Cerca negli script per "curve"
UCS_Squeeze_Timing-V1There is an important information the Squeeze indicator is missing, which is the Pre Squeeze entry. While the Bollinger band begins to curves out of the KC, The breakout usually happens. There are many instances that the Squeeze indicator will fire, after the Major move, I cant blame the indicator, thats the nature (lagging) of all indicators, and we have to live with it.
Therefore pre-squeeze-fire Entry can be critical in timing your entry. Timing it too early could result in stoploss if it turns against you, ( or serious burn on options premium), because we never know when the squeeze will fire with the TTM squeeze, But now We know. Its a little timing tool. Managing position is critical when playing options.
I will code the timing signal when I get some time.
Updated Versions -
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure.
At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior.
The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred.
🔹 Features
🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis)
HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter:
- H > Trend Start threshold suggests trend persistence and directional continuation.
- H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value.
Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias.
This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility.
🔸 Dual Channel Engine (Fast vs Slow Models)
Instead of relying on one fixed channel, HOAC computes two independent channel candidates:
Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments.
Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow.
Each model produces:
- A midline (basis)
- Outer bands (wider deviation)
- Inner bands (tighter deviation)
This structure gives you a clear core zone and an outer envelope that better represents volatility expansion.
🔸 Rolling Optimization Memory (Model Selection by Error)
HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error.
This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?”
Additionally:
If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most.
🔸 Optional Output Smoothing (User-Selectable)
The final selected channel can be smoothed using your choice of:
- SMA
- EMA
- HMA
- RMA
This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine.
🔸 Premium Visualization Layer (Inner Core + Outer Fade)
HOAC uses a layered band design:
- Inner bands define the core equilibrium zone around the midline.
- Outer bands define an extended volatility envelope for extremes.
Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity.
🔸 Adaptive Bar Tinting Strength (Regime Intensity)
Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle.
🔸 Mean-Reversion Signal Layer
Mean-reversion signals are enabled when the environment is not classified as Trending:
- Buy when price crosses back above the lower outer band
- Sell when price crosses back below the upper outer band
This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default.
🔸 Minimalist Dashboard (HUD)
A compact table displays:
- Current regime classification
- Smoothed Hurst value
- Which model is currently preferred (Fast or Slow)
- Trend flow direction (based on midline slope)
🔹 Calculations
1) Robust Hurst Exponent (R/S Analysis)
The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent.
calc_robust_hurst(int length) =>
float r = math.log(close / close )
float returns = array.new_float(length)
for i = 0 to length - 1
array.set(returns, i, r )
float mean = array.avg(returns)
float cumDev = 0.0
float maxCD = -1.0e10
float minCD = 1.0e10
float sumSqDiff = 0.0
for i = 0 to length - 1
float val = array.get(returns, i)
sumSqDiff += math.pow(val - mean, 2)
cumDev += (val - mean)
if cumDev > maxCD
maxCD := cumDev
if cumDev < minCD
minCD := cumDev
float R = maxCD - minCD
float S = math.sqrt(sumSqDiff / length)
float RS = (S == 0) ? 0.0 : (R / S)
float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5
hurst
This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure.
2) Hurst Smoothing
Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions.
float rawHurst = calc_robust_hurst(i_hurstLen)
float hVal = ta.ema(rawHurst, i_smoothHurst)
This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display.
3) Regime Classification
The smoothed Hurst reading is compared to user thresholds to label the environment.
string regime = "NEUTRAL"
if hVal > i_trendZone
regime := "TRENDING"
else if hVal < i_chopZone
regime := "MEAN REV"
Higher Hurst implies more persistence, so the indicator treats it as a trend environment.
Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation.
4) Dual Channel Models (Fast and Slow)
HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers.
Fast model (more reactive):
float fastBasis = ta.wma(close, 20)
float fastDev = ta.stdev(close, 20)
ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis))
Slow model (more stable):
float slowBasis = ta.wma(close, 50)
float slowDev = ta.stdev(close, 50)
ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis))
Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)).
5) Rolling Error Memory and Model Preference
To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals.
var float errFast = array.new_float()
var float errSlow = array.new_float()
update_error(float errArr, float error, int maxLen) =>
errArr.unshift(error)
if errArr.size() > maxLen
errArr.pop()
Each bar updates both error histories and computes which model has lower recent accumulated error.
update_error(errFast, fastM.error, i_optLookback)
update_error(errSlow, slowM.error, i_optLookback)
bool preferFast = errFast.sum() < errSlow.sum()
This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars.
6) Winner Selection Logic (Regime-Aware Hybrid)
The final model selection uses both regime and rolling error performance.
ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM)
rawMid := winner.mid
rawUp := winner.upper
rawDn := winner.lower
rawUpInner := winner.upper_inner
rawDnInner := winner.lower_inner
In Mean Reversion, the script forces the fast model to ensure responsiveness.
Otherwise, it selects the lowest-error model between fast and slow.
7) Optional Output Smoothing
After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type.
smooth(float src, string type, int len) =>
switch type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"HMA" => ta.hma(src, len)
"RMA" => ta.rma(src, len)
=> src
float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid
float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp
float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn
float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner
float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner
This preserves decision integrity since smoothing happens after model selection, not before.
8) Dynamic Visual Intensity From Hurst
Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints.
int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
BTC - BEAM: Adaptive Multiple (Open-Source)Title: BTC - BEAM: Adaptive Multiple Cycle Oscillator | RM
Overview & Philosophy
The BTC - BEAM (Bitcoin Economics Adaptive Multiple) is a premier macro-valuation tool designed to identify the "Logarithmic Pulse" of Bitcoin's 4-year cycles. Unlike standard oscillators that lose relevance as the network grows, BEAM uses an adaptive baseline that tracks Bitcoin’s fundamental growth curve with precision.
It identifies the harmonic distance between the current price and its multi-year mean, helping you spot the rare windows of deep capitulation and terminal euphoria.
Methodology
This edition is a hardened, gap-proof and Open-Source implementation of the canonical BEAM model.
1. The 1400-Day Anchor (200 Weeks):
The model is anchored to a 1400-day Simple Moving Average. On the Weekly chart, this aligns with the legendary 200-week moving average—the historical "floor" of the Bitcoin network. It represents one full halving cycle of data.
2. Daily-Lock Architecture:
Even when viewed on the 1W chart, the script performs its calculations using Daily data. This ensures that the oscillator captures the exact peak day of a cycle, providing a "high-resolution" signal within a "low-noise" weekly environment.
3. Logarithmic Normalization:
We calculate the natural logarithm of the price-to-mean relationship, scaled by a factor of 2.5: Score = ln(Price / 1400d MA) / 2.5 This creates a standardized "Multiple" that remains comparable across all Bitcoin eras.
How to Read the Chart (1W Context)
🟧 The BEAM Line (Orange): Tracks the "macro heat" of the market. On the 1W chart, look for the slope of this line to identify cycle acceleration.
🔴 The Cycle Ceiling (Score > 1.0): Historical Cycle Tops. When the weekly candle sustains in this zone, the market has reached a state of unsustainable mania. Every major blow-off top has been captured in this red corridor.
🟢 The Cycle Floor (Score < 0.1): Generational Accumulation. On the 1W chart, these zones appear as extended "green troughs." These are the only times in history where Bitcoin is fundamentally "too cheap" relative to its 4-year trend.
The Status Dashboard
The bottom-right monitor provides immediate cycle classification:
• BEAM Score: The exact logarithmic multiple.
• Cycle Regime: ACCUMULATION , NEUTRAL , or OVERHEATED .
Credits
BitcoinEcon: For the original concept of the BEAM adaptive model.
⚠️ RECOMMENDATION: While this indicator captures daily data, it is strongly recommended to be viewed on the Weekly (1W) Timeframe. The 1W chart filters market noise and perfectly reveals the long-term "Cycle Narrative."
Disclaimer
This script is for research and educational purposes only. Macro indicators provide structural context; they are not crystal balls. Always manage your risk according to your personal financial plan.
Tags
bitcoin, btc, beam, macro, cycle, halving, log-growth, valuation, on-chain, Rob Maths
CandelaCharts - Composite Pressure Index 📝 Overview
The CandelaCharts – Composite Pressure Index (CPI) is a multi-factor oscillator that blends RSI , Money Flow Index (MFI) , and Chaikin Money Flow (CMF) into a single, stretchable “pressure” line. Instead of looking at three separate indicators, CPI compresses price momentum and volume flow into one normalized curve around 0 , then amplifies extremes using a rolling z-score .
The result is a dynamic gauge of buying vs. selling pressure that can travel beyond ±1 during strong regime shifts, helping you spot exhaustion, climaxes, and trend-strength phases more intuitively.
📦 Features
Composite pressure engine – Combines RSI, MFI, and CMF into a single normalized oscillator around 0, giving you a unified view of market pressure.
Custom weighting of components – Independently weight RSI, MFI, and CMF to prioritize pure price momentum or volume-driven signals.
Rolling z-score stretch – Uses a configurable z-score window to “stretch” the composite values, letting the line exceed ±1 during extremes instead of staying capped.
Adaptive amplitude control – An amplitude (gain) factor lets you scale how aggressive or subtle the CPI swings appear.
EMA smoothing – Optional smoothing removes noise while preserving the timing of swings and reversals.
Visual pressure band – Zero, +1, and -1 reference lines with a shaded band make it easy to see when pressure is “normal” vs. extended.
Dynamic color gradients – Warm/orange tones above 0 for bullish pressure and cool/blue tones below 0 for bearish pressure, with saturation increasing as pressure intensifies.
NA-safe statistics – Custom mean and standard deviation routines ensure stable behavior from the start of the chart and during partial history.
⚙️ Settings
RSI Length : Lookback length for RSI . Higher values smooth the RSI component; lower values make it more reactive to short-term price momentum.
MFI Length : Lookback length for the manual Money Flow Index . Adjust this to control how sensitive CPI is to price–volume interaction.
CMF Length : Lookback length for Chaikin Money Flow . This defines the window used to assess accumulation/distribution through volume flow.
RSI Weight : Relative importance of RSI within the composite. Increasing this emphasizes pure price momentum in the CPI.
MFI Weight : Relative importance of MFI. Higher values strengthen the influence of volume-weighted price moves.
CMF Weight : Relative importance of CMF. Raising this highlights accumulation/distribution as a driver of the pressure index.
Smoothing : EMA length applied to the stretched CPI line. A value of 1 effectively disables smoothing, while higher values reduce noise at the cost of a slight lag.
Z-score Window : Rolling window used to compute the mean and standard deviation of the raw composite. This defines the statistical context for what counts as “extreme”. Shorter windows adapt faster; longer windows give a more stable regime.
Amplitude : Gain factor applied to the z-scored composite. Values above 1.0 exaggerate swings and make extremes more visually pronounced; values below 1.0 compress them.
⚡️ Showcase
Composite Pressure Index
Mean Line
Divergences
📒 Usage
1. Identify directional pressure regimes
Use 0 as the key balance line:
CPI > 0 → Net bullish pressure (buyers in control).
CPI < 0 → Net bearish pressure (sellers in control).
You can treat prolonged stays above or below 0 as confirmations of trend direction, especially when price structure agrees.
2. Read statistical extremes instead of fixed levels
Because CPI is stretched via a z-score , values beyond ±1 typically represent statistically meaningful extremes within your chosen window:
CPI > +1 → Overextended bullish pressure / potential euphoria.
CPI < -1 → Overextended bearish pressure / potential capitulation.
These zones are not automatic reversal signals, but they highlight areas where monitoring for exhaustion, blow-offs, or risk-reward shifts can be beneficial.
3. Spot divergences with price
Classic divergence logic applies particularly well when pressure is composite:
Bearish divergence – Price makes higher highs, but CPI makes lower highs or fails to confirm.
Bullish divergence – Price makes lower lows, but CPI makes higher lows or shows less downside extension.
These patterns can be integrated with support/resistance, liquidity levels, and other CandelaCharts tools.
4. Tune the weights to your strategy
Adjust the three weights to match your focus:
Higher RSI weight → More sensitivity to pure price momentum (good for breakout or trend-following systems).
Higher MFI weight → Greater emphasis on price–volume interaction (ideal for spotting volume-confirmed moves).
Higher CMF weight → Stronger focus on accumulation/distribution (helpful for swing and position traders).
5. Integrate with existing setups
The CPI is designed to sit comfortably below price:
Use it as a “context” oscillator underneath your main price-action and liquidity models.
Combine CPI extremes and divergences with key levels, range models, or order flow signals for higher-confluence entries.
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Auto-Anchored Fibonacci Volume Profile [Custom Array Engine]Description:
1. The Theoretical Foundation: Structure vs. Participation In professional technical analysis, traders often struggle to reconcile two distinct datasets: Price Geometry (where price should go) and Market Participation (where money actually went).
Why Fibonacci? (The Structure) Fibonacci Retracements map the mathematical structure of a trend. They identify psychological and algorithmic "interest zones" (0.382, 0.5, 0.618) where a correction is statistically likely to terminate. However, Fibonacci levels are theoretical—they are "lines in the sand" that do not guarantee liquidity or reaction.
Why Volume Profile? (The Verification) Volume Profile maps the historical exchange of shares at specific price levels. It reveals "fair value" (High Volume Nodes) and "market imbalance" (Low Volume Nodes). It is the only tool that verifies if a specific price level was actually accepted by institutional participants.
2. Underlying Calculations (The Custom Engine) This script operates on a custom-built calculation engine that bypasses standard built-in functions entirely. It uses Pine Script Arrays to build a Volume Profile from scratch. Here is the breakdown of the proprietary code logic:
A. The "Smart-Fill" Distribution Algorithm (Solves Gapping)
The Problem: Standard volume scripts often assign a candle's entire volume to a single price row. In volatile markets or steep trends, this creates visual "gaps" or a "barcode" effect because price moved too fast to register on every row.
My Solution: I wrote a custom loop that calculates the vertical overlap of every candle against the profile grid.
The Math: Volume Per Bin = Total Candle Volume / Bins Touched.
The Result: If a single volatile candle spans 10 price rows (bins), the script mathematically divides that volume and distributes it equally into all 10 array indices. This generates a solid, continuous distribution curve that accurately reflects price action through the entire candle range, not just the close.
B. Dynamic Arrays & Split-Volume Logic The script initializes two separate floating-point arrays (buyVolArray and sellVolArray) sized to the user's resolution (up to 300 rows). It iterates through the specific time-window of the swing:
If Close >= Open, the calculated volume slice is injected into the Buy Array.
If Close < Open, it is injected into the Sell Array.
These arrays are then visually stacked to render the dual-color profile, allowing traders to see the "Delta" (Buyer vs. Seller aggression) at key structural levels.
C. Custom Garbage Collection (Performance) To enable the "Auto-Anchoring" feature without causing chart lag or visual artifacts ("ghosting"), the script includes a Garbage Collection System. Before drawing a new profile, the script iterates through a tracking array of all existing objects (box.delete, line.delete) and clears them from memory. This ensures the indicator remains lightweight and responsive even when dragging chart margins or switching timeframes.
3. The Synthesis: Why Combine Them? The core philosophy of this script is Confluence . A Fibonacci level without volume is merely a suggestion; a Fibonacci level backed by volume is a defensive wall. By algorithmically anchoring a Volume Profile to the exact coordinates of a Fibonacci swing, this tool allows traders to instantly answer critical questions:
"Is the Golden Pocket (0.618) supported by a High Volume Node (HVN), or is it a Low Volume Node (LVN) that price might slice through?"
"Is the Shallow Retracement (0.382) holding because of structural support, or just a lack of selling pressure?"
4. How to Read the Indicator
The Geometry: The script automatically detects the trend and draws standard Fib levels (0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0).
The Confluence Check: Look for the Point of Control (Red Line). If this High Volume Node aligns with a key Fib level (e.g., the 0.618), the probability of a reversal increases significantly.
The Imbalance Check: Look for "Valleys" in the profile (Low Volume Nodes). These gaps often act as "slippage zones" where price travels quickly between structural levels.
Buy/Sell Splits: The dual-color bars (Teal/Red) reveal the composition of the volume. A 0.618 level held up by dominant Buy Volume is a stronger bullish signal than one with mixed volume.
5. Settings & Customization
Lookback Length: Sensitivity of the swing detection (Default: 200 bars).
Resolution: Granularity of the profile rows (Default: 100). Higher values provide smoother definition.
Width (%): Responsive sizing that scales the profile relative to the trend's duration.
Extend Lines: Option to project structural levels infinitely to the right.
Disclaimer This script is an analytical tool for visualizing historical market data. It does not provide trade signals or financial advice.
Trinity Bollinger Bands Pro with BreakoutsTrinity Bollinger Bands Pro Indicator
The **Trinity Bollinger Bands Pro + Triple Bands & Expansion** is a highly customized, advanced volatility and breakout indicator built on the classic Bollinger Bands framework. It expands the standard single-pair bands into **three independent deviation levels** (typically 1σ, 2σ, and 3σ) around a user-selectable moving average basis (default EMA 20). This creates clear "zones" of volatility, with dynamic trend-based coloring, layered fills, fixed-style labels, and a statistical volatility expansion detector shown as a directional background highlight in a separate pane. The result is a visually intuitive tool that helps traders identify consolidation, building momentum, confirmed trends, and rare explosive moves with high-probability filtering.
### Why It's Good and Different from Standard Indicators
This indicator stands out by addressing common limitations of traditional Bollinger Bands and multi-deviation scripts:
- **Layered statistical significance**: Unlike single (2σ) or basic double-band setups, it provides three distinct levels—early momentum (1σ), standard confirmation (2σ), and extreme/rare breakouts (3σ)—making it easier to stage trades progressively rather than relying on one ambiguous cross.
- **Trend-aware visuals**: Bands, basis, and fills change color based on price position relative to a separate trend MA, giving immediate bullish/bearish bias without needing additional indicators.
- **Clean, fixed labels**: Tiny, arrow-pointing labels ("1/2/3 SD Above/Below", "BB Basis") with consistent colors (purple upper, blue lower, yellow basis) provide instant identification
- **Statistical expansion detection**: Uses percentile ranking of band width "bell curve" concept" to identify abnormally high volatility, triggering directional background highlights (green bullish, red bearish) earlier than raw width spikes.
- **Reduced noise and fakeouts**: Tiered breakouts + expansion filter focus alerts on high-probability moves, unlike most BB scripts that flood signals on every touch.
Compared to popular public scripts (e.g., standard Bollinger Bands, Triple BB variants, or separate BBW Percentile tools), this combines everything into one cohesive indicator with superior visual clarity and statistical rigor.
### Key Features
- **Triple customizable bands**: Enable/disable and adjust multipliers for 1σ (early), 2σ (confirmed), 3σ (extreme) deviations.
- **Trend-based dynamic coloring**: Separate editable colors for each band set (bullish/bearish).
- **Layered zone fills**: Colored between bands with transparency, reflecting current trend.
- **Fixed tiny labels**: All left-pointing arrows with purple (upper), blue (lower), yellow (basis) backgrounds for quick reference.
- **Statistical expansion overlay**: with directional background (green/red) during extreme volatility expansions (earlier trigger using 2σ width).
- **Tiered alerts**: Early (Band 1), Confirmed (Band 2), Extreme (Band 3), High-Probability (Extreme + expansion), and general expansion alerts.
- **Fully configurable basis**: Length, type (SMA/EMA/WMA/RMA), and thin fixed lines for minimal clutter.
### How Traders Can Use It
- **Spot squeezes and breakouts**: Watch for tight bands (low width) → expansion background → price closing outside Band 1 (early entry), Band 2 (add/confirm), Band 3 (strong trend conviction).
- **Filter fakeouts**: Only act on crosses accompanied by expansion background color matching trend direction—dramatically reduces whipsaws.
- **Trend riding**: Price "walking" colored bands (e.g., hugging upper purple-label bands in green background = strong bullish momentum).
- **Scalping/intraday**: On lower timeframes (e.g., 10min), use early Band 1 signals with expansion for quick moves.
- **Swing/position trading**: Wait for Band 3 extreme breakout + colored background for higher-probability, larger moves.
- **Risk management**: Place stops near basis or inner band; trail using outer bands during expansions.
Overall, this indicator excels at turning volatility into actionable, staged signals with visual simplicity—ideal for traders seeking an edge in identifying real explosive trends over noise. It's particularly powerful on volatile stocks like AMD/INTC or indices during news/events.
Adaptive 2-Pole Trend Bands [supfabio]Adaptive 2-Pole Trend Bands is a volatility-aware trend filtering indicator designed to identify the dominant market direction while providing dynamic reference zones around price.
Instead of relying on traditional moving averages, this indicator uses a two-pole digital filter to smooth price action while maintaining responsiveness. Around this central trend line, a multi-band structure based on ATR is applied to help traders evaluate pullbacks, extensions, and potential exhaustion areas within a trend.
Core Concept
The indicator is built around three key ideas:
Digital Trend Filtering
Volatility-Adjusted Bands
Trend Persistence Measurement
These components work together to separate meaningful price movement from noise and to provide context for how far price has moved relative to recent volatility.
Two-Pole Trend Filter
At its core, the indicator uses a two-pole smoothing filter, which produces a cleaner trend curve than common moving averages.
Compared to standard averages, this approach:
Reduces market noise
Produces smoother transitions
Responds faster to genuine trend changes
Avoids excessive lag in trending markets
The result is a trend line that represents the structural direction of price, rather than short-term fluctuations.
Adaptive Multi-Band System
Around the central trend filter, the indicator plots four independent volatility-based bands, each derived from the Average True Range (ATR).
Each band represents a different degree of price extension:
Band 1: Shallow pullbacks and minor reactions
Band 2: Moderate extensions within a trend
Band 3: Strong directional moves
Band 4: Extreme extensions relative to recent volatility
Because the bands are ATR-based, they automatically adapt to changing market conditions, expanding during high volatility and contracting during calmer periods.
This makes the indicator suitable for both slow and fast markets without manual recalibration.
Trend State Detection
The color of the central filter dynamically reflects trend persistence, not just direction:
Sustained upward movement highlights bullish conditions
Sustained downward movement highlights bearish conditions
Transitional phases are visually distinct, helping identify regime changes
This logic is based on how long price has maintained directional behavior, reducing sensitivity to isolated candles or short-lived spikes.
Practical Applications
This indicator can be used as:
A trend filter for discretionary or systematic strategies
A context tool to evaluate pullbacks versus overextension
A risk reference to avoid entries in extreme price zones
A confirmation layer when combined with price action or momentum tools
It performs consistently across different asset classes, including futures, cryptocurrencies, forex, indices, and equities.
Configuration
Key parameters such as filter length, damping factor, and band multipliers are fully configurable, allowing traders to adapt the indicator to different timeframes and trading styles.
Important Notes
This indicator does not predict future price movement
It does not generate guaranteed buy or sell signals
Best results are achieved when used in combination with sound risk management and additional confirmation tools
Past behavior does not imply future performance
Disclaimer
This indicator is provided for educational and analytical purposes only and should not be considered financial advice.
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Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
Macro-Sentiment (Macro_Serie 1:7)Part of a 7-indicator macro series. Combines yield curve dynamics, VIX structure, employment data (jobless claims, NFP), ISM manufacturing, US-Japan carry trade flows, and consumer sentiment into a single adaptive stress score. Color-coded regimes guide strategy from "Aggressive" to "Buy the Crash."
Triple ATR Adaptive MAs + VWAP Option + Clouds + Candle Trend V2Another one of my experiences ... combining things...
📘 Indicator Description – Triple ATR Adaptive Moving Averages with VWAP Influence
This indicator plots three adaptive moving averages whose behavior changes dynamically based on market volatility (ATR) and optionally VWAP deviation.
Because they adapt in real time to both volatility and VWAP pressure, their movement, slope, and reaction speed differ significantly from traditional moving averages.
🔶 1. ATR-Adaptive Moving Averages
Each of the three MAs uses a custom adaptive formula:
ATR (Average True Range) is measured over a chosen period.
Higher ATR → more volatility → the MA becomes more reactive and moves closer to price.
Lower ATR → stable market → the MA becomes smoother and slower.
This creates a volatility-aware smoothing factor, making the MA expand, contract, and respond to market conditions in ways a classic SMA, EMA, or HMA cannot.
🔷 2. Optional VWAP Influence
Each MA has an independent toggle allowing it to be influenced by VWAP.
When enabled:
The MA is gently “pulled” toward VWAP.
The strength of this attraction is determined by the VWAP Influence parameter (0–1).
This causes the moving averages to behave differently from normal MAs:
In trending markets, the ATR and price push the MA away from VWAP.
In mean-reverting or balanced conditions, VWAP pulls the MA back toward fair value.
The result is an MA that reflects both trend pressure and fair-value pressure.
🔶 3. Visual Behavior: Non-Traditional Movement
Because each MA is simultaneously influenced by volatility, trend magnitude, and VWAP deviation, their shape is often very distinct from normal moving averages.
They may:
Respond faster during high volatility
Flatten out earlier during consolidation
Curve toward VWAP when price becomes extended
Separate or compress depending on ATR strength
This is intentional and essential, since the goal is to show:
✔ Volatility expansion
✔ Trend exhaustion
✔ Overextended price relative to VWAP
✔ Dynamic trend confirmation
Rather than simply smoothing past price.
🔷 4. Three Independent Adaptive Lines
Each of the three moving averages has:
Its own ATR length
Its own sensitivity multiplier
Its own optional VWAP influence
Its own color and trail
This allows the user to combine:
a fast volatility-adaptive trend line
a mid-range adaptive baseline
a slow adaptive long-trend MA
All adapting independently to volatility and VWAP conditions.
🔶 5. Optional Candle Coloring
The indicator can color candles according to trend strength derived from the fast/slow MAs.
Stronger trends produce more vivid colors. Neutral or conflicting trends produce softer colors.
This adds a visual layer to identify:
Trend direction
Trend strength
Volatility state
Market compression
at a glance.
📌 Summary
This indicator does not behave like standard SMAs or EMAs because each line dynamically adapts to:
🔸 ATR (volatility)
🔸 VWAP (fair value)
This makes the indicator extremely responsive to market conditions while still reducing noise during stable phases.
It provides a more realistic, context-aware, and intelligent representation of price behavior compared to traditional moving averages.
BTC Dynamic Volatility Trend Backtested from 2017 to present, this strategy has delivered a staggering 7100%+ cumulative return. It doesn't just track the market; it dominates it. By capturing major trends and strictly limiting drawdowns, it has significantly outperformed the standard 'Buy & Hold' BTC strategy, proving its ability to generate massive alpha across multiple bull and bear cycles.
自 2017 年至今，本策略实现了惊人的 7100%+ 累计收益率。它不仅仅是跟随市场，更是超越了市场。通过精准捕捉主升浪并严格控制回撤，该策略在穿越多轮牛熊周期后，大幅度跑赢了比特币‘买入持有’（Buy & Hold）的基准收益，展现了极致的阿尔法（Alpha）捕捉能力。"
Introduction ：Simplicity is the ultimate sophistication. This strategy is designed specifically for Bitcoin (BTC), capturing its unique characteristics: high volatility, frequent fakeouts, and massive trend persistence. It abandons complex indicators in favor of a robust logic: "Follow the Trend, Filter the Noise, Let Profits Run."
Core Logic
Trend Filter (Fibonacci EMA 144): We use the 144-period Exponential Moving Average as the baseline. Longs are only taken above this line, and shorts only below. This keeps you on the right side of the major trend.
Volatility Breakout (Donchian Channel 20): Entries are triggered only when price breaks the 20-day high (for longs) or low (for shorts). This confirms momentum and avoids trading in chop.
Dynamic Risk Management (ATR Chandelier Exit):
Instead of fixed % stops, we use Average True Range (ATR) to calculate stop losses.
The Ratchet Mechanism: The stop loss moves up with the price but never moves down (for longs). This locks in profits automatically as the trend develops and exits immediately when volatility turns against you.
Why Use This Strategy?
Zero Repainting: All signals are confirmed.
No Curve Fitting: Uses classic parameters (144, 20) that have worked for decades.
Mental Peace: The strategy handles the exit. You don't need to guess where to sell. It holds through minor corrections and exits only when the trend truly reverses.
Settings
Leverage %: Adjust your position size based on equity (default 100% = 1x).
Timeframe: Recommended for 4H charts.
中文版 (Chinese Version)
简介 ：大道至简。本策略专为 比特币 (BTC) 设计，针对其高波动、假突破多但趋势爆发力强的特点，摒弃了复杂的过度拟合指标，回归交易本质：“顺大势，滤噪音，截断亏损，让利润奔跑”。
核心逻辑
趋势过滤器 (斐波那契 EMA 144)： 使用 144 周期指数移动平均线作为多空分水岭。价格在均线之上只做多，之下只做空。这能有效过滤掉大部分震荡市的噪音。
波动率突破 (唐奇安通道 20)： 只有当价格突破过去 20 根 K 线的最高价（做多）或最低价（做空）时才进场。这确保了我们只在趋势确立的瞬间入场。
动态风控 (ATR 吊灯止损)：
拒绝固定点数止损，使用 ATR（平均真实波幅）根据市场热度动态计算安全距离。
棘轮机制： 止损线会跟随价格上涨而上移，但绝不会下移（做多时）。这实现了自动化的“利润锁定”，既能扛住正常的波动回调，又能在大势反转时果断离场。
策略优势
绝不重绘： 所有信号均为收盘确认或实时触价。
拒绝拟合： 使用经过数十年市场验证的经典参数组合。
心态管理： 策略全自动管理出场。你不需要纠结何时止盈，它会帮你吃到完整的鱼身，直到趋势结束。
使用建议
资金管理： 可通过参数调整仓位占比（默认 100% = 1倍杠杆）。
推荐周期： 建议在4小时 图表上运行效果最佳。
VV Moving Average Convergence Divergence # VMACDv3 - Volume-Weighted MACD with A/D Divergence Detection
## Overview
**VMACDv3** (Volume-Weighted Moving Average Convergence Divergence Version 3) is a momentum indicator that applies volume-weighting to traditional MACD calculations on price, while using the Accumulation/Distribution (A/D) line for divergence detection. This hybrid approach combines volume-weighted price momentum with volume distribution analysis for comprehensive market insight.
## Key Features
- **Volume-Weighted Price MACD**: Traditional MACD calculation on price but weighted by volume for earlier signals
- **A/D Divergence Detection**: Identifies when A/D trend diverges from MACD momentum
- **Volume Strength Filtering**: Distinguishes high-volume confirmations from low-volume noise
- **Color-Coded Histogram**: 4-color system showing momentum direction and volume strength
- **Real-Time Alerts**: Background colors and alert conditions for bullish/bearish divergences
## Difference from ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|---------|
| **MACD Input** | **Price (Close)** | **A/D Line** |
| **Volume Weighting** | Applied to price | Applied to A/D line |
| **Primary Signal** | Volume-weighted price momentum | Volume distribution momentum |
| **Use Case** | Price momentum with volume confirmation | Volume flow and accumulation/distribution |
| **Sensitivity** | More responsive to price changes | More responsive to volume patterns |
| **Best For** | Trend following, breakouts | Volume analysis, smart money tracking |
**Key Insight**: VMACDv3 shows *where price is going* with volume weight, while ACCDv3 shows *where volume is accumulating/distributing*.
## Components
### 1. Volume-Weighted MACD on Price
Unlike standard MACD that uses simple price EMAs, VMACDv3 weights each price by its corresponding volume:
```
Fast Line = EMA(Price × Volume, 12) / EMA(Volume, 12)
Slow Line = EMA(Price × Volume, 26) / EMA(Volume, 26)
MACD = Fast Line - Slow Line
```
**Benefits of Volume Weighting**:
- High-volume price movements have greater impact
- Filters out low-volume noise and false moves
- Provides earlier trend change signals
- Better reflects institutional activity
### 2. Accumulation/Distribution (A/D) Line
Used for divergence detection, measuring buying/selling pressure:
```
A/D = Σ ((2 × Close - Low - High) / (High - Low)) × Volume
```
- **Rising A/D**: Accumulation (buying pressure)
- **Falling A/D**: Distribution (selling pressure)
- **Doji Handling**: When High = Low, contribution is zero
### 3. Signal Lines
- **MACD Line** (Blue, #2962FF): The fast-slow difference showing momentum
- **Signal Line** (Orange, #FF6D00): EMA or SMA smoothing of MACD
- **Zero Line**: Reference for bullish (above) vs bearish (below) bias
### 4. Histogram Color System
The histogram uses 4 distinct colors based on **direction** and **volume strength**:
| Condition | Color | Meaning |
|-----------|-------|---------|
| Rising + High Volume | **Dark Green** (#1B5E20) | Strong bullish momentum with volume confirmation |
| Rising + Low Volume | **Light Teal** (#26A69A) | Bullish momentum but weak volume (less reliable) |
| Falling + High Volume | **Dark Red** (#B71C1C) | Strong bearish momentum with volume confirmation |
| Falling + Low Volume | **Light Pink** (#FFCDD2) | Bearish momentum but weak volume (less reliable) |
Additional shading:
- **Light Cyan** (#B2DFDB): Positive but not rising (momentum stalling)
- **Bright Red** (#FF5252): Negative and accelerating down
### 5. Divergence Detection
VMACDv3 compares A/D trend against volume-weighted price MACD:
#### Bullish Divergence (Green Background)
- **Condition**: A/D is trending up BUT MACD is negative and trending down
- **Interpretation**: Volume is accumulating while price momentum appears weak
- **Signal**: Smart money accumulation, potential bullish reversal
- **Action**: Look for long entries, especially at support levels
#### Bearish Divergence (Red Background)
- **Condition**: A/D is trending down BUT MACD is positive and trending up
- **Interpretation**: Volume is distributing while price momentum appears strong
- **Signal**: Smart money distribution, potential bearish reversal
- **Action**: Consider exits, avoid new longs, watch for breakdown
## Parameters
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **Source** | Close | OHLC/HLC3/etc | Price source for MACD calculation |
| **Fast Length** | 12 | 1-50 | Period for fast EMA (shorter = more sensitive) |
| **Slow Length** | 26 | 1-100 | Period for slow EMA (longer = smoother) |
| **Signal Smoothing** | 9 | 1-50 | Period for signal line (MACD smoothing) |
| **Signal Line MA Type** | EMA | SMA/EMA | Moving average type for signal calculation |
| **Volume MA Length** | 20 | 5-100 | Period for volume average (strength filter) |
## Usage Guide
### Reading the Indicator
1. **MACD Lines (Blue & Orange)**
- **Blue Line (MACD)**: Volume-weighted price momentum
- **Orange Line (Signal)**: Smoothed trend of MACD
- **Crossovers**: Blue crosses above orange = bullish, below = bearish
- **Distance**: Wider gap = stronger momentum
- **Zero Line Position**: Above = bullish bias, below = bearish bias
2. **Histogram Colors**
- **Dark Green (#1B5E20)**: Strong bullish move with high volume - **most reliable buy signal**
- **Light Teal (#26A69A)**: Bullish but low volume - wait for confirmation
- **Dark Red (#B71C1C)**: Strong bearish move with high volume - **most reliable sell signal**
- **Light Pink (#FFCDD2)**: Bearish but low volume - may be temporary dip
3. **Background Divergence Alerts**
- **Green Background**: A/D accumulating while price weak - potential bottom
- **Red Background**: A/D distributing while price strong - potential top
- Most powerful at key support/resistance levels
### Trading Strategies
#### Strategy 1: Volume-Confirmed Trend Following
1. Wait for MACD to cross above zero line
2. Look for **dark green** histogram bars (high volume confirmation)
3. Enter long on second consecutive dark green bar
4. Hold while histogram remains green
5. Exit when histogram turns light green or red appears
6. Set stop below recent swing low
**Example**:
```
Price: 26,400 → 26,450 (rising)
MACD: -50 → +20 (crosses zero)
Histogram: Light teal → Dark green → Dark green
Volume: 50k → 75k → 90k (increasing)
```
#### Strategy 2: Divergence Reversal Trading
1. Identify divergence background (green = bullish, red = bearish)
2. Confirm with price structure (support/resistance, chart patterns)
3. Wait for MACD to cross signal line in divergence direction
4. Enter on first **dark colored** histogram bar after divergence
5. Set stop beyond divergence area
6. Target previous swing high/low
**Example - Bullish Divergence**:
```
Price: Making lower lows (26,350 → 26,300 → 26,250)
A/D: Rising (accumulation)
MACD: Below zero but starting to curve up
Background: Green shading appears
Entry: MACD crosses signal line + dark green bar
Stop: Below 26,230
Target: 26,450 (previous high)
```
#### Strategy 3: Momentum Scalping
1. Trade only in direction of MACD zero line (above = long, below = short)
2. Enter on dark colored bars only
3. Exit on first light colored bar or opposite color
4. Quick in and out (1-5 minute holds)
5. Tight stops (0.2-0.5% depending on instrument)
#### Strategy 4: Histogram Pattern Trading
**V-Bottom Reversal (Bullish)**:
- Red histogram bars start rising (becoming less negative)
- Forms "V" shape at the bottom
- Transitions to light red → light teal → **dark green**
- Entry: First dark green bar
- Signal: Momentum reversal with volume
**Λ-Top Reversal (Bearish)**:
- Green histogram bars start falling (becoming less positive)
- Forms inverted "V" at the top
- Transitions to light green → light pink → **dark red**
- Entry: First dark red bar
- Signal: Momentum exhaustion with volume
### Multi-Timeframe Analysis
**Recommended Approach**:
1. **Higher Timeframe (15m/1h)**: Identify overall trend direction
2. **Trading Timeframe (5m)**: Time entries using VMACDv3 signals
3. **Lower Timeframe (1m)**: Fine-tune entry prices
**Example Setup**:
```
15-minute: MACD above zero (bullish bias)
5-minute: Dark green histogram appears after pullback
1-minute: Enter on break of recent high with volume
```
### Volume Strength Interpretation
The volume filter compares current volume to 20-period average:
- **Volume > Average**: Dark colors (green/red) - high confidence signals
- **Volume < Average**: Light colors (teal/pink) - lower confidence signals
**Trading Rules**:
- ✓ **Aggressive**: Take all dark colored signals
- ✓ **Conservative**: Only take dark colors that follow 2+ light colors of same type
- ✗ **Avoid**: Trading light colored signals during high volatility
- ✗ **Avoid**: Ignoring volume context during news events
## Technical Details
### Volume-Weighted Calculation
```pine
// Volume-weighted fast EMA
fast_ma = ta.ema(src * volume, fast_length) / ta.ema(volume, fast_length)
// Volume-weighted slow EMA
slow_ma = ta.ema(src * volume, slow_length) / ta.ema(volume, slow_length)
// MACD is the difference
macd = fast_ma - slow_ma
// Signal line smoothing
signal = ta.ema(macd, signal_length) // or ta.sma() if SMA selected
// Histogram
hist = macd - signal
```
### Divergence Detection Logic
```pine
// A/D trending up if above its 5-period SMA
ad_trend = ad > ta.sma(ad, 5)
// MACD trending up if above zero
macd_trend = macd > 0
// Divergence when trends oppose each other
divergence = ad_trend != macd_trend
// Specific conditions for alerts
bullish_divergence = ad_trend and not macd_trend and macd < 0
bearish_divergence = not ad_trend and macd_trend and macd > 0
```
### Histogram Coloring Logic
```pine
hist_color = (hist >= 0
? (hist < hist
? (vol_strength ? #1B5E20 : #26A69A) // Rising: dark/light green
: #B2DFDB) // Positive but falling: cyan
: (hist < hist
? (vol_strength ? #B71C1C : #FFCDD2) // Rising (less negative): dark/light red
: #FF5252)) // Falling more: bright red
```
## Alerts
Built-in alert conditions for divergence detection:
### Bullish Divergence Alert
- **Trigger**: A/D trending up, MACD negative and trending down
- **Message**: "Bullish Divergence: A/D trending up but MACD trending down"
- **Use Case**: Potential reversal or continuation after pullback
- **Action**: Look for long entry setups
### Bearish Divergence Alert
- **Trigger**: A/D trending down, MACD positive and trending up
- **Message**: "Bearish Divergence: A/D trending down but MACD trending up"
- **Use Case**: Potential top or trend reversal
- **Action**: Consider exits or short entries
### Setting Up Alerts
1. Click "Create Alert" in TradingView
2. Condition: Select "VMACDv3"
3. Choose alert type: "Bullish Divergence" or "Bearish Divergence"
4. Configure: Email, SMS, webhook, or popup
5. Set frequency: "Once Per Bar Close" recommended
## Comparison Tables
### VMACDv3 vs Standard MACD
| Feature | Standard MACD | VMACDv3 |
|---------|---------------|---------|
| **Price Weighting** | Equal weight all bars | Volume-weighted |
| **Sensitivity** | Fixed | Adaptive to volume |
| **False Signals** | More during low volume | Fewer (volume filter) |
| **Divergence** | Price vs MACD | A/D vs MACD |
| **Volume Analysis** | None | Built-in |
| **Color System** | 2 colors | 4+ colors |
| **Best For** | Simple trend following | Volume-confirmed trading |
### VMACDv3 vs ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|--------|
| **Focus** | Price momentum | Volume distribution |
| **Reactivity** | Faster to price moves | Faster to volume shifts |
| **Best Markets** | Trending, breakouts | Accumulation/distribution phases |
| **Signal Type** | Where price + volume going | Where smart money positioning |
| **Divergence Meaning** | Volume vs price disagreement | A/D vs momentum disagreement |
| **Use Together?** | ✓ Yes, complementary | ✓ Yes, different perspectives |
## Example Trading Scenarios
### Scenario 1: Strong Bullish Breakout
```
Time: 9:30 AM (market open)
Price: Breaks above 26,400 resistance
MACD: Crosses above zero line
Histogram: Dark green bars (#1B5E20)
Volume: 2x average (150k vs 75k avg)
A/D: Rising (no divergence)
Action: Enter long at 26,405
Stop: 26,380 (below breakout)
Target 1: 26,450 (risk:reward 1:2)
Target 2: 26,500 (risk:reward 1:4)
Result: High probability setup with volume confirmation
```
### Scenario 2: False Breakout (Avoided)
```
Time: 2:30 PM (slow period)
Price: Breaks above 26,400 resistance
MACD: Slightly positive
Histogram: Light teal bars (#26A69A)
Volume: 0.5x average (40k vs 75k avg)
A/D: Flat/declining
Action: Avoid trade
Reason: Low volume, no conviction, potential false breakout
Outcome: Price reverses back below 26,400 within 10 minutes
Saved: Avoided losing trade due to volume filter
```
### Scenario 3: Bullish Divergence Bottom
```
Time: 11:00 AM
Price: Making lower lows (26,350 → 26,300 → 26,280)
MACD: Below zero but curving upward
Histogram: Red bars getting shorter (V-bottom forming)
Background: Green shading (divergence alert)
A/D: Rising despite price falling
Volume: Increasing on down bars
Setup:
1. Divergence appears at 26,280 (green background)
2. Wait for MACD to cross signal line
3. First dark green bar appears at 26,290
4. Enter long: 26,295 (next bar open)
5. Stop: 26,265 (below divergence low)
6. Target: 26,350 (previous swing high)
Result: +55 points (30 point risk, 1.8:1 reward)
Key: Divergence + volume confirmation = high probability reversal
```
### Scenario 4: Bearish Divergence Top
```
Time: 1:45 PM
Price: Making higher highs (26,500 → 26,520 → 26,540)
MACD: Positive but flattening
Histogram: Green bars getting shorter (Λ-top forming)
Background: Red shading (bearish divergence)
A/D: Declining despite rising price
Volume: Decreasing on up bars
Setup:
1. Bearish divergence at 26,540 (red background)
2. MACD crosses below signal line
3. First dark red bar appears at 26,535
4. Enter short: 26,530
5. Stop: 26,555 (above divergence high)
6. Target: 26,475 (support level)
Result: +55 points (25 point risk, 2.2:1 reward)
Key: Distribution while price rising = smart money exiting
```
### Scenario 5: V-Bottom Reversal
```
Downtrend in progress
MACD: Deep below zero (-150)
Histogram: Series of dark red bars
Pattern Development:
Bar 1: Dark red, hist = -80, falling
Bar 2: Dark red, hist = -95, falling
Bar 3: Dark red, hist = -100, falling (extreme)
Bar 4: Light pink, hist = -98, rising!
Bar 5: Light pink, hist = -90, rising
Bar 6: Light teal, hist = -75, rising (crosses to positive momentum)
Bar 7: Dark green, hist = -55, rising + volume
Action: Enter long on Bar 7
Reason: V-bottom confirmed with volume
Stop: Below Bar 3 low
Target: Zero line on histogram (mean reversion)
```
## Best Practices
### Entry Rules
✓ **Wait for dark colors**: High-volume confirmation is key
✓ **Confirm divergences**: Use with price support/resistance
✓ **Trade with zero line**: Long above, short below for best odds
✓ **Multiple timeframes**: Align 1m, 5m, 15m signals
✓ **Watch for patterns**: V-bottoms and Λ-tops are reliable
### Exit Rules
✓ **Partial profits**: Take 50% at first target
✓ **Trail stops**: Use histogram color changes
✓ **Respect signals**: Exit on opposite dark color
✓ **Time stops**: Close positions before major news
✓ **End of day**: Square up before close
### Avoid
✗ **Don't chase light colors**: Low volume = low confidence
✗ **Don't ignore divergence**: Early warning system
✗ **Don't overtrade**: Wait for clear setups
✗ **Don't fight the trend**: Zero line dictates bias
✗ **Don't skip stops**: Always use risk management
## Risk Management
### Position Sizing
- **Dark green/red signals**: 1-2% account risk
- **Light signals**: 0.5% account risk or skip
- **Divergence plays**: 1% account risk (higher uncertainty)
- **Multiple confirmations**: Up to 2% account risk
### Stop Loss Placement
- **Trend trades**: Below/above recent swing (20-30 points typical)
- **Breakout trades**: Below/above breakout level (15-25 points)
- **Divergence trades**: Beyond divergence extreme (25-40 points)
- **Scalp trades**: Tight stops at 10-15 points
### Profit Targets
- **Minimum**: 1.5:1 reward to risk ratio
- **Scalps**: 15-25 points (quick in/out)
- **Swing**: 50-100 points (hold through pullbacks)
- **Runners**: Trail with histogram color changes
## Timeframe Recommendations
| Timeframe | Trading Style | Typical Hold | Advantages | Challenges |
|-----------|---------------|--------------|------------|------------|
| **1-minute** | Scalping | 1-5 minutes | Fast profits, many setups | Noisy, high false signals |
| **5-minute** | Intraday | 15-60 minutes | Balance of speed/clarity | Still requires quick decisions |
| **15-minute** | Swing | 1-4 hours | Clearer trends, less noise | Fewer opportunities |
| **1-hour** | Position | 4-24 hours | Strong signals, less monitoring | Wider stops required |
**Recommendation**: Start with 5-minute for best balance of signal quality and opportunity frequency.
## Combining with Other Indicators
### VMACDv3 + ACCDv3
- **Use**: Confirm volume flow with price momentum
- **Signal**: Both showing dark green = highest conviction long
- **Divergence**: VMACDv3 bullish + ACCDv3 bearish = examine price action
### VMACDv3 + RSI
- **Use**: Overbought/oversold with momentum confirmation
- **Signal**: RSI < 30 + dark green VMACD = strong reversal
- **Caution**: RSI > 70 + light green VMACD = potential false breakout
### VMACDv3 + Elder Impulse
- **Use**: Bar coloring + histogram confirmation
- **Signal**: Green Elder bars + dark green VMACD = aligned momentum
- **Exit**: Blue Elder bars + light colors = momentum stalling
## Limitations
- **Requires volume data**: Will not work on instruments without volume feed
- **Lagging indicator**: MACD inherently follows price (2-3 bar delay)
- **Consolidation noise**: Generates false signals in tight ranges
- **Gap handling**: Large gaps can distort volume-weighted values
- **Not standalone**: Should combine with price action and support/resistance
## Troubleshooting
**Problem**: Too many light colored signals
**Solution**: Increase Volume MA Length to 30-40 for stricter filtering
**Problem**: Missing entries due to waiting for dark colors
**Solution**: Lower Volume MA Length to 10-15 for more signals (accept lower quality)
**Problem**: Divergences not appearing
**Solution**: Verify volume data available; check if A/D line is calculating
**Problem**: Histogram colors not changing
**Solution**: Ensure real-time data feed; refresh indicator
## Version History
- **v3**: Removed traditional MACD, using volume-weighted MACD on price with A/D divergence
- **v2**: Added A/D divergence detection, volume strength filtering, enhanced histogram colors
- **v1**: Basic volume-weighted MACD on price
## Related Indicators
**Companion Tools**:
- **ACCDv3**: Volume-weighted MACD on A/D line (distribution focus)
- **RSIv2**: RSI with A/D divergence detection
- **DMI**: Directional Movement Index with A/D divergence
- **Elder Impulse**: Bar coloring system using volume-weighted MACD
**Use Together**: VMACDv3 (momentum) + ACCDv3 (distribution) + Elder Impulse (bar colors) = complete volume-based trading system
---
*This indicator is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose.*
Open Interest RSI [BackQuant]Open Interest RSI
A multi-venue open interest oscillator that aggregates OI across major derivatives exchanges, converts it to coin or USD terms, and runs an RSI-style engine on that aggregated OI so you can track positioning pressure, crowding, and mean reversion in leverage flows, not just in price.
What this is
This tool is an RSI built on top of aggregated open interest instead of price. It pulls futures OI from several major exchanges, converts it into a unified unit (COIN or USD), sums it into a single synthetic OI candle, then applies RSI and smoothing to that combined series.
You can then render that Open Interest RSI in different visual modes:
Clean line or colored line for classic oscillator-style reads.
Column-style oscillator for impulse and compression views.
Flag mode that fills between OI RSI and its EMA for trend/mean reversion blends. See:
Heatmap mode that paints the panel based on OI RSI extremes, ideal for scanning. See:
On top of that it includes:
Aggregated OI source selection (Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit).
Choice of OI units (COIN or USD).
Reference lines and OB/OS zones.
Extreme highlighting for either trend or mean reversion.
A vertical OI RSI meter that acts as a quick strength gauge.
Aggregated open interest source
Under the hood, the indicator builds a synthetic open interest candle by:
Looping over a list of supported exchanges: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Looping over multiple contract suffixes (such as USDT.P, USD.P, USDC.P, USD.PM) to capture different contract types on each venue.
Requesting OI candles from each venue + contract combination for the same underlying symbol.
Converting each OI stream into a common unit: In COIN mode, everything is normalized into coin-denominated OI. In USD mode, coin OI is multiplied by price to approximate notional OI.
Summing up open, high, low and close of OI across venues into a single aggregated OI candle.
If no valid OI is available for the current symbol across all sources, the script throws a clear runtime error so you know you are on an unsupported market.
This gives you a single, exchange-agnostic open interest curve instead of being tied to one venue. That aggregated OI is then passed into the RSI logic.
How the OI RSI is calculated
The RSI side is straightforward, but it is applied to the aggregated OI close:
Compute a base RSI of aggregated OI using the Calculation Period .
Apply a simple moving average of length Smoothing Period (SMA) to reduce noise in the raw OI RSI.
Optionally apply an EMA on top of the smoothed OI RSI as a moving average signal line.
Key parameters:
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – extra smoothing on the RSI value.
EMA Period – EMA length on the smoothed OI RSI.
The result is:
oi_rsi – raw RSI of aggregated OI.
oi_rsi_s – SMA-smoothed OI RSI.
ma – EMA of the smoothed OI RSI.
Thresholds and extremes
You control three core thresholds:
Mid Point – central reference level, typically 50.
Extreme Upper Threshold – high-level OI RSI edge (for example 80).
Extreme Lower Threshold – low-level OI RSI edge (for example 20).
These thresholds are used for:
Reference lines or OB/OS zone fills.
Heatmap gradient bounds.
Background highlighting of extremes.
The Extreme Highlighting mode controls how extremes are interpreted:
None – do nothing special in extreme regions.
Mean-Rev – background turns red on high OI RSI and green on low OI RSI, framing extremes as contrarian zones.
Trend – background turns green on high OI RSI and red on low OI RSI, framing extremes as participation zones aligned with the prevailing move.
Reference lines and OB/OS zones
You can choose:
None – clean plotting without guides.
Basic Reference Lines – mid, upper and lower thresholds as simple gray horizontals.
OB/OS Levels – filled zones between:
Upper OB: from the upper threshold to 100, colored with the short/overbought color.
Lower OS: from 0 to the lower threshold, colored with the long/oversold color.
These guides help visually anchor the OI RSI within "normal" versus "extreme" regions.
Plotting modes
The Plotting Type input controls how OI RSI is drawn. All modes share the same underlying OI and RSI logic, but emphasise different aspects of the signal.
1) Line mode
This is the classic oscillator representation:
Plots the smoothed OI RSI as a simple line using RSI Line Color and RSI Line Width .
Optionally plots the EMA overlay on the same panel.
Works well when you want standard RSI-style signals on leverage flows: crosses of the midline, divergences versus price, and so on.
2) Colored Line mode
In this mode:
The OI RSI is plotted as a line, but its color is dynamic.
If the smoothed OI RSI is above the mid point, it uses the Long/OB Color .
If it is below the mid point, it uses the Short/OS Color .
This creates an instant visual regime switch between "bullish positioning pressure" and "bearish positioning pressure", while retaining the feel of a traditional RSI line.
3) Oscillator mode
Oscillator mode renders OI RSI as vertical columns around the mid level:
The smoothed OI RSI is plotted as columns using plot.style_columns .
The histogram base is fixed at 50, so bars extend above and below the mid line.
Bar color is dynamic, using long or short colors depending on which side of the mid point the value sits.
This representation makes impulse and compression in OI flows more obvious. It is especially useful when you want to focus on how quickly OI RSI is expanding or contracting around its neutral level. See:
4) Flag mode
Flag mode turns OI RSI and its EMA into a two-line band with a filled area between them:
The smoothed OI RSI and its EMA are both plotted.
A fill is drawn between them.
The fill color flips between the long color and the short color depending on whether OI RSI is above or below its EMA.
Black outlines are added to both lines to make the band clear against any background.
This creates a "flag" style region where:
Green fills show OI RSI leading its EMA, suggesting positive positioning momentum.
Red fills show OI RSI trailing below its EMA, suggesting negative positioning momentum.
Crossovers of the two lines can be read as shifts in OI momentum regime.
Flag mode is useful if you want a more structural view that combines both the level and slope behaviour of OI RSI. See:
5) Heatmap mode
Heatmap mode recasts OI RSI as a single-row gradient instead of a line:
A single row at level 1 is plotted using column style.
The color is pulled from a gradient between the lower and upper thresholds: Near the lower threshold it approaches the short/oversold color and near the upper threshold it approaches the long/overbought color.
The EMA overlay and reference lines are disabled in this mode to keep the panel clean.
This is a very compact way to track OI RSI state at a glance, especially when stacking it alongside other indicators. See:
OI RSI vertical meter
Beyond the main plot, the script can draw a small "thermometer" table showing the current OI RSI position from 0 to 100:
The meter is a two-column table with a configurable number of rows.
Row colors form an inverted gradient: red at the top (100) and green at the bottom (0).
The script clamps OI RSI between 0 and 100 and maps it to a row index.
An arrow marker "▶" is drawn next to the row corresponding to the current OI RSI value.
0 and 100 labels are printed at the ends of the scale for orientation.
You control:
Show OI RSI Meter – turn the meter on or off.
OI RSI Blocks – number of vertical blocks (granularity).
OI RSI Meter Position – panel anchor (top/bottom, left/center/right).
The meter is particularly helpful if you keep the main plot in a small panel but still want an intuitive strength gauge.
How to read it as a market pressure gauge
Because this is an RSI built on aggregated open interest, its extremes and regimes speak to positioning pressure rather than price alone:
High OI RSI (near or above the upper threshold) indicates that open interest has been increasing aggressively relative to its recent history. This often coincides with crowded leverage and a buildup of directional pressure.
Low OI RSI (near or below the lower threshold) indicates aggressive de-leveraging or closing of positions, often associated with flushes, forced unwinds or post-liquidation clean-ups.
Values around the mid point indicate more balanced positioning flows.
You can combine this with price action:
Price up with rising OI RSI suggests fresh leverage joining the move, a more persistent trend.
Price up with falling OI RSI suggests shorts covering or longs taking profit, more fragile upside.
Price down with rising OI RSI suggests aggressive new shorts or levered selling.
Price down with falling OI RSI suggests de-leveraging and potential exhaustion of the move.
Trading applications
Trend confirmation on leverage flows
Use OI RSI to confirm or question a price trend:
In an uptrend, rising OI RSI with values above the mid point indicates supportive leverage flows.
In an uptrend, repeated failures to lift OI RSI above mid point or persistent weakness suggest less committed participation.
In a downtrend, strong OI RSI on the downside points to aggressive shorting.
Mean reversion in positioning
Use thresholds and the Mean-Rev highlight mode:
When OI RSI spends extended time above the upper threshold, the crowd is extended on one side. That can set up squeeze risk in the opposite direction.
When OI RSI has been pinned low, it suggests heavy de-leveraging. Once price stabilises, a re-risking phase is often not far away.
Background colours in Mean-Rev mode help visually identify these periods.
Regime mapping with plotting modes
Different plotting modes give different perspectives:
Heatmap mode for dashboard-style use where you just need to know "hot", "neutral" or "cold" on OI flows at a glance.
Oscillator mode for short term impulses and compression reads around the mid line. See:
Flag mode for blending level and trend of OI RSI into a single banded visual. See:
Settings overview
RSI group
Plotting Type – None, Line, Colored Line, Oscillator, Flag, Heatmap.
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – smoothing on RSI.
Moving Average group
Show EMA – toggle EMA overlay (not used in heatmap).
EMA Period – length of EMA on OI RSI.
EMA Color – colour of EMA line.
Thresholds group
Mid Point – central reference.
Extreme Upper Threshold and Extreme Lower Threshold – OB/OS thresholds.
Select Reference Lines – none, basic lines or OB/OS zone fills.
Extreme Highlighting – None, Mean-Rev, Trend.
Extra Plotting and UI
RSI Line Color and RSI Line Width .
Long/OB Color and Short/OS Color .
Show OI RSI Meter , OI RSI Blocks , OI RSI Meter Position .
Open Interest Source
OI Units – COIN or USD.
Exchange toggles: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Notes
This is a positioning and pressure tool, not a complete system. It:
Models aggregated futures open interest across multiple centralized exchanges.
Transforms that OI into an RSI-style oscillator for better comparability across regimes.
Offers several visual modes to match different workflows, from detailed analysis to compact dashboards.
Use it to understand how leverage and positioning are evolving behind the price, to gauge when the crowd is stretched, and to decide whether to lean with or against that pressure. Attach it to your existing signals, not in place of them.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
Interest Rate ExpectationsThis indicator shows how much rate cuts or hikes are currently priced into SOFR futures. You choose two SOFR contracts and the script converts each contract price into basis points relative to the current effective fed funds rate. This gives you a very clear view of how policy expectations shift over time.
You can switch between using a fixed EFFR value or pulling the live EFFR ticker. Colours for each line and label are fully adjustable. The script also includes an optional grid for the plus or minus 25, 50 and 75 basis point levels so the chart does not zoom out too far.
Labels appear at the end of both lines and display how many basis points of cuts or hikes are priced for each contract. A small reference box is added on the chart to remind you what each quarterly code represents. For example H is March and Z is December.
The background shading highlights changes in the timing of cuts. Green shading means the market is pushing cuts further out in time. Red shading means cuts are being pulled closer. This gives a simple and visual way to track how the curve reprices near term versus long term policy expectations.
This tool is useful for anyone tracking fed path repricing, front end volatility, macro catalysts or cross asset rate sensitivity.
Scalp Boost LONG✦ Overview
Scalp Boost LONG is a visual tool designed to highlight potential short-term upward impulses.
A signal is generated only when multiple market conditions align at the candle close, combining momentum dynamics, local probability shifts, and abnormal volume behavior.
The indicator does not repaint.
✦ Concept
The tool focuses on selective situations where the market shows signs of micro-breakout potential.
If all internal conditions are confirmed — a LONG event is displayed.
If not — the chart remains clean.
This builds a low-noise signal model, prioritizing quality over frequency.
✦ Signal Logic
The LONG signal requires confirmation of all core conditions:
• Local impulse dynamics
Identifies short-term acceleration suggesting a breakout from a compressed price structure.
• Probability beyond a statistical zone
Uses relative breakout probability instead of fixed levels, checking whether price exceeds expected local ranges.
• Abnormal volume activity
Highlights candles with monetary flow above a custom threshold, signaling increased market interest.
• Anti-overheat filter
Conditions avoiding exhausted or low-momentum phases where continuation is less likely.
Only when all filters are aligned a LONG marker appears.
✦ Visual Structure
The chart display is intentionally minimal:
• ROC Curve
Subdued line, showing short-term momentum without distraction.
• LONG Marker
Green triangle below the candle on confirmed events.
• Candle Highlight
Soft background highlight on the signal bar.
• Volume Marker
Small red dot at the bottom of candles with abnormal monetary flow.
All visual elements appear only on candle close.
✦ Alerts
A clean event structure is available for notifications:
LONG Signal
This allows receiving alerts during chart analysis or in automated workflows while keeping full control over decision-making.
✦ Notes & Guidelines
This tool:
is not a trading system,
does not provide targets or stops,
may trigger against the dominant trend,
should be combined with the user’s own methodology.
Signals are rare by design.
Do not interpret each event as a trend continuation — it highlights conditions, not outcomes.
✦ Suggested Use
-(Non-mandatory ideas for advanced users)
-identifying potential micro-breakouts,
-timing entries around volume spikes,
-adding context to scalping models,
-filtering impulsive moves from noise.
-suitable for a 5-minute timeframe
The indicator can be helpful as a confirmation layer, not a standalone decision tool.
BTC STH Proxy vs Realized Price (RP) Ratio | STH : LTH📊 REALIZED PRICE MARKET SIGNAL
Indicator that builds a Short-Term Holder (STH) price proxy using a configurable moving average of Bitcoin’s market price and compares it to Bitcoin’s Realized Price (RP) derived from on-chain data.
Realized Price (RP) is calculated from CoinMetrics Realized Market Cap divided by Glassnode circulating supply.
STH Proxy is a user-defined moving average (EMA/SMA/WMA) of BTC price, designed to mimic the behavior of the true STH Realized Price.
Users can adjust the MA type, length, and RP smoothing to closely replicate the STH curve seen on Glassnode, Bitbo, and Bitcoin Magazine Pro.
Optionally, the indicator can display the STH/RP ratio, which highlights transitions between market phases.
This tool provides a simple but effective way to visualize short-term vs long-term holder cost-basis dynamics using only publicly accessible on-chain aggregates and price data.
----------
💡TLDR: An alt take on the Short-Term Holder Realized Price / Long-Term Holder Realized Price cross model | (STH/LTH cross)
- A mix of MAs are used to mimic STH.
- RP here used as a proxy for the long-term holder (LTH) cost basis.
- Bull/Bear signals are generated when the STH proxy crosses above or below RP.
⭐ Free to use • Leave feedback • Happy trading!
Probability Cone█ Overview:
Probability Cone is based on the Expected Move . While Expected Move only shows the historical value band on every bar, probability panel extend the period in the future and plot a cone or curve shape of the probable range. It plots the range from bar 1 all the way to bar 31.
In this model, we assume asset price follows a log-normal distribution and the log return follows a normal distribution.
Note: Normal distribution is just an assumption; it's not the real distribution of return.
The area of probability range is based on an inverse normal cumulative distribution function. The inverse cumulative distribution gives the range of price for given input probability. People can adjust the range by adjusting the standard deviation in the settings. The probability of the entered standard deviation will be shown at the edges of the probability cone.
The shown 68% and 95% probabilities correspond to the full range between the two blue lines of the cone (68%) and the two purple lines of the cone (95%). The probabilities suggest the % of outcomes or data that are expected to lie within this range. It does not suggest the probability of reaching those price levels.
Note: All these probabilities are based on the normal distribution assumption for returns. It's the estimated probability, not the actual probability.
█ Volatility Models :
Sample SD : traditional sample standard deviation, most commonly used, use (n-1) period to adjust the bias
Parkinson : Uses High/ Low to estimate volatility, assumes continuous no gap, zero mean no drift, 5 times more efficient than Close to Close
Garman Klass : Uses OHLC volatility, zero drift, no jumps, about 7 times more efficient
Yangzhang Garman Klass Extension : Added jump calculation in Garman Klass, has the same value as Garman Klass on markets with no gaps.
about 8 x efficient
Rogers : Uses OHLC, Assume non-zero mean volatility, handles drift, does not handle jump 8 x efficient.
EWMA : Exponentially Weighted Volatility. Weight recently volatility more, more reactive volatility better in taking account of volatility autocorrelation and cluster.
YangZhang : Uses OHLC, combines Rogers and Garmand Klass, handles both drift and jump, 14 times efficient, alpha is the constant to weight rogers volatility to minimize variance.
Median absolute deviation : It's a more direct way of measuring volatility. It measures volatility without using Standard deviation. The MAD used here is adjusted to be an unbiased estimator.
You can learn more about each of the volatility models in out Historical Volatility Estimators indicator.
█ How to use
Volatility Period is the sample size for variance estimation. A longer period makes the estimation range more stable less reactive to recent price. Distribution is more significant on larger sample size. A short period makes the range more responsive to recent price. Might be better for high volatility clusters.
People usually assume the mean of returns to be zero. To be more accurate, we can consider the drift in price from calculating the geometric mean of returns. Drift happens in the long run, so short lookback periods are not recommended.
The shape of the cone will be skewed and have a directional bias when the length of mean is short. It might be more adaptive to the current price or trend, but more accurate estimation should use a longer period for the mean.
Using a short look back for mean will make the cone having a directional bias.
When we are estimating the future range for time > 1, we typically assume constant volatility and the returns to be independent and identically distributed. We scale the volatility in term of time to get future range. However, when there's autocorrelation in returns( when returns are not independent), the assumption fails to take account of this effect. Volatility scaled with autocorrelation is required when returns are not iid. We use an AR(1) model to scale the first-order autocorrelation to adjust the effect. Returns typically don't have significant autocorrelation. Adjustment for autocorrelation is not usually needed. A long length is recommended in Autocorrelation calculation.
Note: The significance of autocorrelation can be checked on an ACF indicator.
ACF
Time back settings shift the estimation period back by the input number. It's the origin of when the probability cone start to estimation it's range.
E.g., When time back = 5, the probability cone start its prediction interval estimation from 5 bars ago. So for time back = 5 , it estimates the probability range from 5 bars ago to X number of bars in the future, specified by the Forecast Period (max 1000).
█ Warnings:
People should not blindly trust the probability. They should be aware of the risk evolves by using the normal distribution assumption. The real return has skewness and high kurtosis. While skewness is not very significant, the high kurtosis should be noticed. The Real returns have much fatter tails than the normal distribution, which also makes the peak higher. This property makes the tail ranges such as range more than 2SD highly underestimate the actual range and the body such as 1 SD slightly overestimate the actual range. For ranges more than 2SD, people shouldn't trust them. They should beware of extreme events in the tails.
The uncertainty in future bars makes the range wider. The overestimate effect of the body is partly neutralized when it's extended to future bars. We encourage people who use this indicator to further investigate the Historical Volatility Estimators , Fast Autocorrelation Estimator , Expected Move and especially the Linear Moments Indicator .
The probability is only for the closing price, not wicks. It only estimates the probability of the price closing at this level, not in between.
Linear Trajectory & Volume StructureThe Linear Trajectory & Volume Structure indicator is a comprehensive trend-following system designed to identify market direction, volatility-adjusted channels, and high-probability entry points. Unlike standard Moving Averages, this tool utilizes Linear Regression logic to calculate the "best fit" trajectory of price, encased within volatility bands (ATR) to filter out market noise.
It integrates three core analytical components into a single interface:
Trend Engine: A Linear Regression Curve to determine the mean trajectory.
Volume Verification: Filters signals to ensure price movement is backed by market participation.
Market Structure: Identifies previous high-volume supply and demand zones for support and resistance analysis.
2. Core Components and Logic
The Trajectory Engine
The backbone of the system is a Linear Regression calculation. This statistical method fits a straight line through recent price data points to determine the current slope and direction.
The Baseline: Represents the "fair value" or mean trajectory of the asset.
The Cloud: Calculated using Average True Range (ATR). It expands during high volatility and contracts during consolidation.
Trend Definition:
Bullish: Price breaks above the Upper Deviation Band.
Bearish: Price breaks below the Lower Deviation Band.
Neutral/Chop: Price remains inside the cloud.
Smart Volume Filter
The indicator includes a toggleable volume filter. When enabled, the script calculates a Simple Moving Average (SMA) of the volume.
High Volume: Current volume is greater than the Volume SMA.
Signal Validation: Reversal signals and structure zones are only generated if High Volume is present, reducing the likelihood of trading false breakouts on low liquidity.
Volume Structure (Smart Liquidity)
The script automatically plots Support (Demand) and Resistance (Supply) boxes based on pivot points.
Creation: A box is drawn only if a pivot high or low is formed with High Volume (if the volume filter is active).
Mitigation: The boxes extend to the right. If price breaks through a zone, the box turns gray to indicate the level has been breached.
3. Signal Guide
Trend Reversals (Buy/Sell Labels)
These are the primary signals indicating a potential change in the macro trend.
BUY Signal: Appears when price closes above the upper volatility band after previously being in a downtrend.
SELL Signal: Appears when price closes below the lower volatility band after previously being in an uptrend.
Pullbacks (Small Circles)
These are continuation signals, useful for adding to positions or entering an existing trend.
Long Pullback: The trend is Bullish, but price dips momentarily below the baseline (into the "discount" area) and closes back above it.
Short Pullback: The trend is Bearish, but price rallies momentarily above the baseline (into the "premium" area) and closes back below it.
4. Configuration and Settings
Trend Engine Settings
Trajectory Length: The lookback period for the Linear Regression. This is the most critical setting for tuning sensitivity.
Channel Multiplier: Controls the width of the cloud.
1.0: Aggressive. Results in narrower bands and earlier signals, but more false positives.
1.5: Balanced (Default).
2.0+: Conservative. Creates a wide channel, filtering out significant noise but delaying entry signals.
Signal Logic
Show Trend Reversals: Toggles the main Buy/Sell labels.
Show Pullbacks: Toggles the re-entry circle signals.
Smart Volume Filter: If checked, signals require above-average volume. Unchecking this yields more signals but removes the volume confirmation requirement.
Volume Structure
Show Smart Liquidity: Toggles the Support/Resistance boxes.
Structure Lookback: Defines how many bars constitute a pivot. Higher numbers identify only major market structures.
Max Active Zones: Limits the number of boxes on the chart to prevent clutter.
5. Timeframe Optimization Guide
To maximize the effectiveness of the Linear Trajectory, you must adjust the Trajectory Length input based on your trading style and timeframe.
Scalping (1-Minute to 5-Minute Charts)
Recommended Length: 20 to 30
Multiplier: 1.2 to 1.5
Logic: Fast-moving markets require a shorter lookback to react quickly to micro-trend changes.
Day Trading (15-Minute to 1-Hour Charts)
Recommended Length: 55 (Default)
Multiplier: 1.5
Logic: A balance between responsiveness and noise filtering. The default setting of 55 is standard for identifying intraday sessions.
Swing Trading (4-Hour to Daily Charts)
Recommended Length: 89 to 100
Multiplier: 1.8 to 2.0
Logic: Swing trading requires filtering out intraday noise. A longer length ensures you stay in the trade during minor retracements.
6. Dashboard (HUD) Interpretation
The Head-Up Display (HUD) provides a summary of the current market state without needing to analyze the chart visually.
Bias: Displays the current trend direction (BULLISH or BEARISH).
Momentum:
ACCELERATING: Price is moving away from the baseline (strong trend).
WEAKENING: Price is compressing toward the baseline (potential consolidation or reversal).
Volume: Indicates if the current candle's volume is HIGH or LOW relative to the average.
Disclaimer
*Trading cryptocurrencies, stocks, forex, and other financial instruments involves a high level of risk and may not be suitable for all investors. This indicator is a technical analysis tool provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profit. Past performance of any trading system or methodology is not necessarily indicative of future results.
IDWM Master StructureExecutive Summary
The IDWM Master Structure is a Multi-Timeframe (MTF) trading tool designed to force discipline by aligning traders with the "Parent" trend. It functions by locking onto the "Completed Auction" of a higher timeframe candle (like a Daily or Weekly bar) and projecting that structure onto your lower timeframe chart. Its primary goal is to define the "Dealing Range"—the hard boundaries where value was previously established—so you don't get lost in the noise of smaller price movements.
1. The Principle of Completed Auctions (Hierarchy)
Most technical indicators curve dynamically with every price tick. This script acts differently because it relies on "Settled Arguments." A closed Daily candle represents a finished battle between buyers and sellers; the High and Low are the historical results of that battle.
To enforce this, the script automatically selects a "Parent" timeframe based on your view:
Scalping (charts below 15 minutes) uses the 4-Hour Auction.
Intraday trading (15 minutes to 4 Hours) uses the Daily Auction.
Swing trading (Daily chart) uses the Weekly Auction.
2. Liquidity Pools & The Sticky Range
The High and Low lines drawn by the indicator are not just support and resistance; they represent Liquidity Pools. In market theory, stop-losses (Sell Stops below Lows, Buy Stops above Highs) accumulate at these edges.
Smart money often pushes price just past these lines to grab this liquidity (a "Stop Hunt") before reversing direction. To account for this, the script uses a "Sticky Range" mechanism. It refuses to redraw the box simply because price touched the line. Instead, it uses an Average True Range (ATR) Buffer. A new structure is only formed if the candle closes decisively outside the range plus this volatility buffer. This ensures you are trading real breakouts, not liquidity sweeps.
3. Internal Range Mechanics (Premium vs. Discount)
Inside the Master Box, the script applies Equilibrium Theory to help with trade location.
The most important internal line is the Equilibrium (EQ), which marks the exact 50% point of the range.
Premium Zone (Above EQ): Price is mathematically "expensive" relative to the recent range. Algorithms generally look to establish Short positions here.
Discount Zone (Below EQ): Price is considered "cheap." Algorithms generally look to establish Long positions here.
It also plots the Master Open, which acts as a "Line in the Sand." If price is currently trading above the Master Open, the higher timeframe candle is Green (Bullish), suggesting longs have a higher probability. If below, the candle is Red (Bearish).
4. Wick Theory (Failed Auctions)
The script places special emphasis on the wicks of the Master Candle because a wick represents a "Failed Auction"—a price level the market tried to explore but ultimately rejected.
The indicator highlights the background of the wick area (from the High to the Body). On a retest, these zones often act as supply or demand blocks because the market remembers the previous failure.
It also calculates the "Consequent Encroachment," which is the 50% midpoint of the wick. The rule of thumb here is that if a candle body can close past 50% of a wick, the rejection is nullified, and price will likely travel to fill the entire wick.
5. Energy Expansion (Breakout Targets)
Market energy transfers from Consolidation (inside the box) to Expansion (the breakout). When the price finally breaks the "Sticky Range" (confirming via the ATR buffer), the script projects where that energy will go.
It uses the height of the previous range to calculate Fibonacci extensions. Specifically, it targets the 1.618 Extension, often called the "Golden Ratio." This is a statistically significant level where expansion moves tend to exhaust themselves and reverse.
6. Safety Protocol: Live Detection
A dashboard monitors the state of the parent candle. If the text turns Magenta with a warning symbol, it means the Higher Timeframe candle is "Live" (still forming).
Trading off a live structure is considered higher risk because the "Auction" isn't finished—the High or Low can still shift. The safest approach is to trade when the dashboard indicates a standard, locked, historical structure.
Long Only EMA Strategy (9/20 with 200 EMA Filter)Details:
This strategy is built around a very simple idea: follow the primary trend and enter only when momentum supports it.
It uses three EMAs on a standard candlestick chart:
1. 9‑period EMA – short‑term momentum
2. 20‑period EMA – medium‑term structure
3. 200‑period EMA – long‑term trend filter
The strategy is ** long‑only ** and is mainly designed for swing trading and positional trading.
It avoids counter‑trend trades by taking entries only when price is trading ** above the 200 EMA **, which is commonly used as a long‑term trend reference.
The rules are deliberately kept simple so that they are easy to understand, modify, and test on different markets and timeframes.
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Key Features
1. **Trend‑Filtered Entries**
- Fresh long positions are considered only when:
- The 9 EMA crosses above the 20 EMA
- The closing price is **above** the 200 EMA
- This attempts to combine short‑term momentum with a higher‑timeframe trend filter.
2. **Clean Exit Logic**
- The long position is exited when the closing price crosses **below** the 20 EMA.
- This creates an objective, rule‑based way to trail the trade as long as the medium‑term structure remains intact.
3. **Long‑Only, No Short Selling**
- The script intentionally ignores short setups.
- This makes it suitable for markets or accounts where short selling is restricted, or for traders who prefer to participate only on the long side of the market.
4. **Simple Visuals**
- All three EMAs are plotted directly on the chart:
- 9 EMA (fast)
- 20 EMA (medium)
- 200 EMA (trend)
- Trade entries and exits are handled by TradingView’s strategy engine, so users can see results in the Strategy Tester as well as directly on the chart.
5. **Backtest‑Friendly Structure**
- Uses TradingView’s built‑in `strategy()` framework.
- Can be applied to different symbols, timeframes, and markets (equities, indices, crypto, etc.).
- Works on standard candlestick charts, which are supported by TradingView’s backtesting engine.
6. **Configurable in Code**
- The EMA periods are defined in the code and can be easily adjusted.
- Users can tailor the parameters to fit their own style (for example, faster EMAs for intraday trading, slower EMAs for positional trades).
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How to Use
1. **Add the Strategy to Your Chart**
1. Open any symbol and select a **standard candlestick chart**.
2. Apply the strategy from your “My Scripts” section.
3. Make sure it is enabled so that the trades and results appear.
2. **Select Timeframe**
- The logic can be tested on various timeframes:
- Higher timeframes (1H, 4H, 1D) for swing and positional setups.
- Lower timeframes (5m, 15m) for more active trading, if desired.
- Users should experiment and see where the strategy behaves more consistently for their chosen market.
3. **Read the Signals**
- **Entry:**
- A long trade is opened when the 9 EMA crosses above the 20 EMA while the closing price is above the 200 EMA.
- **Exit:**
- The open long position is closed when the closing price crosses below the 20 EMA.
- All orders are generated automatically once the strategy is attached to the chart.
4. **Use the Strategy Tester**
- Go to the **Strategy Tester** tab in TradingView.
- Check:
- Net profit / drawdown
- Win rate and average trade
- List of trades and the equity curve
- Change the date range and timeframe to see how stable the results are over different periods.
5. **Adjust Parameters if Needed**
- Advanced users can open the code and experiment with:
- EMA lengths (for example 8/21 with 200, or 10/30 with 200)
- Risk sizing and capital settings within the `strategy()` call
- Any changes should be thoroughly re‑tested before considering real‑world application.
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Practical Applications
1. **Swing Trading on Daily Charts**
- Can be applied to stocks, indices, or ETFs on the daily timeframe.
- The 200 EMA acts as a trend filter to stay aligned with the broad direction, while the 9/20 crossover helps catch medium‑term swings inside that trend.
2. **Positional Trades on Higher Timeframes**
- On 4H or 1D charts, this approach can help in holding trades for several days to weeks.
- The exit rule based on the 20 EMA crossing helps avoid emotional decisions and provides a rules‑based way to trail the trend.
3. **Trend‑Following Filter**
- Even if used purely as a filter, the 200 EMA condition can help traders:
- Avoid taking long trades when the market is in a clear downtrend.
- Focus only on instruments that are trading above their long‑term average.
4. **Educational Use**
- The script is intentionally kept straightforward so that newer users can:
- Learn how a moving average crossover strategy works.
- See how to combine a short‑term signal with a long‑term filter.
- Understand how TradingView’s strategy engine handles entries and exits.
5. **Basis for Further Development**
- This can serve as a starting point for more advanced systems.
- Traders can extend it by adding:
- Additional filters (RSI, volume, volatility filters, time‑of‑day filters, etc.)
- Risk management rules (fixed stop loss, take profit, trailing stops).
- The current version is kept minimal on purpose, so modifications are easy to implement and test.
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Important Notes & Disclaimer
1. This strategy is provided **for testing, research, and educational purposes only**.
2. It is ** not ** a recommendation to buy or sell any financial instrument.
3. Past performance on historical data does not guarantee similar results in live markets.
4. Markets are risky and trading can lead to financial loss; users should always do their own research, manage risk appropriately, and consult a qualified financial professional if needed.
5. Before using any strategy with real capital, it is strongly advised to:
- Forward test it on a demo / paper trading account.
- Check how it behaves during different market phases (trending, sideways, high‑volatility conditions).
You are free to modify the parameters and logic to better align it with your own trading style and risk tolerance.
Équilibre du Sentiment – Multi-Périodes (v6)
English
A unique and advanced sentiment indicator based on the harmonic mean of highs and lows over nested rolling windows.
How it works:
The neutral sentiment point is reached when positive sentiment equals negative sentiment, which corresponds to the situation where the percentage between the price and the minimum is equal to the percentage between the maximum and the price.
For each chosen period N, the script calculates N different "neutral feeling" values:
- One using the last 1 bar
- One using the last 2 bars
- …
- One using the last N bars
It then extracts the exact median of these N values using a sorted insertion method (no approximation).
This produces an extremely smooth, non-repainting equilibrium line that represents the true "central sentiment" of the market over the selected lookback.
Features:
- Up to 3 independent periods (365, 52, 26 by default – fully customizable)
- Optional background coloring (green/red) when price is above/below the main curve
- Clean labels on the last bar showing the current value for each active period
- Zero repainting – fully compatible with strategies and alerts
- Highly responsive even with very long periods (up to 3500 bars)
Great for:
- Identifying long-term fair value / equilibrium zones
- Building mean-reversion or breakout systems
Pure Pine Script® v6 – no external libraries, no security calls, no repainting-free.
