)：ATR/ATR% 向上穿越上軌。
Triggers when ATR/ATR% crosses above the upper band.
• Volatility Squeeze (MTF)：ATR/ATR% 向下穿越下軌。
Triggers when ATR/ATR% crosses below the lower band.
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使用建議 / Suggested Uses
• 當沖濾網：於 1–5 分圖選擇 4H / D1 作為 Source Timeframe；僅在 ATR% > 1% 且位於中線以上時允許趨勢進場。
Intraday filter: on 1–5m charts, set 4H/D1 as source TF; allow trend entries only when ATR% > 1% and above the midline.
• 突破前偵測：ATR% 長時間貼近下軌 → 留意可能的波動擴張。
Pre-breakout scan: prolonged ATR% near lower band can foreshadow expansion.
• 跨品種比較：用 ATR% 統一指數、外匯、商品的波動刻度。
Cross-asset comparison: ATR% normalizes volatility across indices/FX/commodities.
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已知限制 / Notes
• MTF 對齊：使用 request.security() 對映高週期資料到當前圖表；在歷史回補與即時邊界棒可能略有差異。
MTF alignment: request.security() maps higher-TF data; boundary bars may differ slightly between historical and realtime.
• 百分比分母：ATR% 的分母為同一週期的 close；若需更平滑可改 ATR / SMA(close, N) × 100。
Denominator: ATR% uses same-TF close; for smoother values consider ATR / SMA(close, N) × 100.
• 風險聲明：僅供研究/教育用途，非投資建議，請自行控管風險。
Disclaimer: For research/education only. Not investment advice.
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版本與更新 / Version & Updates
• v1.0：ATR/ATR% + BB（MTF）、1% 白色點線、兩組告警。
v1.0: ATR/ATR% + BB (MTF), 1% white dotted line, two alert conditions.
`security()` revisited [PineCoders]NOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
█ OVERVIEW
This script presents a new function to help coders use security() in both repainting and non-repainting modes. We revisit this often misunderstood and misused function, and explain its behavior in different contexts, in the hope of dispelling some of the coder lure surrounding it. The function is incredibly powerful, yet misused, it can become a dangerous WMD and an instrument of deception, for both coders and traders.
We will discuss:
• How to use our new `f_security()` function.
• The behavior of Pine code and security() on the three very different types of bars that make up any chart.
• Why what you see on a chart is a simulation, and should be taken with a grain of salt.
• Why we are presenting a new version of a function handling security() calls.
• Other topics of interest to coders using higher timeframe (HTF) data.
█ WARNING
We have tried to deliver a function that is simple to use and will, in non-repainting mode, produce reliable results for both experienced and novice coders. If you are a novice coder, stick to our recommendations to avoid getting into trouble, and DO NOT change our `f_security()` function when using it. Use `false` as the function's last argument and refrain from using your script at smaller timeframes than the chart's. To call our function to fetch a non-repainting value of close from the 1D timeframe, use:
f_security(_sym, _res, _src, _rep) => security(_sym, _res, _src )
previousDayClose = f_security(syminfo.tickerid, "D", close, false)
If that's all you're interested in, you are done.
If you choose to ignore our recommendation and use the function in repainting mode by changing the `false` in there for `true`, we sincerely hope you read the rest of our ramblings before you do so, to understand the consequences of your choice.
Let's now have a look at what security() is showing you. There is a lot to cover, so buckle up! But before we dig in, one last thing.
What is a chart?
A chart is a graphic representation of events that occur in markets. As any representation, it is not reality, but rather a model of reality. As Scott Page eloquently states in The Model Thinker : "All models are wrong; many are useful". Having in mind that both chart bars and plots on our charts are imperfect and incomplete renderings of what actually occurred in realtime markets puts us coders in a place from where we can better understand the nature of, and the causes underlying the inevitable compromises necessary to build the data series our code uses, and print chart bars.
Traders or coders complaining that charts do not reflect reality act like someone who would complain that the word "dog" is not a real dog. Let's recognize that we are dealing with models here, and try to understand them the best we can. Sure, models can be improved; TradingView is constantly improving the quality of the information displayed on charts, but charts nevertheless remain mere translations. Plots of data fetched through security() being modelized renderings of what occurs at higher timeframes, coders will build more useful and reliable tools for both themselves and traders if they endeavor to perfect their understanding of the abstractions they are working with. We hope this publication helps you in this pursuit.
█ FEATURES
This script's "Inputs" tab has four settings:
• Repaint : Determines whether the functions will use their repainting or non-repainting mode.
Note that the setting will not affect the behavior of the yellow plot, as it always repaints.
• Source : The source fetched by the security() calls.
• Timeframe : The timeframe used for the security() calls. If it is lower than the chart's timeframe, a warning appears.
• Show timeframe reminder : Displays a reminder of the timeframe after the last bar.
█ THE CHART
The chart shows two different pieces of information and we want to discuss other topics in this section, so we will be covering:
A — The type of chart bars we are looking at, indicated by the colored band at the top.
B — The plots resulting of calling security() with the close price in different ways.
C — Points of interest on the chart.
A — Chart bars
The colored band at the top shows the three types of bars that any chart on a live market will print. It is critical for coders to understand the important distinctions between each type of bar:
1 — Gray : Historical bars, which are bars that were already closed when the script was run on them.
2 — Red : Elapsed realtime bars, i.e., realtime bars that have run their course and closed.
The state of script calculations showing on those bars is that of the last time they were made, when the realtime bar closed.
3 — Green : The realtime bar. Only the rightmost bar on the chart can be the realtime bar at any given time, and only when the chart's market is active.
Refer to the Pine User Manual's Execution model page for a more detailed explanation of these types of bars.
B — Plots
The chart shows the result of letting our 5sec chart run for a few minutes with the following settings: "Repaint" = "On" (the default is "Off"), "Source" = `close` and "Timeframe" = 1min. The five lines plotted are the following. They have progressively thinner widths:
1 — Yellow : A normal, repainting security() call.
2 — Silver : Our recommended security() function.
3 — Fuchsia : Our recommended way of achieving the same result as our security() function, for cases when the source used is a function returning a tuple.
4 — White : The method we previously recommended in our MTF Selection Framework , which uses two distinct security() calls.
5 — Black : A lame attempt at fooling traders that MUST be avoided.
All lines except the first one in yellow will vary depending on the "Repaint" setting in the script's inputs. The first plot does not change because, contrary to all other plots, it contains no conditional code to adapt to repainting/no-repainting modes; it is a simple security() call showing its default behavior.
C — Points of interest on the chart
Historical bars do not show actual repainting behavior
To appreciate what a repainting security() call will plot in realtime, one must look at the realtime bar and at elapsed realtime bars, the bars where the top line is green or red on the chart at the top of this page. There you can see how the plots go up and down, following the close value of each successive chart bar making up a single bar of the higher timeframe. You would see the same behavior in "Replay" mode. In the realtime bar, the movement of repainting plots will vary with the source you are fetching: open will not move after a new timeframe opens, low and high will change when a new low or high are found, close will follow the last feed update. If you are fetching a value calculated by a function, it may also change on each update.
Now notice how different the plots are on historical bars. There, the plot shows the close of the previously completed timeframe for the whole duration of the current timeframe, until on its last bar the price updates to the current timeframe's close when it is confirmed (if the timeframe's last bar is missing, the plot will only update on the next timeframe's first bar). That last bar is the only one showing where the plot would end if that timeframe's bars had elapsed in realtime. If one doesn't understand this, one cannot properly visualize how his script will calculate in realtime when using repainting. Additionally, as published scripts typically show charts where the script has only run on historical bars, they are, in fact, misleading traders who will naturally assume the script will behave the same way on realtime bars.
Non-repainting plots are more accurate on historical bars
Now consider this chart, where we are using the same settings as on the chart used to publish this script, except that we have turned "Repainting" off this time:
The yellow line here is our reference, repainting line, so although repainting is turned off, it is still repainting, as expected. Because repainting is now off, however, plots on historical bars show the previous timeframe's close until the first bar of a new timeframe, at which point the plot updates. This correctly reflects the behavior of the script in the realtime bar, where because we are offsetting the series by one, we are always showing the previously calculated—and thus confirmed—higher timeframe value. This means that in realtime, we will only get the previous timeframe's values one bar after the timeframe's last bar has elapsed, at the open of the first bar of a new timeframe. Historical and elapsed realtime bars will not actually show this nuance because they reflect the state of calculations made on their close , but we can see the plot update on that bar nonetheless.
► This more accurate representation on historical bars of what will happen in the realtime bar is one of the two key reasons why using non-repainting data is preferable.
The other is that in realtime, your script will be using more reliable data and behave more consistently.
Misleading plots
Valiant attempts by coders to show non-repainting, higher timeframe data updating earlier than on our chart are futile. If updates occur one bar earlier because coders use the repainting version of the function, then so be it, but they must then also accept that their historical bars are not displaying information that is as accurate. Not informing script users of this is to mislead them. Coders should also be aware that if they choose to use repainting data in realtime, they are sacrificing reliability to speed and may be running a strategy that behaves very differently from the one they backtested, thus invalidating their tests.
When, however, coders make what are supposed to be non-repainting plots plot artificially early on historical bars, as in examples "c4" and "c5" of our script, they would want us to believe they have achieved the miracle of time travel. Our understanding of the current state of science dictates that for now, this is impossible. Using such techniques in scripts is plainly misleading, and public scripts using them will be moderated. We are coding trading tools here—not video games. Elementary ethics prescribe that we should not mislead traders, even if it means not being able to show sexy plots. As the great Feynman said: You should not fool the layman when you're talking as a scientist.
You can readily appreciate the fantasy plot of "c4", the thinnest line in black, by comparing its supposedly non-repainting behavior between historical bars and realtime bars. After updating—by miracle—as early as the wide yellow line that is repainting, it suddenly moves in a more realistic place when the script is running in realtime, in synch with our non-repainting lines. The "c5" version does not plot on the chart, but it displays in the Data Window. It is even worse than "c4" in that it also updates magically early on historical bars, but goes on to evaluate like the repainting yellow line in realtime, except one bar late.
Data Window
The Data Window shows the values of the chart's plots, then the values of both the inside and outside offsets used in our calculations, so you can see them change bar by bar. Notice their differences between historical and elapsed realtime bars, and the realtime bar itself. If you do not know about the Data Window, have a look at this essential tool for Pine coders in the Pine User Manual's page on Debugging . The conditional expressions used to calculate the offsets may seem tortuous but their objective is quite simple. When repainting is on, we use this form, so with no offset on all bars:
security(ticker, i_timeframe, i_source )
// which is equivalent to:
security(ticker, i_timeframe, i_source)
When repainting is off, we use two different and inverted offsets on historical bars and the realtime bar:
// Historical bars:
security(ticker, i_timeframe, i_source )
// Realtime bar (and thus, elapsed realtime bars):
security(ticker, i_timeframe, i_source )
The offsets in the first line show how we prevent repainting on historical bars without the need for the `lookahead` parameter. We use the value of the function call on the chart's previous bar. Since values between the repainting and non-repainting versions only differ on the timeframe's last bar, we can use the previous value so that the update only occurs on the timeframe's first bar, as it will in realtime when not repainting.
In the realtime bar, we use the second call, where the offsets are inverted. This is because if we used the first call in realtime, we would be fetching the value of the repainting function on the previous bar, so the close of the last bar. What we want, instead, is the data from the previous, higher timeframe bar , which has elapsed and is confirmed, and thus will not change throughout realtime bars, except on the first constituent chart bar belonging to a new higher timeframe.
After the offsets, the Data Window shows values for the `barstate.*` variables we use in our calculations.
█ NOTES
Why are we revisiting security() ?
For four reasons:
1 — We were seeing coders misuse our `f_secureSecurity()` function presented in How to avoid repainting when using security() .
Some novice coders were modifying the offset used with the history-referencing operator in the function, making it zero instead of one,
which to our horror, caused look-ahead bias when used with `lookahead = barmerge.lookahead_on`.
We wanted to present a safer function which avoids introducing the dreaded "lookahead" in the scripts of unsuspecting coders.
2 — The popularity of security() in screener-type scripts where coders need to use the full 40 calls allowed per script made us want to propose
a solid method of allowing coders to offer a repainting/no-repainting choice to their script users with only one security() call.
3 — We wanted to explain why some alternatives we see circulating are inadequate and produce misleading behavior.
4 — Our previous publication on security() focused on how to avoid repainting, yet many other considerations worthy of attention are not related to repainting.
Handling tuples
When sending function calls that return tuples with security() , our `f_security()` function will not work because Pine does not allow us to use the history-referencing operator with tuple return values. The solution is to integrate the inside offset to your function's arguments, use it to offset the results the function is returning, and then add the outside offset in a reassignment of the tuple variables, after security() returns its values to the script, as we do in our "c2" example.
Does it repaint?
We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does.
As we hope to have clearly demonstrated, traders do have legitimate cause to ask if MTF scripts repaint or not when authors do not specify it in their script's description.
► We recommend that authors always use our `f_security()` with `false` as the last argument to avoid repainting when fetching data dependent on OHLCV information. This is the only way to obtain reliable HTF data. If you want to offer users a choice, make non-repainting mode the default, so that if users choose repainting, it will be their responsibility. Non-repainting security() calls are also the only way for scripts to show historical behavior that matches the script's realtime behavior, so you are not misleading traders. Additionally, non-repainting HTF data is the only way that non-repainting alerts can be configured on MTF scripts, as users of MTF scripts cannot prevent their alerts from repainting by simply configuring them to trigger on the bar's close.
Data feeds
A chart at one timeframe is made up of multiple feeds that mesh seamlessly to form one chart. Historical bars can use one feed, and the realtime bar another, which brokers/exchanges can sometimes update retroactively so that elapsed realtime bars will reappear with very slight modifications when the browser's tab is refreshed. Intraday and daily chart prices also very often originate from different feeds supplied by brokers/exchanges. That is why security() calls at higher timeframes may be using a completely different feed than the chart, and explains why the daily high value, for example, can vary between timeframes. Volume information can also vary considerably between intraday and daily feeds in markets like stocks, because more volume information becomes available at the end of day. It is thus expected behavior—and not a bug—to see data variations between timeframes.
Another point to keep in mind concerning feeds it that when you are using a repainting security() plot in realtime, you will sometimes see discrepancies between its plot and the realtime bars. An artefact revealing these inconsistencies can be seen when security() plots sometimes skip a realtime chart bar during periods of high market activity. This occurs because of races between the chart and the security() feeds, which are being monitored by independent, concurrent processes. A blue arrow on the chart indicates such an occurrence. This is another cause of repainting, where realtime bar-building logic can produce different outcomes on one closing price. It is also another argument supporting our recommendation to use non-repainting data.
Alternatives
There is an alternative to using security() in some conditions. If all you need are OHLC prices of a higher timeframe, you can use a technique like the one Duyck demonstrates in his security free MTF example - JD script. It has the great advantage of displaying actual repainting values on historical bars, which mimic the code's behavior in the realtime bar—or at least on elapsed realtime bars, contrary to a repainting security() plot. It has the disadvantage of using the current chart's TF data feed prices, whereas higher timeframe data feeds may contain different and more reliable prices when they are compiled at the end of the day. In its current state, it also does not allow for a repainting/no-repainting choice.
When `lookahead` is useful
When retrieving non-price data, or in special cases, for experiments, it can be useful to use `lookahead`. One example is our Backtesting on Non-Standard Charts: Caution! script where we are fetching prices of standard chart bars from non-standard charts.
Warning users
Normal use of security() dictates that it only be used at timeframes equal to or higher than the chart's. To prevent users from inadvertently using your script in contexts where it will not produce expected behavior, it is good practice to warn them when their chart is on a higher timeframe than the one in the script's "Timeframe" field. Our `f_tfReminderAndErrorCheck()` function in this script does that. It can also print a reminder of the higher timeframe. It uses one security() call.
Intrabar timeframes
security() is not supported by TradingView when used with timeframes lower than the chart's. While it is still possible to use security() at intrabar timeframes, it then behaves differently. If no care is taken to send a function specifically written to handle the successive intrabars, security() will return the value of the last intrabar in the chart's timeframe, so the last 1H bar in the current 1D bar, if called at "60" from a "D" chart timeframe. If you are an advanced coder, see our FAQ entry on the techniques involved in processing intrabar timeframes. Using intrabar timeframes comes with important limitations, which you must understand and explain to traders if you choose to make scripts using the technique available to others. Special care should also be taken to thoroughly test this type of script. Novice coders should refrain from getting involved in this.
█ TERMINOLOGY
Timeframe
Timeframe , interval and resolution are all being used to name the concept of timeframe. We have, in the past, used "timeframe" and "resolution" more or less interchangeably. Recently, members from the Pine and PineCoders team have decided to settle on "timeframe", so from hereon we will be sticking to that term.
Multi-timeframe (MTF)
Some coders use "multi-timeframe" or "MTF" to name what are in fact "multi-period" calculations, as when they use MAs of progressively longer periods. We consider that a misleading use of "multi-timeframe", which should be reserved for code using calculations actually made from another timeframe's context and using security() , safe for scripts like Duyck's one mentioned earlier, or TradingView's Relative Volume at Time , which use a user-selected timeframe as an anchor to reset calculations. Calculations made at the chart's timeframe by varying the period of MAs or other rolling window calculations should be called "multi-period", and "MTF-anchored" could be used for scripts that reset calculations on timeframe boundaries.
Colophon
Our script was written using the PineCoders Coding Conventions for Pine .
The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication.
Snippets were lifted from our MTF Selection Framework , then massaged to create the `f_tfReminderAndErrorCheck()` function.
█ THANKS
Thanks to apozdnyakov for his help with the innards of security() .
Thanks to bmistiaen for proofreading our description.
Look first. Then leap.
FvgPanel█ OVERVIEW
This library provides functionalities for creating and managing a display panel within a Pine Script™ indicator. Its primary purpose is to offer a structured way to present Fair Value Gap (FVG) information, specifically the nearest bullish and bearish FVG levels across different timeframes (Current, MTF, HTF), directly on the chart. The library handles the table's structure, header initialization, and dynamic cell content updates.
█ CONCEPTS
The core of this library revolves around presenting summarized FVG data in a clear, tabular format. Key concepts include:
FVG Data Aggregation and Display
The panel is designed to show at-a-glance information about the closest active FVG mitigation levels. It doesn't calculate these FVGs itself but relies on the main script to provide this data. The panel is structured with columns for timeframes (TF), Bullish FVGs, and Bearish FVGs, and rows for "Current" (LTF), "MTF" (Medium Timeframe), and "HTF" (High Timeframe).
The `panelData` User-Defined Type (UDT)
To facilitate the transfer of information to be displayed, the library defines a UDT named `panelData`. This structure is central to the library's operation and is designed to hold all necessary values for populating the panel's data cells for each relevant FVG. Its fields include:
Price levels for the nearest bullish and bearish FVGs for LTF, MTF, and HTF (e.g., `nearestBullMitLvl`, `nearestMtfBearMitLvl`).
Boolean flags to indicate if these FVGs are classified as "Large Volume" (LV) (e.g., `isNearestBullLV`, `isNearestMtfBearLV`).
Color information for the background and text of each data cell, allowing for conditional styling based on the FVG's status or proximity (e.g., `ltfBullBgColor`, `mtfBearTextColor`).
The design of `panelData` allows the main script to prepare all display-related data and styling cues in one object, which is then passed to the `updatePanel` function for rendering. This separation of data preparation and display logic keeps the library focused on its presentation task.
Visual Cues and Formatting
Price Formatting: Price levels are formatted to match the instrument's minimum tick size using an internal `formatPrice` helper function, ensuring consistent and accurate display.
Large FVG Icon: If an FVG is marked as a "Large Volume" FVG in the `panelData` object, a user-specified icon (e.g., an emoji) is prepended to its price level in the panel, providing an immediate visual distinction.
Conditional Styling: The background and text colors for each FVG level displayed in the panel can be individually controlled via the `panelData` object, enabling the main script to implement custom styling rules (e.g., highlighting the overall nearest FVG across all timeframes).
Handling Missing Data: If no FVG data is available for a particular cell (i.e., the corresponding level in `panelData` is `na`), the panel displays "---" and uses a specified background color for "Not Available" cells.
█ CALCULATIONS AND USE
Using the `FvgPanel` typically involves a two-stage process: initialization and dynamic updates.
Step 1: Panel Creation
First, an instance of the panel table is created once, usually during the script's initial setup. This is done using the `createPanel` function.
Call `createPanel()` with parameters defining its position on the chart, border color, border width, header background color, header text color, and header text size.
This function initializes the table with three columns ("TF", "Bull FVG", "Bear FVG") and three data rows labeled "Current", "MTF", and "HTF", plus a header row.
Store the returned `table` object in a `var` variable to persist it across bars.
// Example:
var table infoPanel = na
if barstate.isfirst
infoPanel := panel.createPanel(
position.top_right,
color.gray,
1,
color.new(color.gray, 50),
color.white,
size.small
)
Step 2: Panel Updates
On each bar, or whenever the FVG data changes (typically on `barstate.islast` or `barstate.isrealtime` for efficiency), the panel's content needs to be refreshed. This is done using the `updatePanel` function.
Populate an instance of the `panelData` UDT with the latest FVG information. This includes setting the nearest bullish/bearish mitigation levels for LTF, MTF, and HTF, their LV status, and their desired background and text colors.
Call `updatePanel()`, passing the persistent `table` object (from Step 1), the populated `panelData` object, the icon string for LV FVGs, the default text color for FVG levels, the background color for "N/A" cells, and the general text size for the data cells.
The `updatePanel` function will then clear previous data and fill the table cells with the new values and styles provided in the `panelData` object.
// Example (inside a conditional block like 'if barstate.islast'):
var panelData fvgDisplayData = panelData.new()
// ... (logic to populate fvgDisplayData fields) ...
// fvgDisplayData.nearestBullMitLvl = ...
// fvgDisplayData.ltfBullBgColor = ...
// ... etc.
if not na(infoPanel)
panel.updatePanel(
infoPanel,
fvgDisplayData,
"🔥", // LV FVG Icon
color.white,
color.new(color.gray, 70), // NA Cell Color
size.small
)
This workflow ensures that the panel is drawn only once and its cells are efficiently updated as new data becomes available.
█ NOTES
Data Source: This library is solely responsible for the visual presentation of FVG data in a table. It does not perform any FVG detection or calculation. The calling script must compute or retrieve the FVG levels, LV status, and desired styling to populate the `panelData` object.
Styling Responsibility: While `updatePanel` applies colors passed via the `panelData` object, the logic for *determining* those colors (e.g., highlighting the closest FVG to the current price) resides in the calling script.
Performance: The library uses `table.cell()` to update individual cells, which is generally more efficient than deleting and recreating the table on each update. However, the frequency of `updatePanel` calls should be managed by the main script (e.g., using `barstate.islast` or `barstate.isrealtime`) to avoid excessive processing on historical bars.
`series float` Handling: The price level fields within the `panelData` UDT (e.g., `nearestBullMitLvl`) can accept `series float` values, as these are typically derived from price data. The internal `formatPrice` function correctly handles `series float` for display.
Dependencies: The `FvgPanel` itself is self-contained and does not import other user libraries. It uses standard Pine Script™ table and string functionalities.
█ EXPORTED TYPES
panelData
Represents the data structure for populating the FVG information panel.
Fields:
nearestBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point (bottom for bull) on the LTF.
isNearestBullLV (series bool) : True if the nearest bullish FVG on the LTF is a Large Volume FVG.
ltfBullBgColor (series color) : Background color for the LTF bullish FVG cell in the panel.
ltfBullTextColor (series color) : Text color for the LTF bullish FVG cell in the panel.
nearestBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point (top for bear) on the LTF.
isNearestBearLV (series bool) : True if the nearest bearish FVG on the LTF is a Large Volume FVG.
ltfBearBgColor (series color) : Background color for the LTF bearish FVG cell in the panel.
ltfBearTextColor (series color) : Text color for the LTF bearish FVG cell in the panel.
nearestMtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the MTF.
isNearestMtfBullLV (series bool) : True if the nearest bullish FVG on the MTF is a Large Volume FVG.
mtfBullBgColor (series color) : Background color for the MTF bullish FVG cell.
mtfBullTextColor (series color) : Text color for the MTF bullish FVG cell.
nearestMtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the MTF.
isNearestMtfBearLV (series bool) : True if the nearest bearish FVG on the MTF is a Large Volume FVG.
mtfBearBgColor (series color) : Background color for the MTF bearish FVG cell.
mtfBearTextColor (series color) : Text color for the MTF bearish FVG cell.
nearestHtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the HTF.
isNearestHtfBullLV (series bool) : True if the nearest bullish FVG on the HTF is a Large Volume FVG.
htfBullBgColor (series color) : Background color for the HTF bullish FVG cell.
htfBullTextColor (series color) : Text color for the HTF bullish FVG cell.
nearestHtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the HTF.
isNearestHtfBearLV (series bool) : True if the nearest bearish FVG on the HTF is a Large Volume FVG.
htfBearBgColor (series color) : Background color for the HTF bearish FVG cell.
htfBearTextColor (series color) : Text color for the HTF bearish FVG cell.
█ EXPORTED FUNCTIONS
createPanel(position, borderColor, borderWidth, headerBgColor, headerTextColor, headerTextSize)
Creates and initializes the FVG information panel (table). Sets up the header rows and timeframe labels.
Parameters:
position (simple string) : The position of the panel on the chart (e.g., position.top_right). Uses position.* constants.
borderColor (simple color) : The color of the panel's border.
borderWidth (simple int) : The width of the panel's border.
headerBgColor (simple color) : The background color for the header cells.
headerTextColor (simple color) : The text color for the header cells.
headerTextSize (simple string) : The text size for the header cells (e.g., size.small). Uses size.* constants.
Returns: The newly created table object representing the panel.
updatePanel(panelTable, data, lvIcon, defaultTextColor, naCellColor, textSize)
Updates the content of the FVG information panel with the latest FVG data.
Parameters:
panelTable (table) : The table object representing the panel to be updated.
data (panelData) : An object containing the FVG data to display.
lvIcon (simple string) : The icon (e.g., emoji) to display next to Large Volume FVGs.
defaultTextColor (simple color) : The default text color for FVG levels if not highlighted.
naCellColor (simple color) : The background color for cells where no FVG data is available ("---").
textSize (simple string) : The text size for the FVG level data (e.g., size.small).
Returns: _void
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Opening Range Breakout with Multi-Timeframe Liquidity]═══════════════════════════════════════
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
═══════════════════════════════════════
A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
───────────────────────────────────────
WHAT THIS INDICATOR DOES
───────────────────────────────────────
This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
───────────────────────────────────────
HOW IT WORKS
───────────────────────────────────────
OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: 🚀 (bullish) or 🔻 (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: 🚀⭐ (bullish) or 🔻⭐ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
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HOW TO USE
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OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart → Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
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TRADING STRATEGIES
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CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
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CONFIGURATION GUIDE
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OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
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BEST PRACTICES
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Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
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PERFORMANCE OPTIMIZATION
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This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
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EDUCATIONAL DISCLAIMER
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This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
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CREDITS & ATTRIBUTION
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ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
SMC Analysis - Fair Value Gaps (Enhanced)SMC Analysis - Fair Value Gaps (Enhanced) Script Summary
Overview
The "SMC Analysis - Fair Value Gaps (Enhanced)" script, written in Pine Script (version 6), is a technical analysis indicator designed for TradingView to identify and visualize Fair Value Gaps (FVGs) on a price chart. It supports both the main timeframe and multiple higher timeframes (MTF) for comprehensive market analysis. FVGs are price gaps formed by a three-candle pattern, indicating potential areas of market inefficiency where price may return to fill the gap.
Key Features
FVG Detection:
Identifies bullish FVGs: Occur when the high of a candle two bars prior is lower than the low of the current candle, with the middle candle being bullish (close > open).
Identifies bearish FVGs: Occur when the low of a candle two bars prior is higher than the high of the current candle, with the middle candle being bearish (close < open).
Visualizes FVGs as colored boxes on the chart (green for bullish, red for bearish).
Mitigation Tracking:
Tracks when FVGs are touched (price overlaps the gap range) or mitigated (price fully closes the gap).
Strict Mode: Marks an FVG as mitigated when price touches the gap range.
Normal Mode: Requires a full breakthrough (price crossing the gap’s bottom for bullish FVGs or top for bearish FVGs) for mitigation.
Optionally converts FVG box borders to dashed lines and increases transparency when partially touched.
Multi-Timeframe (MTF) Support:
Analyzes FVGs on three user-defined higher timeframes (default: 15m, 60m, 240m).
Displays MTF FVGs with distinct labels and slightly more transparent colors.
Ensures no duplicate processing of MTF bars to maintain performance.
Customization Options:
FVG Length: Adjustable duration for how long FVGs are displayed (default: 20 bars).
Show/Hide FVGs: Toggle visibility for main timeframe and each MTF.
Color Customization: User-defined colors for bullish and bearish FVGs (default: green and red).
Display Options: Toggle for showing dashed lines after partial touches and strict mitigation mode.
Performance Optimization:
Limits the number of displayed boxes (50 for main timeframe, 20 per MTF) to prevent performance issues.
Automatically removes older boxes to maintain a clean chart.
Functionality
Visualization: Draws boxes around detected FVGs, with customizable colors and text labels ("FVG" for main timeframe, "FVG " for MTF).
Dynamic Updates: Extends or terminates FVG boxes based on mitigation status and user settings.
Efficient Storage: Uses arrays to manage FVG data (boxes, tops, bottoms, indices, mitigation status, and touch status) separately for main and MTF analyses.
Use Case
This indicator is designed for traders using Smart Money Concepts (SMC) to identify areas of market inefficiency (FVGs) for potential price reversals or continuations. The MTF support allows analysis across different timeframes, aiding in confirming trends or spotting higher-timeframe support/resistance zones.
SuperTrend Cyan — Split ST & Triple Bands (A/B/C)SuperTrend Cyan — Split ST & Triple Bands (A/B/C)
✨ Concept:
The SuperTrend Cyan indicator expands the classical SuperTrend logic into a split-line + triple-band visualization for clearer structure and volatility mapping.
Instead of a single ATR-based line, this tool separates SuperTrend direction from volatility envelopes (A/B/C), providing a layered view of both regime and range compression.
✨ The design goal:
Preserve the simplicity of SuperTrend
Add volatility context via multi-band envelopes
Provide a compact MTF (Multi-Timeframe) summary for broader trend alignment
✨ How It Works
1. SuperTrend Core (Active & Opposite Lines)
Uses ATR-based bands (Factor × ATR-Length).
Active SuperTrend is plotted according to current regime.
Opposite SuperTrend (optional) shows potential reversal threshold.
2. Triple Band System (A/B/C)
Each band (A, B, C) scales from the median price (hl2) by different ATR multipliers.
A: Outer band (wider, long-range context)
B: Inner band (mid-range activity)
C: Core band (closest to price, short-term compression)
Smoothness can be controlled with EMA.
Uptrend fills are lime-toned, downtrend fills are red-toned, with adjustable opacity (gap intensity).
3. Automatic Directional Switch
When the regime flips from up → down (or vice versa), the overlay automatically switches between lower and upper bands for a clean transition.
4. Multi-Timeframe SuperTrend Table
Displays SuperTrend direction across 5m, 15m, 1h, 4h, and 1D frames.
Green ▲ = Uptrend, Red ▼ = Downtrend.
Useful for checking cross-timeframe trend alignment.
✨ How to Read It
Green SuperTrend + Lime Bands
- Uptrend regime; volatility expanding upward
Red SuperTrend + Red Bands
- Downtrend regime; volatility expanding downward
Narrow gaps (A–C)
- Low volatility / compression (potential squeeze)
Wide gaps
- High volatility / active trend phase
Opposite ST line close to price
- Early warning for regime transition
✨ Practical Use
Identify trend direction (SuperTrend color & line position).
Assess volatility conditions (band width and gap transparency).
Watch for MTF alignment: consistent up/down signals across 1h–4h–1D = strong structural trend.
Combine with momentum indicators (e.g., RSI, DFI, PCI) for confirmation of trend maturity or exhaustion.
✨ Customization Tips
ST Factor / ATR Length
- Adjust sensitivity of SuperTrend direction changes
Band ATR Length
- Controls overall smoothness of volatility envelopes
Band Multipliers (A/B/C)
- Define how wide each volatility band extends
Gap Opacity
- Affects visual contrast between layers
MTF Table
- Enable/disable multi-timeframe display
✨ Educational Value
This script visualizes the interaction between trend direction (SuperTrend) and volatility envelopes, helping traders understand how price reacts within layered ATR zones.
It also introduces a clean MTF (multi-timeframe) perspective — ideal for discretionary and system traders alike.
✨ Disclaimer
This indicator is provided for educational and research purposes only.
It does not constitute financial advice or a trading signal.
Use at your own discretion and always confirm with additional tools.
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📘 한국어 설명 (Korean translation below)
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✨개념
SuperTrend Cyan 지표는 기존의 SuperTrend를 확장하여,
추세선 분리(Split Line) + 3중 밴드 시스템(Triple Bands) 으로
시장의 구조적 흐름과 변동성 범위를 동시에 시각화합니다.
단순한 SuperTrend의 강점을 유지하면서도,
ATR 기반의 A/B/C 밴드를 통해 변동성 압축·확장 구간을 직관적으로 파악할 수 있습니다.
✨ 작동 방식
1. SuperTrend 코어 (활성/반대 라인)
ATR×Factor를 기반으로 추세선을 계산합니다.
현재 추세 방향에 따라 활성 라인이 표시되고, “Show Opposite” 옵션을 켜면 반대편 경계선도 함께 보입니다.
2. 트리플 밴드 시스템 (A/B/C)
hl2(중간값)를 기준으로 ATR 배수에 따라 세 개의 밴드를 계산합니다.
A: 외곽 밴드 (가장 넓고 장기 구조 반영)
B: 중간 밴드 (중기적 움직임)
C: 코어 밴드 (가격에 가장 근접, 단기 변동성 반영)
EMA 스무딩으로 부드럽게 조정 가능.
업트렌드 구간은 라임색, 다운트렌드는 빨간색 음영으로 표시됩니다.
3. 자동 전환 시스템
추세가 전환될 때(Up ↔ Down), 밴드 오버레이도 자동으로 교체되어 깔끔한 시각적 구조를 유지합니다.
4. MTF SuperTrend 테이블
5m / 15m / 1h / 4h / 1D 프레임별 SuperTrend 방향을 표시합니다.
초록 ▲ = 상승, 빨강 ▼ = 하락.
복수 타임프레임 정렬 확인용으로 유용합니다.
✨ 해석 방법
초록 SuperTrend + 라임 밴드
- 상승 추세 및 확장 구간
빨강 SuperTrend + 레드 밴드
- 하락 추세 및 확장 구간
밴드 폭이 좁음
- 변동성 축소 (스퀴즈)
밴드 폭이 넓음
- 변동성 확장, 추세 강화
반대선이 근접
- 추세 전환 가능성 높음
✨ 활용 방법
SuperTrend 색상으로 추세 방향을 확인
A/B/C 밴드 폭으로 변동성 수준을 판단
MTF 테이블을 통해 복수 타임프레임 정렬 여부 확인
RSI, DFI, PCI 등 다른 지표와 함께 활용 시, 추세 피로·모멘텀 변화를 조기에 파악 가능
✨ 교육적 가치
이 스크립트는 추세 구조(SuperTrend) 와 변동성 레이어(ATR Bands) 의 상호작용을
시각적으로 학습하기 위한 교육용 지표입니다.
또한, MTF 구조를 통해 시장의 “위계적 정렬(hierarchical alignment)”을 쉽게 인식할 수 있습니다.
✨ 면책
이 지표는 교육 및 연구 목적으로만 제공됩니다.
투자 판단의 책임은 사용자 본인에게 있으며, 본 지표는 매매 신호를 보장하지 않습니다.
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
DynamoSent DynamoSent Pro+ — Professional Listing (Preview)
— Adaptive Macro Sentiment (v6)
— Export, Adaptive Lookback, Confidence, Boxes, Heatmap + Dynamic OB/OS
Preview / Experimental build. I’m actively refining this tool—your feedback is gold.
If you spot edge cases, want new presets, or have market-specific ideas, please comment or DM me on TradingView.
⸻
What it is
DynamoSent Pro+ is an adaptive, non-repainting macro sentiment engine that compresses VIX, DXY and a price-based activity proxy (e.g., SPX/sector ETF/your symbol) into a 0–100 sentiment line. It scales context by volatility (ATR%) and can self-calibrate with rolling quantile OB/OS. On top of that, it adds confidence scoring, a plain-English Context Coach, MTF agreement, exportable sentiment for other indicators, and a clean Light/Dark UI.
Why it’s different
• Adaptive lookback tracks regime changes: when volatility rises, we lengthen context; when it falls, we shorten—less whipsaw, more relevance.
• Dynamic OB/OS (quantiles) self-calibrates to each instrument’s distribution—no arbitrary 30/70 lines.
• MTF agreement + Confidence gate reduce false positives by highlighting alignment across timeframes.
• Exportable output: hidden plot “DynamoSent Export” can be selected as input.source in your other Pine scripts.
• Non-repainting rigor: all request.security() calls use lookahead_off + gaps_on; signals wait for bar close.
Key visuals
• Sentiment line (0–100), OB/OS zones (static or dynamic), optional TF1/TF2 overlays.
• Regime boxes (Overbought / Oversold / Neutral) that update live without repaint.
• Info Panel with confidence heat, regime, trend arrow, MTF readout, and Coach sentence.
• Session heat (Asia/EU/US) to match intraday behavior.
• Light/Dark theme switch in Inputs (auto-contrasted labels & headers).
⸻
How to use (examples & recipes)
1) EURUSD (swing / intraday blend)
• Preset: EURUSD 1H Swing
• Chart: 1H; TF1=1H, TF2=4H (default).
• Proxies: Defaults work (VIX=D, DXY=60, Proxy=D).
• Dynamic OB/OS: ON at 20/80; Confidence ≥ 55–60.
• Playbook:
• When sentiment crosses above 50 + margin with Δ ≥ signalK and MTF agreement ≥ 0.5, treat as trend breakout.
• In Oversold with rising Coach & TF agreement, take fade longs back toward mid-range.
• Alerts: Enable Breakout Long/Short and Fade; keep cooldown 8–12 bars.
2) SPY (daytrading)
• Preset: SPY 15m Daytrade; Chart: 15m.
• VIX (D) matters more; preset weights already favor it.
• Start with static 30/70; later try dynamic 25/75 for adaptive thresholds.
• Use Coach: in US session, when it says “Overbought + MTF agree → sell rallies / chase breakouts”, lean momentum-continuation after pullbacks.
3) BTCUSD (crypto, 24/7)
• Preset: BTCUSD 1H; Chart: 1H.
• DXY and BTC.D inform macro tone; keep Carry-forward ON to bridge sparse ticks.
• Prefer Dynamic OB/OS (15/85) for wider swings.
• Fade signals on weekend chop; Breakout when Confidence > 60 and MTF ≥ 1.0.
4) XAUUSD (gold, macro blend)
• Preset: XAUUSD 4H; Chart: 4H.
• Weights tilt to DXY and US10Y (handled by preset).
• Coach + MTF helps separate trend legs from news pops.
⸻
Best practices
• Theme: Switch Light/Dark in Inputs; the panel adapts contrast automatically.
• Export: In another script → Source → DynamoSent Pro+ → DynamoSent Export. Build your own filters/strategies atop the same sentiment.
• Dynamic vs Static OB/OS:
• Static 30/70: fast, universal baseline.
• Dynamic (quantiles): instrument-aware; use 20/80 (default) or 15/85 for choppy markets.
• Confidence gate: Start at 50–60% to filter noise; raise when you want only A-grade setups.
• Adaptive Lookback: Keep ON. For ultra-liquid indices, you can switch it OFF and set a fixed lookback.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off and gaps=barmerge.gaps_on.
• No forward references; signals & regime flips are confirmed on bar close.
• History-dependent funcs (ta.change, ta.percentile_linear_interpolation, etc.) are computed each bar (not conditionally).
• Adaptive lookback is clamped ≥ 1 to avoid lowest/highest errors.
• Missing-data warning triggers only when all proxies are NA for a streak; carry-forward can bridge small gaps without repaint.
⸻
Known limits & tips
• If a proxy symbol isn’t available on your plan/exchange, you’ll see the NA warning: choose a different symbol via Symbol Search, or keep Carry-forward ON (it defaults to neutral where needed).
• Intraday VIX is sparse—using Daily is intentional.
• Dynamic OB/OS needs enough history (see dynLenFloor). On short histories it gracefully falls back to static levels.
Thanks for trying the preview. Your comments drive the roadmap—presets, new proxies, extra alerts, and integrations.
CCI Stochastic - YOSI
CCI Stochastic (Pro v6) – MTF, Adaptive Bands & Live Label
What it does
This indicator applies a Stochastic calculation on the CCI (K/D lines) to highlight momentum shifts, overbought/oversold zones, and adaptive market regimes. It comes with optional higher-timeframe confirmation, adaptive volatility bands, a live value label, and built-in alerts.
Key Features
Core Signal: Choose between D or K line of the Stoch-CCI.
Extreme Zones: Customizable OB/OS thresholds (default 80/20) and a midline (50), with dynamic background shading.
Adaptive Bands (optional): Mean ± k·standard deviation of the signal, to capture cyclic extremes.
MTF Confirmation (optional): Fetches the same signal from a higher timeframe via request.security.
Arrows/Signals:
Enter – Cross above OS (Buy) / below OB (Sell).
Center – Cross of the 50 midline (momentum shift).
Exit – Exit from extreme zones.
Alerts: All arrow signals + adaptive band crosses.
Live Value Label: Shows the latest signal value near the last bar, customizable decimals/offset/background colors.
Visuals: Red line above OB, green below OS, gray neutral; adaptive band fills.
Use Cases
Momentum / Reversals: Enter with OS/OB crosses confirmed by MTF.
Trend validation: Combine with moving averages (e.g., EMA200) or support/resistance.
Mean Reversion: Fade extreme zones, especially with adaptive band or OB/OS exit alerts.
Inputs
CCI Period, Stoch Period, Smooth K/D – core calculation.
Overbought / Oversold – thresholds (default 80/20).
Line to plot – K or D.
Show Arrows (Enter, Center, Exit) – visual control.
Adaptive Bands – length and k multiplier.
Higher TF – optional confirmation timeframe.
Live Label – decimals, offset, colors.
Quick Tips
For scalping/short-term setups: tighten OB/OS (e.g., 85/15) to filter noise.
In high volatility: increase adaptLen or decrease k to smooth bands.
Reduce false signals: require local + MTF alignment (e.g., only long if MTF > 50).
Disclaimer
This is a technical analysis tool – not a standalone buy/sell signal. Always use with proper risk management, key levels, and confluence from multiple factors.
מה זה עושה?
האינדיקטור מחשב Stochastic על CCI (קו K/D) ומציג אזורי קיצון, חציות ומשטרי שוק. הוא כולל אופציה לאישור מטיימפריים גבוה, בנדים אדפטיביים, תווית ערך חיה והתרעות מוכנות.
יכולות עיקריות
סיגנל מרכזי: בחירה בין קו D או K של Stoch-CCI.
אזורי קיצון: קווים ניתנים להגדרה (ברירת מחדל 80/20) וקו אמצע 50, עם צביעת רקע דינמית כשנכנסים לקיצון.
Adaptive Bands (אופציונלי): ממוצע ± k·סטיית תקן של הסיגנל—מסייע לזהות overheat ומחזוריות.
אישור MTF (אופציונלי): אותו סיגנל מטיימפריים גבוה באמצעות request.security.
חיצים/סיגנלים:
Enter – חציה מלמטה מעל OS (קנייה) / מלמעלה מתחת OB (מכירה).
Center – חציה של 50 (שינוי מומנטום).
Exit – יציאה מאזורים קיצוניים (OS/OB).
Alerts: לכל הסיגנלים לעיל + כניסה/יציאה לבנדים האדפטיביים.
תווית ערך חיה: מציגה את ערך הסיגנל האחרון ליד הנקודה (ספרות ו־offset ניתנים להגדרה).
עיצוב קריא: צבע קו אדום מעל OB, ירוק מתחת OS, אפור ניטרלי; מילוי אזורים.
שימוש מומלץ
מומנטום/היפוכים: כניסה עם חציה מה-OS/OB ואישור מה-MTF.
ממוצע נע/רמות מחיר: חברו לאימות מגמה (למשל EMA200 או תמיכה/התנגדות).
Mean Reversion: חיפוש חזרה מאזורי קיצון, במיוחד כשיש התרעת יציאה מ-OB/OS או נגיעה בבנד אדפטיבי.
קלטים מרכזיים
CCI Period, Stoch Period, Smooth K/D – פרמטרי חישוב.
Overbought / Oversold – ספי קיצון (ברירת מחדל 80/20).
Line to plot – בחירה בין K או D.
Show Arrows/Center/Exit/Enter – שליטה בתצוגת החיצים.
Adaptive Bands (len, k) – חלון ורגישות לבנדים.
Higher TF – טיימפריים לאישור (אופציונלי).
Live Label – ספרות, היסט ברים, צבעי רקע.
טיפים מהירים
בסקלפים/טווחים קצרים: הקשיחו ספי קיצון (למשל 85/15) להפחתת רעש.
בשוק תנודתי: העלו את adaptLen או הורידו את k כדי לקבל בנדים רגישים פחות.
להקטנת אותות שווא: דרשו התאמה בין הסיגנל המקומי ל-MTF (לדוגמה, לונג רק כשה-MTF מעל 50).
הערה חשובה
זהו כלי ניתוח טכני—לא אות קנייה/מכירה בפני עצמו. שלבו אותו עם ניהול סיכונים (SL/TP), בדיקת רמות מפתח ואימות ממספר אינדיקטורים או טיימפריימים.
Multi Timeframe Relative Strength Index {DCAquant}Overview
The Multi Timeframe Relative Strength Index (MTF RSI) is a powerful technical analysis tool designed to provide insights into market momentum and potential trend reversals across multiple timeframes. Leveraging the Relative Strength Index (RSI) formula, this indicator offers traders a comprehensive view of market sentiment and identifies overbought and oversold conditions.
Key Features
RSI Calculation:
Utilizes the standard RSI calculation formula to measure the magnitude of recent price changes and assess the strength of market trends.
Employs a user-defined length parameter to customize the sensitivity of the RSI calculation based on trading preferences.
Multiple Timeframe Analysis:
Allows traders to analyze RSI values across up to six different timeframes, ranging from minutes to days, providing a holistic perspective on market dynamics.
Calculates RSI values independently for each selected timeframe, enabling comparison and trend identification.
Threshold Levels:
Defines overbought and oversold levels to highlight potential reversal points in market trends.
Offers flexibility in adjusting threshold levels based on individual risk tolerance and trading strategies.
Neutral Zone:
Establishes upper and lower neutral thresholds to identify periods of consolidation or sideways movement in price.
Helps traders distinguish between trending and ranging market conditions for more accurate analysis.
Moving Average Smoothing:
Provides the option to apply moving average smoothing to aggregated RSI values for enhanced clarity and reduced noise.
Enables smoother visualization of RSI trends, facilitating easier interpretation for traders.
Visual Representation:
Plots the aggregated MTF RSI values on the price chart, allowing traders to visually assess market momentum and potential reversal points.
Utilizes color-coded backgrounds to indicate Long, Short, or Neutral conditions for quick identification.
Dynamic Table Display:
Displays trading signals alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table format.
Offers flexibility in table placement and size to accommodate user preferences.
How to Use:
Parameter Configuration:
Adjust the length parameter to fine-tune the sensitivity of the RSI calculation based on the desired timeframe and trading strategy.
Define overbought and oversold levels to identify potential reversal points in market trends.
Customize upper and lower neutral thresholds to differentiate between trending and ranging market conditions.
Interpretation:
Monitor the aggregated MTF RSI values plotted on the price chart for signals of overbought or oversold conditions.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable trading insights.
Trading Strategy:
Consider entering Long positions when the aggregated MTF RSI is above the upper neutral threshold, indicating potential bullish momentum.
Evaluate Short opportunities when the aggregated MTF RSI falls below the lower neutral threshold, signaling possible bearish momentum.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management:
Combine MTF RSI analysis with robust risk management strategies, including stop-loss and take-profit levels, to manage trading risks effectively.
Practice prudent risk management and trade within your risk tolerance to minimize potential losses.
Disclaimer
Trading in financial markets involves risk, and past performance is not indicative of future results. The use of the MTF RSI indicator does not guarantee profits or prevent losses. Traders should conduct their own analysis, exercise caution, and seek advice from qualified financial professionals before making trading decisions.
Fair Value Gap█ OVERVIEW
This indicator displays the Fair Value Gap of the current timeframe and an additional higher timeframe. For each FVG the gaps act as targets creating bullish and bearish gaps that are often filled.
█ FEATURES
MTF Options
MidPoint FIll
Delete Old On Fill
Label FVG Timeframe
MTF Options
Enabling the MTF Options will allow the user to use the "MTF Timeframe" setting to choose what HTF Fair Value Gap to display
MidPoint FIll
A line plot at the Half way point will be included in the Fair Value Gap, this will be used to delete the gap when reached instead of a full fill.
Delete Old On Fill
Deletes historical Fair Value Gaps when filled.
Label FVG Timeframe
Labels Every Fair Value gap with there relevant timeframe to make it easier to determine which gap is being filled.
█ HOW TO USE IT
The indicator is quite straight forward in its application, providing users with targets that are often filled as they are seen as market imbalance.
Just applying it to your chart will provide the existing Fair Value Gaps. MTF Confluence is helpful in seeing what is happening on the macro perspective.
█ SUGGESTION
My suggestion for clarity is to use a different color to some degree between the MTF and Current TF as Opposed to text, keeps the chart clear.
█ LIMITATIONS OF PINE (Please read)
I see many users going on different indicators with MTF in mind and trying to use it for LTF data e.g. 1hour chart, and selecting 5min in chart settings.
This is not recommended by the team themselves and should be noted for use always use HTF: www.tradingview.com
To understand how to use fair value gaps I recommend learning about the subject some more, searching online will provide you resources. The internet is your friend when learning. All the best.
Multi SMA EMA WMA HMA BB (5+5 MAs + Bollinger Bands) by RRB
Multi SMA EMA WMA HMA BB (5+5 Moving Averages of Any Type with Bollinger Bands) by RagingRocketBull 2018
Version 1.0
This indicator shows multiple MAs of any type (SMA EMA WMA HMA etc) with BB on a chart at the same time with/without MTF support depending on the version.
There are several versions (published later): Simple, MTF, Pro MTF and Ultimate MTF. This is the Simple version. The Differences are listed below. All versions have BB
- Simple: you have 2 groups of MAs that can be assigned any type (5+5)
- MTF: +assign 1 custom Timeframe to any group combo (5+5 Custom TF)
- Pro MTF: +multiple Timeframes for multiple MA groups (4*3 MTF), horizontal levels and show max bars back options
- Ultimate MTF: +individual settings for each MA, multiple Timeframes
You can use different types of MAs as dynamic S/R levels to trade of off and MA crosses as signals for possible trend change (golden/death bull/bear crosses).
Most common MA types are: SMA, EMA, WMA, HMA.
Most common MA lengths are: 12, 20, 26, 30, 50, 100, 200, 400 etc.
Features:
- 2 groups of custom 5+5 MAs of any type including Hull Moving Average (HMA)
- BB
1. based on 3EmaBB, uses plot, fill, stdev and custom hma functions
2. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
Feel free to use. Good Luck!
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex)
# Short Description
Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX.
---
# What it does (Quick)
* **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle.
* **Real-time** — accumulates intrabar volume live by tick-direction.
* **History Mode** — splits Up/Down on closed bars via simple or range-aware logic.
* **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend).
* **Contextual opacity** — stronger signals appear bolder.
* **Label density** — draw every N-th bar and limit to last X bars for performance.
* **Alerts** — thresholds for |Δ|, Δ%, and UpShare%.
---
# How it works (Real-Time vs History)
* **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available.
* **History (closed bars):**
* **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history.
* **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars.
* **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low.
* **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**.
---
# Rows & Meaning
* **Volume** — total bar volume (no split).
* **UpVol / DownVol** — directional intrabar volume.
* **Delta (Δ)** — UpVol − DownVol.
* **Absolute**: raw units
* **Relative (Δ%)**: Δ / (Up+Down) × 100
* **Both**: shows both formats
* **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish.
* Helpful icons: ▲ (>65%), ▼ (<35%).
---
# MTF Dashboard (🔧 Enable Dashboard)
A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons.
---
# Inputs (Grouped)
## Display
* Toggle rows: **Volume / Up / Down / Delta / UpShare**
* **Delta Display**: Absolute / Relative / Both
## Realtime & History
* **History Mode**: Auto / None / Approx / Price Action Based
* **Compact Numbers**: 1.2k, 1.25M, 3.4B…
## Theme & UI
* **Theme Mode**: Auto / Light / Dark
* **Row Spacing**: vertical spacing between rows
* **Top Row Y**: moves the whole grid vertically
* **Draw Guide Lines**: faint dotted guides
* **Text Size**: Tiny / Small / Normal / Large
## 🔧 Dashboard Settings
* **Enable Dashboard**
* **📏 Table Text Size**: Tiny…Huge
* **🦓 Zebra Rows**
* **🔲 Table Border**
## ⏰ Timeframes (for Dashboard)
* **M1…D1** toggles
## Contextual Coloring
* **Enable Contextual Coloring**: opacity by signal strength
* **Δ% cap / Share offset cap**: saturation caps
* **Min/Max transparency**: solid vs faint extremes
## Label Density & Size
* **Show every N-th bar**: draw labels only every Nth bar
* **Limit to last X bars**: keep labels only in the most recent X bars
## Colors
* Up / Down / Text / Guide
## Alerts
* **Delta Threshold (abs)** — |Δ| in volume units
* **UpShare > / <** — bullish/bearish thresholds
* **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels
---
# How to use (Quick Start)
1. Add the indicator to your chart (overlay=false → separate pane).
2. **History Mode**:
* Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history.
* Stocks/Index → prefer **None** or **Price Action Based** for safer splits.
3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**.
4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves.
5. **Dashboard**: enable and pick only the TFs you actually use.
6. **Alerts**: set thresholds (ideas below).
---
# Alerts (in TradingView)
Add alert → pick this indicator → choose any of:
* **Delta exceeds threshold** (|Δ| > X)
* **UpShare above threshold** (UpShare% > X)
* **UpShare below threshold** (UpShare% < X)
* **Relative Delta above +X%**
* **Relative Delta below −X%**
**Starter thresholds (tune per symbol & TF):**
* **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish)
* **FX (tick volume)**: UpShare > 60–65% or < 40–35%
* **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k)
---
# Notes by Market Type
* **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx.
* **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday.
* **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx.
---
# “All Timeframes” accuracy
* Works on **any TF** (M1 → D1/W1).
* **Real-time accuracy** is strong for the open bar (live accumulation).
* **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced).
* The MTF dashboard uses `request.security` and therefore follows the same logic per TF.
---
# Trade Ideas (Use-Cases)
* **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries.
* **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend.
* **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias.
---
# Advantages
* **True-feeling live flow** on the open bar.
* **Adaptable history** (three modes) to match data quality.
* **Clean visual layout** with guides, compact numbers, contextual opacity.
* **MTF snapshot** for quick bias read.
* **Performance controls** (last X bars, every N-th bar).
---
# Limitations & Care
* **FX uses tick volume** — interpret Δ/Share accordingly.
* **History Mode is an approximation** — confirm with trend/structure/liquidity context.
* **Illiquid symbols** can produce noisy or contradictory signals.
* **Too many labels** can slow charts → raise N, lower X, or disable guides.
---
# Best Practices (Checklist)
* Crypto/Futures: prefer **Price Action Based** for history.
* Stocks: **None** or **Price Action Based**; be cautious with **Approx**.
* FX: pair Δ% & UpShare% with session context (London/NY) and volatility.
* If labels overlap: tweak **Row Spacing** and **Text Size**.
* In the dashboard, keep only the TFs you actually act on.
* Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset.
---
# FAQ
**1) Why do some closed bars show 0%/100% UpShare?**
You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits.
**2) Δ% looks strong but price doesn’t move — why?**
Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations.
**3) Performance slowdown — what to do?**
Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**.
**4) Dashboard values don’t “match” the grid exactly?**
Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal.
---
# Short “Store” Marketing Blurb
Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
QFisher-R™ [ParadoxAlgo]QFISHER-R™ (Regime-Aware Fisher Transform)
A research/education tool that helps visualize potential momentum exhaustion and probable inflection zones using a quantitative, non-repainting Fisher framework with regime filters and multi-timeframe (MTF) confirmation.
What it does
Converts normalized price movement into a stabilized Fisher domain to highlight potential turning points.
Uses adaptive smoothing, robust (MAD/quantile) thresholds, and optional MTF alignment to contextualize extremes.
Provides a Reversal Probability Score (0–100) to summarize signal confluence (extreme, slope, cross, divergence, regime, and MTF checks).
Key features
Non-repainting logic (bar-close confirmation; security() with no lookahead).
Dynamic exhaustion bands (data-driven thresholds vs fixed ±2).
Adaptive smoothing (efficiency-ratio based).
Optional divergence tags on structurally valid pivots.
MTF confirmation (same logic computed on a higher timeframe).
Compact visuals with subtle plotting to reduce chart clutter.
Inputs (high level)
Source (e.g., HLC3 / Close / HA).
Core lookback, fast/slow range blend, and ER length.
Band sensitivity (robust thresholding).
MTF timeframe(s) and agreement requirement.
Toggle divergence & intrabar previews (default off).
Signals & Alerts
Turn Candidate (Up/Down) when multiple conditions align.
Trade-Grade Turn when score ≥ threshold and MTF agrees.
Divergence Confirmed when structural criteria are met.
Alerts are generated on confirmed bar close by default. Optional “preview” mode is available for experimentation.
How to use
Start on your preferred timeframe; optionally enable an HTF (e.g., 4×) for confirmation.
Look for RPS clusters near the exhaustion bands, slope inflections, and (optionally) divergences.
Combine with your own risk management, liquidity, and trend context.
Paper test first and calibrate thresholds to your instrument and timeframe.
Notes & limitations
This is not a buy/sell signal generator and does not predict future returns.
Readings can remain extreme during strong trends; use HTF context and your own filters.
Parameters are intentionally conservative by default; adjust carefully.
Compliance / Disclaimer
Educational & research tool only. Not financial advice. No recommendation to buy/sell any security or derivative.
Past performance, backtests, or examples (if any) are not indicative of future results.
Trading involves risk; you are responsible for your own decisions and risk management.
Built upon the Fisher Transform concept (Ehlers); all modifications, smoothing, regime logic, scoring, and visualization are original work by Paradox Algo.
[Mad]Triple Bollinger Bands ForecastTriple Bollinger Bands Forecast (BBx3+F)
This open-source indicator is an advanced version of the classic Bollinger Bands, designed to provide a more comprehensive and forward-looking view of market volatility and potential price levels.
It plots three distinct sets of Bollinger Bands and projects them into the future based on statistical calculations.
How It Is Built and Key Features
Triple Bollinger Bands: Instead of a single set of bands, this indicator plots three. All three share the same central basis line (a Simple Moving Average), but each has a different standard deviation multiplier. This creates three distinct volatility zones for analyzing price deviation from its mean.
Multi-Timeframe (MTF) Capability: The indicator can calculate and display Bollinger Bands from a higher timeframe (e.g., showing daily bands on a 4-hour chart). This allows for contextualizing price action within the volatility structure of a more significant trend.
(Lower HTF selection will result in script-crash!)
Future Forecasting: This is the indicator's main feature. It projects the calculated Bollinger Bands up to 8 bars into the future. This forecast is a recalculation of the Simple Moving Average and Standard Deviation based on a projected future source price.
Selectable Forecast Methods: The mathematical model for estimating the future source price can be selected:
Flat: A model that uses the most recent closing price as the price for all future bars in the calculation window.
Linreg (Linear Regression): A model that calculates a linear regression trend on the last few bars and projects it forward to estimate the future source price.
Efficient Drawing with Polylines: The future projections are drawn on the chart using Pine Script's polyline object. This is an efficient method that draws the forecast data only on the last bar, which avoids repainting issues.
Differences from a Classical Bollinger Bands Indicator
Band Count: A classical indicator shows one set of bands. This indicator plots three sets for a multi-layered view of volatility.
Perspective: Classical Bollinger Bands are purely historical. This indicator is both historical and forward-looking .
Forecasting: The classic version has no forecasting capability. This indicator projects the bands into the future .
Timeframe: The classic version works only on the current timeframe. This indicator has full Multi-Timeframe (MTF) support .
The Mathematics Behind the Future Predictions
The core challenge in forecasting Bollinger Bands is that a future band value depends on future prices, which are unknown. This indicator solves this by simulating a future price series. Here is the step-by-step logic:
Forecast the Source Price for the Next Bar
First, the indicator estimates what the price will be on the next bar.
Flat Method: The forecasted price is the current bar's closing price.
Price_forecast = close
Linreg Method: A linear regression is calculated on the last few bars and extrapolated one step forward.
Price_forecast = ta.linreg(close, linreglen, 1)
Calculate the Future SMA (Basis)
To calculate the Simple Moving Average for the next bar, a new data window is simulated. This window includes the new forecasted price and drops the oldest historical price. For a 1-bar forecast, the calculation is:
SMA_future = (Price_forecast + close + close + ... + close ) / length
Calculate the Future Standard Deviation
Similarly, the standard deviation for the next bar is calculated over this same simulated window of prices, using the new SMA_future as its mean.
// 1. Calculate the sum of squared differences from the new mean
d_f = Price_forecast - SMA_future
d_0 = close - SMA_future
// ... and so on for the rest of the window's prices
SumOfSquares = (d_f)^2 + (d_0)^2 + ... + (d_length-2)^2
// 2. Calculate future variance and then the standard deviation
Var_future = SumOfSquares / length
StDev_future = sqrt(Var_future)
Extending the Forecast (2 to 8 Bars)
For forecasts further into the future (e.g., 2 bars), the script uses the same single Price_forecast for all future steps in the calculation. For a 2-bar forecast, the simulated window effectively contains the forecasted price twice, while dropping the two oldest historical prices. This provides a statistically-grounded projection of where the Bollinger Bands are likely to form.
Usage as a Forecast Extension
This indicator's functionality is designed to be modular. It can be used in conjunction with as example Mad Triple Bollinger Bands MTF script to separate the rendering of historical data from the forward-looking forecast.
Configuration for Combined Use:
Add both the Mad Triple Bollinger Bands MTF and this Triple Bollinger Bands Forecast indicator to your chart.
Open the Settings for this indicator (BBx3+F).
In the 'General Settings' tab, disable the Activate Plotting option.
To ensure data consistency, the Bollinger Length, Multipliers, and Higher Timeframe settings should be identical across both indicators.
This configuration prevents the rendering of duplicate historical bands. The Mad Triple Bollinger Bands MTF script will be responsible for visualizing the historical and current bands, while this script will overlay only the forward-projected polyline data.
Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
TTM Squeeze Pro - IntradayTTM Squeeze Pro – Intraday (AI MTF Edition)
Design Rationale
This indicator is built to help traders identify when markets are consolidating, when volatility is building (squeeze), and when a breakout or trend is starting — all across multiple timeframes.
The design combines three powerful ideas:
Volatility Compression & Expansion (TTM Squeeze Logic):
By comparing Bollinger Bands (BB) and Keltner Channels (KC), the indicator detects when volatility contracts (BB inside KC). These moments often precede explosive moves. White dots on the BB basis line mark these “squeeze” periods.
Trend Strength & Direction (ADX System):
The ADX (Average Directional Index) measures how strong a trend is.
ADX rising above the threshold → trending market.
ADX falling below the threshold → consolidation.
The system classifies each bar as Trending Up, Trending Down, Consolidating, or Neutral, depending on ADX and momentum direction.
Multi-Timeframe (MTF) Alignment:
The same logic is applied to several timeframes (1m, 3m, 5m, 15m, 30m, 1h).
A compact table at the top-right shows each timeframe’s trend and squeeze strength.
This helps traders see whether short-term and higher timeframes are aligned, improving trade confidence and timing.
The AI Enhancer automatically adjusts all parameters (ADX, BB, KC lengths, and thresholds) depending on the current chart timeframe, keeping signals consistent between scalping and swing trading setups.
Trend and squeeze strengths are normalized on a 1–9 scale, giving users a quick numerical sense of trend power and squeeze intensity. The design emphasizes clarity, speed, and adaptability — critical for intraday trading decisions.
How to Use
Identify a Squeeze Setup:
Look for white dots on the chart — this marks low volatility and potential energy buildup.
Wait for Breakout Confirmation:
When the white dots disappear, volatility expands.
Check the MTF table — if multiple timeframes show green (uptrend) or red (downtrend) in the “TR” column, momentum is aligning.
Enter the Trade:
Go long if breakout happens above BB basis and most timeframes show green.
Go short if breakout happens below BB basis and most timeframes show red.
Exit or Manage Position:
When new white dots appear → volatility contracting again → consider exiting or tightening stops.
If MTF colors become mixed → trend losing strength.
In Summary
The TTM Squeeze Pro – Intraday AI MTF Indicator blends volatility analysis, trend strength, momentum, and multi-timeframe alignment into one adaptive tool.
Its design aims to simplify complex market behavior into a visual, data-backed format — enabling traders to catch high-probability breakout trends early and avoid false moves during low-volatility phases.
Session Volume Spike DetectorSession Volume Spike Detector (Buy/Sell, Dual Windows, MTF + Edge/Cooldown)
What it does
Detects statistically significant buy/sell volume spikes inside two DST-aware Mountain Time sessions and projects 1m / 5m / 10m signals onto any chart timeframe (even 1s). Spikes are confirmed at the close of their native bar and are edge-triggered with optional cooldowns to prevent duplicate alerts.
How spikes are detected
Volume ≥ SMA × multiplier
Optional jump vs recent highest volume
Optional Z-Score gate for significance
Separate Buy/Sell logic using your Direction Mode (Prev Close or Candle Body)
Multi-Timeframe (MTF) display
Shows 1m, 5m, 10m arrows on your current chart
Each HTF fires once on its bar close (no repaint after close)
Sessions (DST-aware, MT)
Morning: 05:30–08:30
Midday: 11:00–13:30
Spikes only count inside these windows.
Inputs & styling
Thresholds: SMA length, multipliers, recent lookback, Z-Score toggle/level
Toggles for which TFs to display (chart TF, 1m, 5m, 10m)
Per-TF colors + cooldowns (seconds) for Any TF, 1m, 5m, 10m
Alerts (edge + cooldown)
MTF Volume Spike (Any TF) — fires on the first qualifying spike across enabled TFs
1m / 5m / 10m Volume Spike — per-TF alerts, Buy or Sell
Recommended: set alert Trigger = Once per bar close. Cooldowns tame “triggered too often” warnings.
Great with
FVG zones, bank/insto levels, session range breaks, and trend filters. Use the MTF arrows as a participation/pressure tell to confirm or fade moves.
Notes
Works on any symbol/timeframe; best viewed on 1m or sub-minute charts.
HTF spikes appear on the bar close of 1m/5m/10m respectively.
No dynamic plot titles; Pine v6-safe.
Short summary (≤250 chars):
MTF volume-spike detector for intraday sessions (DST-aware, MT). Projects 1m/5m/10m buy/sell spikes onto any chart, with edge-triggered alerts and per-TF cooldowns to prevent duplicates. Ideal for spotting institutional participation.
Multi-TF 👀### Multi-Timeframe Analysis (MTF-Analysis)
**Overview**
The Multi-Timeframe Analysis indicator is a powerful visualization tool designed for traders who incorporate multi-timeframe (MTF) strategies into their decision-making process. It overlays compact, customizable candle representations from up to four higher timeframes directly on your chart, positioned to the right of the last bar for quick reference. This allows you to monitor price action, momentum via EMAs, and key levels like Fair Value Gaps (FVGs) across multiple resolutions without switching charts. Built with efficiency in mind, it supports automatic timeframe detection, real-time updates, and a clean, non-intrusive design that enhances your trading workflow.
Ideal for day traders, swing traders, and scalpers, this indicator helps identify alignments between timeframes, spot potential reversals or continuations, and validate entries/exits based on higher-timeframe context. It leverages Pine Script v6 for smooth performance, with optimizations to handle up to 5000 bars back and extensive drawing limits.
**Key Features**
- **Multi-Timeframe Candle Display**: Renders recent candles (configurable from 5 to 100 per timeframe) from selected higher timeframes (e.g., 5m, 15m, 1H, 4H) as compact bars with customizable width, spacing, and padding. Bullish and bearish candles are color-coded for instant recognition.
- **Automatic Timeframe Adaptation**: When enabled, the indicator intelligently selects complementary timeframes based on your chart's resolution (e.g., on a 1m chart, it might show 5m, 15m, and 1H). Manual overrides are available for full control.
- **EMA Overlays**: Plots EMA9, EMA21, and EMA50 on each MTF section using a user-defined source (e.g., OHLC/4, close). EMAs can be dashed for clarity and enabled/disabled per timeframe, helping to gauge momentum and trend strength.
- **Fair Value Gaps (FVGs)**: Detects bullish (+FVG) and bearish (-FVG) gaps with a configurable lookback length (5-50 bars). Gaps are visualized as dotted boxes extending from the candle, highlighting potential support/resistance zones or imbalances.
- **Time Labels and Debugging**: Displays timestamp labels under every fourth candle for chronological context. A debug mode expands spacing and adds detailed labels (e.g., OHLC, volume, EMA values) for testing and verification.
- **Customization Options**: Extensive inputs for colors (bodies, wicks, EMAs, FVGs), label sizes/styles, and layout ensure seamless integration with your chart theme. Supports futures symbols with a time offset adjustment.
- **Performance Optimizations**: Uses arrays for efficient data management, clears drawings on realtime updates or timeframe changes, and limits buffer sizes to prevent overload.
**How to Use**
1. Add the indicator to your chart via TradingView's "Indicators" menu.
2. Configure timeframes: Enable/disable up to four TFs and set the number of candles to display. Use "Auto Timeframe" for smart defaults.
3. Adjust EMAs: Select the source type and toggle per TF to focus on relevant momentum signals (e.g., EMA9 crossovers for short-term trades).
4. Enable FVGs: Activate per TF and tweak the length to suit your market (shorter for volatile assets, longer for trends).
5. Fine-tune appearance: Modify padding, candle width, and colors to avoid clutter. Use debug mode during setup.
6. Interpret: Align your chart's price action with MTF candles—look for confluence in trends, FVGs filling as support/resistance, or EMA alignments for high-probability setups.
**Input Settings**
- **General**: Hour offset for time adjustments (useful for futures).
- **Timeframes**: Enable TFs 1-4, select resolutions (e.g., "5m"), and set candle counts. Auto mode simplifies this.
- **FVG/iFVG**: Toggle per TF, customize colors and detection length.
- **EMA**: Enable per TF, choose source, colors, and dashed style.
- **Candle Appearance**: Bull/bear colors for bodies/wicks, width/spacing/padding, label size/color.
- **Debug**: Expands view for detailed inspection.
**Notes**
- This indicator is non-repainting and updates in realtime, but performance may vary on lower timeframes with many candles—reduce counts if needed.
- FVGs are calculated locally on recent bars for efficiency; historical gaps beyond the buffer aren't shown.
- Compatible with all symbols, but best on volatile markets like forex, crypto, or indices.
- Feedback welcome—updates may include more MA types or advanced FVG filters.
Enhance your edge with multi-timeframe insights—try MTF-Analysis today!
Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
CM MACD Custom Indicator - Multiple Time Frame - V2***For a Detailed Video Overview Showing all of the Settings...
Click HERE to View Video
New _CM_MacD_Ult_MTF _V2 Update 07-28-2021
Thanks to @SKTennis for help in Updating code to V2
Added Groups to Settings Pane.
Added Color Plots to Settings Pane
Switched MTF Logic to turn ON/OFF automatically w/ TradingView's Built in Feature
Updated Color Transparency plots to work in future update
Added Ability to Turn ON/OFF Show MacD & Signal Line
Added Ability to Turn ON/OFF Show Histogram
Added Ability to Change MACD Line Colors Based on Trend
Added Ability to Highlight Price Bars Based on Trend
Added Alerts to Settings Pane.
Customized how Alerts work. Must keep Checked in Settings Pane, and When you go to Alerts Panel, Change Symbol to Indicator (CM_Ult_MacD_MTF_V2)
Customized Alerts to Show Symbol, TimeFrame, Closing Price, MACD Crosses Up & MACD Crosses Down Signals in Alert
Alerts are Pre-Set to only Alert on Bar Close
See Video for Detailed Overview
New Updates Coming Soon!!!
***Please Post Feedback and Any Feature Requests in the Comments Section Below***
