Volume-Gated Trend Ribbon [QuantAlgo]🟢 Overview
The Volume-Gated Trend Ribbon employs a selective price-updating mechanism that filters market noise through volume validation, creating a trend-following system that responds exclusively to significant price movements. The indicator gates price updates to moving average calculations based on volume threshold crossovers, ensuring that only bars with significant participation influence the trend direction. By interpolating between fast and slow moving averages to create a multi-layered visual ribbon, the indicator provides traders and investors with an adaptive trend identification framework that distinguishes between volume-backed directional shifts and low-conviction price fluctuations across multiple timeframes and asset classes.
🟢 How It Works
The indicator first establishes a dynamic baseline by calculating the simple moving average of volume over a configurable lookback period, then applies a user-defined multiplier to determine the significance threshold:
avgVol = ta.sma(volume, volPeriod)
highVol = volume >= avgVol * volMult
The gated price mechanism employs conditional updating where the close price is only captured and stored when volume exceeds the threshold. During low-volume periods, the indicator maintains the last qualified price level rather than tracking every minor fluctuation:
var float gatedClose = close
if highVol
gatedClose := close
Dual moving averages are calculated using the gated price input, with the indicator supporting various MA types. The fast and slow periods create the outer boundaries of the trend ribbon:
fastMA = volMA(gatedClose, close, fastPeriod)
slowMA = volMA(gatedClose, close, slowPeriod)
Ribbon interpolation creates intermediate layers by blending the fast and slow moving averages using weighted combinations, establishing a gradient effect that visually represents trend strength and momentum distribution:
midFastMA = fastMA * 0.67 + slowMA * 0.33
midSlowMA = fastMA * 0.33 + slowMA * 0.67
Trend state determination compares the fast MA against the slow MA, establishing bullish regimes when the faster average trades above the slower average and bearish regimes during the inverse relationship. Signal generation triggers on state transitions, producing alerts when the directional bias shifts:
bullish = fastMA > slowMA
longSignal = trendState == 1 and trendState != 1
shortSignal = trendState == -1 and trendState != -1
The visualization architecture constructs a three-tiered opacity gradient where the ribbon's core (between mid-slow and slow MAs) displays the highest opacity, the inner layer (between mid-fast and mid-slow) shows medium opacity, and the outer layer (between fast and mid-fast) presents the lightest fill, creating depth perception that emphasizes the trend center while acknowledging edge uncertainty.
🟢 How to Use This Indicator
▶ Long and Short Signals: The indicator generates long/buy signals when the trend state transitions to bullish (fast MA crosses above slow MA) and short/sell signals when transitioning to bearish (fast MA crosses below slow MA). Because these crossovers only reflect volume-validated price movements, they represent significant level of participation rather than random noise, providing higher-conviction entry signals that filter out false breakouts occurring on thin volume.
▶ Ribbon Width Dynamics: The spacing between the fast and slow moving averages creates the ribbon width, which serves as a visual proxy for trend strength and volatility. Expanding ribbons indicate accelerating directional movement with increasing separation between short-term and long-term momentum, suggesting robust trend development. Conversely, contracting ribbons signal momentum deceleration, potential trend exhaustion, or impending consolidation as the fast MA converges toward the slow MA.
▶ Preconfigured Presets: Three optimized parameter sets accommodate different trading styles and market conditions. Default provides balanced trend identification suitable for swing trading on daily timeframes with moderate volume filtering and responsiveness. Fast Response delivers aggressive signal generation optimized for intraday scalping on 1-15 minute charts, using lower volume thresholds and shorter moving average periods to capture rapid momentum shifts. Smooth Trend offers conservative trend confirmation ideal for position trading on 4-hour to weekly charts, employing stricter volume requirements and extended periods to filter noise and identify only the most robust directional moves.
▶ Built-in Alerts: Three alert conditions enable automated monitoring: Bullish Trend Signal triggers when the fast MA crosses above the slow MA confirming uptrend initiation, Bearish Trend Signal activates when the fast MA crosses below the slow MA confirming downtrend initiation, and Trend Change alerts on any directional transition regardless of direction. These notifications allow you to respond to volume-validated regime shifts without continuous chart monitoring.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and display preferences, ensuring optimal contrast and visual clarity across trading environments. The adjustable fill opacity control (0-100%) allows fine-tuning of ribbon prominence, with lower opacity values create subtle background context while higher values produce bold trend emphasis. Optional bar coloring extends the trend indication directly to the price bars, providing immediate directional reference without requiring visual cross-reference to the ribbon itself.
Volatility
PMax - Asymmetric MultipliersDescription: This script is an enhanced version of the popular PMax (Profit Maximizer) indicator, originally developed by KivancOzbilgic. It has been converted into a full strategy with advanced customization options for backtesting and trend following.
Key Features & Modifications:
Asymmetric ATR Multipliers: Unlike the standard version, this script allows you to set different ATR multipliers for Upper (Short/Resistance) and Lower (Long/Support) bands.
Default Upper: 1.5 (Tighter trailing for Short positions)
Default Lower: 3.0 (Wider trailing for Long positions to avoid whipsaws)
Expanded MA Types: Added HULL (HMA) and VAR (Variable Index Dynamic Average) options.
VAR is highly recommended for filtering out noise in ranging markets.
HULL is ideal for scalping and faster reactions.
Built-in Risk Management: A fixed 5% Stop Loss mechanism is integrated into the strategy. It protects your capital by closing positions if the price moves 5% against you, even if the trend hasn't reversed yet.
Visibility Fix: Solved the issue where the PMax line would disappear or start at zero in the initial bars.
How to Use:
Use the VAR MA type for trend following in volatile markets.
Adjust the "Stop Loss Percent" input to fit your risk appetite.
The strategy employs an "Always In" logic (Long/Short) but respects the hard Stop Loss.
Credits: Original PMax logic by KivancOzbilgic.
VEGA (Velocity of Efficient Gain Adaptation)VEGA (Velocity of Efficient Gain Adaptation)
VEGA is a momentum oscillator that measures the velocity of an efficiency-weighted adaptive moving average. Unlike traditional momentum indicators that react uniformly to all price movements, VEGA intelligently adapts its sensitivity based on market conditions—responding quickly during trending periods and filtering noise during consolidation.
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What Makes VEGA Different
Efficiency-Driven Adaptation
At its core, VEGA uses the Efficiency Ratio (ER) to distinguish between trending and choppy markets. When price moves efficiently in one direction, VEGA's underlying adaptive MA speeds up to capture the move. When price chops sideways, it slows down to avoid whipsaws. This creates a momentum reading that's inherently cleaner than fixed-period alternatives.
Linear Regression Smoothed Source
VEGA offers an optional LinReg-smoothed price source that blends regular candles with linear regression values. This pre-smoothing reduces noise before it ever enters the calculation, resulting in a histogram that's easier to read without sacrificing responsiveness. The mix ratio lets you dial in exactly how much smoothing you want.
Z-Score Normalization with Dead Zone
Rather than arbitrary oscillator bounds, VEGA normalizes output as standard deviations from the mean. This gives statistically meaningful levels: readings above +2σ or below -2σ represent genuinely extreme momentum. The configurable dead zone (with Snap, Soft Fade, or None modes) filters out insignificant movements near zero, keeping you focused on signals that matter.
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How It Works
1. Source Preparation — Price is smoothed via a LinReg/regular candle blend
2. Efficiency Ratio — Measures directional movement vs total movement over the lookback period
3. Adaptive MA — Applies variable smoothing based on efficiency (fast during trends, slow during chop)
4. Velocity — Calculates the rate of change of the adaptive MA
5. Normalization — Converts to Z-Score (standard deviations) or ATR-normalized percentage
6. Dead Zone — Optionally filters near-zero values to reduce noise
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How To Read VEGA
Signal and Interpretation
Histogram above zero | Bullish momentum
Histogram below zero | Bearish momentum
Bright color | Momentum accelerating
Faded color | Momentum decelerating
Beyond ±1σ bands | Above-average momentum
Beyond ±2σ bands | Extreme momentum (potential reversal zone)
Zero line cross*| Momentum shift
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Key Settings
ER Length — Lookback for efficiency ratio calculation. Higher = smoother, slower adaptation.
Fast/Slow Smoothing — Controls the adaptive MA's responsiveness range. The MA blends between these based on efficiency.
LinReg Settings — Enable smoothed candles and adjust the blend ratio (0 = regular candles, 1 = full LinReg, 0.5 = 50/50 mix).
Z-Score Lookback — Period for calculating mean and standard deviation. Shorter = more reactive normalization.
Dead Zone Type — How to handle near-zero values:
Snap — Hard cutoff to zero
Soft Fade — Gradual reduction toward zero
None — No filtering
Dead Zone Threshold — Values within this Z-Score range are affected by the dead zone setting.
VEGA works on any timeframe and any market. For best results, adjust the ER Length and LinReg settings to match your trading style and the volatility characteristics of your instrument.
Volatility Targeting: Single Asset [BackQuant]Volatility Targeting: Single Asset
An educational example that demonstrates how volatility targeting can scale exposure up or down on one symbol, then applies a simple EMA cross for long or short direction and a higher timeframe style regime filter to gate risk. It builds a synthetic equity curve and compares it to buy and hold and a benchmark.
Important disclaimer
This script is a concept and education example only . It is not a complete trading system and it is not meant for live execution. It does not model many real world constraints, and its equity curve is only a simplified simulation. If you want to trade any idea like this, you need a proper strategy() implementation, realistic execution assumptions, and robust backtesting with out of sample validation.
Single asset vs the full portfolio concept
This indicator is the single asset, long short version of the broader volatility targeted momentum portfolio concept. The original multi asset concept and full portfolio implementation is here:
That portfolio script is about allocating across multiple assets with a portfolio view. This script is intentionally simpler and focuses on one symbol so you can clearly see how volatility targeting behaves, how the scaling interacts with trend direction, and what an equity curve comparison looks like.
What this indicator is trying to demonstrate
Volatility targeting is a risk scaling framework. The core idea is simple:
If realized volatility is low relative to a target, you can scale position size up so the strategy behaves like it has a stable risk budget.
If realized volatility is high relative to a target, you scale down to avoid getting blown around by the market.
Instead of always being 1x long or 1x short, exposure becomes dynamic. This is often used in risk parity style systems, trend following overlays, and volatility controlled products.
This script combines that risk scaling with a simple trend direction model:
Fast and slow EMA cross determines whether the strategy is long or short.
A second, longer EMA cross acts as a regime filter that decides whether the system is ACTIVE or effectively in CASH.
An equity curve is built from the scaled returns so you can visualize how the framework behaves across regimes.
How the logic works step by step
1) Returns and simple momentum
The script uses log returns for the base return stream:
ret = log(price / price )
It also computes a simple momentum value:
mom = price / price - 1
In this version, momentum is mainly informational since the directional signal is the EMA cross. The lookback input is shared with volatility estimation to keep the concept compact.
2) Realized volatility estimation
Realized volatility is estimated as the standard deviation of returns over the lookback window, then annualized:
vol = stdev(ret, lookback) * sqrt(tradingdays)
The Trading Days/Year input controls annualization:
252 is typical for traditional markets.
365 is typical for crypto since it trades daily.
3) Volatility targeting multiplier
Once realized vol is estimated, the script computes a scaling factor that tries to push realized volatility toward the target:
volMult = targetVol / vol
This is then clamped into a reasonable range:
Minimum 0.1 so exposure never goes to zero just because vol spikes.
Maximum 5.0 so exposure is not allowed to lever infinitely during ultra low volatility periods.
This clamp is one of the most important “sanity rails” in any volatility targeted system. Without it, very low volatility regimes can create unrealistic leverage.
4) Scaled return stream
The per bar return used for the equity curve is the raw return multiplied by the volatility multiplier:
sr = ret * volMult
Think of this as the return you would have earned if you scaled exposure to match the volatility budget.
5) Long short direction via EMA cross
Direction is determined by a fast and slow EMA cross on price:
If fast EMA is above slow EMA, direction is long.
If fast EMA is below slow EMA, direction is short.
This produces dir as either +1 or -1. The scaled return stream is then signed by direction:
avgRet = dir * sr
So the strategy return is volatility targeted and directionally flipped depending on trend.
6) Regime filter: ACTIVE vs CASH
A second EMA pair acts as a top level regime filter:
If fast regime EMA is above slow regime EMA, the system is ACTIVE.
If fast regime EMA is below slow regime EMA, the system is considered CASH, meaning it does not compound equity.
This is designed to reduce participation in long bear phases or low quality environments, depending on how you set the regime lengths. By default it is a classic 50 and 200 EMA cross structure.
Important detail, the script applies regime_filter when compounding equity, meaning it uses the prior bar regime state to avoid ambiguous same bar updates.
7) Equity curve construction
The script builds a synthetic equity curve starting from Initial Capital after Start Date . Each bar:
If regime was ACTIVE on the previous bar, equity compounds by (1 + netRet).
If regime was CASH, equity stays flat.
Fees are modeled very simply as a per bar penalty on returns:
netRet = avgRet - (fee_rate * avgRet)
This is not realistic execution modeling, it is just a simple turnover penalty knob to show how friction can reduce compounded performance. Real backtesting should model trade based costs, spreads, funding, and slippage.
Benchmark and buy and hold comparison
The script pulls a benchmark symbol via request.security and builds a buy and hold equity curve starting from the same date and initial capital. The buy and hold curve is based on benchmark price appreciation, not the strategy’s asset price, so you can compare:
Strategy equity on the chart symbol.
Buy and hold equity for the selected benchmark instrument.
By default the benchmark is TVC:SPX, but you can set it to anything, for crypto you might set it to BTC, or a sector index, or a dominance proxy depending on your study.
What it plots
If enabled, the indicator plots:
Strategy Equity as a line, colored by recent direction of equity change, using Positive Equity Color and Negative Equity Color .
Buy and Hold Equity for the chosen benchmark as a line.
Optional labels that tag each curve on the right side of the chart.
This makes it easy to visually see when volatility targeting and regime gating change the shape of the equity curve relative to a simple passive hold.
Metrics table explained
If Show Metrics Table is enabled, a table is built and populated with common performance statistics based on the simulated daily returns of the strategy equity curve after the start date. These include:
Net Profit (%) total return relative to initial capital.
Max DD (%) maximum drawdown computed from equity peaks, stored over time.
Win Rate percent of positive return bars.
Annual Mean Returns (% p/y) mean daily return annualized.
Annual Stdev Returns (% p/y) volatility of daily returns annualized.
Variance of annualized returns.
Sortino Ratio annualized return divided by downside deviation, using negative return stdev.
Sharpe Ratio risk adjusted return using the risk free rate input.
Omega Ratio positive return sum divided by negative return sum.
Gain to Pain total return sum divided by absolute loss sum.
CAGR (% p/y) compounded annual growth rate based on time since start date.
Portfolio Alpha (% p/y) alpha versus benchmark using beta and the benchmark mean.
Portfolio Beta covariance of strategy returns with benchmark returns divided by benchmark variance.
Skewness of Returns actually the script computes a conditional value based on the lower 5 percent tail of returns, so it behaves more like a simple CVaR style tail loss estimate than classic skewness.
Important note, these are calculated from the synthetic equity stream in an indicator context. They are useful for concept exploration, but they are not a substitute for professional backtesting where trade timing, fills, funding, and leverage constraints are accurately represented.
How to interpret the system conceptually
Vol targeting effect
When volatility rises, volMult falls, so the strategy de risks and the equity curve typically becomes smoother. When volatility compresses, volMult rises, so the system takes more exposure and tries to maintain a stable risk budget.
This is why volatility targeting is often used as a “risk equalizer”, it can reduce the “biggest drawdowns happen only because vol expanded” problem, at the cost of potentially under participating in explosive upside if volatility rises during a trend.
Long short directional effect
Because direction is an EMA cross:
In strong trends, the direction stays stable and the scaled return stream compounds in that trend direction.
In choppy ranges, the EMA cross can flip and create whipsaws, which is where fees and regime filtering matter most.
Regime filter effect
The 50 and 200 style filter tries to:
Keep the system active in sustained up regimes.
Reduce exposure during long down regimes or extended weakness.
It will always be late at turning points, by design. It is a slow filter meant to reduce deep participation, not to catch bottoms.
Common applications
This script is mainly for understanding and research, but conceptually, volatility targeting overlays are used for:
Risk budgeting normalize risk so your exposure is not accidentally huge in high vol regimes.
System comparison see how a simple trend model behaves with and without vol scaling.
Parameter exploration test how target volatility, lookback length, and regime lengths change the shape of equity and drawdowns.
Framework building as a reference blueprint before implementing a proper strategy() version with trade based execution logic.
Tuning guidance
Lookback lower values react faster to vol shifts but can create unstable scaling, higher values smooth scaling but react slower to regime changes.
Target volatility higher targets increase exposure and drawdown potential, lower targets reduce exposure and usually lower drawdowns, but can under perform in strong trends.
Signal EMAs tighter EMAs increase trade frequency, wider EMAs reduce churn but react slower.
Regime EMAs slower regime filters reduce false toggles but will miss early trend transitions.
Fees if you crank this up you will see how sensitive higher turnover parameter sets are to friction.
Final note
This is a compact educational demonstration of a volatility targeted, long short single asset framework with a regime gate and a synthetic equity curve. If you want a production ready implementation, the correct next step is to convert this concept into a strategy() script, add realistic execution and cost modeling, test across multiple timeframes and market regimes, and validate out of sample before making any decision based on the results.
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.
Trinity Real Move Detector DashboardRelease Notes (critical)
1. This code "will" require tweaks for different timeframes to the multiplier, do not assume the data in the table is accurate, cross check it with the Trinity Real Move Detector or another ATR tool, to validate the values in the table and ensure you have set the correct values.
2. I mention this below. But please understand that pine code has a limitation in the number of security calls (40 request.security() calls per script). This code is on the limit of that threshold and I would encourage developers to see if they can find a way around this to improve the script and release further updates.
What do we have...
The Trinity Real Move Detector Dashboard is a powerful TradingView indicator designed to scan multiple assets at once and show when each one has genuine short-term volatility "energy" — the kind that makes directional options trades (especially 0DTE or short-dated) have a high probability of follow-through, and can be used for swing trading as well. It combines a simple ATR-based volatility filter with a SuperTrend-style bias to tell you not only if the market is "awake" but also in which direction the momentum is leaning.
At its core, the indicator calculates the current ATR on your chosen timeframe and compares it to a user-defined percentage of the asset's daily ATR. When the short-term ATR spikes above that threshold, it signals "enough energy" — meaning the underlying is moving with real force rather than choppy noise. The SuperTrend logic then determines bullish or bearish bias, so the status shows "BULLISH ENERGY" (green) or "BEARISH ENERGY" (red) when energy is on, or "WAIT" when it's not. It also counts how many bars the energy has been active and shows the current ATR vs threshold for quick visual confirmation.
The dashboard displays all this in a clean table with columns for Symbol, Multiplier, Current ATR, Threshold, Status, Bars Active, and Bias (UP/DOWN). It's perfect for 3-minute charts but works on any timeframe — just adjust the multiplier based on the hints in the settings.
Editing symbols and multipliers is straightforward and user-friendly. In the indicator settings, you'll see numbered inputs like "1. Symbol - NVDA" and "1. Multiplier". To change an asset, simply type the new ticker in the symbol field (e.g., replace "NVDA" with "TSLA", "AVGO", or "ADAUSD"). You can also adjust the multiplier for each asset individually in the corresponding "Multiplier" field to make it more or less sensitive — lower numbers give more signals, higher numbers give stricter, higher-quality ones. This lets you customize the dashboard to your watchlist without any coding. For example, if you switch to a 4-hour chart or a slower-moving stock like AVGO, you may need to raise the multiplier (e.g., to 0.3–0.4) to avoid false "bullish" signals during minor bounces in a larger downtrend.
One important note about the multiplier and timeframes: the default values are optimized for fast intraday charts (like 3-minute or 5-minute). On higher timeframes (15-minute, 1-hour, 4-hour, or daily), the SuperTrend bias can be too sensitive with low multipliers (1.0 default in the code), leading to situations like the AVGO 4-hour example — where price is clearly downtrending, but the dashboard shows "BULLISH ENERGY" because the tight bands flip on small bounces. To fix this, you need to manually increase the multiplier for that asset (or all assets) in the settings. For 4-hour or daily charts, 0.25–0.35 is often better to match smoother SuperTrend indicators like Trinity. Always test on your timeframe and asset — crypto usually needs slightly lower multipliers than stocks due to higher volatility.
TradingView has a hard limit of 40 request.security() calls per script. Each asset in the dashboard requires several calls (current ATR, daily ATR, SuperTrend components, etc.), so with the full ATR-based bias, you can safely monitor about 6–8 assets before hitting the limit. Adding more symbols increases the number of calls and will trigger the "too many securities" error. This is a platform restriction to prevent excessive server load, and there's no official way around it in a single script. Some advanced coders use tricks like caching or lower-timeframe requests to squeeze in a few more, but for reliability, sticking to 6–8 assets is recommended. If you need more, the common workaround is to create two separate indicators (e.g., one for stocks, one for crypto) and add both to the same chart.
Overall, this dashboard gives you a professional-grade multi-asset scanner that filters out low-energy noise and highlights real momentum opportunities across stocks and crypto — all in one glance. It's especially valuable for options traders who want to avoid theta decay on weak moves and only strike when the market has true fuel. By tweaking the per-symbol multipliers in the settings, you can perfectly adapt it to any timeframe or asset behavior, avoiding issues like the AVGO false bullish signal on higher timeframes.
ATR Trailing StopATR Trailing Stop (Dynamic Volatility Regimes)
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This indicator implements an adaptive ATR-based trailing stop for long positions. The stop automatically adjusts based on stock volatility, tightening during fast movements and widening during calm periods. It is designed as a trade management tool to help protect profits while staying aligned with strong trends.
How It Works
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* Tracks the highest high over a configurable lookback window and ensures this “top” never moves downward.
* Computes the trailing stop as:**Top – ATR × Dynamic Multiplier**
* The ATR multiplier changes depending on volatility:
* Low volatility → Wide stop (slower trailing)
* Medium volatility → Standard trailing
* High volatility → Tight stop (faster trailing)
* The trailing stop only moves upward; it never decreases.
* If price falls significantly below the stop (default: 5%), the system resets and begins trailing from a new top.
* An optional price-scale label displays:
* Current stop value
* Volatility regime (LOW / MID / HIGH)
* ATR percentage and active multiplier
Alerts
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Two alert conditions are included:
### Trailing Stop – Near
Triggers when price moves within a user-defined percentage above the stop.
### Trailing Stop – Hit
Triggers when price touches or closes below the stop.
How to Use
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1. Add the indicator to any chart (daily timeframe recommended).
2. Configure:
* ATR length
* Lookback bars
* Volatility thresholds
* ATR multipliers
3. Set alerts for early warnings or stop-hit events.
4. Use the stop line as a dynamic risk-management tool to guide exit decisions and protect profits.
Notes
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* Designed for long-only trailing logic.
* This indicator does not generate entry signals; it is intended for stop management.
Golden Volume Lines📌 Golden Volume — Lines (Golden Team)
Golden Volume — Lines is an advanced volume-based indicator that detects Ultra High Volume candles using a statistical percentile model, then automatically draws and tracks key price levels derived from those candles.
The indicator highlights where real market interest and liquidity appear and shows how price reacts when those levels are broken.
🔍 How It Works
Volume Measurement
Choose between:
Units (raw volume)
Money (Volume × Average Price)
Average price can be calculated using HL2 or OHLC4.
Percentile-Based Classification
Volume is classified into:
Medium
High
Ultra High Volume
Thresholds are calculated using a rolling percentile window.
Ultra Volume candles are colored orange.
Dynamic High & Low Levels
For every Ultra Volume candle:
A High and Low dotted line is drawn.
Lines extend to the right until price breaks them.
Smart Line Break Detection (Wick-Based)
A line is considered broken when price wicks through it.
When a break occurs:
🟧 Orange line → broken by an Ultra Volume candle
⚪ White line → broken by a normal candle
The line stops exactly at the breaking candle.
🔔 Alerts
Alert on Ultra High Volume candles
Alert when a High or Low line is broken
Separate alerts for:
Break by Ultra Volume candle
Break by Normal candle
🎯 Use Cases
Breakout & continuation confirmation
Liquidity sweep detection
Volume-validated support & resistance
Market reaction after extreme participation
⚙️ Key Inputs
Volume display mode (Units / Money)
Percentile thresholds
Lookback window size
Maximum number of active Ultra levels
Optional dynamic alerts
⚠️ Disclaimer
This indicator is a volume and market structure tool, not a standalone trading system.
Always use proper risk management and additional confirmation.
Relative Volume Bollinger Band %
The Relative Volume Bollinger Band % indicator is a powerful tool designed for traders seeking insights into volume, Bollinger band and relative strength dynamics. This indicator assesses the deviation of a security's trading volume relative to the Bollinger band % indicator and the RSI moving average. Together, these shed light on potential zones of interests where market shifts have a high probability of occurring.
Key Features:
Period: Tailor the indicator's sensitivity by adjusting the period of the smooth moving average and/or the period of the Bollinger band.
How it Works:
Moving Average Calculation: The script computes the simple moving average (SMA) of the relative strength over a defined period. When the higher SMA (orange line) is in the top grey zone, the security is in a zone where it has a high probability of becoming bullish. When the higher SMA is in the lower grey zone, the security is in a zone where it has a high probability of becoming bearish.
-Bollinger Band %: The script also computes the BB% which is primarily used to confirm overbought and oversold areas. When overbought, it turns white and remains white until the overbuying pressure is released indicating that the security is about to become bearish. The script indicates a bearish reversal when the BB% and RVOL bars are both red or when there are no more yellow RVOL bars, if present. When the BB% is<0 and rising, it will also appear white with yellow RVOL bars above. This is a good indication that bulls are beginning to enter buying positions. Confirmation here is indicated when the yellow RVOL bars change to green.
Relative Volume: The indicator then also normalizes the difference volume to indicate areas of high and low volatility. This shows where higher than normal volumes are being traded and can be used as a good indication of when to enter or exit a trade when the above criterions are met.
Visual Representation: The result is visually represented on the chart using columns. Bright green columns signify bullish relative volume values that are much greater than normal. Green columns signify bullish relative volume values that are significant. Red columns represent bearish values that are significant. Blue columns on the BB% indicator represent significant bullish buying in overbought areas. Red columns on the BB% indicator that are < 0 represent a bearish trend that is in an oversold area. This is there to prevent early entry into the market.
Enhancements:
Areas of Interest: Optionally, Areas of interest are represented by red, yellow and green circles on the higher SMA line, aiding in the identification of significant deviations.
Range-Weighted Volatility (Comparable)I wrote an indicator to measure volatility inside a range. It’s extremely useful for choosing a trading pair for grid strategies, because it lets you quickly, easily, and fairly identify which asset is the volatility leader. It measures volatility “fairly” relative to the asset’s trading range, not just by absolute price changes.
For example: if an asset trades in a 50–100 range and over a week it moves many, many times between 52 and 98, then it’s highly volatile. But if another asset trades in a 50–1000 range and makes the same 52–98 moves, its volatility is actually low — because the “weight” of that movement relative to the full range is small. The indicator accounts for this “movement weight” relative to the range, then sums these weights into a single number. That number makes it easy to judge whether an asset is suitable for a grid strategy.
That’s exactly what grids need: not just high volatility, but high volatility within a narrow range.
Settings: the Window (bars) field defines how many bars are used to calculate volatility. On a 5-minute chart, one week is 2016 bars (2460/57). By default, the script calculates over 30 days on 5-minute charts. The script also allows you to set a second symbol for comparison, so you can see both results on the same chart.
Написал индикатор для определения волатильности в диапазоне, очень-очень полезно для выбора торговой пары на гриде, позволяет легко и быстро и честно определить лидера по волатильности, при этом определяет ее "честно", относительно торгового диапазона, а не просто изменения цены.
Например если актив торгуется в диапазоне 50-100 и за неделю много-много раз сходил 52-98, то это очень волатильный актив, и в то же время если актив торгуется в диапазоне 50-1000 и сходил так же 52-98, то это будет низко волатильный актив, т.е. учитывается "вес" движения относительно диапазона и данные "веса" суммируются в одну единую цифру по которой и можно оценивать насколько актив подходит под грид стратегию.
А ведь именно это для гридов и нужно, не просто высокая волатильность, а именно высокая волатильность в узком диапазоне.
Касательно настроек , в поле Windows (bars) задается количество баров по которым скрипт будет считать волатильность, на 5-ти минутки неделя это 2016 (24*60/5*7), стандартно скрипт считает за 30 дней на 5-ти минутки. + в самом скрипте можно указать вторую пару для сравнения чтоб на одном графике увидеть результат.
Gamma & Volatility Levels [Pro]General Purpose
This indicator analyzes volatility levels and expected price movements, combining gamma concepts (financial options) with volatility analysis to identify support and resistance zones.
Main Components
High Volatility Level (HVL): Calculates a volatility level based on the simple moving average (SMA) of the price plus one standard deviation. This level is represented by an orange line showing where volatility is concentrated.
Expected Movement (Movimiento Esperante): Uses the Average True Range (ATR) multiplied by an adjustable factor to project potential upward and downward movement ranges from the current price. It is drawn in green (upward) and red (downward).
Gamma Levels (Nivelas Gamma): Identifies two key levels: the call resistance (highest high of the last 50 periods) in blue, and the put support (lowest low) in purple. These are based on recent extreme prices.
Additional Information: The indicator calculates the percentage distance between the current price and the HVL, displaying it in a label.
Visual Elements
Colored lines on the chart for each level.
Labels with exact values next to each line.
A table in the upper right corner summarizing all calculated values.
Options to show or hide each element according to preference.
This is a useful tool for traders who work with options or seek to identify levels of extreme volatility and dynamic support/resistance zones.
Quantum Darvas BoxesQuantum Darvas Boxes - The Modern Evolution
The original Darvas Box methodology, conceived by Nicolas Darvas in the 1950s, revolutionized breakout trading by identifying consolidation phases as "boxes." However, modern markets move with algorithmic speed and fractal volatility that often trigger false breakouts. Quantum Darvas Boxes were designed not as a nostalgic tribute, but as a computational upgrade. By anchoring boxes to volatility-adjusted boundaries rather than raw highs/lows, and introducing adaptive stability mechanisms, this indicator transforms a classic discretionary tool into a systematic, noise-filtered engine.
Description & Improvements
Quantum Darvas Boxes solve the three fatal flaws of the original: false breakouts, arbitrary box sizing, and lack of confirmation. Instead of drawing boxes at exact recent highs/lows, it creates volatility-buffered boundaries using ATR, ensuring breakouts require meaningful momentum. The boxes remain anchored until a confirmed close beyond the buffer occurs, preventing the constant redrawing that plagued traditional Darvas implementations. Built-in volume and RSI filters add discretionary-grade confirmation to pure price action. Visually, the system presents as a stable, semi-transparent blue zone between red (resistance) and lime (support) lines, with clear triangle signals appearing only on validated breakouts.
How It's Based on Darvas
The core philosophy remains true to Darvas' 1950s methodology:
Identify Consolidation: Finds price ranges where the market consolidates
Draw Box: Creates a "box" representing the accumulation zone
Breakout Trading: Enters when price breaks out of the box with momentum
Volatility-Adjusted Boundaries
Original: Boxes at exact highs/lows → prone to false breakouts
QDB: Boxes set at High - (ATR × Multiplier) and Low + (ATR × Multiplier)
→ Breakouts require meaningful momentum, not just price tags
→ Adapts to different volatility regimes
Signal Logic:
Long: Close above box top, previous close was inside box
Short: Close below box bottom, previous close was inside box
Ideal Settings:
For daily charts, use lookback=13 and mult=2.4.
For intraday (1H-4H), reduce to lookback=8 and mult=1.8. Enable volume filter in trending markets and RSI filter in ranging conditions.
Trade Execution: Enter long on the green triangle below the bar following a close above the red top line; enter short on the red triangle above the bar after a close below the lime bottom line. The background glow provides immediate visual confirmation.
Risk Management: Set stops at the opposite box boundary. The volatility multiplier inherently calculates a risk buffer—larger multipliers create wider, higher-conviction boxes; smaller multipliers produce more frequent, sensitive signals. This system excels in trending markets and provides clear exit/reversal points, transforming Darvas's original speculation into a quantified, repeatable edge.
VixTrixVixTrix - Because markets move in both directions.
VixTrix was born from a fundamental limitation in traditional volatility indicators: they only measure downside panic, completely missing the greed-driven extremes that form market tops.
How It Works:
Dual-Component Analysis:
vixBear = Panic selling intensity (distance from recent highs)
vixBull = FOMO buying intensity (distance from recent lows)
Oscillator = vixBear - vixBull = Net fear/greed imbalance
When the oscillator is positive, fear dominates (potential bottom forming). When negative, greed dominates (potential top forming).
Professional-Grade Filtering:
The magic happens with the symmetric RMS (Root Mean Square) bands. Unlike fixed percentage bands or standard deviation, RMS:
Creates mathematically symmetric positive/negative thresholds
Naturally adapts to changing volatility regimes
Provides statistical significance to extremes
VixTrix also adds selectable MA smoothing for the RMS calculation:
WMA (default): Balanced – middle-ground approach
VWMA: Volume-weighted – filters low-volume noise
EMA: Responsive – catches quick reversals
SMA: Stable – for swing trading
HMA: Fast and smooth – ideal for day trading
Signals require triple confirmation:
Statistical Extreme: Oscillator beyond RMS band
Price Action Confirmation: Correct candle color (bullish for bottoms, bearish for tops)
Momentum Continuation: Oscillator still moving toward extreme (exhaustion)
This multi-filter approach reduces premature entries and false signals while maintaining early positioning at potential reversal points.
Why This Matters for Your Trading:
In bull markets, traditional fear indicators sit near zero, giving no warning of impending tops.
VixTrix identifies when greed becomes excessive – when FOMO buying reaches statistical extremes that often precede corrections.
In range-bound markets, VixTrix excels at identifying overreactions in both directions, providing high-probability mean reversion opportunities.
During crashes, it captures the panic selling with the same precision as VixFix, but with better timing through its momentum confirmation.
VixTrix spots continuations through:
"No Signal" = Healthy Trend – Oscillator stays between RMS bands (no exhaustion)
Failed Extremes – Touches band but no triple confirmation = trend likely continues
Hidden Divergence – Price makes higher low while oscillator makes shallower low = uptrend continues
Controlled Emotions – Oscillator negative but not extreme in uptrends (greed present but not excessive)
Key Insight: When VixTrix doesn't give a signal during a pullback, institutions aren't panicking – they're just pausing before resuming the trend.
Green columns = Bullish exhaustion (potential bottoms)
Red columns = Bearish exhaustion (potential tops)
Golden RMS bands = Dynamic thresholds adapting to current volatility
Background highlights = Active signal conditions
The Result: A professional-grade oscillator that works in all market conditions – trending up, trending down, or ranging – by measuring the complete emotional spectrum driving price action.
ZigZag++ UltraAlgo EditionLagging indicator used to understand trends and entry / exit points. Suggest using at 4h - 1d intervals first, then 1-2h, to identify zones of opportunities and validate your position.
Custom RSI + Divergence + Bold Lines (v6, matched)📌 Custom RSI with Divergence & Dynamic Coloring
This indicator enhances the classic Relative Strength Index (RSI) by combining
dynamic visual feedback with automatic regular divergence detection.
It is designed to help traders quickly identify overbought / oversold conditions
and potential momentum shifts through clear and intuitive visualization.
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🔍 Key Features
1️⃣ Dynamic RSI Line Coloring
• Overbought zone (RSI > Overbought level) → RSI line turns green
• Oversold zone (RSI < Oversold level) → RSI line turns red
• Neutral zone → RSI line remains white
This allows instant recognition of the current RSI state.
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2️⃣ Overbought / Oversold Visual Highlighting
• Clear overbought and oversold reference lines
• Background shading when RSI enters these zones
→ improves signal visibility and reaction speed
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3️⃣ Automatic Regular Divergence Detection
• Bullish Divergence
• Price makes a lower low
• RSI makes a higher low
• Pivot lows are connected with a bold green line
• Bearish Divergence
• Price makes a higher high
• RSI makes a lower high
• Pivot highs are connected with a bold red line
Pivot points are connected directly, making divergence structures easy to identify at a glance.
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4️⃣ Clear Signal Markers
• Bullish divergence: ▲ (bottom of the RSI pane)
• Bearish divergence: ▼ (top of the RSI pane)
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⚙️ Inputs
• RSI Length
• Overbought / Oversold Levels
• Pivot Length (controls divergence sensitivity)
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💡 How to Use
• Oversold + Bullish Divergence → Potential rebound setup
• Overbought + Bearish Divergence → Potential pullback or reversal
• Best used in combination with trend analysis, support/resistance, and volume
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⚠️ Notes
• Divergence signals are probabilistic, not guaranteed.
• In ranging markets, divergences may appear more frequently.
• Always apply proper risk management.
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🎯 Best For
• Traders who actively use RSI
• Traders looking for clean and intuitive divergence visualization
• Users who prefer minimal but informative indicators
NeoChartLabs Trend VolatalityAn Experimental Indicator - Trend Volatility
Using the Trix & ATR, it becomes possible to measure the volatility in the trend.
When the ATR% is below the user defined rate (default is 5%), the background turns RED signaling a low vol asset.
If ATRP goes under 5% in Crypto and the background turns RED - expect a large move to happen soon either up or down.
Miela Labs | John Dee's Watchtower [257-463]Bridging the gap between 16th-century esoteric mathematics and modern algorithmic trading.
The Enochian Watchtower is not merely a trend indicator; it is a computational artifact developed by Miela Labs LLC. This script translates Dr. John Dee’s "Great Table of the Watchtowers" and the "Sigil Dei Aemeth" into actionable financial data points.
Using our proprietary Occultator V2.0 Engine, we have derived specific mathematical constants that resonate with the current market structure.
🏛️ The Algorithmic Logic
This indicator utilizes three sacred numbers to construct a "Future Vision" of the market:
1. The Axis Mundi (Vector 257): derived from Fermat Primes and John Dee’s Grid coordinates. This Weighted Moving Average (WMA) acts as the spinal cord of the trend.
2. The Gates (Cipher 463): A prime number derived from the "Galethog" cipher stride. These bands define the absolute volatility limits (Heaven & Earth Gates).
3. Future Vision (Offset 21): Utilizing Fibonacci time sequences, the indicator projects Support and Resistance levels 21 bars into the future, allowing traders to anticipate market movements before they occur.
⚡ How to Use
• The Trend: If price is above the Purple Axis (257), the market is in a bullish phase.
• The Entry: Look for "L" (Long) and "S" (Short) signals. These are confirmed when the signal path crosses the Axis.
• The Future: Watch the projected lines on the right side of the chart to identify upcoming resistance zones.
About Miela Labs
Miela Labs is a Technomancy Research Institute based in McKinney, Texas. We specialize in building open-source esoteric trading tools and the Magic Programming Language (MPL).
🌐 Official Hub: Visit Miela Labs
💻 Source Code & Research: GitHub Repository
Disclaimer: This tool is for educational and research purposes only. It demonstrates the application of esoteric mathematics in financial analysis. Trade responsibly.
ATR Regime Filter (ATR14 vs SMA20)ATR volatility + ATR SMA
Green ATR above Red SMA + green background
→ Volatility expanding
→ Trend mode only
Green ATR below Red SMA + blue background
→ Volatility compressing
→ Mean reversion allowed
Crossovers / flickering
→ Transition
→ Size down or stay flat
FxAST Trend Force [ALLDYN]Attribution
This indicator is based on the original Trend Speed Analyzer created by Zeiierman .
FxAST Trend Force is a modified and simplified derivative that preserves the core methodology while focusing on clarity, usability, and practical trend interpretation .
This indicator is intended for educational and analytical use. Derivative works must retain attribution and license terms.
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FxAST Trend Force
Overview
FxAST Trend Force is a directional pressure indicator designed to show who is in control of the market and how strong that control is, in real time.
Instead of measuring raw price speed or traditional momentum, this tool focuses on trend force — the sustained push of price relative to a dynamic trend baseline. The result is a clean, intuitive view of trend direction, strength, and condition without complex math or hard-to-interpret ratios.
This indicator is best used as a trend confirmation and trade management tool , not a standalone signal generator.
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How It Works
FxAST Trend Force uses a Dynamic Moving Average (DMA) that adapts to changing market conditions. Price behavior relative to this adaptive trend line determines the current trend regime.
While price remains on one side of the trend:
Directional pressure accumulates
Strength builds or weakens
The regime resets only when price decisively crosses the trend
This creates a clear visual representation of trend persistence vs exhaustion , rather than short-term noise.
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Core Concepts (Plain English)
Trend
Shows the current directional bias:
Bull → price above the dynamic trend
Bear → price below the dynamic trend
This answers: “Which side is currently in control?”
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Strength
Displays how strong the current trend pressure is on a 0–100 scale , normalized to recent market conditions.
Strength is shown both as:
A simple label: Weak / Normal / Strong
A visual meter for quick interpretation
This answers: “Is this move weak, average, or meaningful?”
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State
Indicates whether trend force is:
Building → pressure increasing
Fading → pressure weakening
This answers: “Is the trend gaining energy or losing it?”
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Visual Meter
A compact bar at the bottom of the table represents trend force intensity at a glance.
Longer bar → stronger sustained pressure
Shorter bar → weaker or stalling trend
No ratios. No multipliers. Just visual clarity.
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How to Use
Trend Confirmation
Favor longs when Trend = Bull and Strength = Normal/Strong
Favor shorts when Trend = Bear and Strength = Normal/Strong
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Trade Management
Building state supports continuation
Fading state warns of exhaustion, consolidation, or potential reversal
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Filtering Noise
Weak strength often signals chop or low-quality conditions
Strong force helps filter false breakouts
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Settings (Simplified)
Maximum Length
Controls how smooth or responsive the dynamic trend is.
Accelerator Multiplier
Adjusts how quickly the trend adapts to price changes.
Lookback Period
Defines the window used to normalize trend force.
Enable Candles
Colors price candles by trend force for visual clarity.
Show Simple Table
Toggles the Trend / Strength / State display.
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Philosophy
FxAST Trend Force is intentionally not a signal-spamming indicator.
It is designed to reduce cognitive load , not increase it.
If you need:
exact entries → use price action
exact exits → use structure
context and confirmation → use Trend Force
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Disclaimer
This indicator is provided for educational purposes only and does not constitute financial advice. Trading involves risk, and users are responsible for their own decisions.
CODEX OB + BBMA V1CODEX OB + BBMA is a multi-purpose Smart Money Concepts (SMC) indicator that automatically detects and visualizes key institutional trading elements such as Order Blocks, Fair Value Gaps, Rejection Blocks, Break of Structure, Pivots, High Volume Bars, and several qualitative SMC signals.
In addition to SMC tools, this indicator also incorporates multi-timeframe BBMA logic, allowing traders to view higher-timeframe momentum, trend direction, and volatility envelopes directly from the current chart. This makes it easier to align SMC setups—like OB, FVG, and BOS—with BBMA structure such as MA touches, re-entry zones, extreme candles, and volatility expansions.
This combination helps traders identify institutional footprints, multi-timeframe confluence, and displacement-based setups with high clarity.
The Abramelin Protocol [MPL]"Any sufficiently advanced technology is indistinguishable from magic." — Arthur C. Clarke
🌑 SYSTEM OVERVIEW
The Abramelin Protocol is not a standard technical indicator; it is a "Technomantic" trading algorithm engineered to bridge the gap between 15th-century esoteric mathematics and modern high-frequency markets.
This script is the flagship implementation of the MPL (Magic Programming Language) project—an open-source experimental framework designed to compile metaphysical intent into executable Python and Pine Script algorithms.
Unlike traditional indicators that rely on arbitrary constants (like the 14-period RSI or 200 SMA), this protocol calculates its parameters using "Dynamic Entity Gematria." We utilize a custom Python backend to analyze the ASCII vibrational frequencies of specific metaphysical archetypes, reducing them via Tesla's 3-6-9 harmonic principles to derive market-responsive periods.
🧬 WHAT IS ?
MPL (Magic Programming Language) is a domain-specific language and research initiative created to explore Technomancy—the art of treating code as a spellbook and the market as a chaotic entity to be tamed.
By integrating the logic of ancient Grimoires (such as The Book of Abramelin) with modern Data Science, MPL aims to discover hidden correlations in price action that standard tools overlook.
🔗 CONNECT WITH THE PROJECT:
If you are a developer, a trader, or a seeker of hidden knowledge, examine the source code and join the order:
• 📂 Official Project Site: hakanovski.github.io
• 🐍 MPL Source Code (GitHub): github.com
• 👨💻 Developer Profile (LinkedIn): www.linkedin.com
🔢 THE ALGORITHM: 452 - 204 - 50
The inputs for this script are mathematically derived signatures of the intelligence governing the system:
1. THE PAIMON TREND (Gravity)
• Origin: Derived from the ASCII summation of the archetype PAIMON (King of Secret Knowledge).
• Function: This 452-period Baseline acts as the market's "Event Horizon." It represents the deep, structural direction of the asset.
• Price > Line: Bullish Domain.
• Price < Line: Bearish Void.
2. THE ASTAROTH SIGNAL (Trigger)
• Origin: Derived from the ASCII summation of ASTAROTH (Knower of Past & Future), reduced by Tesla’s 3rd Harmonic.
• Function: This is the active trigger line. It replaces standard moving averages with a precise, gematria-aligned trajectory.
3. THE VOLATILITY MATRIX (Scalp)
• Origin: Based on the 9th Harmonic reduction.
• Function: Creates a "Cloud" around the signal line to visualize market noise.
🛡️ THE MILON GATE (Matrix Filter)
Unique to this script is the "MILON Gate" toggle found in the settings.
• ☑️ Active (Default): The algorithm applies the logic of the MILON Magic Square. Signals are ONLY generated if Volume and Volatility align with the geometric structure of the move. This filters out ~80% of false signals (noise).
• ⬜ Inactive: The algorithm operates in "Raw Mode," showing every mathematical crossover without the volume filter.
⚠️ OPERATIONAL USAGE
• Timeframe: Optimized for 4H (The Builder) and Daily (The Architect) charts.
• Strategy: Use the Black/Grey Line (452) as your directional bias. Take entries only when the "EXECUTE" (Long) or "PURGE" (Short) sigils appear.
Use this tool wisely. Risk responsibly. Let the harmonics guide your entries.
— Hakan Yorganci
Technomancer & Full Stack Developer
RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
