Rectified BB% for option tradingThis indicator shows the bollinger bands against the price all expressed in percentage of the mean BB value. With one sight you can see the amplitude of BB and the variation of the price, evaluate a reenter of the price in the BB.
The relative price is visualized as a candle with open/high/low/close value exspressed as percentage deviation from the BB mean
The indicator include a modified RSI, remapped from 0/100 to -100/100.
You can choose the BB parameters (length, standard deviation multiplier) and the RSI parameter (length, overbougth threshold, ovrsold threshold)
You can exclude/include the candles and the RSI line.
The indicator can be used to sell options when the volatility is high (the bollinger band is wide) and the price is reentering inside the bands.
If the price is forming a supply or demand area it can be a good opportunity to sell a bull put or a bear call
The RSI can be used as confirm of the supply/demand formation
If the bollinger band is narrow and the RSI is overbought/oversold it indicate a better opportunity to buy options
the indicator is designed to work with daily timeframe and default parameters.
在脚本中搜索"band"
DBMA - Dual Bollinger Moving AverageThe Dual Bollinger moving average (DBMA) consists of a moving average (MA) & two Bollinger Bands (BB), with the color of the bands representing the level of price compression. In its default settings, it is a 20-day simple moving average with 2 upper Bollinger Bands, having the standard deviation (SD) settings of 0.5 & 1, respectively.
How close the price is to the moving average?
For a pullback trader, the entry point should be close to the moving average, preferably with price compression. How close should it be, is where the bands serve as a guide. The low of the pullback candle should be within the bands, that is, at least within the far band (1 SD of the MA), or even better if it's within the near band (0.5 SD). When the price is outside the bands, it should not be considered favourable for a pullback entry.
For how long has the price been closer to the moving average?
John Carter’s TTM Squeeze indicator looked at the relationship between Bollinger Bands and Keltner's Channels to help identify period of volatility contractions. Bollinger Bands being completely enclosed within the Keltner Channels is indicative of a very low volatility. This is a state of volatility contraction known as squeeze. Using different ATR lengths (1.0, 1.5 and 2.0) for Keltner Channels, we can differentiate between levels of squeeze (High, Mid & Low compression, respectively). Greater the compression, higher the potential for explosive moves.
The squeeze portion of the script is based on LazyBear's script ( Squeeze Momentum Indicator )
The High, Mid & Low compression squeezes are depicted via the color of the bands being red, orange, or yellow, respectively. With the low of the pullback candle within the bands, & the squeeze color changing to red, it should be considered favourable for a pullback entry.
Trailing the price with the lower bands
The lower bands can be used for trailing with the moving average. While trailing, once the price closes below the moving average, the trailing stoploss (TSL) is said to be triggered, & the trade is exited. Here we use the bands to give it some cushion. Let the price close below the 1SD band for labelling the TSL as being triggered to exit the trade. If the price closes below the MA but is still within the bands, the signal is to keep holding the trade.
Edri Extreme Points Buy & SellEDRI EXTREME POINTS BUY & SELL INDICATOR
This Buy and Sell (non-repainting) indicator uses signals based on the combined CCI/Momentum and RSI indicators and optional regular divergence.
The idea of the indicator is to look for a potential reversal after the price reached extreme points (overbought or oversold) and signals an entry when the price shows signs of momentum for reversal.
Optionally, it considers finding a divergence while RSI is at the extreme levels to improve the predictability of a possible reversal.
Additionally, the indicator includes a simple Mean Reversion visual on the chart to assist users in identifying extreme price levels and potential reversal opportunities. It features upper and lower bands that can be optionally plotted, showing calculated values where price bounces at those extreme levels.
The purpose of these bands is to help traders avoid getting trapped in the middle of a trend and to guide them to buy low and sell high. (It's important to note that this is purely a visual aid and does not impact the generation of trade signals.)
By utilizing the Mean Reversion bands alongside the entry conditions, traders can gain insights into potential price reversals and make more informed decisions about when to enter or exit trades.
Buy and Sell Entry conditions:
• The indicator looks at the CCI/Momentum indicator to turn positive (if buy) or negative (if sell) after the RSI was overbought or oversold in the recent past.
• It also checks if there is a 3-period regular bullish divergence in the RSI (if buy), or regular bearish divergence (if sell) and consider these in the entry condition.
• If these conditions are met, this indicator suggests that it may be a good time to enter a trade.
In summary this is how this indicator works:
• The indicator takes input settings such as the choice between using CCI or Momentum as the entry signal source, length parameters for CCI/Momentum, RSI levels for overbought and oversold conditions, RSI length, and options to plot mean reversion bands on the chart.
• It calculates the CCI and Momentum and RSI values based on user-defined length..
• It checks for regular bullish and bearish divergences (3 periods) in the RSI if the option is enabled.
• The script plots shapes on the chart to indicate the buy and sell signals based on the entry conditions.
• If the mean reversion bands option is enabled, it calculates the mean reversion, standard deviation, upper band, and lower band values.
• It also plots the upper band, mean reversion line, and lower band on the chart if the mean reversion bands option is enabled.
• This indicator includes alert conditions to generate alerts for the buy and sell signals.
• On top of that, users can opt to use only one alert for both buy and sell signals. (This can save Trading view subscribers with limited alerts.)
Important! Please do not consider everything you read here as financial advice. Additionally, do not rely solely on indicators for making your trading decisions. It is important to note that no indicator or strategy is perfect. Therefore, it is always recommended to backtest everything and practice proper risk management.
I appreciate your feedback on this indicator. As I am new to script development, I am open to comments and suggestions to improve it. If you encounter any issues while using this indicator, please let me know in the comments section. If you find it helpful, I kindly ask for your support in boosting it. Thank you for your cooperation.
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
Nadaraya-Watson Envelope Alternative [CHE] Super EnvelopeThe problem of the wonderfuls Nadaraya-Watson indicators is that they repainting, so I use a John Ehlers’ 2-pole Butterworth filter “Super Smoother”. With this indicator you are able to make adjustments to the length and using the multiplier out and thus to make the analysis as good as possible.
Settings:
smoothing length: Determines the length of the Super Envelope.
Adjustable multiplier: Multiplier for the bands
Show middle band: On and off center line
Hide Disclaimer: Uncheck to hide the disclaimer
Usage
This tool outlines extremes made by the prices within the selected window size. This is achieved by estimating the underlying trend in the price using Ehlers Super smoothing, calculating the mean absolute deviations from it, and adding/subtracting it from the estimated underlying trend.
We can expect the price to reverse when crossing one of the envelope extremities. Crosses between the price and the envelopes extremities are indicated with triangles on the chart.
I have integrated alerts for this indicator from the crosses between the price and the envelope extremities. However, i do not recommend this tool to be used alone or solely for real time applications.
best regards
Chervolino
.b dual dynamic SRThis is dual band dynamic S/R indicator
It works on longger swing than BB 20,2 band rage, and I think It works well.
even on the rapid price change, it quite woks well.
If price goes out of 1st S/R band range, 2nd S/R band shows up on the chart.
Because of large bandwidth, An area in which an actual candle is drawn may be displayed as small.
So, with some codework, I made the S/R band occupy only the area near the actual candle drawing area.
The S/R band value is calculated as a combination of donchian band, high/low, atr, etc.
and regular default setting value is fixed on the code level. you can change the color set.
For more information, please refer to the source code.
if you have any questions freely contact to me by message on tradingview, or telegram @sr_bt
but please understand that responses may be quite late.
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Special thanks to all of contributors of community.
The script (originaly .b) may be freely distributed under the MIT license.
without a clear understanding of the house rules,
Several indicators on the charts, it should be clean chart on publishing.
So I am re-publishing as a new one, sorry about that.
Bar By Bar ATR [upslidedown]After seeing strategy after strategy refer to calculating ATR values using a "calculator" (how barbaric!), I thought I'd take a stab at one possible solution to the "problem" as an overlay indicator on the main chart that replaces traditional standard ATR bands. This indicator presents ATR within a channel with a slick trick: invisible hover-able tooltips for you to know the ATR value for your strategy from bar to bar. Just zoom in and hover over the high ATR range and you'll see take profit and stop loss values for whatever strategy you might be running. I defaulted the indicator to a 1:1.5 ATR standard setup because that is good for many strategies but this is as configurable as you'd like to make it. One notable improvement for this indicator over standard ATR bands is that many existing ATR bands only use integers and this one uses a float value, so you can endlessly customize based on whatever strategy you might be running.
Note: Because labels are limited by default, the best way to historically see ATR values is to use TV's replay feature. I did this on purpose to limit resource usage. One could certainly print more labels but I felt it unnecessary to go beyond the default number of labels.
Sniper BB + VWAP System (with SMT Divergence Arrows)STEP 1: Load two correlated futures charts.
Example: CL + RB/SI+GC/ NQ+ES
STEP 2: Add Bollinger Bands (20, 2.0) on both.
Optional add (20, 3.0).
STEP 3: Watch for a BB tag on one chart but not the other.
STEP 4: Wait for a reclaim candle back inside the band.
STEP 5: Enter with stop below/above the wick + 3.0 BB.
STEP 6: Scale out midline, then opposite band.
STEP 7: Hold partials when both pairs confirm trend.
*You can take the vwap bands off the chart if it is too cluttered.
NeuroPolynomial Channel🧠 NeuroPolynomial Channel – AI-Inspired Market Structure Engine
In modern market microstructure analysis, price is no longer treated as a simple line — it is viewed as a continuously evolving signal governed by nonlinear dynamics, volatility deformation, and behavioral state shifts.
The NeuroPolynomial Channel (NPC) is a mathematically structured, AI-inspired indicator designed to approximate this dynamic behavior using a hybrid of:
• Polynomial regression smoothing
• Neural blending functions
• Volatility-adaptive envelopes
• Distribution-based bias levels
While full deep-learning models cannot be directly implemented in Pine Script due to computational and architectural limitations, the NeuroPolynomial Channel brings core AI concepts into TradingView through mathematically constrained approximations, creating an efficient, real-time neural structure model suitable for intraday and swing analysis.
📐 Mathematical Foundation
NPC is not a standard moving average or simple channel system.
It applies a multi-layer non-linear approximation built on four core mathematical components.
1️⃣ NeuroPolynomial Core Line
At the heart of the system lies a recursive polynomial smoothing kernel inspired by neural weighted blending:
K = α · K
+ (1 - α) · P
+ Δx · ( K - K ) / F
Where:
• K = Neuro core estimate
• P = Current price input
• α = Neural morph factor
• F = Flattening constant
• Δx = Position delta (horizontal deformation component)
The recursive references introduce memory similar to RNN-style feedback behavior.
This produces a structurally smooth, non-linear trajectory that adapts to both local and historical price deformation.
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2️⃣ Neural Volatility Envelope
Instead of classical standard deviation, NPC uses a cumulative error field:
E = ( Σ | P - K | ) / N
Using this error field, the dynamic envelope bands are constructed as:
Inner Band = K ± E · m1
Mid Band = K ± E · m2
Outer Band = K ± E · m3
Where:
• m1, m2, m3 are probabilistic band multipliers
• E represents actual observed deviation, not synthetic volatility
This creates a probabilistic price container that deforms with real market behavior rather than static statistical assumptions.
The channel automatically adapts its curvature based on current price regime:
trending, compressing, or expanding.
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3️⃣ Neural Regression Spine
Alongside the polynomial core, NPC calculates a ridge-regularized regression spine:
y = β · x + α (with L2 regularization)
This acts as a structural bias vector or "neural backbone".
It prevents overfitting and provides directional stabilization during extended trend phases.
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4️⃣ Neuro Bias Zones (Daily Reset)
NPC also introduces daily volatility-anchored regime thresholds:
Z_levels = Open ± ATR_daily × {0.1, 0.382, 0.618}
These act as:
• Neuro Mid Zones – equilibrium bands
• Neuro Strong Zones – trend activation boundaries
Unlike classical pivot systems, these levels reset daily and expand dynamically based on real volatility.
They approximate probability field boundaries similar to those used in institutional volatility modeling.
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🤖 AI Philosophy
While Pine Script cannot host full neural networks, GPU models or multi-layer AI pipelines, NeuroPolynomial Channel introduces AI concepts through mathematical abstraction, including:
• Neural blending mechanics
• Memory-based recursion
• Volatility adaptation
• Bias field modeling
• Structured envelope projection
This creates an AI-style behavior using real-time deterministic mathematics — allowing performance on TradingView while preserving interpretability and stability.
🛠 How To Use
NPC is designed for structure-based interpretation, not random signal chasing.
① Trend Structure
Use the Neural Core Line and channel slope to establish trend direction and regime.
② Compression & Expansion
Observe band width.
Contracting channels signal volatility compression.
Expanding channels signal range expansion.
③ Bias Zones
Neuro Mid and Strong levels act as macro intraday bias framework — especially powerful for session trading and index futures.
⚙️ Settings Overview
• Morph Factor – Controls neural blending strength (higher = smoother, lower = reactive)
• Flatten – Reduces polynomial curvature noise
• Band Multipliers – Adjust envelope thickness
• Neural Bias Levels – ATR-anchored regime zones resetting daily
• Theme & Visual Controls – Dark/Light with pro-grade visibility
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Companion AI:
I also built a free Trading AI on ChatGPT that reads chart screenshots and enforces a rule-based intraday checklist.
Use with this indicator: chatgpt.com
For educational & decision-support only. Not financial advice.
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⚠️ Disclaimer
The information contained in my Scripts / Indicators / Ideas / Systems does not constitute financial advice or a solicitation to buy or sell any securities.
All markets carry risk. This tool is for educational and analytical purposes only.
I do not accept liability for any financial loss or damage resulting from direct or indirect use of this script.
Trading decisions must be made independently based on your own risk profile and financial assessment.
Donchian Predictive Channel (Zeiierman)█ Overview
Donchian Predictive Channel (Zeiierman) extends the classic Donchian framework into a predictive structure. It does not just track where the range has been; it projects where the Donchian mid, high, and low boundaries are statistically likely to move based on recent directional bias and volatility regime.
By quantifying the linear drift of the Donchian midline and the expansion or compression rate of the Donchian range, the indicator generates a forward propagation cone that reflects the prevailing trend and volatility state. This produces a cleaner, more analytically grounded projection of future price corridors, and it remains fully aligned with the signal precision of the underlying Donchian logic.
█ How It Works
⚪ Donchian Core
The script first computes a standard Donchian Channel over a configurable Length:
Upper Band (dcHi) – highest high over the lookback.
Lower Band (dcLo) – lowest low over the lookback.
Midline (dcMd) – simple midpoint of upper and lower: (dcHi + dcLo)/ 2.
f_getDonchian(length) =>
hi = ta.highest(high, length)
lo = ta.lowest(low, length)
md = (hi + lo) * 0.5
= f_getDonchian(lenDC)
⚪ Slope Estimation & Range Dynamics
To turn the Donchian Channel into a predictive model, the script measures how both the midline and the range are changing over time:
Midline Slope (mSl) – derived from a 1-bar difference in linear regression of the midline.
Range Slope (rSl) – derived from a 1-bar difference in linear regression of the Donchian range (dcHi − dcLo).
This pair describes both directional drift (uptrend vs. downtrend) and range expansion/compression (volatility regime).
f_getSlopes(midLine, rngVal, length) =>
mSl = ta.linreg(midLine, length, 0) - ta.linreg(midLine, length, 1)
rSl = ta.linreg(rngVal, length, 0) - ta.linreg(rngVal, length, 1)
⚪ Forward Projection Engine
At the last bar, the indicator constructs a set of forward points for the mid, upper, and lower projections over Forecast Bars:
The midline is projected linearly using the midline slope per bar.
The range is adjusted using the range slope per bar, creating either a widening cone (expansion) or a tightening cone (compression).
Upper and lower projections are then anchored around the projected midline, with logic that keeps the structure consistent and prevents pathological flips when slope changes sign.
f_generatePoints(hi0, md0, lo0, steps, midSlp, rngSlp) =>
upPts = array.new()
mdPts = array.new()
dnPts = array.new()
fillPts = array.new()
hi_vals = array.new_float()
md_vals = array.new_float()
lo_vals = array.new_float()
curHiLocal = hi0
curLoLocal = lo0
curMidLocal = md0
segBars = math.floor(steps / 3)
segBars := segBars < 1 ? 1 : segBars
for b = 0 to steps
mdProj = md0 + midSlp * b
prevRange = curHiLocal - curLoLocal
rngProj = prevRange + rngSlp * b
hiTemp = 0.0
loTemp = 0.0
if midSlp >= 0
hiTemp := math.max(curHiLocal, mdProj + rngProj * 0.5)
loTemp := math.max(curLoLocal, mdProj - rngProj * 0.5)
else
hiTemp := math.min(curHiLocal, mdProj + rngProj * 0.5)
loTemp := math.min(curLoLocal, mdProj - rngProj * 0.5)
hiProj = hiTemp < mdProj ? curHiLocal : hiTemp
loProj = loTemp > mdProj ? curLoLocal : loTemp
if b % segBars == 0
curHiLocal := hiProj
curLoLocal := loProj
curMidLocal := mdProj
array.push(hi_vals, curHiLocal)
array.push(md_vals, curMidLocal)
array.push(lo_vals, curLoLocal)
array.push(upPts, chart.point.from_index(bar_index + b, curHiLocal))
array.push(mdPts, chart.point.from_index(bar_index + b, curMidLocal))
array.push(dnPts, chart.point.from_index(bar_index + b, curLoLocal))
ptSet.new(upPts, mdPts, dnPts)
⚪ Rejection Signals
The script also tracks failed Donchian breakouts and marks them as potential reversal/reversion cues:
Signal Down: Triggered when price makes an attempt above the upper Donchian band but then pulls back inside and closes above the midline, provided enough bars have passed since the last signal.
Signal Up: Triggered when price makes an attempt below the lower Donchian band but then snaps back inside and closes below the midline, also requiring sufficient spacing from the previous signal.
// Base signal conditions (unfiltered)
bearCond = high < dcHi and high >= dcHi and close > dcMd and bar_index - lastMarker >= lenDC
bullCond = low > dcLo and low <= dcLo and close < dcMd and bar_index - lastMarker >= lenDC
// Apply MA filter if enabled
if signalfilter
bearCond := bearCond and close < ma // Bearish only below MA
bullCond := bullCond and close > ma // Bullish only above MA
signalUp := false
signalDn := false
if bearCond
lastMarker := bar_index
signalDn := true
if bullCond
lastMarker := bar_index
signalUp := true
█ How to Use
The Donchian Predictive Channel is designed to outline possible future price trajectories. Treat it as a directional guide, not a fixed prediction tool.
⚪ Map Future Support & Resistance
Use the projected upper and lower paths as dynamic future reference levels:
Projected upper band ≈ is likely a resistance corridor if the current trend and volatility persist.
Projected lower band ≈ likely support corridor or expected downside range.
⚪ Trend Path & Volatility Cone
Because the projection is driven by midline and range slopes, the channel behaves like a trend + volatility cone:
Steep positive midline slope + expanding range → accelerating, high-volatility trend.
Flat midline + compressing range → coiling/contracting regime ahead of potential expansion.
This helps you distinguish between a gentle drift and an aggressive move that likely needs more risk buffer.
⚪ Reversion & Rejection Signals
The Donchian-based signals are especially useful for mean-reversion and fade-style trades.
A Signal Down near the upper band can mark a failed breakout and a potential rotation back toward the midline or the lower projected band.
A Signal Up near the lower band can flag a failed breakdown and a potential snap-back up the channel.
When Filter Signals is enabled, these signals are only generated when they align with the chart’s directional bias as defined by the moving average. Bullish signals are allowed only when the price is above the MA, and bearish signals only when the price is below it.
This reduces noise and helps ensure that reversions occur in harmony with the prevailing trend environment.
█ Settings
Length – Donchian lookback length. Higher values produce a smoother channel with fewer but more stable signals. Lower values make the channel more reactive and increase sensitivity at the cost of more noise.
Forecast Bars – Number of bars used for projecting the Donchian channel forward.
Higher values create a broader, longer-term projection. Lower values focus on short-horizon price path scenarios.
Filter Signals – Enables directional filtering of Donchian signals using the selected moving average. When ON, bullish signals only trigger when the price is above the MA, and bearish signals only trigger when the price is below it. This helps reduce noise and aligns reversions with the broader trend context.
Moving Average Type – The type of moving average used for signal filtering and optional plotting.
Choose between SMA, EMA, WMA, or HMA depending on desired responsiveness. Faster averages (EMA, HMA) react quickly, while slower ones (SMA, WMA) smooth out short-term noise.
Moving Average Length – Lookback length of the moving average. Higher values create a slower, more stable trend filter. Lower values track price more tightly and can flip the directional bias more frequently.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
KC-BB Squeeze Trend Trader█ OVERVIEW
The KC-BB Squeeze Trend Trader identifies volatility compression and expansion by detecting when Bollinger Bands contract inside Keltner Channels and then release with confirmed momentum. It highlights potential trend-starting breakouts by combining squeeze detection, directional momentum, trend bias, and optional volume filters.
During periods of low volatility, price consolidates and energy builds. When volatility expands again, strong directional moves often follow. This tool helps traders spot those opportunities early with clear visual cues and optional performance tracking.
█ KEY FEATURES
Squeeze detection using Bollinger Bands inside Keltner Channels
Automatic identification of volatility expansion after the squeeze ends
Optional filters for momentum, trend direction, volume, and signal cooldown
Dynamic color fills for squeeze, bullish expansion, bearish expansion, and neutral states
Dashboard showing squeeze duration, tightness, momentum, trend, and volume context
Optional win-rate analytics using ATR-based target and stop evaluation
Multi-timeframe confirmation for higher-quality breakouts
█ HOW IT WORKS
A squeeze occurs when both Bollinger Bands sit inside the Keltner Channels.
A breakout begins when the Bollinger Bands expand outside the KCs.
Long signals appear when squeeze release aligns with bullish momentum and trend strength.
Short signals appear when bearish momentum and trend conditions agree.
Volume and cooldown filters help reduce noise and avoid low-quality entries.
█ HOW TO USE
Wait for a squeeze period (yellow fill).
Monitor duration and tightness: longer/tighter squeezes often lead to stronger moves.
When a long or short signal appears, use the plotted ATR-based target and stop as reference levels.
Watch for contraction or exit hints when momentum fades or volatility narrows again.
Higher timeframes generally provide cleaner and more reliable signals.
█ TIMEFRAME GUIDANCE
Crypto: 4H or 1D; consider increasing KC multiplier for high volatility.
Forex: 1H–4H; longer squeeze duration can improve selectivity.
Stocks: 1D–1W; consider slightly higher BB multiplier on slow-moving markets.
█ SETTINGS SUMMARY
Adjustable Bollinger Band and Keltner Channel lengths and multipliers
Three momentum modes: Linear Regression, Price–SMA, or ROC
Trend and volume filters (optional)
Configurable minimum squeeze duration and signal cooldown
ATR-based target and stop multipliers
Optional historically tight squeeze filter (percentile-based)
█ ALERTS
Squeeze Detected
Squeeze Released
Long Entry
Short Entry
Exit Hint
Historically Tight Squeeze
█ NOTES
ATR-based win-rate calculations provide simplified performance estimates.
Past behavior does not guarantee future movement.
Use position sizing and risk management appropriate for the instrument and timeframe.
█ CREDITS
Inspired by the Bollinger Band and Keltner Channel squeeze concept popularized by John Carter’s TTM Squeeze, with added enhancements for squeeze strength, filtering, and real-time performance metrics.
VWAP + Volume Spikes See Where Smart Money ExhaustsVolume tells the truth. VWAP tells the bias. This script shows both — live.
If you trade intraday momentum, reversals, or liquidity sweeps, this indicator is built for you.
It shows where volume spikes hit extreme levels, anchored around VWAP and its dynamic bands, so you can instantly spot capitulation or hidden absorption.
🎯 What This Indicator Does
✅ Plots VWAP — session-anchored, updates automatically
✅ Adds dynamic VWAP bands — standard deviation envelopes showing volatility context
✅ Highlights volume spikes — colored candles + background for abnormal prints
✅ Includes alerts — “Volume Spike”, “VWAP Cross”, or a combined alert with direction
✅ Clean visual design — instantly readable in fast markets
It’s your visual orderflow radar — whether you’re trading gold, indices, or small caps.
🔍 Why It Works
Institutions build and unwind positions around VWAP.
Retail often chases volume… this script shows you when that volume becomes too extreme.
A spike above VWAP near resistance? → Likely distribution.
A spike below VWAP near support? → Likely capitulation.
Combine volume exhaustion + VWAP context, and you’ll see market turning points form before most indicators react.
⚙️ Inputs You Can Tune
Bands lookback: adjusts how reactive the VWAP bands are
Band width (σ): set how tight or wide your deviation envelope is
Volume baseline length: controls how “abnormal” a spike must be
Spike threshold: multiplier vs. average volume
Toggle color-coding, bands, and labels
Default settings work well across 1m–15m intraday charts and 1h–4h swing frames.
💡 How Traders Use It
1️⃣ Fade Parabolics:
When a green spike candle pierces upper VWAP band on high volume → smart money unloading.
Look for rejection and short into VWAP.
2️⃣ Catch Capitulations:
When a red spike candle dumps below lower VWAP band → panic selling.
Watch for stabilization and long back to VWAP.
3️⃣ VWAP Rotation Plays:
Alerts for price crossing VWAP help you spot shift in intraday control.
Above VWAP = buyers in charge.
Below VWAP = sellers in charge.
🧠 Best Practices
Pair it with Volume Profile or Delta/Flow tools to confirm exhaustion.
Don’t chase — wait for spike confirmation + reversal candle.
Use it on liquid tickers (NASDAQ, SPY, GOLD, BTC, etc.).
Great for Dux-style small-cap shorts or index pullbacks.
🔔 Alerts Ready
Choose from:
Volume Spike (single-bar explosion)
VWAP Cross Up/Down (trend shift confirmation)
One Combined Alert (any signal, includes ticker, price, and volume)
Set once — get real-time push notifications, Telegram, or webhook signals.
📊 My Favorite Setups
US100 / NASDAQ: fade rallies above VWAP + spike
Gold / Silver: trade reversals from VWAP bands
Small caps: short back-side after volume climax
ES, DAX, Oil: scalp VWAP rotation with confluence
❤️ Support This Work
I release free and premium scripts weekly — combining smart money concepts, VWAP tools, and volume analytics.
👉 Follow me on TradingView for more indicators and setups.
👉 Comment “🔥” if you want me to post the multi-timeframe VWAP + Volume Pressure version next.
👉 Share this with your team — it helps the community grow.
Exponential Moving Average + ATR MTF [YSFX]Description:
This indicator is a reupload of a previously published EMA + ATR tool, updated and enhanced after a house rule violation to provide additional features and a cleaner, more versatile experience for traders.
It combines trend analysis and volatility measurement into one intuitive tool, allowing traders to visualize market direction, dynamic support and resistance, and adaptive risk levels—all in a clean, minimal interface.
The indicator calculates a customizable moving average (MA) type—EMA, SMA, WMA, HMA, RMA, DEMA, TEMA, VWMA, LSMA, or KAMA—and surrounds it with ATR-based bands that expand and contract with market volatility. This creates a dynamic envelope around price, helping traders identify potential breakouts, pullbacks, or high-probability entry/exit zones.
Advanced Features:
Multiple MA types: Supports all major moving averages, including advanced options like KAMA, DEMA, and TEMA.
KAMA customization: Adjustable fast and slow lengths for precise tuning.
Dual timeframe support: Optionally use separate timeframes for the MA and ATR, or a global timeframe for both.
Dynamic ATR bands: Automatically adjust to market volatility, useful for setting adaptive stop-loss levels.
Optional fill: Shade the area between upper and lower ATR bands for a clear visual representation of volatility.
Flexible for all markets: Works across any timeframe or asset class.
Who It’s For:
This indicator is ideal for trend-following traders, swing traders, and volatility-focused analysts who want to:
Confirm trend direction while accounting for volatility
Identify high-probability trade entries and exits
Implement dynamic, ATR-based stop-loss strategies
Keep charts clean and uncluttered while still capturing key market information
This reuploaded version ensures compliance with platform rules while offering enhanced flexibility and clarity for modern trading workflows.
HEK Dinamik Fiyat Kanalı Stratejisi v1HEK Dynamic Price Channel Strategy
Concept
The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium.
Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions.
How It Works
When the price reacts to the midline, the channel bands automatically reposition themselves.
Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum.
This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality.
Advantages
✅ Maintains trend continuity while avoiding overtrading.
✅ Automatically adapts to changing volatility conditions.
✅ Detects early signals of short- and mid-term trend reversals.
Applications
Directional confirmation in spot and futures markets.
A supporting tool in channel breakout strategies.
Identifying price consolidation and equilibrium zones.
Note
This strategy is intended for educational and research purposes only.
It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions.
© HEK — Adaptive Channel Approach on Dynamic Market Structures
6 gün önce
Sürüm Notları
HEK Dynamic Price Channel Strategy
Concept
The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium.
Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions.
How It Works
When the price reacts to the midline, the channel bands automatically reposition themselves.
Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum.
This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality.
Advantages
✅ Maintains trend continuity while avoiding overtrading.
✅ Automatically adapts to changing volatility conditions.
✅ Detects early signals of short- and mid-term trend reversals.
Applications
Directional confirmation in spot and futures markets.
A supporting tool in channel breakout strategies.
Identifying price consolidation and equilibrium zones.
Note
This strategy is intended for educational and research purposes only.
It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions.
© HEK — Adaptive Channel Approach on Dynamic Market Structures
RSI: chart overlay
This indicator maps RSI thresholds directly onto price. Since the EMA of price aligns with RSI’s 50-line, it draws a volatility-based band around the EMA to reveal levels such as 70 and 30.
By converting RSI values into visible price bands, the overlay lets you see exactly where price would have to move to hit traditional RSI boundaries. These bands adapt in real time to both price movement and market volatility, keeping the classic RSI logic intact while presenting it in the context of price action. This approach helps traders interpret RSI signals without leaving the main chart window.
The calculation uses the same components as the RSI: alternative derivation script: Wilder’s EMA for smoothing, a volatility-based unit for scaling, and a normalization factor. The result is a dynamic band structure on the chart, representing RSI boundary levels in actual price terms.
Key components and calculation breakdown:
Wilder’s EMA
Used as the anchor point for measuring price position.
myEMA = ta.rma(close, Length)
Volatility Unit
Derived from the EMA of absolute close-to-close price changes.
CC_vol = ta.rma(math.abs(close - close ), Length)
Normalization Factor
Scales the volatility unit to align with the RSI formula’s structure.
normalization_factor = 1 / (Length - 1)
Upper and Lower Boundaries
Defines price bands corresponding to selected RSI threshold values.
up_b = myEMA + ((upper - 50) / 50) * (CC_vol / normalization_factor)
down_b = myEMA - ((50 - lower) / 50) * (CC_vol / normalization_factor)
Inputs
RSI length
Upper boundary – RSI level above 50
Lower boundary – RSI level below 50
ON/OFF toggle for 50-point line (EMA of close prices)
ON/OFF toggle for overbought/oversold coloring (use with line chart)
Interpretation:
Each band on the chart represents a chosen RSI level.
When price touches a band, RSI is at that threshold.
The distance between moving average and bands adjusts automatically with volatility and your selected RSI length.
All calculations remain fully consistent with standard RSI values.
Feedback and code suggestions are welcome, especially regarding implementation efficiency and customization.
Yearly VWAP with Z-Score V2This script extends the traditional Volume Weighted Average Price (VWAP) by applying it to yearly sessions (with a customizable start month) and combining it with a Z-Score framework to standardize price deviations from VWAP.
Features
Yearly VWAP: Automatically resets at the selected month, making it possible to align VWAP with fiscal or seasonal cycles (e.g., June–May).
Volatility-Weighted Bands: Standard deviation is calculated using volume-weighted price variance, creating adaptive upper and lower bands around VWAP.
Z-Score Calculation: Converts price distance from VWAP into standardized scores, ranging from +2.5 to –2.5. This enables statistical interpretation of whether price is trading at fair value, extended, or oversold relative to VWAP.
Custom Session Control: Input allows users to change the yearly anchor month.
On-Chart Display: VWAP and bands are plotted, with a live Z-Score label shown on the latest bar.
How to Use
Fair Value Reference: VWAP reflects the average price weighted by volume over the yearly session — a natural equilibrium point.
Overbought / Oversold Detection: Extreme Z-Score readings (±2 or beyond) highlight when price is stretched relative to VWAP.
Cycle Analysis: Resetting VWAP by custom months allows studying market behavior over fiscal years, seasons, or custom trading cycles.
Part of a Broader Toolkit: This script is not a standalone trading system. It works best when aggregated with other indicators, confluence factors, or a structured strategy.
Originality
Unlike a standard VWAP, this version:
Uses yearly anchoring with custom start month instead of session/day anchoring.
Adds volume-weighted standard deviation bands for statistical context.
Translates distance into a Z-Score scale for objective overbought/oversold assessment.
Positive Z-Score values indicate zones where price is positioned favorably for accumulation or potential buys, while negative values highlight areas more suitable for distribution or profit-taking — always best used in confluence with other tools rather than as a standalone signal
Crypto Breakout Buy/Sell Sequence
⚙️ Components & Sequence Multiple Timeframe (What It Does)
1. Bollinger Bands – Form the foundation by measuring volatility and creating the dynamic range where squeezes and breakouts occur.
2. Squeeze Dots – Show when price compresses inside the bands, signaling reduced volatility before expansion.
3. Breakout Event (Brk Dot) – Fires when price expands beyond the squeeze zone, confirming volatility expansion. (This paints Intra, before candle close)
4. Buy Signal – Confirms entry after a breakout is validated. (This paints at candle close)
5. Pump Signal – Flags sudden surges that extend sharply from the bands, often linked to strong inflows.
6. Momentum Stream – Tracks the strength of movement following the breakout, from continuation (🟢) to slowing (🟡) to exhaustion (🔴). (Resets at Pump Signal)
7. Overbought Indicator – Confirms when momentum has reached overheated conditions, often aligning with band extremes.
8. Sell Signal – Prints when exhaustion/reversal conditions are met, closing the trade cycle.
The Crypto Breakout Buy/Sell Sequence is a no-repaint event indicator that maps a full trade cycle using Bollinger-band-based volatility states: Bollinger Bands → Squeeze → Breakout → Buy → Pump → Momentum → Top Test → Overbought → Sell. Each stage is rule-based and designed to be read on standard candlesticks.
How It Works (System Logic)
Volatility framework: Bollinger Bands define dynamic range and compression/expansion.
Initiation: Squeeze → Breakout confirms expansion; Buy validates participation after expansion begins.
Management: Pump highlights unusual acceleration; Momentum stream tracks continuation → slowing → exhaustion.
Exhaustion/Exit: Top Testing + Overbought build the exhaustion case; Sell marks the sequence end.
How To Use (Quick Guide)
Wait for Squeeze → Breakout → Buy to establish a structured start.
Manage with Momentum:
🟢 continuation, 🟡 slowing, 🔴 exhaustion pressure.
Monitor extremes: Top Testing and/or Overbought = tighten risk.
Exit on Sell or on your risk rules when exhaustion builds.
Limitations & Good Practice
Signals reflect price/volatility behavior, not certainty.
Strong trends can remain extended; Overbought/Top Test ≠ instant reversal.
Always confirm with your own risk rules, position sizing, and market context.
Initial public release: integrated Squeeze/Breakout/Buy → Momentum → Exhaustion → Sell cycle; improved label clarity; cleaned defaults.
Disclaimer
For educational purposes only. Not financial advice. Past performance does not guarantee future results. Test before live use.
Thank You
Scalping, Swing Pro: Urban Towers + Bollinger(0.5)+ WMA by KidevThis indicator combines narrow Bollinger Bands (σ = 0.5) with a Weighted Moving Average (WMA-96) to provide traders with a reliable framework for identifying both short-term scalps and medium-term swing setups.
Bollinger Bands (0.5σ):
Traditional Bollinger Bands at 2σ cover ~95% of price movement, while 0.5σ bands narrow the focus to ~50% of price activity. This tighter structure makes them ideal for detecting volatility contractions, consolidations, and early breakout signals.
WMA-96 as Trend Reference:
The 96-period WMA acts as a slower, more stable directional guide. Unlike shorter WMAs, this longer setting filters noise and serves as a reference line for the dominant trend. Traders can use it as an anchor for intraday or swing positions.
Scalping & Swing Benefits:
Price holding above the WMA-96 while staying near the upper 0.5σ band often signals strength.
Contractions (squeezes) in the 0.5σ band followed by expansion frequently mark breakout zones.
Pullbacks toward the WMA-96 combined with band signals can act as re-entry or risk-defined trade areas.
This script provides a balanced view of momentum and stability — the 0.5σ bands reveal short-term volatility shifts, while the WMA-96 grounds the trader in the prevailing trend.
ATR-limited Donchian ChannelThe ATR-limited Donchian Channel is a modified version of the classic Donchian Channel that adapts more quickly to changing market conditions.
While a traditional Donchian Channel is based only on the highest high and lowest low over a given lookback period, this version introduces an ATR-based constraint that prevents the channel lines from extending too far away from price. This makes the channel more responsive and reduces lag compared to the standard Donchian Channel.
How it works
The upper band is based on the highest high of the last N candles, but it cannot exceed a maximum distance of ATR × Factor above the current median price (midpoint of high and low).
The lower band is based on the lowest low of the last N candles, but it cannot drop more than ATR × Factor below the median price.
If the Donchian Channel would normally extend further than this ATR-limited boundary, the line is capped and marked in blue .
Otherwise, the upper band is drawn in red and the lower band in green .
A middle line is also plotted as the average of the modified upper and lower bands.
An optional offset allows you to shift the channel backward or forward in time for easier visual alignment.
Why use this version?
Faster reaction: By constraining the channel with ATR, the indicator adapts quicker to volatility changes and avoids long periods of overextended levels.
Noise control: ATR filtering prevents extreme spikes or outlier highs/lows from stretching the channel unnecessarily.
Visual clarity: Color-coding highlights when ATR filtering is active, making it easy to distinguish capped vs. natural Donchian levels.
Typical use cases
Trend-following breakout systems, but with volatility-aware limits.
Identifying dynamic support and resistance zones that adjust to market conditions.
Filtering false breakouts by monitoring when the Donchian channel is capped by ATR.
✅ This indicator is designed for traders who want the structure of a Donchian Channel but with an adaptive, volatility-sensitive adjustment that makes it react faster and more reliably than the classic version.
The Kyber Cell's – TTM Squeeze ProThe Kyber Cell’s TTM Squeeze Pro
TTM Squeeze + ALMA + VWAP for Precision Trade Timing
⸻
1. Introduction
Kyber Cell’s Squeeze Pro is a comprehensive, all-in-one overlay indicator built on top of John Carter’s famous TTM Squeeze concept. It integrates advanced momentum and trend analysis using Arnaud Legoux Moving Averages (ALMA), a scroll-aware VWAP with optional deviation bands, and a clean, user-friendly visual system. The goal is simple: give traders a clear and configurable chart that identifies price compression, detects release moments, confirms direction, and helps manage risk and reward visually and effectively.
This tool is intended for traders of all styles — scalpers, swing traders, or intraday strategists — looking for cleaner signals, better visual cues, and more confidence in entry/exit timing.
⸻
2. Core Concepts
At its heart, the Squeeze Pro builds an in-chart visualization of the TTM Squeeze, a strategy that identifies when price volatility compresses inside a Bollinger Band that is narrower than a Keltner Channel. These moments often precede explosive breakouts. This version categorizes squeezes into three levels of compression:
• Blue Dot – Low Compression
• Orange Dot – Medium Compression
• Red Dot – High Compression
When the squeeze “fires” (i.e., the Bollinger Bands expand beyond all Keltner thresholds), the indicator flips to a Green Dot, signaling potential entry if confirmed by trend direction.
The indicator also includes a momentum model using linear regression on smoothed price deviation to determine directional bias. Momentum is further reinforced by a customizable trend engine, allowing you to switch between EMA-21 or HMA 34/144 logic.
An ALMA ribbon is plotted across the chart to represent smoothed trend strength with minimal lag, and a scroll-aware VWAP (Volume-Weighted Average Price) line, optionally with ±σ bands, helps confirm mean-reversion or momentum continuation setups.
⸻
3. Visual Components
Squeeze Pro replaces the traditional histogram with bar coloring logic based on your selected overlay mode:
• Momentum Mode colors bars based on whether momentum is rising or falling and in which direction (aqua/blue for bullish, red/yellow for bearish).
• Trend Mode colors bars using EMA or HMA logic to identify whether price is in a bullish, bearish, or neutral trend state.
A colored backdrop is triggered when a squeeze fires and momentum direction is confirmed. It remains green for bullish runs and red for bearish runs. The background disappears when the trend exhausts or reverses.
Each squeeze level (low, medium, high) is plotted as tiny dots above or below candles, with configurable colors. On the exact bar where the squeeze fires, the indicator optionally plots entry markers — either arrows or triangles — which can be placed with adjustable padding using ATR. These provide an at-a-glance signal of possible long or short entries.
EXPERIMENTAL : For risk and reward management, protective stop lines and limit targets can be toggled on. Stops are calculated using either recent swing highs/lows or a fixed ATR multiple, depending on user preference. Limit targets are calculated from entry price using ATR-based projections.
All colors are customizable.
⸻
4. Multi-Timeframe Squeeze Panel
An optional MTF Squeeze Panel appears in the top-right corner of the chart, displaying the squeeze status across multiple timeframes — from 1-minute to Monthly. Each timeframe is color-coded:
• Red for High Compression
• Orange for Medium Compression
• Blue for Low Compression
• Yellow for Open/No Compression
This provides rapid context for whether multiple timeframes are simultaneously compressing (a common precursor to explosive moves), helping traders align higher- and lower-timeframe signals. Colors are customizable.
The MTF panel dynamically adjusts to chart space and only renders the selected intervals for clarity and performance.
⸻
5. Inputs and Configuration Options
Squeeze Pro offers a rich configuration suite:
• Squeeze Settings: Control the Bollinger Band standard deviation, and three separate Keltner Channel multipliers (for low, medium, and high compression zones).
• ALMA Controls: Adjust the smoothing length, offset, and σ factor to control ribbon sensitivity.
• VWAP Options: Toggle VWAP on/off and optionally show ±σ bands for mean reversion signals.
• Entry Markers: Customize marker shape (arrow or triangle), size (tiny to huge), color, and padding using ATR multipliers.
• Stops and Targets:
• Choose between Swing High/Low or ATR-based stop logic.
• Define separate ATR lengths and multipliers for stops and targets.
• Independently toggle their visibility and color.
• Bar Coloring Mode: Select either Momentum or Trend logic for bar overlays.
• Trend Engine: Choose between EMA-21 or HMA 34/144 for identifying trend direction.
• Squeeze Dot Colors: Customize the colors for each compression level and release state.
• MTF Panel: Toggle visibility per timeframe — from 1m to Monthly.
This high degree of customization ensures that the indicator can adapt to nearly any trading style or preference.
⸻
6. Trade Workflow Suggestions
To get the most out of this tool, traders can follow a consistent workflow:
1. Watch Dot Progression: Blue → Orange → Red indicates increasing compression and likelihood of breakout.
2. Enter on Green Dot: When the squeeze fires (green dot), confirm entry direction with bar color and backdrop.
3. Use Confirmation Tools:
• ALMA should slope in the trade direction.
• VWAP should support the price move or confirm expansion away from mean.
4. Manage Risk and Reward (experimental):
• Respect stop-loss placements (Swing/ATR).
• Use ATR-based limit targets if enabled.
5. Exit:
• Consider exiting when momentum crosses zero.
• Or exit when the background color disappears, signaling potential trend exhaustion.
⸻
7. Alerts
Includes built-in alert conditions to notify you when a squeeze fires in either direction:
• “Squeeze Long”: Triggers when a green dot appears and momentum is bullish.
• “Squeeze Short”: Triggers when a green dot appears and momentum is bearish.
You can use these alerts for automation or to stay notified of new setups even when away from the screen.
⸻
8. Disclaimer
This indicator is designed for educational purposes only and should not be interpreted as financial advice. Trading is inherently risky, and any decisions based on this tool should be made with full awareness of personal risk tolerance and capital exposure.
Bitcoin Cycle Log-Curve (JDK-Analysis)Important: The standard parameters provided in the script are specifically tuned for the TradingView Bitcoin Index chart on a monthly timeframe on logarithmic scale, and will yield the most accurate visual alignment when applied to that dataset. (more below)
This very simple script visualizes Bitcoin’s long-term price behavior using a logarithmic regression model designed to reflect the cyclical nature of Bitcoin’s historical market trends. Unlike typical technical indicators that react to recent price movements, this tool is built on the assumption that Bitcoin follows an exponential growth path over time, shaped by its fixed supply structure and four-year halving cycles.
The calculation behind the curved bands:
An upper boundary, a lower boundary, and a central midline, are calculated based on logarithmic functions applied to the bar index (which serves as a proxy for time). The upper and lower bounds are defined using exponential formulas of the type y = exp(constant + coefficient * log(bar_index)), allowing the curves to evolve dynamically over time. These bands serve as a macro-level guide for identifying periods of historical overvaluation (upper red curve) and undervaluation (lower green curve), with a central black curve representing the geometric average of the two.
How to customize the parameters:
The lower1_const and upper1_const values vertically shift the respective lower and upper curves—more negative values push the curve downward, while higher values lift it.
The lower1_coef and upper1_coef control the steepness of the curves over time, with higher values resulting in faster growth relative to time.
The shift_factor allows for uniform vertical adjustment of all curves simultaneously.
Additionally, the channel_width setting determines how far the mirrored bands extend from the original curves, creating a visual “channel” that can highlight more conservative or aggressive valuation zones depending on preference.
How to use this indicator:
This indicator is not intended for short-term trading or intraday signals. Rather, it serves as a contextual framework for long-term investors to identify high-risk zones near the upper curve and potential long-term value opportunities near the lower curve. These areas historically align with cycle tops and bottoms, and the model helps to place current price action within that broader cyclical narrative. While the concept draws inspiration from Bitcoin’s halving-driven market cycles and exponential adoption curve, the implementation is original in its use of time-based logarithmic regression to define dynamic trend boundaries.
It is best used as a strategic tool for cycle analysis, macro positioning, and trend anchoring—rather than as a short-term signal provider.
Quantum Reversal# 🧠 Quantum Reversal
## **Quantitative Mean Reversion Framework**
This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**.
---
## ⚡ **Core Technical Architecture**
### 📊 **Statistical Foundation**
- **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals
- **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns
- **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions
### 🔬 **Momentum Analysis Layer**
- **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45
- **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals
- **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings
### ⚙️ **Entry Logic Architecture**
```
Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45)
```
- **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry
- **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity
- **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure
### 🎯 **Exit Strategy Optimization**
- **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L
- **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion
- **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels
---
## 📈 **Statistical Properties**
### **Risk Management Framework**
- **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets
- **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves
- **Position Management**: Single position limit prevents over-leveraging
### **Signal Processing Characteristics**
- **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations
- **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility
- **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment
---
## 🔧 **Parameter Configuration**
| Technical Parameter | Value | Statistical Significance |
|-------------------|-------|-------------------------|
| Bollinger Period | 20 | Standard statistical lookback for volatility calculation |
| Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) |
| RSI Period | 14 | Traditional momentum oscillator period |
| RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics |
| Smoothing Period | 5 | Noise reduction filter for momentum signals |
---
## 📊 **Algorithmic Advantages**
✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets
✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions
✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives
✅ **Momentum Integration**: RSI smoothing improves signal quality and timing
✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias
---
## 🔬 **Mathematical Foundation**
The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal.
**Statistical Basis:**
- Mean reversion follows the principle that extreme price deviations from the moving average are temporary
- The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution
- RSI momentum smoothing reduces noise inherent in oscillator calculations
---
## ⚠️ **Risk Considerations**
This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential.
---
## 🎯 **Implementation Notes**
- **Market Regime Awareness**: Most effective in ranging/consolidating markets
- **Volatility Sensitivity**: Performance may vary during extreme volatility events
- **Backtesting Recommended**: Historical performance analysis advised before live implementation
- **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach
---
**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
Multi-EnvelopeRMA Multi-Envelope Indicator
The RMA Multi-Envelope Indicator is a technical analysis tool designed for TradingView, utilizing Pine Script v6. It creates eight customizable envelope bands around a 200-period Running Moving Average (RMA) on a 5-minute timeframe, based on current market measurements. Each band has independent upper and lower percentage deviations, preset to: Band 1 (0.42%, 0.46%), Band 2 (0.78%, 0.69%), Band 3 (1.01%, 1.03%), Band 4 (1.36%, 1.39%), Band 5 (1.80%, 1.62%), Band 6 (2.15%, 2.13%), Band 7 (2.93%, 2.81%), and Band 8 (4.65%, 4.18%). Users can adjust the timeframe, moving average type (RMA, SMA, or EMA), length, and colors for the basis line and bands via hex codes (e.g., #FF6D00 for the basis and Band 8) with semi-transparent color.rgb fills. Ideal for identifying support/resistance, overbought/oversold conditions, or trend boundaries on a 5-minute chart.
