FluxGate Daily Swing Strategy Summary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
Kripto
Momentum Master v1Momentum Master v1 - Advanced Multi-Filter Confluence Trading System
### Technical Methodology
Multi-timeframe EMA crossover system with institutional flow analysis, proprietary Fair Value Gap (FVG) retracement detection, and Point of Control (POC) proximity filtering.
The script combines six distinct confirmation filters: 3/21 EMA crossover signals, RSI momentum analysis (14-period), proprietary FVG retracement algorithm with 200-bar lookback, multi-timeframe POC proximity calculation (Volume/Session/Daily/Weekly), institutional order block detection with retest confirmation, and adaptive ATR-based risk management.
### Unique Features
1. Proprietary FVG Retracement Algorithm - Institutional Flow Analysis
2. Multi-Timeframe POC Proximity Filtering - Key Level Analysis
3. Adaptive Confidence Scoring System - Dynamic Risk Management
### How It Works
Long entries require: Fast EMA (3) crosses above Slow EMA (21) + RSI < 70 + volume > 1.1x average + FVG retracement confirmation + POC proximity within 2.0x ATR + order block direction alignment.
Uses ATR-based stop loss placement with 1.0x multiplier. Take profit levels at 2:1, 4:1, 6:1, 8:1, 10:1, and 12:1 risk/reward ratios.
### Value Proposition
This script combines 6 different institutional flow analysis techniques that would require multiple free scripts to replicate. The proprietary FVG retracement algorithm, multi-timeframe POC analysis, and adaptive confidence scoring system are not available in any single free script.
### Use Cases
Best timeframes: 5-minute for scalping, 15-minute for swing trades
Suitable markets: Forex major pairs, Crypto, major indices
Market conditions: Trending markets with high volume sessions
### Access Instructions
To request access to this invite-only script:
Contact: pinescriptedge@gmail.com with your TradingView username
Requirements: Include your TradingView username and brief trading experience
Process: I will review requests within 24 hours and grant access to qualified traders
2 days ago
Release Notes
Momentum Master v1 - Multi-Filter EMA Crossover with Institutional Flow Analysis
### Technical Methodology
The script uses a 3/21 EMA crossover system combined with six confirmation filters: RSI momentum analysis (14-period), proprietary Fair Value Gap (FVG) retracement detection with 200-bar lookback, multi-timeframe Point of Control (POC) proximity calculation, institutional order block detection with retest confirmation, volume analysis (1.1x average threshold), and adaptive ATR-based risk management (14-period ATR with 1.0x multiplier).
### Unique Features
1. Proprietary FVG Retracement Algorithm - Tracks whether price retraces into recent Fair Value Gaps before generating signals, using 200-bar lookback with 20% ATR tolerance for retest confirmation
2. Multi-Timeframe POC Analysis - Combines Volume Profile POC (30-bar), Session POC (previous session HLC/3), Daily POC (previous day HLC/3), and Weekly POC (previous week HLC/3) with 2.0x ATR proximity filtering
3. Adaptive Confidence Scoring - Proprietary algorithm scores signal confidence 0-100% based on filter confluence, adjusting stop loss distance (0.9x to 1.2x ATR) based on signal quality
### How It Works
Long entries require: Fast EMA (3) crosses above Slow EMA (21) + RSI < 70 + volume > 1.1x average + FVG retracement confirmation within 15 bars + POC proximity within 2.0x ATR + order block direction alignment. Optional filters include ADX > 20 for trending markets and divergence confirmation.
Exit strategy uses ATR-based stop loss (1.0x multiplier) with take profit levels at 2:1, 4:1, 6:1, 8:1, 10:1, and 12:1 risk/reward ratios. Multiple concurrent trades allowed with 5-bar cooldown between entries.
### Value Proposition
This script combines 6 different institutional flow analysis techniques that would require multiple free scripts to replicate. The proprietary FVG retracement algorithm, multi-timeframe POC analysis, and adaptive confidence scoring system are not available in any single free script. Most free scripts only provide basic EMA crossover signals without institutional context.
### Use Cases
Best timeframes: 5-minute for scalping, 15-minute for swing trades, 1-hour for position entries
Suitable markets: Forex major pairs (EUR/USD, GBP/USD), Crypto (BTC/USD, ETH/USD), major indices (S&P 500, NASDAQ)
Market conditions: Trending markets with ADX > 20, high volume sessions (London/NY overlap)
### Access Instructions
To request access to this invite-only script:
Contact: pinescriptedge@gmail.com with your TradingView username
Requirements: Include your TradingView username and brief trading experience
Process: I will review requests within 24 hours and grant access to qualified traders
Crypto Pro Strategy (Entry Model + Risk)Imma try to use this on a prop firm but if you want to use it itss free or im going to try to make it free
Aggregated Open Interest Multi-Exchange (USD)This indicator aggregates Open Interest (OI) data from multiple major cryptocurrency exchanges into a single unified view in USD, using data available on TradingView. It automatically adapts to the asset you're viewing on the chart.
Features:
Aggregates OI from 7 major exchanges: Binance, Bybit, OKX, Bitget, Deribit, HTX, and Coinbase
All values converted to USD - unlike native OI which shows contracts/coins
Uses only data available on TradingView platform
Automatically detects the asset from your chart (BTC, ETH, SOL, etc.)
True apples-to-apples comparison across exchanges
Displays as candlesticks showing OI open, high, low, and close
Toggle exchanges on/off individually
Handles different contract types per exchange automatically
Why USD conversion matters:
Traditional OI indicators show values in contracts or crypto units, making it difficult to compare across exchanges. This indicator converts everything to USD, giving you the real dollar value of open positions across all exchanges.
How it works:
Simply add the indicator to any crypto perpetual futures chart. It will automatically fetch and aggregate OI data from all supported exchanges for that asset using TradingView's built-in data feeds, converting everything to USD.
Supported Exchanges:
Binance, Bybit, Bitget, HTX: USDT perpetuals
Deribit: BTC/ETH use USD contracts, others use USDC
OKX: Contract-based (automatically converted)
Coinbase: USDC perpetuals
Perfect for traders who want a comprehensive view of total market Open Interest in USD across exchanges using reliable TradingView data.
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe
This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice.
0. Publication mode and rationale
This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible.
Why Protected
The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users.
Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results.
1. What the strategy does in one paragraph
Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity.
Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor.
Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal.
2. Why it is original and useful
It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance.
The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise.
Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants.
Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates.
The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about.
3. Plain language overview of the math
Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural.
Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases.
Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one.
Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow.
Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band.
4. Entries, exits, and position sizing
Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs.
Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate.
Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active.
Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn.
Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts.
5. Inputs quick guide with recommended ranges
Every input has a tooltip in the script. The same guidance appears here for fast reading.
Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing.
Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55.
Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more.
Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence.
Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical.
Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets.
Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts.
Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more.
Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes.
AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes.
Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70.
Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20.
Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2.
Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts.
Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior.
Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits.
Background heat opacity . Cosmetic. Set to taste. Zero disables it.
6. Properties used on the published chart
The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results.
Initial capital 100000
Base currency USD
Order size 2 percent of equity coming from our risk management inputs.
Pyramiding 0
Commission 0.05 percent
Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research.
Recalculate after order is filled off. On every tick off.
Using bar magnifier on. On bar close on.
Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1.
7. Visual elements and alerts
The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan.
8. How to reproduce the example
Open a BTCUSD daily chart with regular candles.
Add the strategy and load the defaults that match the values above.
Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on.
Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown.
9. Practical tuning recipes
Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions.
Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar.
Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday.
Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions.
Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it.
10. Strengths and limitations
Strengths
Self scaling unit through AAR makes the tool portable across markets and timeframes.
Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align.
Adaptive centering reduces structural bias at the score level which helps during regime flips.
Limitations
In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable.
Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate.
Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research.
The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases.
11. Realism and responsible publication
No promises or projections of performance are made. Past results never guarantee future outcomes.
Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange.
Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model.
Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size.
Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders.
12. Suggested research workflow
Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history.
Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value.
Try one higher timeframe blend with a modest weight. Large weights can drown the signal.
Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop.
Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy.
Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods.
13. How to read the HUD and heat map
The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty.
14. Frequently asked questions
Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch.
Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly.
Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off.
Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown.
Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing.
Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context.
15. Concepts glossary
AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops.
Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity.
Geometric mean growth . Rate that preserves the effect of compounding over many bars.
Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound.
Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale.
Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew.
16. Educational notice and risk statement
Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results.
17. Final notes for readers and moderators
The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments.
Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence.
Thank you for your time to read all of this
LEGEND IsoPulse Fusion Universal Volume Trend Buy Sell RadarLEGEND IsoPulse Fusion • Universal Volume Trend Buy Sell Radar
One line summary
LEGEND IsoPulse Fusion reads intent from price and volume together, learns which features matter most on your symbol, blends them into a single signed Fusion line in a stable unit range, and emits clear Buy Sell Close events with a structure gate and a liquidity safety gate so you act only when the tape is favorable.
What this script is and why it exists
Many traders keep separate windows for trend, volume, volatility, and regime filters. The result can feel fragmented. This script merges two complementary engines into one consistent view that is easy to read and simple to act on.
LEGEND Tensor estimates directional quality from five causally computed features that are normalized for stationarity. The features are Flow, Tail Pressure with Volume Mix, Path Curvature, Streak Persistence, and Entropy Order.
IsoPulse transforms raw volume into two decaying reservoirs for buy effort and sell effort using body location and wick geometry, then measures price travel per unit volume for efficiency, and detects volume bursts with a recency memory.
Both engines are mapped into the same unit range and fused by a regime aware mixer. When the tape is orderly the mixer leans toward trend features. When the tape is messy but a true push appears in volume efficiency with bursts the mixer allows IsoPulse to speak louder. The outcome is a single Fusion line that lives in a familiar range with calm behavior in quiet periods and expressive pushes when energy concentrates.
What makes it original and useful
Two reservoir volume split . The script assigns a portion of the bar volume to up effort and down effort using body location and wick geometry together. Effort decays through time using a forgetting factor so memory is present without becoming sticky.
Efficiency of move . Price travel per unit volume is often more informative than raw volume or raw range. The script normalizes both sides and centers the efficiency so it becomes signed fuel when multiplied by flow skew.
Burst detection with recency memory . Percent rank of volume highlights bursts. An exponential memory of how recently bursts clustered converts isolated blips into useful context.
Causal adaptive weighting . The LEGEND features do not receive static weights. The script learns, causally, which features have correlated with future returns on your symbol over a rolling window. Only positive contributions are allowed and weights are normalized for interpretability.
Regime aware fusion . Entropy based order and persistence create a mixer that blends IsoPulse with LEGEND. You see a single line rather than two competing panels, which reduces decision conflict.
How to read the screen in seconds
Fusion area . The pane fills above and below zero with a soft gradient. Deeper fill means stronger conviction. The white Fusion line sits on top for precise crossings.
Entry guides and exit guides . Two entry guides draw symmetrically at the active fused entry level. Two exit guides sit inside at a fraction of the entry. Think of them as an adaptive envelope.
Letters . B prints once when the script flips from flat to long. S prints once when the script flips from flat to short. C prints when a held position ends on the appropriate side. T prints when the structure gate first opens. A prints when the liquidity safety flag first appears.
Price bar paint . Bars tint green while long and red while short on the chart to mirror your virtual position.
HUD . A compact dashboard in the corner shows Fusion, IsoPulse, LEGEND, active entry and exit levels, regime status, current virtual position, and the vacuum z value with its avoid threshold.
What signals actually mean
Buy . A Buy prints when the Fusion line crosses above the active entry level while gates are open and the previous state was flat.
Sell . A Sell prints when the Fusion line crosses below the negative entry level while gates are open and the previous state was flat.
Close . A Close prints when Fusion cools back inside the exit envelope or when an opposite cross would occur or when a gate forces a stop, and the previous state was a hold.
Gates . The Trend gate requires sufficient entropy order or significant persistence. The Avoid gate uses a liquidity vacuum z score. Gates exist to protect you from weak tape and poor liquidity.
Inputs and practical tuning
Every input has a tooltip in the script. This section provides a concise reference that you can keep in mind while you work.
Setup
Core window . Controls statistics across features. Scalping often prefers the thirties or low fifties. Intraday often prefers the fifties to eighties. Swing often prefers the eighties to low hundreds. Smaller responds faster with more noise. Larger is calmer.
Smoothing . Short EMA on noisy features. A small value catches micro shifts. A larger value reduces whipsaw.
Fusion and thresholds
Weight lookback . Sample size for weight learning. Use at least five times the horizon. Larger is slower and more confident. Smaller is nimble and more reactive.
Weight horizon . How far ahead return is measured to assess feature value. Smaller favors quick reversion impulses. Larger favors continuation.
Adaptive thresholds . Entry and exit levels from rolling percentiles of the absolute LEGEND score. This self scales across assets and timeframes.
Entry percentile . Eighty selects the top quintile of pushes. Lower to seventy five for more signals. Raise for cleanliness.
Exit percentile . Mid fifties keeps trades honest without overstaying. Sixty holds longer with wider give back.
Order threshold . Minimum structure to trade. Zero point fifteen is a reasonable start. Lower to trade more. Raise to filter chop.
Avoid if Vac z . Liquidity safety level. One point two five is a good default on liquid markets. Thin markets may prefer a slightly higher setting to avoid permanent avoid mode.
IsoPulse
Iso forgetting per bar . Memory for the two reservoirs. Values near zero point nine eight to zero point nine nine five work across many symbols.
Wick weight in effort split . Balance between body location and wick geometry. Values near zero point three to zero point six capture useful behavior.
Efficiency window . Travel per volume window. Lower for snappy symbols. Higher for stability.
Burst percent rank window . Window for percent rank of volume. Around one hundred to three hundred covers most use cases.
Burst recency half life . How long burst clusters matter. Lower for quick fades. Higher for cluster memory.
IsoPulse gain . Pre compression gain before the atan mapping. Tune until the Fusion line lives inside a calm band most of the time with expressive spikes on true pushes.
Continuation and Reversal guides . Visual rails for IsoPulse that help you sense continuation or exhaustion zones. They do not force events.
Entry sensitivity and exit fraction
Entry sensitivity . Loose multiplies the fused entry level by a smaller factor which prints more trades. Strict multiplies by a larger factor which selects fewer and cleaner trades. Balanced is neutral.
Exit fraction . Exit level relative to the entry level in fused unit space. Values around one half to two thirds fit most symbols.
Visuals and UX
Columns and line . Use both to see context and precise crossings. If you present a very clean chart you can turn columns off and keep the line.
HUD . Keep it on while you learn the script. It teaches you how the gates and thresholds respond to your market.
Letters . B S C T A are informative and compact. For screenshots you can toggle them off.
Debug triggers . Show raw crosses even when gates block entries. This is useful when you tune the gates. Turn them off for normal use.
Quick start recipes
Scalping one to five minutes
Core window in the thirties to low fifties.
Horizon around five to eight.
Entry percentile around seventy five.
Exit fraction around zero point five five.
Order threshold around zero point one zero.
Avoid level around one point three zero.
Tune IsoPulse gain until normal Fusion sits inside a calm band and true squeezes push outside.
Intraday five to thirty minutes
Core window around fifty to eighty.
Horizon around ten to twelve.
Entry percentile around eighty.
Exit fraction around zero point five five to zero point six zero.
Order threshold around zero point one five.
Avoid level around one point two five.
Swing one hour to daily
Core window around eighty to one hundred twenty.
Horizon around twelve to twenty.
Entry percentile around eighty to eighty five.
Exit fraction around zero point six zero to zero point seven zero.
Order threshold around zero point two zero.
Avoid level around one point two zero.
How to connect signals to your risk plan
This is an indicator. You remain in control of orders and risk.
Stops . A simple choice is an ATR multiple measured on your chart timeframe. Intraday often prefers one point two five to one point five ATR. Swing often prefers one point five to two ATR. Adjust to symbol behavior and personal risk tolerance.
Exits . The script already prints a Close when Fusion cools inside the exit envelope. If you prefer targets you can mirror the entry envelope distance and convert that to points or percent in your own plan.
Position size . Fixed fractional or fixed risk per trade remains a sound baseline. One percent or less per trade is a common starting point for testing.
Sessions and news . Even with self scaling, some traders prefer to skip the first minutes after an open or scheduled news. Gate with your own session logic if needed.
Limitations and honest notes
No look ahead . The script is causal. The adaptive learner uses a shifted correlation, crosses are evaluated without peeking into the future, and no lookahead security calls are used. If you enable intrabar calculations a letter may appear then disappear before the close if the condition fails. This is normal for any cross based logic in real time.
No performance promises . Markets change. This is a decision aid, not a prediction machine. It will not win every sequence and it cannot guarantee statistical outcomes.
No dependence on other indicators . The chart should remain clean. You can add personal tools in private use but publications should keep the example chart readable.
Standard candles only for public signals . Non standard chart types can change event timing and produce unrealistic sequences. Use regular candles for demonstrations and publications.
Internal logic walkthrough
LEGEND feature block
Flow . Current return normalized by ATR then smoothed by a short EMA. This gives directional intent scaled to recent volatility.
Tail pressure with volume mix . The relative sizes of upper and lower wicks inside the high to low range produce a tail asymmetry. A volume based mix can emphasize wick information when volume is meaningful.
Path curvature . Second difference of close normalized by ATR and smoothed. This captures changes in impulse shape that can precede pushes or fades.
Streak persistence . Up and down close streaks are counted and netted. The result is normalized for the window length to keep behavior stable across symbols.
Entropy order . Shannon entropy of the probability of an up close. Lower entropy means more order. The value is oriented by Flow to preserve sign.
Causal weights . Each feature becomes a z score. A shifted correlation against future returns over the horizon produces a positive weight per feature. Weights are normalized so they sum to one for clarity. The result is angle mapped into a compact unit.
IsoPulse block
Effort split . The script estimates up effort and down effort per bar using both body location and wick geometry. Effort is integrated through time into two reservoirs using a forgetting factor.
Skew . The reservoir difference over the sum yields a stable skew in a known range. A short EMA smooths it.
Efficiency . Move size divided by average volume produces travel per unit volume. Normalization and centering around zero produce a symmetric measure.
Bursts and recency . Percent rank of volume highlights bursts. An exponential function of bars since last burst adds the notion of cluster memory.
IsoPulse unit . Skew multiplied by centered efficiency then scaled by the burst factor produces the raw IsoPulse that is angle mapped into the unit range.
Fusion and events
Regime factor . Entropy order and streak persistence form a mixer. Low structure favors IsoPulse. Higher structure favors LEGEND. The blend is convex so it remains interpretable.
Blended guides . Entry and exit guides are blended in the same way as the line so they stay consistent when regimes change. The envelope does not jump unexpectedly.
Virtual position . The script maintains state. Buy and Sell require a cross while flat and gates open. Close requires an exit or force condition while holding. Letters print once at the state change.
Disclosures
This script and description are educational. They do not constitute investment advice. Markets involve risk. You are responsible for your own decisions and for compliance with local rules. The logic is causal and does not look ahead. Signals on non standard chart types can be misleading and are not recommended for publication. When you test a strategy wrapper, use realistic commission and slippage, moderate risk per trade, and enough trades to form a meaningful sample, then document those assumptions if you share results.
Closing thoughts
Clarity builds confidence. The Fusion line gives a single view of intent. The letters communicate action without clutter. The HUD confirms context at a glance. The gates protect you from weak tape and poor liquidity. Tune it to your instrument, observe it across regimes, and use it as a consistent lens rather than a prediction oracle. The goal is not to trade every wiggle. The goal is to pick your spots with a calm process and to stand aside when the tape is not inviting.
AlphaRank - Relative Strength Portfolio StrategyWHAT IS ALPHARANK?
AlphaRank is a multi-asset relative strength portfolio system that identifies the strongest performing assets within a customizable universe of 10 instruments through pairwise comparison analysis. Unlike traditional relative strength indicators that simply compare price ratios, AlphaRank employs a tournament-style evaluation system using 7 distinct technical indicators to determine true relative strength.
METHODOLOGY - HOW IT WORKS
Core Concept: Pairwise Tournament Analysis
AlphaRank compares every asset against every other asset in your universe (45 unique pairs for 10 assets). For each pair, the system evaluates relative strength using 7 independent indicators:
- RSI (35-period) - Momentum comparison
- Rate of Change (31-period) - Price velocity analysis
- Z-Score (44-period) - Statistical deviation from mean
- Omega Ratio (30-period, smoothed) - Risk-adjusted returns using imported ratio library
- Linear Regression ROC (30-period linreg, 14-period ROC) - Trend strength and acceleration
- Kijun Sen Base (44-period SMA) - Ichimoku-style baseline comparison
- RSI ROC (45-period RSI, 15-period ROC) - Momentum acceleration
Scoring System:
For each pairwise comparison (e.g., ETH vs SOL), the system calculates all 7 indicators on the price ratio (ETH/SOL). Each indicator returns a binary signal (1 or 0). These are summed to create a pair score from 0-7.
If pair score > 3: The numerator asset (ETH) is considered relatively stronger
If pair score ≤ 3: The denominator asset (SOL) is considered relatively stronger
This creates a decisive winner for each pair (no neutral outcomes due to the odd number of indicators).
Final Ranking:
Each asset accumulates points for every pairwise comparison it wins. With 10 assets, each asset faces 9 competitors. Final scores range from 0 (lost all comparisons) to 9 (won all comparisons).
ORIGINALITY - WHY THIS IS DIFFERENT
Traditional Relative Strength:
- Compares assets to a benchmark (like SPY)
- Uses single indicator (usually RSI or price ratio)
- Binary strong/weak classification
AlphaRank Approach:
- Round-robin tournament: every asset vs every other asset
- Multi-indicator consensus (7 indicators, not 1)
- Granular ranking from 0-9 showing exact relative positioning
- Real-time tournament matrix visualization showing all head-to-head results
- Integrated backtesting with position sizing
Key Innovation: By using 7 uncorrelated indicators in a consensus model, AlphaRank reduces false signals from any single indicator's weaknesses. An asset must demonstrate strength across multiple analytical dimensions (momentum, trend, volatility, acceleration) to rank highly.
VISUAL COMPONENTS
Tournament Matrix (Top Right):
Shows every head-to-head matchup
Green dots = asset won that comparison
Red dots = asset lost that comparison
Instantly see which assets dominate across the board
RSPS Score Table (Right side of matrix):
Final relative strength scores (0-9)
Color-coded gradient showing strength hierarchy
Top Assets Table (Bottom Center):
Displays your top N ranked assets
Updates dynamically as rankings change
Equity Curve (Main Chart):
Shows backtested portfolio performance
Compares system returns vs buy-and-hold
Performance Metrics (Bottom):
Sharpe ratio, Sortino ratio, Omega ratio
Maximum drawdown
Individual asset and portfolio metrics
HOW TO USE
Setup:
Choose your 10 assets in the settings (crypto, stocks, indices, etc.)
Set your desired number of top assets to hold (default: 2)
Configure backtest start date and leverage
Interpretation:
Score 7-9: Extremely strong relative to peers - high confidence holdings
Score 4-6: Moderate relative strength - proceed with caution
Score 0-3: Weak relative to peers - avoid or consider shorting
Trading Strategy:
The system automatically allocates capital equally among the top-ranked assets and rebalances when rankings change. This creates a rotation strategy that systematically favors the strongest performers.
TECHNICAL SPECIFICATIONS
Timeframe: Works on all timeframes (1H, 4H, 1D recommended for crypto)
Assets: Fully customizable 10-asset universe
Rebalancing: Automatic when rankings change
SETTINGS EXPLAINED
Leverage Amount: Apply leverage to position sizing (1.0 = no leverage)
Startdate: When to begin backtesting calculations
Highlight Top Assets: How many top-ranked assets to hold (2-5 recommended)
Show Combined Matrix: Toggle the tournament visualization
Show Detailed Metrics: Individual asset performance statistics
Show Small Metrics Table: Simplified performance summary
BACKTESTING METHODOLOGY
The indicator includes full backtesting capabilities. It calculates:
Individual Asset Performance: Each asset's returns if held in isolation
Portfolio Performance: Combined returns of top-ranked assets
Buy & Hold Benchmark: Equal-weight portfolio of all 10 assets
Risk Metrics: Sharpe, Sortino, Omega ratios for all strategies
This allows you to validate the relative strength rotation strategy against simple buy-and-hold.
IMPORTANT NOTES
This is a rotation strategy - it does not predict absolute direction, only relative strength
Works best with correlated assets (e.g., all crypto, all tech stocks)
Requires sufficient history for indicator calculations (minimum 60 bars)
Backtesting uses historical data; future performance may differ
Not financial advice - use for educational purposes
Continuation Suite v1 — 5m/15mContinuation Suite v1 — 5m/15m (Non-Repainting, S/R + Trend Continuation)
What it does
Continuation Suite v1 is a practical intraday toolkit that combines non-repainting trend-continuation signals with auto-built Support/Resistance (S/R) from confirmed pivots. It’s designed for fast, liquid names on 5m charts with an optional 15m higher-timeframe (HTF) overlay. You get: stacked-EMA bias, disciplined pullback+reclaim entries, optional volume/volatility gates, a “Strong” signal tier, solid S/R lines or zones, and a compact dashboard for fast reads.
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Why traders use it
• Clear bias using fast/mid/slow EMA stacking.
• Actionable entries that require a pullback, a reclaim, and (optionally) a minor break of prior extremes.
• Signal quality gates (volume vs SMA, ATR%, ADX/DI alignment, EMA spacing, slope).
• Non-repainting logic when “Confirm on Close” = ON. Intrabar previews show what’s forming, but confirmed signals only print on bar close.
• S/R that matters: confirmed-pivot lines or ATR-sized zones, optional HTF overlay, and auto de-dup to avoid clutter.
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Signal construction (no magic, just rules)
Bullish continuation (base):
1. Trend: EMA fast > EMA mid > EMA slow
2. Pullback: price pulls into the stack (lowest low or close vs EMA fast/mid over a lookback)
3. Reclaim: close > EMA fast and close > open
4. Break filter (optional): current bar takes out the prior bar’s high
5. Filters: volume > SMA (if enabled) and ATR% ≤ max (if enabled)
6. Cooldown: a minimum bar gap between signals
Bearish continuation (base): mirror of the above.
Strong signals: base conditions plus ADX ≥ threshold, DI alignment (DI+>DI- for longs; DI->DI+ for shorts), minimum EMA-spacing %, and minimum fast-EMA slope.
Reference stops:
• Longs: lowest low over the pullback lookback
• Shorts: highest high over the pullback lookback
Alerts are included for: Bullish Continuation, Bearish Continuation, STRONG Bullish, STRONG Bearish.
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S/R engine (current TF + optional HTF)
• Builds S/R from confirmed pivots only (left/right bars).
• Choose Lines (midlines) or Zones (ATR-sized).
• Zones merge when a new pivot lands near an existing zone’s mid (ATR-scaled epsilon).
• Touches counter tracks significance; you can require a minimum to draw.
• HTF overlay (default 15m) draws separate lines/zones with tiny TF tags on the right.
• De-dup option hides current-TF zones that sit too close to HTF zones (ATR-scaled), reducing overlap.
• Freeze on Close (optional) keeps arrays stable intrabar; snapshots show levels immediately as bars open.
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Presets
• Auto: Detects QQQ-like tickers (QQQ, QLD, QID) or SoFi; else defaults to Custom.
• QQQ: Tighter ATR% and EMA settings geared to index-ETF behavior.
• SoFi: Wider ATR allowances and longer mid/slow for single-name behavior.
• Custom: Expose all key inputs to tune for your product.
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Dashboard (top-right)
• Preset in use
• Bias (Bullish CONT / Bearish CONT / Neutral)
• Strong (Yes/No)
• Volatility (ATR% bucket)
• Trend (ADX bucket)
• HTF timeframe tag
• Volume (bucket or “off”)
• Signals mode (Close-Confirmed vs Intrabar)
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Inputs you’ll actually adjust
Trend/Signals
• Fast/Mid/Slow EMA lengths
• Pullback lookback, Min bars between signals
• Volume filter (vol > SMA N)
• ATR% max filter (cap excessive volatility)
• Require break of prior bar’s high/low
• “Strong” gates: min EMA slope, min EMA spacing %, ADX length & threshold
Support/Resistance
• Lines vs Zones
• Pivot left/right bars
• Extend left/right (bars)
• Max pivots kept (current & HTF)
• Zone width (× ATR), Merge epsilon (× ATR), Min gap (× ATR)
• Min touches, Max zones per side near price
• De-dup current TF vs HTF (× ATR)
Repainting control
• Confirm on Close: when ON, signals/SR finalize on bar close (non-repainting)
• Freeze on Close: freeze S/R intrabar with snapshot updates
• Show previews: translucent intrabar labels for what’s forming
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How to use it (straightforward)
1. Load on 5-minute chart (baseline). Keep Confirm on Close ON if you hate repainting.
2. Use Bias + Strong + S/R context. If a long prints into HTF resistance, you have information.
3. Manage risk off the reference stop (pullback extreme). If ATR% reads “Great,” widen expectations; if “Poor,” size down or pass.
4. Alerts: wire the four alert types to your workflow.
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Notes and constraints
• Designed for liquid symbols. Thin books and synthetic “volume” will degrade the volume gate.
• S/R is pivot-based. On very choppy tape, touch counts help. Increase min touches or switch to Lines to declutter.
• If your chart timeframe isn’t 5m, behavior changes because lengths are in bars, not minutes. Tune lengths accordingly.
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Disclaimers
This is a research tool. No signals are guaranteed. Markets change, outliers happen, slippage is real. Nothing here is financial advice—use your own judgment and risk management.
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Author: DaddyScruff
License: MPL-2.0 (Mozilla Public License 2.0)
CISD & OB [BLAZ]Version 1.0 – Published October 2025: Initial release
1. Overview & Purpose
The CISD & OB indicator identifies and plots Order Blocks (OB) and Changes in State of Delivery (CISD) on price charts using a strict rule-based approach designed to highlight structural turning points and continuation zones in price action. It automatically detects these formations when price creates confirmed swing highs or lows, followed by opposing directional moves that break predefined structural levels.
Detection logic is consistently applied across all market conditions, allowing the indicator to identify areas where notable price reactions or liquidity shifts have occurred. These levels are plotted as horizontal lines on the chart and are updated in real time to reflect the latest structural developments, helping traders visualise potential reversal or continuation zones.
The methodology used in this indicator represents the author's specific approach to Order Block and CISD identification, incorporating custom criteria for swing validation and confirmation logic that differ from standard implementations. Detection operates entirely mechanically, without discretionary intervention, to ensure consistency and objectivity across use cases. This indicator functions on all standard timeframes and supports multiple asset classes, including Forex, Stocks, Cryptocurrencies, Futures, and Commodities.
The indicator is unique in its ability to apply detection logic to a custom timeframe, enabling multi-timeframe structural analysis without switching charts. Let’s begin by explaining key terminologies based on the author’s perception to aid in understanding the functionality of the indicator.
2. Order Block (OB)
An Order Block is identified when price creates a swing high or swing low followed by a directional move that closes beyond the open of the opposing candle(s) structure.
2.1. For bearish Order Blocks:
Price must form a confirmed swing high (higher than surrounding candles).
A subsequent bearish candle must close below the open of the bullish candle(s) that created the swing high.
2.2. For bullish Order Blocks:
Price must form a confirmed swing low (lower than surrounding candles).
A subsequent bullish candle must close above the open of the bearish candle(s) that created the swing low.
The indicator only validates Order Blocks where the structural formation meets minimum swing criteria and the confirming move demonstrates sufficient momentum beyond the identified level.
3. Change in State of Delivery (CISD)
A CISD occurs when a valid Order Block forms in the opposite direction to the previously confirmed Order Block, indicating a potential shift in market structure.
3.1. Formation criteria:
A bullish CISD forms when a valid bullish Order Block is detected after the most recent confirmed structure was a bearish Order Block.
A bearish CISD forms when a valid bearish Order Block is detected after the most recent confirmed structure was a bullish Order Block.
Each CISD represents the first opposing Order Block in a sequence, distinguishing it from continuation Order Blocks that follow in the same direction.
The indicator tracks the sequence of Order Block formations to automatically classify each new structure as either a CISD (directional change) or continuation Order Block based on the preceding confirmed structure.
4. Detection Logic & Visual Management
The indicator continuously scans price action in real time, validating only those patterns that meet predefined technical thresholds. Once a structure is confirmed, it is plotted as a horizontal line extending from the origin candle’s open to the confirming close.
To maintain chart clarity, the script integrates automatic display management, limiting the number of plotted lines according to user-defined settings. Independent styling options are available for bullish and bearish structures, including colour, width, and line thickness. CISD and OB structures are styled separately to provide a clear distinction between reversal and continuation events.
Developing structures appear as dotted potential horizontal lines until they are validated, at which point they transition to solid lines. The indicator also allows users to restrict visibility of plotted lines above a selected timeframe, ensuring that higher timeframe charts remain clean and readable.
If configuration settings conflict, such as incompatible timeframe or visibility filters, the indicator displays on-chart warning messages to guide users in adjusting their setup appropriately.
The indicator supports multi-timeframe plotting capability, allowing structures identified on higher timeframes to be visualised directly on the active lower timeframe chart. This feature allows traders to observe how market structures align across multiple timeframes, providing greater confirmation of overall trend direction, reinforcing analytical confidence through cross‑timeframe confluence, and ensuring short‑term decisions remain aligned with the prevailing market context.
Traders can configure alerts to receive notifications when new CISD or OB structures are confirmed. Alerts are fully customisable via the indicator input settings and can be defined by direction (bullish/bearish) and pattern type (OB or CISD).
5. Usage Instructions
5.1. Alert Setup:
Enable "Set Alert?" toggle in indicator settings.
Configure alert preferences for specific pattern types.
On the chart, click the three dots menu beside the indicator's name or press Alt + A.
Select "Add Alert" and click “Create” to activate the alert.
Alerts trigger when new patterns are confirmed.
5.2. Display Controls:
Use "Bullish Lines" and "Bearish Lines" toggles to show/hide patterns by direction.
Adjust line quantity settings (1-25) to control how many patterns display simultaneously.
Enable “Timeframe” to apply detection logic to a higher timeframe of choice, displaying CISD and OB patterns directly on the active chart.
5.3. Visibility Filter:
Use “Show below” to limit indicator visibility to specific timeframes. When enabled, the indicator hides automatically on any timeframe equal to or higher than the selected setting.
5.4. Appearance Customisation:
Toggle “CISD” or “OB” on/off to show or hide individual pattern types.
Modify colours and line widths independently for bullish and bearish structures.
The “Show potential line” option displays developing patterns as dotted horizontal lines until confirmed.
5.5. Warning Message:
Enable “Show warning messages” to display on‑chart guidance for conflicting or invalid configurations.
Choose the preferred message box position and colour styling for readability.
6. Protected Logic & Original Design
This indicator has been developed from the ground up using proprietary algorithms and a custom structural classification logic derived from original research into Order Block and CISD identification methods. The internal mechanics, including real-time pre-confirmation logic, multi-timeframe adaptation, directional classification sequencing, and automated display management, are not based on any publicly available script or third-party resource.
7. Disclaimer
This indicator is provided for educational and analytical purposes only. It does not constitute financial advice, investment recommendations, or trading signals. All trading and investment decisions remain solely the responsibility of the user.
Trading financial instruments involves substantial risk of loss. Past performance of any trading methodology or indicator does not guarantee future results. Users should conduct their own research and consider consulting with qualified financial professionals before making trading decisions.
The indicator's pattern detection is based on technical analysis principles and should be used as part of a comprehensive trading approach. No trading tool can guarantee profitable outcomes or eliminate market risk.
By using this indicator, users acknowledge they understand these risks and accept full responsibility for their trading decisions and outcomes.
Crypto ETFs AUM📘 Description: BTC ETFs AUM Tracker
This indicator tracks the Assets Under Management (AUM) and daily inflows/outflows of the main U.S.-listed Bitcoin ETFs, allowing you to visualize institutional capital movement into Bitcoin products over time. It helps traders correlate institutional capital movement with Bitcoin price behavior.
🧩 Overview
The script adds up the daily AUM changes from selected Bitcoin ETFs to estimate the total net inflow/outflow of capital into spot BTC funds. It also accumulates those flows over time to display the total aggregated AUM balance, giving you a clearer sense of market direction and institutional sentiment. Two display modes are available: Balance view: plots the cumulative sum of net inflows (total ETF AUM). Inflows view: shows daily inflows (green) and outflows (red) as histogram columns, together with a smoothed moving average line.
⚙️ Inputs
Explained Base Settings Base Multiplier (base_multi) – Scaling factor applied to all AUM values. Leave at 1 for USD units, or adjust to display values in millions (1e6) or billions (1e9). Smoothing (c_smoothing) – Period length for the simple moving average used to calculate the smoothed mean inflow/outflow line. Show Balance (showBalance) – When enabled, displays the total cumulative AUM balance (sum of all net inflows over time). Show Inflows (showInflows) – When enabled, displays the daily inflows/outflows as colored columns. ETF Selection You can toggle which ETFs are included in the calculation:
BIT (BlackRock)
GBTC (Grayscale)
FBTC (Fidelity)
ARKB (ARK/21Shares)
BITB (Bitwise)
EZBC (Franklin Templeton)
BTCW (WisdomTree)
BTCO (Invesco Galaxy)
BRRR (Valkyrie)
HODL (VanEck)
Each switch determines whether the ETF’s AUM and daily flow data are included in the total calculation.
📊 Displayed Values Green Columns → Positive daily net inflows (AUM increased). Red Columns → Negative daily net outflows (AUM decreased). Orange Line → Smoothed moving average of net flows, used to identify persistent inflow/outflow trends. Blue Line (if enabled) → Total cumulative AUM balance (sum of all historical flows).
💡 Usage Notes Works best on daily timeframe, since ETF data is typically updated once per trading day. Not all ETFs have identical data history; missing data points are automatically skipped. The indicator doesn’t represent official fund NAV or guarantee data accuracy — it visualizes TradingView’s public financial feed. You can combine this tool with price action or on-chain metrics to analyze institutional Bitcoin flows.
Note: Some ETF data may not be available to all users depending on their TradingView data subscription or market access. Missing values are automatically skipped.
🧠 Disclaimer This script is for educational and analytical purposes only. It is not financial advice, and no investment decisions should be based solely on this indicator. Data accuracy depends on TradingView’s financial data sources and exchange reporting frequency.
Trap LineTrap Line W — Weekly Trend Barrier (Closed-source)
Overview
Trap Line W is a trend-following overlay that plots a single weekly baseline to define the market’s higher-timeframe regime. Price above the line indicates a bullish regime; price below the line indicates a bearish regime. The goal is to promote regime discipline—staying aligned with the dominant direction and avoiding late, emotionally driven entries. Core parameters are fixed to ensure consistent behavior across symbols.
What it does (principles, not secrets)
• Builds a smoothed weekly baseline designed to approximate the higher-timeframe trend path.
• Uses higher-timeframe aggregation so regime assessments align with closed weekly candles.
• Acts as a simple, binary bias filter: long-only above, short/avoid longs below (framework, not advice).
Inputs
• No user-tweakable inputs. Parameters are fixed to reduce overfitting and improve repeatability.
How to read it
• Above the line ⇒ bullish regime.
• Below the line ⇒ bearish regime.
• A confirmed weekly close through the line suggests a potential regime transition; intrawEEK moves may fade.
Practical use cases
• Bias gating: enable/disable long or short playbooks based on the weekly regime.
• Portfolio overlay: apply to a watchlist; prefer allocations aligned with the weekly regime.
• Risk context: in a bullish regime, tolerate pullbacks selectively; in a bearish regime, be conservative with counter-trend exposure.
• Timeframe bridging: weekly sets bias; lower timeframes handle entries/exits.
Best practices
• Wait for the weekly close before declaring a regime flip.
• Combine with market structure (HH/HL vs. LH/LL), volume behavior, and higher-timeframe S/R.
• Prefer time-based candles and liquid instruments for clearer behavior.
Charting & data notes
• Values derive from the weekly timeframe and finalize on the weekly close; interim values may update during formation.
• Use standard time-based candles. Avoid interpreting signals on Heikin Ashi, Renko, Kagi, Point & Figure, or Range charts.
Common pitfalls
• Front-running the weekly close can cause false regime flips.
• Overtrading counter-trend near the line often has lower expectancy.
• Ignoring liquidity/news risk can lead to whipsaws around the baseline.
Who it’s for
• Swing and position traders needing a clear, rules-based regime filter.
• Systematic traders who prefer a simple, fixed-parameter bias overlay.
Limitations & disclosures
• Closed-source; for educational and analytical use only.
• Not financial advice. Markets involve risk; past performance is not indicative of future results.
Suggested screenshot captions
• “Bullish regime: weekly close above Trap Line W; pullbacks respecting the line.”
• “Bearish regime: weekly close below Trap Line W; rallies capped near the line.”
OBV Cloud v1.0 [PriceBlance]🌐 English
OBV Cloud v1.0 – Free & Open-Source
OBV Cloud v1.0 integrates On-Balance Volume (OBV) with a Cloud model and enhanced trend filters.
It helps traders quickly identify:
Money Flow Trend: OBV Cloud acts as a dynamic support/resistance zone.
Trend Filters: EMA9 (short-term) and WMA45 (medium-term) directly applied on OBV.
OBV–Price Divergence: Detects both regular and hidden bullish/bearish divergences.
Trend Strength: Measured with ADX calculated on OBV.
OBV Cloud is suitable for both swing and day trading, allowing traders to spot breakouts, reversals, or sustained trends through volume-based analysis.
AlgoAIDESIGNED FOR HEIKEN ASHI BARS
Gain Access here: algoai.store
AlgoAI
The Dark Edge of Trading
An AI-powered TradingView strategy that thrives across all markets. Short altcoin pumps. Ride NAS100 waves. Dominate gold, FX, stocks, and futures — all with one AI brain.
#1
Semi-Automatic Trading (Recommended)
Set up alerts on AlgoAI signals. As they come in, grade the setups and choose to enter manually. This gives you full control while leveraging AI precision.
#2
Fully Automated Trading
Pass signals via webhooks to TradersPost for futures or PineConnector for FX. Note: When running fully automated, it's suggested to use long-only or short-only mode to avoid side swiping and potential unintended drawdown.
BITSTAMP:BTCUSD
Maple MomoriderMaple MomoRider is a trend-continuation algorithm crafted for highly volatile markets such as cryptocurrencies and gold (XAUUSD).
It adapts to market rhythm and volatility, identifying pullback zones where momentum continuation is more probable.
📌 Optimized for assets with strong intraday swings
📌 Best used on 15m and higher timeframes
📌 Helps traders ride the momentum with 1:2 RRR or more when combined with solid risk management
Instead of relying on static averages, Maple MomoRider employs a dynamic algorithmic filter that reacts to market conditions, making it an excellent companion for traders seeking to catch the next impulsive move in crypto or gold.
BTC Lead(v3.31)Summary
A 15-minute, BTC-focused lead/divergence indicator designed for simple execution: when a ▲/▼ appears, start scaling in with small clips; when a ■ (black square) prints, it means the indicator’s edge has weakened (not that the market trend is over). Real-time expected move label and alert templates included. Do not fade the signal—if you must try the opposite side, wait until a ■ appears.
How to read the signals
▲ Green → Long bias increased
▼ Pink → Short bias increased
■ Black → Edge weakened; consider taking profits/standing aside
Multiple level markers on the same bar (L2/L3/L4) = stronger setup
Live label (top of chart)
A single line shows the Expected Move (%) with arrow and color-coded background (↑ green / ↓ pink) for instant direction clarity.
Tip: Use Replay to watch label → ▲/▼ → ■ sequences on past data.
Confidence filter (important)
|Expected Move| < 1% → treat as noise / ignore
If considering the opposite direction, wait for a ■ first (edge reduced).
Scope
Internal calculations are fixed to 15-minute resolution.
Built for BTC 15m. It may display on other crypto symbols/timeframes, but performance is not guaranteed.
Alerts
Ready-made conditions: ENTRY LONG / ENTRY SHORT / EXIT LONG / EXIT SHORT. Add an alert on this indicator and choose the condition you want.
Risk note
For research/education only. Past behavior doesn’t guarantee future results. Predefine position sizing, stops, and profit-taking, and execute consistently.
TPO Levels [VAH/POC/VAL] with Poor H/L, Single Prints & NPOCs### 🎯 Advanced Market Profile & Key Level Analysis
This script is a unique and comprehensive technical analysis tool designed to help traders understand market structure, value, and key liquidity levels using the principles of **Auction Market Theory** and **Market Profile**.
This script is unique (and shouldn't be censored) because :
It allows large history of levels to be displayed
Accurate as possible tick size
Doesn't draw a profile but only the actual levels
Supports multi-timeframe levels even on the daily mode giving macro context
There is no indicator out there that does it
While these concepts are universal, this indicator was built primarily for the dynamic, 24/7 nature of the **cryptocurrency market**. It helps you move beyond simple price action to understand *why* the market is moving, which is especially crucial in the volatile crypto space.
### ## 📊 The Concepts Behind the Calculations
To use this script effectively, it's important to understand the core concepts it is built upon. The entire script is self-contained and does not require other indicators.
* **What is Market Profile?**
Market Profile is a unique charting technique that organizes price and time data to reveal market structure. It's built from **Time Price Opportunities (TPOs)**, which are 30-minute periods of market activity. By stacking these TPOs, the script builds a distribution, showing which price levels were most accepted (heavily traded) and which were rejected (lightly traded) during a session.
* **What is the Value Area (VA)?**
The Value Area is the heart of the profile. It represents the price range where **70%** of the session's trading volume occurred. This is considered the "fair value" zone where both buyers and sellers were in general agreement.
* **Point of Control (POC):** The single price level with the most TPOs. This was the most accepted or "fairest" price of the session and acts as a gravitational line for price.
* **Value Area High (VAH):** The upper boundary of the 70% value zone.
* **Value Area Low (VAL):** The lower boundary of the 70% value zone.
VAH and VAL are dynamic support and resistance levels. Trading outside the previous session's value area can signal the start of a new trend.
***
### ## 📈 Key Features Explained
This script automatically calculates and displays the following critical market-generated information:
* **Multi-Timeframe Market Profile**
Automatically draws Daily, Weekly, and Monthly profiles, allowing you to analyze market structure across different time horizons. The script preserves up to 20 historical sessions to provide deep market context.
* **Naked Point of Control (nPOC)**
A "Naked" POC is a Point of Control from a previous session that has **not** been revisited by price. These levels often act as powerful magnets for price, representing areas of unfinished business that the market may seek to retest. The script tracks and displays Daily, Weekly, and Monthly nPOCs until they are touched.
* **Single Prints (Imbalance Zones)**
A Single Print is a price level where only one TPO traded during the session's development. This signifies a rapid, aggressive price move and an imbalanced market. These areas, like gaps in a traditional chart, are frequently revisited as the market seeks to "fill in" these thin parts of the profile.
* **Poor Structure (Unfinished Auctions)**
A **Poor High** or **Poor Low** occurs when the top or bottom of a profile is flat, with two or more TPOs at the extreme price. This suggests that the auction in that direction was weak and inconclusive. These weak structures often signal a high probability that price will eventually break that high or low.
***
### ## 💡 How to Use This Indicator
This tool is not a signal generator but an analytical framework to improve your trading decisions.
1. **Determine Market Context:** Start by asking: Is the current price trading *inside* or *outside* the previous session's Value Area?
* **Inside VA:** The market is in a state of balance or range-bound. Look for trades between the VAH and VAL.
* **Outside VA:** The market is in a state of imbalance and may be starting a trend. Look for continuation or acceptance of prices outside the prior value.
2. **Identify Key Levels:**
* Use historical **nPOCs** as potential profit targets or areas to watch for a price reaction.
* Treat historical **VAH** and **VAL** levels as significant support and resistance zones.
* Note where **Single Prints** are. These are often price magnets that may get "filled" in the future.
3. **Spot Weakness:**
* A **Poor High** suggests weak resistance that may be easily broken.
* A **Poor Low** suggests weak support, signaling a potential for a continued move lower if broken.
***
### ## ⚙️ Customization & Crypto Presets
The indicator is highly customizable, allowing you to change colors, transparency, the number of historical sessions, and more.
To help traders get started quickly, the indicator includes **built-in layout presets** specifically calibrated for major cryptocurrencies: ** BINANCE:BTCUSDT.P , BINANCE:ETHUSDT.P , and BINANCE:SOLUSDT.P **. These presets automatically adjust key visual parameters to better suit the unique price characteristics and volatility of each asset, providing an optimized view right out of the box.
***
### ## ⚠️ Disclaimer
This indicator is a tool for market analysis and should not be interpreted as direct buy or sell signals. It provides information based on historical price action, which does not guarantee future results. Trading involves significant risk, and you should always use proper risk management. This script is designed for use on standard chart types (e.g., Candlesticks, Bar) and may produce misleading information on non-standard charts.
Extended Majors Rotation System | AlphaNattExtended Majors Rotation System | AlphaNatt
A sophisticated cryptocurrency rotation system that dynamically allocates capital to the strongest trending major cryptocurrencies using multi-layered relative strength analysis and adaptive filtering techniques.
"In crypto markets, the strongest get stronger. This system identifies and rides the leaders while avoiding the laggards through mathematical precision."
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📊 SYSTEM OVERVIEW
The Extended Majors Rotation System (EMRS) is a quantitative momentum rotation strategy that:
Analyzes 10 major cryptocurrencies simultaneously
Calculates relative strength between all possible pairs (45 comparisons)
Applies fractal dimension analysis to identify trending behavior
Uses adaptive filtering to reduce noise while preserving signals
Dynamically allocates to the mathematically strongest asset
Implements multi-layer risk management through market regime filters
Core Philosophy:
Rather than trying to predict which cryptocurrency will perform best, the system identifies which one is already performing best relative to all others and maintains exposure until leadership changes.
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🎯 WHAT MAKES THIS SYSTEM UNEQUIVOCALLY UNIQUE
1. True Relative Strength Matrix
Unlike simple momentum strategies that look at individual asset performance, EMRS calculates the complete relative strength matrix between all assets. Each asset is compared against every other asset using fractal analysis, creating a comprehensive strength map of the entire crypto market.
2. Hurst Exponent Integration
The system employs the Hurst Exponent to distinguish between:
Trending behavior (H > 0.5) - where momentum is likely to persist
Mean-reverting behavior (H < 0.5) - where reversals are likely
Random walk (H ≈ 0.5) - where no edge exists
This ensures the system only takes positions when mathematical evidence of persistence exists.
3. Dual-Layer Filtering Architecture
Combines two advanced filtering techniques:
Laguerre Polynomial Filters: Provides low-lag smoothing with minimal distortion
Kalman-like Adaptive Smoothing: Adjusts filter parameters based on market volatility
This dual approach preserves important price features while eliminating noise.
4. Market Regime Awareness
The system monitors overall crypto market conditions through multiple lenses and only operates when:
The broad crypto market shows positive technical structure
Sufficient trending behavior exists across major assets
Risk conditions are favorable
5. Rank-Based Selection with Trend Confirmation
Rather than simply choosing the top-ranked asset, the system requires:
High relative strength ranking
Positive individual trend confirmation
Alignment with market regime
This multi-factor approach reduces false signals and whipsaws.
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🛡️ SYSTEM ROBUSTNESS & DEVELOPMENT METHODOLOGY
Pre-Coding Design Philosophy
This system was completely designed before any code was written . The mathematical framework, indicator selection, and parameter ranges were determined through:
Theoretical analysis of market microstructure
Study of persistence and mean reversion in crypto markets
Mathematical modeling of relative strength dynamics
Risk framework development based on regime theory
No Post-Optimization
Zero parameter fitting: All parameters remain at their originally designed values
No curve fitting: The system uses the same settings across all market conditions
No cherry-picking: Parameters were not adjusted after seeing results
This approach ensures the system captures genuine market dynamics rather than historical noise
Parameter Robustness Testing
Extensive testing was conducted to ensure stability:
Sensitivity Analysis: System maintains positive expectancy across wide parameter ranges
Walk-Forward Analysis: Consistent performance across different time periods
Regime Testing: Performs in both trending and choppy conditions
Out-of-Sample Validation
System was designed on a selection of 10 assets
System was tested on multiple baskets of 10 other random tokens, to simualte forwards testing
Performance remains consistent across baskets
No adjustments made based on out-of-sample results
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📈 PERFORMANCE METRICS DISPLAYED
The system provides real-time performance analytics:
Risk-Adjusted Returns:
Sharpe Ratio: Measures return per unit of total risk
Sortino Ratio: Measures return per unit of downside risk
Omega Ratio: Probability-weighted ratio of gains vs losses
Maximum Drawdown: Largest peak-to-trough decline
Benchmark Comparison:
Live comparison against Bitcoin buy-and-hold strategy
Both equity curves displayed with gradient effects
Performance metrics shown for both strategies
Visual representation of outperformance/underperformance
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🔧 OPERATIONAL MECHANICS
Asset Universe:
The system analyzes 10 major cryptocurrencies, customizable through inputs:
Bitcoin (BTC)
Ethereum (ETH)
Solana (SOL)
XRP
BNB
Dogecoin (DOGE)
Cardano (ADA)
Chainlink (LINK)
Additional majors
Signal Generation Process:
Calculate relative strength matrix
Apply Hurst Exponent analysis to each ratio
Rank assets by aggregate relative strength
Confirm individual asset trend
Verify market regime conditions
Allocate to highest-ranking qualified asset
Position Management:
Single asset allocation (no diversification)
100% in strongest trending asset or 100% cash
Daily rebalancing at close
No leverage employed in base system
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📊 VISUAL INTERFACE
Information Dashboard:
System state indicator (ON/OFF)
Current allocation display
Real-time performance metrics
Sharpe, Sortino, Omega ratios
Maximum drawdown tracking
Net profit multiplier
Equity Curves:
Cyan curve: System performance with gradient glow effect
Magenta curve: Bitcoin HODL benchmark with gradient
Visual comparison of both strategies
Labels indicating current values
Alert System:
Alerts fire when allocation changes
Displays selected asset symbol
"CASH" alert when system goes defensive
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⚠️ IMPORTANT CONSIDERATIONS
Appropriate Use Cases:
Medium to long-term crypto allocation
Systematic approach to crypto investing
Risk-managed exposure to cryptocurrency markets
Alternative to buy-and-hold strategies
Limitations:
Daily rebalancing required
Not suitable for high-frequency trading
Requires liquid markets for all assets
Best suited for spot trading (no derivatives)
Risk Factors:
Cryptocurrency markets are highly volatile
Past performance does not guarantee future results
System can underperform in certain market conditions
Not financial advice - for educational purposes only
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🎓 THEORETICAL FOUNDATION
The system is built on several academic principles:
1. Momentum Anomaly
Extensive research shows that assets exhibiting strong relative momentum tend to continue outperforming in the medium term (Jegadeesh & Titman, 1993).
2. Fractal Market Hypothesis
Markets exhibit fractal properties with periods of persistence and mean reversion (Peters, 1994). The Hurst Exponent quantifies these regimes.
3. Adaptive Market Hypothesis
Market efficiency varies over time, creating periods where momentum strategies excel (Lo, 2004).
4. Cross-Sectional Momentum
Relative strength strategies outperform time-series momentum in cryptocurrency markets due to the high correlation structure.
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💡 USAGE GUIDELINES
Capital Requirements:
Suitable for any account size
No minimum capital requirement
Scales linearly with account size
Implementation:
Can be traded manually with daily signals
Suitable for automation via alerts
Works with any broker supporting crypto
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📝 FINAL NOTES
The Extended Majors Rotation System represents a systematic, mathematically-driven approach to cryptocurrency allocation. By combining relative strength analysis with fractal market theory and adaptive filtering, it aims to capture the persistent trends that characterize crypto bull markets while avoiding the drawdowns of buy-and-hold strategies.
The system's robustness comes not from optimization, but from sound mathematical principles applied consistently. Every component was chosen for its theoretical merit before any backtesting occurred, ensuring the system captures genuine market dynamics rather than historical artifacts.
"In the race between cryptocurrencies, bet on the horse that's already winning - but only while the track conditions favour racing."
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Developed by AlphaNatt | Quantitative Rotation Systems
Version: 1.0
Strategy Type: Momentum Rotation
Classification: Systematic Trend Following
Not financial advice. Always DYOR.
Bitcoin vs. Gold correlation with lagBTC vs Gold (Lag) + Correlation — multi-timeframe, publication notes
What it does
Plots Gold on the same chart as Bitcoin, with a configurable lead/lag.
Lets you choose how the series is displayed:
Gold shifted forward (+lag on chart) — shows gold ahead of BTC on the time axis (visual offset).
Gold aligned to BTC (gold lag) — standard alignment; gold is lagged for calculation and plotted in place.
BTC 200D Lag (BTC shifted forward) — visualizes BTC shifted forward (like popular “BTC 200D Lag” charts).
Computes Pearson correlations between BTC (no lag) and Gold (with lag) over multiple lookback windows equivalent to:
30d, 60d, 90d, 180d, 365d, 2y (730d), 3y (1095d), 5y (1825d).
Shows a table with the correlation values, automatically scaled to the current timeframe.
Why this is useful
A common macro claim is that BTC tends to follow Gold with a delay (e.g., ~200 trading days). This tool lets you:
Visually advance Gold (or BTC) to see that lead-lag relationship on the chart.
Quantify the relationship with rolling correlations.
Switch timeframes (D/W/M/…): everything automatically stays in sync.
Quick start
Open a BTC chart (any exchange).
Add the indicator.
Set Gold symbol (default TVC:GOLD; alternatives: OANDA:XAUUSD, COMEX:GC1!, etc.).
Choose Lag value and Lag unit (Days/Weeks/Months/Years/Bars).
Pick Visual Mode:
To mirror those “BTC 200D Lag” posts: choose “BTC 200D Lag (BTC shifted forward)” with 200 Days.
To view Gold 200D ahead of BTC: select “Gold shifted forward (+lag on chart)” with 200 Days.
Keep Rebase to 100 ON for an apples-to-apples visual scale. (You can move the study to the left price scale if needed.)
Inputs
Gold symbol: external series to pair with BTC.
Lag value: numeric value.
Lag unit: Days, Weeks, Months (≈30d), Years (≈365d), or direct Bars.
Visual mode:
Gold shifted forward (+lag on chart) → gold is offset to the right by the lag (visual only).
Gold aligned to BTC (gold lag) → standard plot (no visual offset); correlations still use lagged gold.
BTC 200D Lag (BTC shifted forward) → BTC is offset to the right by the lag (visual only).
Rebase to 100 (visual): rescales each series to 100 on its first valid bar for clearer comparison.
Show gold without lag (debug): optional reference line.
Show price tag for gold (lag): toggles the track price label.
Timeframe handling
The study uses the current chart timeframe for both BTC and Gold (timeframe.period).
Lag in time units (Days/Weeks/Months/Years) is internally converted to an integer number of bars of the active timeframe (using timeframe.in_seconds).
Example: on W (weekly), 200 days ≈ 29 bars.
On intraday timeframes, days are converted proportionally.
Correlation math
Correlation = ta.correlation(BTC, Gold_lagged, length_in_bars)
Lookback lengths are the bar-equivalents of 30/60/90/180/365/730/1095/1825 days in the active timeframe.
Important: correlations are computed on prices (not returns). If you prefer returns-based correlation (often more statistically robust), duplicate the script and replace price inputs with change(close) or ta.roc(close, 1).
Reading the table
Window: nominal day label (e.g., 30d, 1y, 5y).
Bars (TF): how many bars that window equals on the current timeframe.
Correlation: Pearson coefficient . Background tint shows intensity and sign.
Tips & caveats
Visual offsets (offset=) move series on screen only; they don’t affect the math. The math always uses BTC (no lag) × Gold (lagged).
With large lags on high timeframes, early bars will be na (normal). Scroll forward / reduce lag.
If your Gold feed doesn’t load, try an alternative symbol that your plan supports.
Rebase to 100 helps visibility when BTC ($100k) and Gold ($2k) share a scale.
Months/Years use 30/365-day approximations. For exact control, use Days or Bars.
Correlations on very short lengths or sparse data can be unstable; consider the longer windows for sturdier signals.
This is a visual/analytical tool, not a trading signal. Always apply independent risk management.
Suggested setups
Replicate “BTC 200D Lag” charts:
Visual Mode: BTC 200D Lag (BTC shifted forward)
Lag: 200 Days
Rebase: ON
Gold leads BTC (Gold ahead):
Visual Mode: Gold shifted forward (+lag on chart)
Lag: 200 Days
Rebase: ON
Compatibility: Pine v6, overlay study.
Best with: BTCUSD (any exchange) + a reliable Gold feed.
Author’s note: Lead-lag relationships are not stable over time; treat correlations as descriptive, not predictive.
Algorithmic Kalman Filter [CRYPTIK1]Price action is chaos. Markets are driven by high-frequency algorithms, emotional reactions, and raw speculation, creating a constant stream of noise that obscures the true underlying trend. A simple moving average is too slow, too primitive to navigate this environment effectively. It lags, it gets chopped up, and it fails when you need it most.
This script implements an Algorithmic Kalman Filter (AKF), a sophisticated signal processing algorithm adapted from aerospace and robotic guidance systems. Its purpose is singular: to strip away market noise and provide a hyper-adaptive, self-correcting estimate of an asset's true trajectory.
The Concept: An Adaptive Intelligence
Unlike a moving average that mindlessly averages past data, the Kalman Filter operates on a two-step principle: Predict and Update.
Predict: On each new bar, the filter makes a prediction of the true price based on its previous state.
Update: It then measures the error between its prediction and the actual closing price. It uses this error to intelligently correct its estimate, learning from its mistakes in real-time.
The result is a flawlessly smooth line that adapts to volatility. It remains stable during chop and reacts swiftly to new trends, giving you a crystal-clear view of the market's real intention.
How to Wield the Filter: The Core Settings
The power of the AKF lies in its two tuning parameters, which allow you to calibrate the filter's "brain" to any asset or timeframe.
Process Noise (Q) - Responsiveness: This controls how much you expect the true trend to change.
A higher Q value makes the filter more sensitive and responsive to recent price action. Use this for highly volatile assets or lower timeframes.
A lower Q value makes the filter smoother and more stable, trusting that the underlying trend is slow-moving. Use this for higher timeframes or ranging markets.
Measurement Noise (R) - Smoothness: This controls how much you trust the incoming price data.
A higher R value tells the filter that the price is extremely noisy and to be more skeptical. This results in a much smoother, slower-moving line.
A lower R value tells the filter to trust the price data more, resulting in a line that tracks price more closely.
The interaction between Q and R is what gives the filter its power. The default settings provide a solid baseline, but a true operator will fine-tune these to perfectly match the rhythm of their chosen market.
Tactical Application
The AKF is not just a line; it's a complete framework for viewing the market.
Trend Identification: The primary signal. The filter's color code provides an unambiguous definition of the trend. Teal for an uptrend, Pink for a downtrend. No more guesswork.
Dynamic Support & Resistance: The filter itself acts as a dynamic level. Watch for price to pull back and find support on a rising (Teal) filter in an uptrend, or to be rejected by a falling (Pink) filter in a downtrend.
A Higher-Order Filter: Use the AKF's trend state to filter signals from your primary strategy. For example, only take long signals when the AKF is Teal. This single rule can dramatically reduce noise and eliminate low-probability trades.
This is a professional-grade tool for traders who are serious about gaining a statistical edge. Ditch the lagging averages. Extract the signal from the noise.
Crypto Position CalculatorAlpha2Million - Crypto Position Calculator (Margin, Leverage, % Fees, Exchange Presets)
This script is a crypto trading risk & position calculator built directly into TradingView.
It helps futures/perpetual traders size positions, calculate margin requirements, and visualize risk-to-reward levels on the chart — with exchange fee presets for real-world accuracy.
• Position Sizing by Risk %
• Enter account size and % risk per trade.
• Script calculates exact position size (coins) based on SL distance.
• Leverage & Margin
• Shows required notional and margin (USDT) for the trade.
• Exchange Fee Presets
• Supports Binance, Bybit, Pionex, MEXC, Gate.io, KuCoin, HTX.
• Maker vs Taker fee selection.
• Custom option to enter your own per-side fee %.
• Fee Breakeven Line (Orange)
• Plots the exact price level you need to reach to cover entry + exit fees.
• Lets you see how far price must move before you are at true breakeven.
• Risk vs Reward Calculation
• Risk is calculated on price movement only (SL distance).
• Profit targets include fees, so “1R / 2R / 3R (net)” lines show realistic levels.
• Smart Table Display
• Account size, leverage, entry, stop, target.
• Position size (coins), notional (USDT), required margin.
• Risk at SL, fees (round trip), fee breakeven move/price.
• Profit @ TP (after fees) and net RR.
EWC Precision Blocks📌 EWC Precision Blocks
🔎 Overview
EWC Precision Blocks is a professional market analysis tool designed to highlight high-probability trading zones on the chart. Instead of relying on lagging signals, this indicator maps out Alpha Zones (bullish) and Beta Zones (bearish), allowing traders to identify potential market reaction areas with clarity.
The algorithm is built to adapt across Scalp, Swing, and Position trading modes, making it flexible for short-term intraday traders as well as long-term investors.
⚡ Key Features
Multi-Mode Detection – Switch between Scalp, Swing, or Position modes depending on your trading style.
EWC Alpha Zone (Bullish Detection) – Highlights areas where the market may find strong upward momentum.
EWC Beta Zone (Bearish Detection) – Highlights areas where the market may face downward pressure.
Zone Break Tracking – Visualizes when a zone has been invalidated or broken.
Body-Based Detection – Option to base calculations on candle bodies instead of wicks for precision.
Zone Flips – Displays polarity shifts when zones transition from supportive to resistive behavior (and vice versa).
Custom Styling – Full control of zone and break colors for clear chart visualization.
🎯 How to Use
Select Your Mode
Scalp → Designed for fast intraday moves.
Swing → Medium-term setups, ideal for session trading.
Position → Long-term outlook, suitable for investors.
Watch the Alpha Zones
Highlighted bullish areas can serve as potential support or accumulation zones.
Watch the Beta Zones
Highlighted bearish areas may act as resistance or distribution zones.
Monitor Breaks & Flips
Alpha Breaks → Bullish zones failing.
Beta Breaks → Bearish zones failing.
Zone Flips → Polarity changes, often powerful signals.
🛠 Inputs & Customization
EWC Mode → Choose Scalp, Swing, or Position.
Show Last Alpha Zone → Set how many bullish zones to display.
Show Last Beta Zone → Set how many bearish zones to display.
Body-Based Detection → Toggle candle body vs. wick calculation.
EWC Alpha Zone / Beta Zone Styling → Customize zone colors.
Alpha Break / Beta Break Colors → Adjust break visuals.
Show Zone Flips → Enable/disable historical polarity labels.
Status Bar → Display inputs directly in the chart status line.
📈 Best Practices
Works across all timeframes and markets (forex, crypto, indices, stocks).
Combine with your existing strategy for confirmation.
Use in alignment with higher timeframe structure for maximum accuracy.
⚠ Disclaimer
EWC Precision Blocks is a market visualization tool provided for educational purposes only. It does not provide financial advice, signals, or guaranteed results. Always do your own research and manage risk responsibly.
🔹 About EWC
EWC (EastWave Capital) is dedicated to developing professional-grade trading tools and strategies for traders across forex, crypto, commodities, and indices. With over a decade of combined market experience, our mission is to empower traders with precision, clarity, and confidence in their decision-making.
EWC Precision Blocks is one of our flagship tools, reflecting our commitment to innovation, transparency, and trader-focused solutions.
📌 Published by Usama Manzoor — Founder of EastWave Capital (EWC)
DEE's Indicator v2 — Daily Range, Averages & Previous High/Low🇺🇸 English
This indicator is designed to help traders analyze market volatility and daily price ranges.
It includes the following features:
• 5-bar analysis: Shows high-low ranges and percentage changes of the last 5 bars.
• Daily Average Range: Calculates daily average ranges based on the last 5 bars.
• Daily AVG Lines: Plots expected top and bottom range levels based on the daily average.
• Previous Day High/Low: Automatically draws lines from the previous day's high and low.
• Timeframe Separators: Adds visual separators between days, months, and years.
• Optional arrows: Displays arrow markers for the last detected bars used in the calculation.
Use cases:
● Intraday traders can quickly measure daily progress compared to the average daily range.
● Swing traders can identify support/resistance levels from previous daily highs and lows.
● Risk managers can monitor when current volatility deviates significantly from the average.
⚠️ Notes:
The script does not generate buy/sell signals; it provides analytical tools only.
All displayed information is for visual/educational purposes and should be combined with your own trading strategy.
👉 Don’t forget to adjust the settings to suit your needs.
If you are using a multi-chart layout with different timeframes and apply this indicator to each chart, the 5-bar data will be calculated separately based on each chart’s TF. However, the “Daily AVG” section will always show the same value for the 1D timeframe.
🇺🇿 O‘zbekcha
Ushbu indikator treyderlarga bozor volatilligi va kundalik narx diapazonlarini tahlil qilishda yordam berish uchun mo‘ljallangan.
Unda quyidagi funksiyalar mavjud:
• 5-bar tahlili: So‘nggi 5 ta bar diapazoni (high–low) va foiz o‘zgarishini ko‘rsatadi.
• Kundalik o‘rtacha diapazon: So‘nggi 5 ta bar asosida o‘rtacha kundalik diapazonni hisoblaydi.
• AVG Lines: Daily AVGning yuqori va pastki diapazon darajalarini chizadi.
• Oldingi kunning High/Low darajalari: Avtomatik ravishda oldingi kunning high va low darajalarini chizadi.
• Vaqt ajratgichlari: Kunlar, oylar va yillar orasiga vizual ajratgich qo‘shadi.
• Ixtiyoriy strelkalar: Hisoblash uchun foydalanilgan so‘nggi barlarda strelka belgilarini ko‘rsatadi.
Qo‘llanilishi:
● Intraday treyderlar kundalik natijani o‘rtacha kundalik diapazon bilan tezda solishtira olishadi.
● Swing treyderlar oldingi kunning high va low darajalaridan qo‘llab-quvvatlash/qarshilik darajalarini aniqlashlari mumkin.
● Risk-menejerlar hozirgi volatillik o‘rtachadan sezilarli darajada og‘ib ketganini kuzatishlari mumkin.
⚠️ Eslatma:
Ushbu indikator sotib olish/sotish signallarini bermaydi; u faqat tahliliy vosita sifatida ishlatiladi.
Ko‘rsatilgan barcha ma’lumotlar vizual/ta’limiy maqsadlarda mo‘ljallangan bo‘lib, o‘z strategiyangiz bilan birgalikda qo‘llanilishi lozim.
👉 Sozlamalarni ehtiyojlaringizga qarab moslashtirishni unutmang.
Agar siz multi-chart rejimida turli timeframelar bilan ishlasangiz va ushbu indikatorni har bir grafikda qo‘llasangiz, 5 ta bar haqidagi ma’lumotlar har bir grafikning o‘z TFiga qarab hisoblanadi. Ammo “Daily AVG” bo‘limida esa faqat 1D timeframe uchun bir xil qiymat ko‘rsatiladi.
🇷🇺 Русский
Этот индикатор предназначен для помощи трейдерам в анализе волатильности рынка и дневных ценовых диапазонов.
Он включает в себя следующие функции:
• Анализ 5 свечей: Показывает диапазон high–low и процентные изменения последних 5 свечей.
• Средний дневной диапазон: Рассчитывает средний дневной диапазон на основе последних 5 свечей.
• Линии среднего диапазона (AVG Lines): Строит ожидаемые верхние и нижние уровни диапазона на основе среднего дневного значения.
• Максимум/минимум предыдущего дня: Автоматически наносит линии с уровнями high и low предыдущего дня.
• Разделители временных интервалов: Добавляет визуальные разделители между днями, месяцами и годами.
• Опциональные стрелки: Показывает стрелки на последних свечах, использованных в расчётах.
Применение:
● Интрадей-трейдеры могут быстро измерять дневное движение по сравнению со средним дневным диапазоном.
● Свинг-трейдеры могут определять уровни поддержки/сопротивления по максимумам и минимумам предыдущего дня.
● Риск-менеджеры могут контролировать ситуации, когда текущая волатильность значительно отклоняется от среднего.
⚠️ Примечания:
Этот индикатор не генерирует сигналы на покупку/продажу; он предоставляет только аналитические инструменты.
Вся отображаемая информация предназначена для визуальных/образовательных целей и должна использоваться совместно с вашей торговой стратегией.
👉 Не забудьте настроить параметры под свои нужды.
Если вы работаете в режиме мульти-графика с разными таймфреймами и применяете этот индикатор на каждом графике, данные по 5 барам будут рассчитываться отдельно для каждого ТФ. Однако в разделе “Daily AVG” всегда отображается одно и то же значение для таймфрейма 1D.
© Dilshod Nurmatov Shuhratovich | deetradesonline | 2025
