Daily Volume Ratio Bands (20MA)
Daily Volume Ratio Bands (20MA) — by CryptoDaily
This indicator normalizes daily trading volume against the recent 20-day moving average (20MA) and plots it as a volume ratio.
It allows traders to quickly identify whether current volume is strong, weak, or within a normal range compared to historical averages.
Key Features
Normalized volume ratio with 20-day average = baseline (1.0)
Clear bands for easy interpretation (1.0 ~ 1.3 = normal, above = overheated, below = weak)
Intuitive color coding:
🟨 Yellow: Normal range (1.0 ~ 1.3)
🔵 Blue: Above 1.3× average (high/strong volume, breakout confirmation)
⚪️ Gray: Below average (low volume)
🔴 Red: At or below 0.7× (extremely low volume / lack of interest)
How to Use
Breakouts with strong volume (Blue) → higher confidence in trend continuation
Gray/Red during consolidation → signal of weak momentum or sideways phase
Quickly assess whether the market is in overheated or low-activity conditions
Notes
Designed for Daily timeframe (1D) only. It will not function properly on intraday charts.
For educational purposes only. This is not financial advice.
Author
CryptoDaily (YouTube & TradingView)
YouTube channel: cryptodaily_tv
A-trend
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
RB — Rejection Blocks (Price Structure)This indicator detects and visualizes Rejection Blocks (RBs) using pure price action logic.
A bullish RB occurs when a down candle forms a lower low than both its neighbors. A bearish RB occurs when an up candle forms a higher high than both its neighbors.
Validated RBs are displayed as boxes, optional lines, or labels. Blocks are automatically removed when invalidated (price closes through them), keeping the chart uncluttered and focused.
How to use
• Apply on any timeframe, from intraday to higher timeframes.
• Watch how price reacts when revisiting RB zones.
• Treat these zones as contextual areas, not entry signals.
• Combine with your own trading methods for confirmation.
Originality
Unlike generic support/resistance tools, this indicator isolates a specific structural pattern (rejection blocks) and renders it visually on the chart. This selective focus allows traders to study structural reactions with more clarity and precision.
⚠️ Disclaimer: This is not a trading system or a signal provider. It is a visual analysis tool designed for structural and educational purposes.
Smart Structure Breaks & Order BlocksOverview (What it does)
The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition.
Main Components
Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points.
BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover.
OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone.
Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states.
Input Parameters
Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings.
Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten.
Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows.
Show Swing Points (default ON): Displays triangles on swing highs/lows.
Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover).
Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF).
Signal Definition & Logic
Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel.
BOS (Break of Structure):
Bullish – close breaks last swing high.
Bearish – close breaks last swing low.
Only one valid BOS per swing (avoids duplicates).
OB Detection:
Bullish BOS → previous bearish candle with lowest low forms the OB.
Bearish BOS → previous bullish candle with highest high forms the OB.
Zones: Bull = green, Bear = red, semi-transparent, extended to the right.
Zone States:
Mitigated: Price touches the zone → border highlighted.
Invalidated:
Bull zone → close below → turns red.
Bear zone → close above → turns green.
Chart Appearance
Swing High: red triangle above bar
Swing Low: green triangle below bar
Bull OB: green zone (border highlighted on touch)
Bear OB: red zone (border highlighted on touch)
Invalid Zones: Bull zones turn reddish, Bear zones turn greenish
Practical Use (Trading Assistance)
Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends.
Focus on First Touch: First mitigation after BOS often has higher reaction probability.
Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.).
Stops/Targets:
Bull – stop below zone, partial take profit at swing high or resistance.
Bear – stop above zone, partial take profit at swing low or support.
Parameter Tuning (per market/timeframe)
Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise.
Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals.
Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments.
Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones.
Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter.
Strengths
Standardizes BOS and OB detection that is usually subjective.
Tracks mitigation and invalidation automatically.
Adaptable: allows body/wick zone switching for different instruments.
Limitations
Pivot-based: Signals appear only after pivots confirm (slight lag).
Zones reflect past balance: Can fail after new events (news, earnings, macro data).
Range-heavy markets: More false BOS; consider stricter settings.
Backtesting: This script is for drawing/visual aid; trading rules must be defined separately.
Workflow Example
Identify higher timeframe trend (4H/Daily).
On lower TF (15–60m), wait for BOS and new OB.
Enter on first mitigation with confirmation candle.
Stop beyond zone; targets based on R multiples and swing points.
FAQ
Q: Why are zones invalidated quickly?
A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise.
Q: What does “tagged” mean?
A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled.
Q: Body or Wick zones?
A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas.
Customization Tips (Code perspective)
Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones.
Automated testing: Add strategy.entry/exit for rule-based backtests.
Multi-timeframe: Use request.security() for higher timeframe swings/BOS.
Visualization: Add labels for BOS bars, tag zones with IDs, count touches.
Summary
This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
ADX Tide ZonesADX Tide Zones – Adaptive Momentum & Trend Strength Framework
Overview
ADX Tide Zones – Professional is a dynamic trend-strength visualizer designed for traders who want to interpret momentum with precision and context. By combining the Average Directional Index (ADX) with adaptive threshold logic, the indicator segments price action into distinct “tide zones” that reflect varying levels of market strength: Calm, Rising, Strong, and Falling Tides. These zones transform raw ADX readings into an interpretable framework that highlights when markets are consolidating, building momentum, trending strongly, or losing strength.
Unlike standard ADX readings, which can be difficult to interpret in real time, ADX Tide Zones translate momentum shifts into a continuous, color-coded system that traders can instantly read. Whether applied to scalping, intraday, or swing trading, the indicator offers a consistent methodology for identifying actionable opportunities across assets and timeframes.
How It Works
The foundation of ADX Tide Zones lies in momentum analysis via the ADX. By measuring the strength (not direction) of a trend, ADX provides an objective read on when markets are gaining or losing energy. ADX Tide Zones enhances this by applying threshold logic to classify ADX values into four distinct states:
Calm Tide : Low ADX values indicate sideways or consolidating conditions.
Rising Tide : ADX increases past a threshold, signaling momentum building.
Strong Tide : ADX remains elevated, confirming robust and sustained trend strength.
Falling Tide : ADX declines after strength, hinting at exhaustion or early reversal setups.
These states are displayed on the chart through adaptive visualizations (zones, bar colors, or overlays), offering real-time clarity on when to expect expansion, continuation, or contraction in price action.
Interpretation
Trend Analysis : By mapping transitions between tides, traders can instantly gauge whether markets are in accumulation, expansion, or exhaustion phases. Rising/Strong Tides reinforce trend continuation, while Falling Tides highlight weakening conditions.
Volatility & Risk Assessment : Shifts between Calm → Rising Tide often precede volatility expansions. Falling Tides can signal a period of compression or corrective moves, warning traders to manage risk proactively.
Market Context : The indicator does not dictate direction; instead, it overlays strength on top of price action, allowing traders to combine it with directional tools such as moving averages, order blocks, or liquidity zones for confirmation.
Strategy Integration
ADX Tide Zones adapts seamlessly to a wide range of trading strategies by translating momentum dynamics into actionable frameworks:
Trend Following : Traders can align with dominant flows by entering positions when the indicator confirms a Rising Tide or Strong Tide. These conditions signal persistent directional strength, making them ideal for continuation setups. Combining directional bias with ADX confirmation reduces the risk of trading against prevailing momentum.
Breakout Trading : When the market transitions from Calm Tide into a Rising Tide, it often precedes a volatility expansion. This shift highlights breakout conditions where accumulation gives way to impulsive price movement. Traders can use this transition as a timing tool to catch early entries into new momentum phases.
Exhaustion Reversals : Strong Tide phases don’t last forever—when they begin to fade into Falling Tide, it can mark trend fatigue or liquidity exhaustion. This offers contrarian traders an early edge in spotting overextended moves and positioning for corrective pullbacks or full reversals.
Multi-Timeframe Analysis : By overlaying higher timeframe tide zones on intraday or scalping charts, traders can filter noise and trade in alignment with larger flows. For example, combining a daily Rising Tide bias with a 15-minute breakout confirmation can significantly improve entry precision while reducing exposure to false signals.
Advanced Techniques
For traders seeking an extra edge, ADX Tide Zones can be pushed further with advanced methods:
Volume & Liquidity Confirmation : Pair the tide transitions with volume spikes, order flow, or liquidity sweep tools. When directional strength confirmed by the ADX coincides with institutional activity, it validates setups and increases probability of follow-through.
Cross-Asset Synchronization : Momentum rarely exists in isolation. Monitoring tide shifts across correlated instruments (e.g., majors vs. USD, or indices vs. risk assets) can uncover synchronized volatility events. These correlations help traders identify whether a move is isolated noise or part of a broader systemic trend.
Threshold Optimization : The sensitivity of ADX Tide Zones can be fine-tuned for different trading objectives. Lower thresholds heighten responsiveness, capturing micro-moves suitable for scalpers. Higher thresholds filter minor fluctuations, isolating major structural swings that align with swing or position trading.
Contextual Trade Management : Instead of using static stops or targets, traders can adapt risk management dynamically by tracking tide progression. For example, a trade initiated during Rising Tide may remain valid as long as conditions sustain, but partial profits or tighter stops can be applied once the zone shifts to Calm Tide.
Inputs & Customization
ADX Length : Define the lookback period for ADX calculation.
Threshold Levels : Adjust sensitivity for Calm, Rising, Strong, and Falling Tides.
Zone Visualization : Choose between bar coloring, background shading, or overlays.
Color Customization : Configure bullish, bearish, neutral, and tide-specific colors.
Multi-Timeframe Options : Enable tide readings from higher timeframes for confirmation.
Why Use ADX Tide Zones
ADX Tide Zones turns the complexity of momentum analysis into a visual system that highlights when markets are gearing up for moves, trending with conviction, or running out of steam. By combining adaptive ADX interpretation with customizable thresholds, traders can:
Anticipate breakouts before volatility expands.
Confirm the strength behind price trends.
Spot exhaustion phases early to secure profits or prepare for reversals.
Adapt strategies seamlessly between scalping, intraday, and swing trading.
With its balance of simplicity and depth, ADX Tide Zones provides a structured lens for reading market momentum, equipping traders with the clarity needed to execute with discipline and confidence.
The Bravo KitThe Bravo Suite is an all-encompassing toolset that provides traders with various indicators and technical analysis tools. It is designed for ease of use, with simple inputs and intuitive visuals, to assist the average trader in making informed decisions. This guide will provide an overview of the different features included in the Bravo Suite and delve into some of the more intricate details.
Features of the Bravo Suite
Bravo Candles
These candles provide a unique way of visualizing price action by color-coding the candles based on their angle relative to the past price. Users have the option to enable or disable the Bravo Candles theme.
As shown below purple shades start to appear when price is overextended - leveraging the trend angle calculation:
Bravo Sequential
The Bravo Sequential system is a unique take on the traditional 9 count system that aims to identify potential trend exhaustion points. The major difference in the Bravo Sequential is that it uses the trend angle once again, instead of the generic method of counting candlesticks. By incorporating trend angle, it can potentially provide better insights into the momentum behind the current price trend and identify trend exhaustion points more effectively.
This approach allows the Bravo Sequential system to take into account not only the number of consecutive price increases or decreases but also the strength of these movements. Consequently, it can provide a more accurate depiction of the underlying trend, especially if the momentum of the price action is changing.
While the traditional 9 count system only counts the number of sequential candles based on consecutive higher or lower closes, the Bravo Sequential system uses the angle of the trend to identify if the trend is losing strength. It displays a 9 count when it detects a possible trend exhaustion point, accompanied by an optional label for better visibility on the chart.
+ Icons are also produced at the custom 9 count levels making it clearer to see these potential exhaustion zones.
Bravo Fibonacci Bands
The Bravo Fibonacci Bands are an advanced and innovative feature of the Bravo Suite, specifically designed to offer a more precise and dynamic price channel using a custom blend of Fibonacci numbers and weighted averages. This powerful combination allows traders to observe potential support and resistance levels, providing valuable insights into market direction and price movements.
Fibonacci numbers are a well-known and incredibly important concept in mathematics, with various applications in trading and technical analysis.
The Bravo Suite harnesses the power of Fibonacci numbers in the Bravo Fibonacci Bands by building a custom low lag weighted average from the input length. This is achieved by applying the metallic mean (also known as the "golden mean" or "silver mean") to the input series. By leveraging Fibonacci numbers in this manner, the weighted average effectively shifts more weight to the most recent values, emphasizing the importance of the current market trend.
The Bravo Fibonacci Bands dynamically adjust to the ever-changing market conditions, offering the trader an powerful level of precision in identifying crucial price levels. This approach blends the best of both worlds.
The end result is a reliable, easy-to-read price channel that gives traders the confidence to make informed decisions no matter what the market throws their way.
Moving Averages
The Bravo 9 Moving Average is included in the suite, alongside other useful Moving Averages for various timeframes, such as 200-day Moving Average, and 200-week Moving Average. Traders can toggle the visibility of each Moving Average. These are custom designed lower lag moving averages designed as assistive and supporting features in the toolkit.
POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV)
Version: PineScript™v6
📌Description
The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss.
POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously.
The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities.
🚀Points of Innovation
Micro-POC calculation using advanced OHLC-based volume distribution estimation
Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency
Persistence scoring system that quantifies directional consistency over multiple periods
Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts
Dynamic color-coded visualization system with intensity-based feedback
Comprehensive customization options for resolution, periods, and thresholds
🔧Core Components
POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms
Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization
Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration
Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting
Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation
Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships
🔥Key Features
Real-time POC calculation with 10-100 configurable price bands for optimal precision
Velocity tracking with customizable lookback periods from 5 to 50 bars
Acceleration measurement for detecting momentum changes in POC movement
Persistence scoring to validate signal strength and filter false signals
Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions
Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps
Adjustable information table displaying real-time metrics and current signals
Heat ribbon visualization showing price-POC relationship intensity
Multiple threshold settings for customizing signal sensitivity
Export capability for use with separate panel indicators
🎨Visualization
POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude
Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity
Signal Markers: Clear exhaustion top/bottom signals with labeled shapes
Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status
Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions
📖Usage Guidelines
POC Calculation Settings
POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar
Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation
POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise
Velocity Settings
Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity
Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration
Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals
Persistence Settings
Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation
Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals
Visual Settings
Show POC Connecting Lines: Toggle display of colored lines connecting POC levels
Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship
Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon
Alert Settings
Enable Continuation Alerts: Toggle alerts for continuation pattern detection
Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection
Enable POC Gap Alerts: Toggle alerts for significant POC gaps
Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts
✅Best Use Cases
Identifying trend continuation opportunities when POC velocity aligns with price direction
Spotting potential reversal points through exhaustion pattern detection
Confirming breakout validity by monitoring POC gap behavior
Adding volume-based context to traditional technical analysis
Managing position sizing based on POC-price basis strength
⚠️Limitations
POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution
Effectiveness may vary in low-volume or highly volatile market conditions
Requires complementary analysis tools for complete trading decisions
Signal frequency may be lower in ranging markets compared to trending conditions
Performance optimization needed for very short timeframes below 1-minute
💡What Makes This Unique
Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data
Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels
Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator
Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions
Persistence Validation: Unique scoring system to filter signals based on directional consistency
🔬How It Works
Volume Distribution Estimation:
Divides each bar into configurable price bands for volume analysis
Applies sophisticated weighting based on OHLC relationships and proximity to close
Identifies the price level with maximum estimated volume as the POC
Velocity and Acceleration Calculation:
Measures POC rate of change over specified lookback periods
Normalizes values using ATR for consistent cross-market performance
Calculates acceleration as the rate of change of velocity
Signal Generation Process:
Combines trend direction analysis using EMA crossovers
Applies velocity and persistence thresholds to filter signals
Generates continuation, exhaustion, and gap alerts based on specific criteria
💡Note:
This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.
Universal Trend+ [BackQuant]Universal Trend+
This indicator blends several well-known technical ideas into a single composite trend and momentum model. It can be show primarily as an overlay or a oscillator:
In which it produces two things:
a composite oscillator that summarizes multiple signals into one normalized score
a regime signal rendered on the chart as a colored ribbon with optional 𝕃 and 𝕊 markers
The goal is to simplify decision-making by having multiple, diverse measurements vote in a consistent framework, rather than relying on any single indicator in isolation.
What it does
Computes five independent components, each reading a different aspect of price behavior
Converts each component into a standardized bullish / neutral / bearish vote
Averages the available votes to a composite score
Compares that score to user thresholds to label the environment bullish, neutral, or bearish
Colors a fast/slow moving-average ribbon by the current regime, optionally paints candles, and can plot the composite oscillator in a lower pane
The five components (conceptual)
1)RSI Momentum Bias
A classic momentum gauge on a selectable source and lookback. The component emphasizes whether conditions are persistently strong or weak and applies a neutral buffer to avoid reacting to trivial moves. Output is expressed as a vote: bullish, neutral, or bearish.
2) Rate-of-Change Impulse
A smoothed rate-of-change that focuses on short bursts in acceleration. It is used to detect impulsive pushes rather than slow drift. Extreme readings cast a directional vote, mid-range readings abstain.
3) EMA Oscillator
A slope-style trend gauge formed by contrasting a fast and a slow EMA on a chosen source, normalized so that the sign and relative magnitude matter more than absolute price. A small dead-zone reduces whipsaws.
4) T3-Based Normalized Oscillator
A T3 smoother is transformed into a bounded oscillator via rolling normalization, then optionally smoothed by a user-selectable MA. This highlights directional drift while keeping scale consistent across symbols and regimes.
5) DEMA + ATR Bands State
A double-EMA core is wrapped in adaptive ATR bands to create a stepping state that reacts when pressure exceeds a volatility envelope. The component contributes an event-style vote on meaningful shifts.
Each component is designed to measure something different: trend slope, momentum impulse, normalized drift, and volatility-aware pressure. Their diversity is the point.
Composite scoring model
Standardization: Each component is mapped to -1 (bearish), 0 (neutral), or +1 (bullish) using bands and guards to cut noise.
Aggregation: The composite score is the average of the available votes. If a component is inactive on a bar, the composite uses the votes that are present.
Decision layer: Two user thresholds define your action bands.
Above the upper band → bullish regime
Below the lower band → bearish regime
Between the bands → neutral
This separation between measurement, aggregation, and decision avoids over-fitting any single threshold and makes the tool adaptable across assets and timeframes.
Plots and UI
Composite oscillator (optional lower pane): A normalized line that trends between bearish and bullish zones with user thresholds drawn for context.
Signal ribbon (on price): A fast/slow MA pair tinted by the current regime to give an at-a-glance market state.
Markers: Optional 𝕃 and 𝕊 labels when the regime flips.
Candle painting and background tint: Optional visual reinforcement of state.
Color and style controls: User inputs for long/short colors, threshold line color, and visibility toggles.
How it can be used
1) Regime filter
Use the composite regime to define bias. Trade only long in a bullish regime, only short in a bearish regime, and stand aside or scale down in neutral. This simple filter often reduces whipsaw.
2) Confirmation layer
Keep your entry method the same (breaks, pullbacks, liquidity sweeps, order-flow cues) but require agreement from the composite regime or a fresh flip in the 𝕃/𝕊 markers.
3) Momentum breakouts
Look for the composite oscillator to leave neutrality while the EMA oscillator is already positive and the ATR-band state has flipped. Confluence across components is the intent.
4) Pullback entries within trend
In a bullish regime, consider entries on shallow composite dips that recover before breaching the lower band. Reverse the logic in a bearish regime.
5) Exits and risk
Common choices are:
reduce on a return to neutral,
exit on an opposite regime flip, or
trail behind your own stop model (ATR, structure, session levels) while using the ribbon for context.
6) Multi-timeframe workflow
Select a higher timeframe for bias with this indicator, and time executions on a lower timeframe. The indicator itself stays on a single chart; you can load a second chart or pane if you prefer a strict top-down process.
Strengths
Diversified evidence: Five independent perspectives keep the model from hinging on one idea.
Noise control: Neutral buffers and a composite layer reduce reaction to minor wiggles.
Clarity: A single oscillator and a clearly colored ribbon present a complex assessment in a simple form.
Adaptable: Thresholds and lookbacks let you tune for faster or slower markets.
Practical tuning
Thresholds: Wider bands produce fewer regime flips and longer holds. Narrower bands increase sensitivity.
Lookbacks: Shorter lookbacks emphasize recent action; longer lookbacks emphasize stability.
T3 normalization window and volume factor: Increase the window to suppress noise on choppy symbols; tweak the factor to adjust the smoother’s response.
ATR factor for the band state: Raise it to demand more decisive pressure before registering a shift; lower it to respond earlier.
Alerts
Built-in alerts trigger when the regime flips long or short. If you prefer confirmed signals, set your alerts to bar close on your timeframe. Intrabar the composite can move with price; bar-close confirmation stabilizes behavior.
Limitations
Sideways markets: Even with buffers, any trend model can chop in range-bound conditions.
Lag vs sensitivity trade-off: Tighter thresholds react faster but flip more often; wider thresholds are steadier but later.
Asset specificity: Volatility regimes differ. Expect to retune ATR and normalization settings when switching symbols or timeframes.
Final Remarks
Universal Trend+ is meant to act like a disciplined voting committee. Each component contributes a different angle on the same underlying question: is the market pressing up, pressing down, or doing neither with conviction. By standardizing and aggregating those views, you get a single regime read that plays well with many entry styles and risk frameworks, while keeping the heavy math under the hood.
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000)
Overview
Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index.
This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements.
Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days.
Core Features
✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection
✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days
✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level
✅ Zero Statistical Lag - No rolling averages or standard deviation calculations
✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles
Trading Zone Optimization
📊 Lookback Period Strategies
Short-term (1-3 days):
Ultra-responsive to recent price action
Perfect for scalping and day trading
Tight range produces more sensitive signals
Medium-term (7-14 days):
Balanced view of recent trading range
Ideal for swing trading
Captures meaningful support/resistance levels
Long-term (21-30 days):
Broader market context
Excellent for position trading
Smooths out short-term market noise
⚡ Market Condition Adaptation
Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges
Trending Markets: Use longer lookback (14-21 days) for broader context
Ranging Markets: Use medium lookback (7-10 days) for clear boundaries
🎯 Timeframe Optimization
1-minute charts: 1-2 day lookback
5-minute charts: 2-5 day lookback
Hourly charts: 7-14 day lookback
Daily charts: 21-50 day lookback
Trading Applications
Scalping Setup (2-day lookback):
Super tight range for quick reversals
ZTI 800+ = immediate short opportunity
ZTI 200- = immediate long opportunity
Swing Trading Setup (10-day lookback):
Meaningful swing levels captured
ZTI extremes = high-probability reversal zones
More stable signals, reduced whipsaws
Advanced Usage
🔧 Real-Time Adaptability
Trending days: Increase to 14+ days for broader perspective
Range-bound days: Decrease to 3 days for tighter signals
High volatility: Shorter lookback for responsiveness
Low volatility: Longer lookback to avoid false signals
💡 Multi-Timeframe Approach
Entry signals: Use 7-day ZTI on main timeframe
Trend confirmation: Use 21-day ZTI on higher timeframe
Exit timing: Use 3-day ZTI for precise exits
🌐 Session Optimization
Asian session: Shorter lookback (3-5 days) for range-bound conditions
London/NY session: Longer lookback (7-14 days) for trending conditions
How It Works
The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages:
Price at recent high = ZTI at 1000
Price at recent low = ZTI at 1
Price at mid-range = ZTI at 500
This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators.
This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level.
Credits
ZLEMA techniques widely attributed to John Ehlers.
Disclaimer
This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk.
Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
SMA MAD SuperTrend | OquantThe SMA MAD SuperTrend | Oquant is an trend-following indicator designed to help traders identify potential trend directions and reversals using a unique combination of a Simple Moving Average (SMA), Mean Absolute Deviation (MAD), and a SuperTrend mechanism. This script aims to provide clear visual signals for trend entries and exits, making it suitable for traders looking to capture trends.
This indicator innovatively combines the smoothing properties of an SMA with the volatility-adaptive qualities of MAD to create dynamic SuperTrend bands. Unlike traditional SuperTrend indicators that rely on Average True Range (ATR) for volatility, this script uses Mean Absolute Deviation(MAD) to measure the average absolute deviation from the mean price, providing a different perspective on price volatility. The result is a SuperTrend system that adapts to market conditions with a focus on price deviation, offering a unique tool for trend detection.
Components and Calculations
Simple Moving Average (SMA):
The SMA is a widely used indicator that calculates the average of a specified number of closing prices. It smooths price data to identify the overall trend direction. In this script, the SMA serves as the baseline for calculating dynamic upper and lower bands.
Mean Absolute Deviation (MAD):
MAD measures the average absolute deviation of the price from its mean. It quantifies volatility by calculating how far prices deviate from the mean price, offering an alternative to ATR.
SuperTrend Mechanism:
This SuperTrend indicator generates dynamic upper and lower bands around the Simple Moving Average (SMA) using mean absolute deviation as measure of volatility.
It tracks trend direction by comparing the close price to the bands:
If the price crosses above the upper band, the trend turns bullish, and the SuperTrend follows the lower band.
If the price crosses below the lower band, the trend turns bearish, and the SuperTrend follows the upper band.
The bands adjust based on their previous values, updating only when the price crosses a band or the band shifts in the correct direction, reducing false signals and ensuring stable trend detection.
How to Use the Indicator
Trend Signals:
Green Line: Indicates a bullish trend (price above the SuperTrend line).
Purple Line: Indicates a bearish trend (price below the SuperTrend line).
Bar and Candle Coloring: Bars and candles are colored green for bullish trends and purple for bearish trends, making it easy to visualize trend direction.
Filled Areas: The area between the price and the SuperTrend line is filled with transparent colors (green for bullish, purple for bearish) to highlight trend.
Inputs:
Source: Choose the price data for calculations.
SMA Length: Adjust the period for the SMA. Longer periods smooth the trend further.
MAD Length: Set the period for MAD calculation. Shorter periods make the MAD more sensitive.
Factor: Control the distance of the SuperTrend bands from the SMA. Higher values widen the bands, reducing sensitivity to price fluctuations.
Alerts:
The script includes alert conditions for trend changes:
SMA MAD SuperTrend Long: Triggered when the trend turns bullish.
SMA MAD SuperTrend Short: Triggered when the trend turns bearish.
Set up alerts in TradingView to receive notifications for these conditions.
Why Use This Script?
The SMA MAD SuperTrend | Oquant offers a fresh take on trend-following by integrating SMA as baseline and MAD for volatility measurement, providing an alternative to ATR-based SuperTrend indicators. Its clear visual signals, customizable inputs, and alert conditions make it versatile for traders of all levels.
⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
SMAs, EMAs, 52W High Low, CPRThis is all in one indicator which has SMAs, EMAs, CPR, Trend ribbon and SuperTrend.
We are adding other indicator in upcoming days.
Snapfront Market Clarity Index (MCI) — LiteMarket Clarity Index (MCI) — Lite + Signals
The Market Clarity Index (MCI) measures trend clarity vs. noise using returns, drift, and volume shock dynamics. Values are normalized through a φ²-based sigmoid for smooth, interpretable signals.
Features:
Clear 0–100 scale (Lite version)
Heatmap background for clarity regimes
Bull/Bear signal arrows with EMA filter
High/Low threshold lines for easy context
Trading Logic:
✅ Bull signal when MCI crosses into the high zone with price above EMA
❌ Bear signal when MCI crosses into the low zone with price below EMA
Use MCI as a trend filter, entry trigger, or market condition gauge across any timeframe or asset.
Dual Channel System [Alpha Extract]A sophisticated trend-following and reversal detection system that constructs dynamic support and resistance channels using volatility-adjusted ATR calculations and EMA smoothing for optimal market structure analysis. Utilizing advanced dual-zone methodology with step-like boundary evolution, this indicator delivers institutional-grade channel analysis that adapts to varying volatility conditions while providing high-probability entry and exit signals through breakthrough and rejection detection with comprehensive visual mapping and alert integration.
🔶 Advanced Channel Construction
Implements dual-zone architecture using recent price extremes as foundation points, applying EMA smoothing to reduce noise and ATR multipliers for volatility-responsive channel widths. The system creates resistance channels from highest highs and support channels from lowest lows with asymmetric multiplier ratios for optimal market reaction zones.
// Core Channel Calculation Framework
ATR = ta.atr(14)
// Resistance Channel Construction
Resistance_Basis = ta.ema(ta.highest(high, lookback), lookback)
Resistance_Upper = Resistance_Basis + (ATR * resistance_mult)
Resistance_Lower = Resistance_Basis - (ATR * resistance_mult * 0.3)
// Support Channel Construction
Support_Basis = ta.ema(ta.lowest(low, lookback), lookback)
Support_Upper = Support_Basis + (ATR * support_mult * 0.4)
Support_Lower = Support_Basis - (ATR * support_mult)
// Smoothing Application
Smoothed_Resistance_Upper = ta.ema(Resistance_Upper, smooth_periods)
Smoothed_Support_Lower = ta.ema(Support_Lower, smooth_periods)
🔶 Volatility-Adaptive Zone Framework
Features dynamic ATR-based width adjustment that expands channels during high-volatility periods and contracts during consolidation phases, preventing false signals while maintaining sensitivity to genuine breakouts. The asymmetric multiplier system optimizes zone boundaries for realistic market behavior patterns.
// Dynamic Volatility Adjustment
Channel_Width_Resistance = ATR * resistance_mult
Channel_Width_Support = ATR * support_mult
// Asymmetric Zone Optimization
Resistance_Zone = Resistance_Basis ± (ATR_Multiplied * )
Support_Zone = Support_Basis ± (ATR_Multiplied * )
🔶 Step-Like Boundary Evolution
Creates horizontal step boundaries that update on smoothed bound changes, providing visual history of evolving support and resistance levels with performance-optimized array management limited to 50 historical levels for clean chart presentation and efficient processing.
🔶 Comprehensive Signal Detection
Generates break and bounce signals through sophisticated crossover analysis, monitoring price interaction with smoothed channel boundaries for high-probability entry and exit identification. The system distinguishes between breakthrough continuation and rejection reversal patterns with precision timing.
🔶 Enhanced Visual Architecture
Provides translucent zone fills with gradient intensity scaling, step-like historical boundaries, and dynamic background highlighting that activates upon zone entry. The visual system uses institutional color coding with red resistance zones and green support zones for intuitive
market structure interpretation.
🔶 Intelligent Zone Management
Implements automatic zone relevance filtering, displaying channels only when price proximity warrants analysis attention. The system maintains optimal performance through smart array management and historical level tracking with configurable lookback periods for various market conditions.
🔶 Multi-Dimensional Analysis Framework
Combines trend continuation analysis through breakthrough patterns with reversal detection via rejection signals, providing comprehensive market structure assessment suitable for both trending and ranging market conditions with volatility-normalized accuracy.
🔶 Advanced Alert Integration
Features comprehensive notification system covering breakouts, breakdowns, rejections, and bounces with customizable alert conditions. The system enables precise position management through real-time notifications of critical channel interaction events and zone boundary violations.
🔶 Performance Optimization
Utilizes efficient EMA smoothing algorithms with configurable periods for noise reduction while maintaining responsiveness to genuine market structure changes. The system includes automatic historical level cleanup and performance-optimized visual rendering for smooth operation across all timeframes.
Why Choose Dual Channel System ?
This indicator delivers sophisticated channel-based market analysis through volatility-adaptive ATR calculations and intelligent zone construction methodology. By combining dynamic support and resistance detection with advanced signal generation and comprehensive visual mapping, it provides institutional-grade channel analysis suitable for cryptocurrency, forex, and equity markets. The system's ability to adapt to varying volatility conditions while maintaining signal accuracy makes it essential for traders seeking systematic approaches to breakout trading, zone reversals, and trend continuation analysis with clearly defined risk parameters and comprehensive alert integration. Also to note, this indicator is best suited for the 1D timeframe.
Modern Trend Indicator_GirishThis Indicator is a Powerful Buy and Sell Indicator to catch the Trend in all time frame.
LogPressure Envelope [BOSWaves]LogPressure Envelope – Adaptive Volatility & Trend Visualizer
Overview
LogPressure Envelope is a specialized trading tool designed to normalize market behavior using logarithmic price scaling while providing an adaptive framework for volatility and trend detection. The indicator calculates a log-based moving average midline, surrounds it with asymmetric volatility envelopes, and replaces the conventional cloud with progressive fan lines to present price action in a more interpretable form.
By integrating rate-of-change midline coloring, fading trend strength, and structured buy/sell markers, LogPressure Envelope simplifies the reading of complex market dynamics. Its design makes it suitable for multiple trading approaches, including scalping, intraday, and swing trading, where volatility behavior and trend shifts must be understood quickly and objectively.
Unlike static envelope indicators, LogPressure Envelope adapts continuously to price scale and volatility conditions. It evaluates log-transformed prices, applies configurable moving average methods (EMA, SMA, WMA), and derives asymmetric standard-deviation bands for both upside and downside moves. These envelopes are projected as fan lines with adjustable opacity, producing a layered volatility map that evolves with the market.
This system ensures each visual element—midline shading, candle coloring, fan structure, and signal markers—reflects real-time market conditions, allowing traders to interpret volatility expansion, contraction, and directional bias with clarity.
How It Works
The foundation of LogPressure Envelope is the logarithmic transformation of price. By operating in log space, the indicator removes distortions caused by large nominal price differences across assets, enabling consistent analysis of both low-priced and high-priced instruments.
A moving average of log prices is calculated (EMA, SMA, or WMA depending on user input) and then re-converted to normal price scale, forming the log midline. Standard deviation of log prices is then measured over a separate period, with independent multipliers for upside and downside deviations. This asymmetry captures the fact that markets often expand differently in bullish versus bearish phases.
Instead of plotting a filled cloud, the envelope is expressed as ten equidistant fan lines stretching from the lower to upper boundary. Each line is shaded progressively to visualize volatility clustering and directional strength without overloading the chart.
Trend determination is smoothed using a fade mechanism: shifts in bias do not flip instantly but gradually move toward the new state, producing fewer false transitions. Buy and sell markers are generated when trend strength crosses confirmation thresholds, ensuring signals are event-driven and contextually meaningful.
Signals and Visuals
LogPressure Envelope provides multiple layers of structured signals:
Midline Bias – Central moving average colored by rate-of-change, reflecting directional acceleration or deceleration.
Volatility Fan – Ten progressive lines forming a gradient between lower and upper bands, visually encoding volatility spread.
Buy Signals – Labels below bars when upward trend strength is confirmed.
Sell Signals – Labels above bars when downward trend strength is confirmed.
Candle Coloring – Optional shading of candles based on trend alignment with the log midline, highlighting bullish, bearish, or neutral conditions.
These signals remain clear even during high-volatility phases, with visual hierarchy maintained through progressive opacity control.
Interpretation
Trend Analysis : Midline direction and candle coloring provide continuous feedback on prevailing bias. Upward-sloping midlines with blue shading indicate bullish phases, while downward slopes with orange shading confirm bearish conditions.
Volatility and Risk Assessment : Expansion of fan lines indicates rising volatility and potential breakout conditions; contraction indicates consolidation and possible mean reversion.
Signal Confirmation : Buy and sell markers validate transitions when trend strength thresholds are crossed, aligning with volatility envelope dynamics.
Market Context : Asymmetric envelopes allow traders to see where bearish acceleration differs from bullish expansion, improving interpretation of liquidity conditions and institutional pressure.
Strategy Integration
LogPressure Envelope can be applied across trading styles:
Trend Following : Enter trades in the direction of midline bias, confirmed by buy or sell markers.
Pullback Entries : Use midline retests during trending conditions as lower-risk continuation points.
Volatility Breakouts : Identify sharp expansions in fan line spacing as early signals of directional moves.
Reversal Strategies : Fade extreme envelope touches when momentum shows exhaustion and fan contraction begins.
Multi-Timeframe Confirmation : Align signals from higher and lower timeframes to reduce noise and validate trade setups.
Stop-loss levels can be set near the opposite envelope boundary, while targets may be managed through progressive volatility zones or midline convergence.
Advanced Techniques
For greater precision, LogPressure Envelope can be combined with other analytical tools:
Pair with volume or liquidity measures to validate breakout or reversal conditions.
Use momentum indicators to confirm ROC-based midline bias.
Track sequences of fan line expansions and contractions to anticipate regime shifts in volatility.
Apply across multiple timeframes to monitor how volatility clusters align at different market scales.
Adjusting parameters such as envelope multipliers, moving average type, and fade bars allows the indicator to adapt to diverse asset classes and volatility environments.
Inputs and Customization
Midline Type : Select EMA, SMA, or WMA.
Line Opacity : Control visibility of fan lines.
Enable Candle Coloring : Toggle trend-based bar shading.
MA Length / StdDev Length : Define periods for midline and volatility calculation.
Multipliers : Set asymmetric scaling for upside and downside envelopes.
Fade Bars : Control smoothness of trend strength transitions.
Fan Lines : Adjust number of envelope subdivisions for visualization granularity.
Why Use LogPressure Envelope
LogPressure Envelope translates complex volatility and trend interactions into a structured and adaptive framework. By combining logarithmic normalization, asymmetric standard deviation envelopes, and smoothed trend confirmation, it allows traders to:
Normalize price analysis across assets of different scales.
Visualize volatility expansion and contraction in real time.
Identify and confirm directional shifts with objective signal markers.
Apply a disciplined system for trend, breakout, and reversal strategies.
This indicator is designed for traders who want a systematic, visually clear approach to volatility-based market analysis without relying on static bands or arbitrary scaling.
Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI
What this is
A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts:
• A sensitivity window that scans several recent bars to capture the strongest up and down impulses.
• A selectable moving average that smooths those impulses before computing RSI.
The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection.
How it works
Impulse extraction
• For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price.
• It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise.
MA-based averaging
• The up and down impulse series are averaged with your chosen MA over rsi_len bars.
• Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA.
Zero-centered RSI transform
• RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) .
• Above 0 implies positive momentum bias. Below 0 implies negative momentum bias.
Optional extra smoothing
• A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”.
Visual encoding
• The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes.
• Static bands mark 80 to 100 and −80 to −100 for extreme conditions.
Key inputs and what they change
• Price Source : input series for momentum.
• Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower.
• Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts.
• Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower.
• Smoothing Type and Length : optional second pass to calm noise on the final output.
• UI toggles : show or hide the oscillator, candle painting, and extreme bands.
Reading the oscillator
• Midline cross up (0) : momentum bias turning positive.
• Midline cross down (0) : momentum bias turning negative.
• Positive territory :
– 0 to 40: constructive but not stretched.
– 40 to 80: strong momentum, continuation more likely.
– Above 80: extreme risk of mean reversion grows.
• Negative territory : mirror the same levels for the downside.
Divergence detection
The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR .
• Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion.
• Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up.
• Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion.
• Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down.
Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish.
Candle coloring
• Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only.
Strengths
• Adaptive sensitivity via a rolling impulse window that responds to genuine bursts.
• Configurable MA core so you can match responsiveness to the instrument.
• Zero-centered scale for simple regime reads with 0 as a clear bias line.
• Built-in regular and hidden divergence mapping.
• Flexible across symbols and timeframes once tuned.
Limitations and cautions
• Trends can remain extended. Treat extremes as context rather than automatic reversal signals.
• Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag.
• Double smoothing can delay zero-line transitions. Balance smoothness and timeliness.
Practical usage ideas
• Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0.
• Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends.
• Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence.
• Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts.
Alerts
• MA-A RSI Long : oscillator crosses above 0.
• MA-A RSI Short : oscillator crosses below 0.
Use these as bias or timing aids, not standalone trade commands.
Settings quick reference
• Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity.
• Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing.
• UI : Show Oscillator, Paint Candles, Show Static High and Low Levels.
• Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences.
Final thoughts
This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.
Better Pivot Points [LuminoAlgo]Overview
The Better Pivot Points indicator is an advanced trend analysis tool that combines Supertrend methodology with automated pivot point identification and zigzag visualization. This indicator helps traders identify significant price turning points and visualize market structure through dynamic pivot labeling and connecting lines.
How It Works
This indicator utilizes a Supertrend-based algorithm to detect meaningful pivot points in price action. Unlike traditional pivot point indicators that rely on fixed time periods, this tool dynamically identifies pivots based on trend changes, providing more relevant and timely signals.
The algorithm tracks trend changes using ATR-based Supertrend crossovers to determine when significant highs and lows have formed. When a trend reversal is detected, the indicator marks the pivot point and draws connecting lines to visualize price flow and market structure progression.
Key Features
• Dynamic Pivot Detection: Automatically identifies high and low pivot points using Supertrend crossovers
• Market Structure Labeling: Labels pivots as HH (Higher High), LH (Lower High), HL (Higher Low), or LL (Lower Low)
• Zigzag Visualization: Connects pivot points with customizable lines to clearly show price flow and market structure
• Color-Coded Analysis: Uses distinct colors to indicate bullish trends (green), bearish trends (red), and neutral conditions (yellow)
• Customizable Parameters: Adjustable ATR period, factor, line width, and line style
Input Settings
• ATR Length: Controls the sensitivity of the Supertrend calculation (default: 21)
• Factor: Multiplier for the ATR-based Supertrend bands (default: 2.0)
• Zigzag Line Width: Customize the thickness of connecting lines (1-4)
• Zigzag Line Style: Choose between Solid, Dashed, or Dotted line styles
What Makes This Original
This indicator combines several analytical concepts into a cohesive tool that differentiates it from standard pivot point indicators:
1. Uses Supertrend crossovers as the trigger for pivot detection rather than traditional high/low lookback periods
2. Automatically categorizes market structure using HH/LH/HL/LL labeling system based on pivot relationships
3. Provides real-time zigzag visualization with intelligent color coding that reflects trend direction
4. Integrates trend direction analysis with structural pivot identification in a single comprehensive tool
The underlying calculations use custom logic for tracking trend states, validating pivot points, and determining appropriate color coding based on market structure analysis.
How to Use
1. Trend Identification: Green lines indicate bullish market structure, red lines show bearish structure, yellow indicates transitional periods
2. Support/Resistance: Pivot points often act as future support and resistance levels for price action
3. Market Structure Analysis: HH and HL patterns suggest uptrends, while LH and LL patterns indicate downtrends
4. Entry/Exit Planning: Use pivot points and trend changes to plan potential trade entries and exits
Important Limitations and Warnings
• This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions
• Pivot points are identified after price moves occur, meaning this indicator has inherent lag and cannot predict future pivots
• False signals can occur during ranging or choppy market conditions where trends are unclear
• Past performance of any indicator does not guarantee future results or trading success
• The indicator works best in clearly trending markets and may produce less reliable signals in sideways price action
• This tool requires interpretation and should be combined with other forms of analysis
• Always use proper risk management and position sizing strategies when trading
Why This Script Is Protected
This indicator uses proprietary algorithms for pivot detection timing, trend state management, and market structure analysis that represent original research and development. The specific logic for pivot validation, color-coding methodology, and structural relationship calculations contains unique approaches that differentiate it from standard pivot point indicators available in the public library.
Disclaimer
This indicator is for educational and analysis purposes only and does not constitute investment advice. Trading involves substantial risk and is not suitable for all investors. Past results are not indicative of future performance. The future is fundamentally unknowable and past results in no way guarantee future performance. Always conduct your own research and consider your risk tolerance before making any trading decisions.
Ichimoku HorizonIchimoku Horizon – Multi-Timeframe Analysis
A multi-timeframe Ichimoku faithful to Hosoda, with authentic real-time calculations.
Ichimoku Horizon is an indicator based on the original method developed by Goichi Hosoda in the 1930s. It strictly respects the authentic formulas and prioritizes mathematical fidelity.
Key Features
Intelligent Multi-Timeframe
Native chart: Ichimoku from your trading timeframe
3 higher timeframes: Daily (1D), Weekly (1W), Monthly (1M) by default
Automatic projection: only higher timeframes relative to the chart are displayed
Precise offsets: displacement adapted to each timeframe
Guaranteed Authenticity
Hosoda’s original formulas fully respected
lookahead_off exclusively: lines calculated in real time with the current candle
Traditional displacement: 26 periods for cloud projection and Chikou shift
Why lookahead_off?
lookahead_off is the calculation mode that respects Hosoda’s logic:
Tenkan, Kijun, SSA and SSB all include the current candle and move in real time.
Chikou is the only exception: shifted 26 periods but calculated only with confirmed closes.
This way, what you see always matches the actual market as it is forming.
What is the no repaint approach?
A no repaint indicator displays values exactly as they exist in the present moment:
Lines update in real time during the formation of a candle.
Once the candle closes, they remain permanently fixed.
This ensures that the plots reflect the true construction of the market.
Main Parameters
Tenkan: 9 periods (short term)
Kijun: 26 periods (medium term)
SSB: 52 periods (long term)
Displacement: 26 periods (+26 for the cloud, −26 for the Chikou)
Timeframe Selection
TF1: Daily (structure aligned with trading activity)
TF2: Weekly (intermediate trend)
TF3: Monthly (macro vision)
Example Configurations
Scalping: Chart 1m → TF1: 5m, TF2: 15m, TF3: 1H
Intraday: Chart 5m → TF1: 15m, TF2: 1H, TF3: 4H
The indicator automatically hides inconsistent timeframes (lower than the chart).
Natural Line Display
Some lines will sometimes appear flat or straight: this is the normal behavior of Ichimoku, directly reflecting the highs and lows of their calculation windows.
Conclusion
Ichimoku Horizon is designed to remain true to Hosoda’s vision while offering the clarity of a modern multi-timeframe tool.
It delivers authentic, real-time calculations with no compromise.
Trend Shift Histogram By Clarity ChartsTrend Shift Histogram – A Brand New Formula by Clarity Charts
The Trend Shift Histogram is a brand-new mathematical formula designed to capture market momentum shifts with exceptional clarity.
Unlike traditional histograms, this indicator focuses on detecting early changes in market direction by analyzing underlying trend strength and momentum imbalances.
Key Features:
New Formula – Built from scratch to highlight momentum reversals and hidden trend shifts.
Visual Clarity – Green and red histogram bars make it easy to identify bullish and bearish phases, and grey area as trend reversal or sideways zone.
Trend Detection – Helps traders spot when the market is about to shift direction, often before price reacts strongly.
Scalable Settings –
Use smaller lengths for scalping and short-term trades.
Use larger lengths for swing trading and longer trend analysis.
Every Timeframe Ready – Whether you’re scalping on 1m or analyzing weekly charts, the histogram adapts seamlessly.
Power of Combining with the Fear Index
The Trend Shift Histogram becomes even more powerful when combined with Fear Index by Clarity Charts :
Fear Index by Clarity Charts
Together:
Fear Index highlights market fear & exhaustion levels, showing when traders are capitulating.
Trend Shift Histogram confirms the direction of the new trend once fear has peaked.
How to Use:
📈 Long Entry Condition
A long position is triggered when the following conditions align:
The Fear Index Bulls are showing upward momentum, indicating strengthening bullish sentiment.
The Fear Index Bears are simultaneously declining, signaling weakening bearish pressure.
The Trend Shift Histogram transitions from a short bias to a long bias, confirming a structural shift in market direction.
When all three conditions occur together, it provides a strong confluence to initiate a long trade entry.
📉 Short Entry Condition
A short position is triggered when the opposite conditions align:
The Fear Index Bears are showing upward momentum, indicating strengthening bearish sentiment.
The Fear Index Bulls are simultaneously declining, signaling weakening bullish pressure.
The Trend Shift Histogram transitions from a long bias to a short bias, confirming a structural shift in market direction.
When all three conditions occur together, it provides a strong confluence to initiate a short trade entry.
🔄 Bullish Trend Cycle
During a bullish phase as per the Fear Index, you can capture the entire cycle by:
Entry: Taking entries when the Trend Shift Histogram begins printing green bars, which mark the start of a bullish trend shift.
Exit: Closing the position when the histogram transitions to grey bars, signaling exhaustion or a potential pause in the bullish cycle.
This approach allows you to ride the bullish momentum effectively while respecting market cycle shifts.
🔻 Bearish Trend Cycle
During a bearish phase as per the Fear Index, you can capture the entire cycle by:
Entry: Taking entries when the Trend Shift Histogram begins printing red bars, which mark the start of a bearish trend shift.
Exit: Closing the position when the histogram transitions to grey bars, signaling exhaustion or a potential pause in the bearish cycle.
This approach ensures that bearish trends are traded with precision, avoiding late entries and capturing maximum move potential.
Watch for histogram color changes (green = bullish, red = bearish, grey = sideways).
Adjust length settings based on your style:
Small = intraday & scalping precision.
Large = swing & positional confidence.
Combine signals with Fear Index peaks for high-probability reversal zones.
Apply across any timeframe for flexible strategy building.
Who Can Use This
Scalpers – Catch quick intraday shifts.
Swing Traders – Ride bigger moves with confidence.
Long-Term Investors – Spot early warning signs of market trend reversals.
Contact & Support
For collaboration, premium indicators, or custom strategy building:
theclaritycharts@gmail.com
Price Heat Meter [ChartPrime]⯁ OVERVIEW
Price Heat Meter visualizes where price sits inside its recent range and turns that into an intuitive “temperature” read. Using rolling extremes, candles fade from ❄️ aqua (cold) near the lower bound to 🔥 red (hot) near the upper bound. The tool also trails recent extreme levels, tags unusually persistent extremes with a % “heat” label, and shows a bottom gauge (0–100%) with a live arrow so you can read market heat at a glance.
⯁ KEY FEATURES
Rolling Heat Map (0–100%):
The script measures where the close sits between the current Lowest Low and Highest High over the chosen Length (default 50).
Candles use a two-stage gradient: aqua → yellow (0–50%), then yellow → red (50–100%). This makes “how stretched are we?” instantly visible.
Dynamic Extremes with Time Decay:
When a new rolling High or Low is set, the script starts a faint horizontal trail at that price. Each bar that passes without a new extreme increases a counter; the line’s color gradually fades over time and fully disappears after ~100 bars, keeping the chart clean.
Persistent-Extreme Tags (Reversal Hints):
If an extreme persists for 40 bars (i.e., price hasn’t reclaimed or surpassed it), the tool stamps the original extreme pivot with its recorded Heat% at the moment the extreme formed.
• Upper extremes print a red % label (possible exhaustion/resistance context).
• Lower extremes print an aqua % label (possible exhaustion/support context).
Bottom Heat Gauge (0–100% Scale):
A compact, gradient bar renders at the bottom center showing the current Heat% with an arrow/label. ❄️ anchors the left (0%), 🔥 anchors the right (100%). The arrow adopts the same candle heat color for consistency.
Minimal Inputs, Clear Theme:
• Length (lookback window for H/L)
• Heat Color set (Cold / Mid / Hot)
The defaults give a balanced, legible gradient on most assets/timeframes.
Signal Hygiene by Design:
The meter doesn’t “call” reversals. Instead, it contextualizes price within its range and highlights the aging of extremes. That keeps it robust across regimes and assets, and ideal as a confluence layer with your existing triggers.
⯁ HOW IT WORKS (UNDER THE HOOD)
Range Model:
H = Highest(High, Length), L = Lowest(Low, Length). Heat% = 100 × (Close − L) / (H − L).
Extreme Tracking & Fade:
When High == H , we record/update the current upper extreme; same for Low == L on the lower side. If the extreme doesn’t change on the next bar, a counter increments and the plotted line’s opacity shifts along a 0→100 fade scale (visual decay).
40-Bar Persistence Labels:
On the bar after the extreme forms, the code stores the bar_index and the contemporaneous Heat% . If the extreme survives 40 bars, it places a % label at the original pivot price and index—flagging levels that were meaningfully “tested by time.”
Unified Color Logic:
Both candles and the gauge use the same two-stage gradient (Cold→Mid, then Mid→Hot), so your eye reads “heat” consistently across all elements.
⯁ USAGE
Treat >80% as “hot” and <20% as “cold” context; combine with your trigger (e.g., structure, OB, div, breakouts) instead of acting on heat alone.
Watch persistent extreme labels (40-bar marks) as reference zones for reaction or liquidity grabs.
Use the fading extreme lines as a memory map of where price last stretched—levels that slowly matter less as they decay.
Tighten Length for intraday sensitivity or increase it for swing stability.
⯁ WHY IT’S UNIQUE
Rather than another oscillator, Price Heat Meter translates simple market geometry (rolling extremes) into a readable temperature layer with time-aware extremes and a synchronized gauge . You get a continuously updated sense of stretch, persistence, and potential reversal context—without clutter or overfitting.
DM Impulse Enhanced [BackQuant]DM Impulse Enhanced
What this is (and what it isn’t)
DM Impulse Enhanced is a signal-driven overlay that classifies market action into two practical regimes: Long (risk-on) and Cash (risk-off). It’s built around a proprietary impulse model from the directional-movement family, wrapped in a persistence test and a state machine. Because this script is private, the core mechanics are intentionally abstracted here; what follows explains how to read and use it without revealing the protected calculation.
Why traders use it
Many tools oscillate or describe “how stretched” price is; fewer make a firm, operational call that you can automate. DM Impulse Enhanced aims to do exactly that declare when upside pressure is broad and durable enough to justify a long bias, and when deterioration is strong enough to stand aside (cash/short discretion). The emphasis is on impulse persistence rather than one-off spikes.
What you see on the chart
• Long / Cash markers – Green up-triangles (Long) and red down-triangles (Cash) plot at the bar where the regime changes.
• Regime-tinted bars (optional) – Candles can be softly shaded green during Long and red during Cash for at-a-glance context.
• Trend ribbon (context only) – A narrow ribbon (fast/slow moving averages) is tinted by the current regime to show trend alignment; it does not generate signals on its own.
• No separate sub-pane – Signals are intended to sit directly on price for immediate decision-making.
How the logic behaves (high-level)
Impulse core – A directional-movement–based engine estimates the strength of buying vs. selling pressure over a user-defined horizon.
Persistence gate – Instead of reacting to a single reading, the model evaluates how consistently that impulse dominates across a configurable lookback range.
State machine – When persistence clears (or fails) a pair of thresholds, the model flips and stays in that regime until evidence justifies a change. This “stickiness” is intentional; it reduces whipsaws in choppy tape.
Inputs & controls
Calculation Settings
• DM Length – The base horizon for the impulse engine. Longer = smoother/steadier; shorter = quicker/more reactive.
• Start / End – Defines the span of the persistence check. Expanding the span asks the market to prove itself against more history before changing regime.
Signal Settings
• Long Threshold – The persistence level required to promote the model into Long.
• Short Threshold – The level that, once crossed to the downside, demotes the model into Cash. Using a cross-under event for risk-off helps avoid premature exits on noise.
Visual Settings
• Long / Short colours – Customize marker and shading hues.
• Color Bars? – Toggle candle tinting by regime (off if you prefer a clean chart).
Reading the signals
• Long prints only when the model observes sustained upside pressure across the configured span. Treat this as permission to engage with pullbacks, breakouts, or your preferred setups in the direction of the trend.
• Cash prints when downside deterioration is strong enough to invalidate the prior regime. It’s a risk-off directive—flatten, hedge, or switch to short strategies according to your plan.
• Regime persistence is a feature: once Long, the model won’t flip on minor dips; once Cash, it won’t re-arm on minor bounces. If you want more flips, shorten the spans and relax thresholds; if you want fewer, do the opposite.
Practical tuning guide
Match DM Length to your timeframe
– Intraday: smaller length for timely response.
– Swing/Position: larger length to filter desk-noise and track higher-timeframe flows.
Size the persistence span to your goal
– Narrow span: faster regime changes, more trades, more noise.
– Wide span: fewer, higher-conviction calls, longer holds.
Set realistic thresholds
– The Long threshold should be reachable with your chosen span; the Short threshold should be low enough to catch genuine deterioration but not so tight that it flips on every dip.
Decide on cosmetics
– Turn on bar tinting for discretionary reading, or keep it off when exporting screenshots or running other overlays.
Suggested workflows
• Trend-following with discipline – Trade only in the Long regime; use structure (higher lows, anchored VWAP, or pullbacks to your MA stack) for entries and the Cash flip as a portfolio-level exit.
• Risk overlay – Keep your normal strategy, but: reduce size when Cash appears; re-enable full risk only after Long reasserts.
• Multi-timeframe gating – Require Long on a higher timeframe (e.g., 4H or 1D), then take entries on a lower one. If the high-TF posts Cash, stand down.
How the ribbon fits in
The ribbon visualizes short- vs. intermediate-term trend in the same colour as the regime. It’s deliberately “dumb”: it does not change the signal, it just helps you see when price action and regime are in harmony (e.g., pullbacks during Long that hold above the ribbon).
Alerts included
• DM Impulse LONG – Triggers as the persistence measure clears the Long threshold.
• DM Impulse CASH – Triggers when deterioration crosses the Short threshold from above.
Configure alerts to fire on bar close if you want final (non-intrabar) decisions.
Strengths
• Actionable binary output – Long/Cash is unambiguous and easy to automate.
• Persistence-aware – Focuses on runs that endure, not one-bar excitement.
• Asset/timeframe agnostic – Works anywhere you trust directional-movement concepts (equities, futures, crypto, FX).
Limitations & cautions
• Not a reversal caller – It’s a regime classifier. If you need early bottoms/tops, pair it with your own exhaustion or liquidity tools.
• Parameter feasibility matters – If your thresholds are set beyond what your span can reasonably achieve, signals may rarely (or never) trigger.
• Chop happens – In mean-reverting or news-driven tape, expect more frequent flips unless you widen spans and thresholds.
• Intrabar movement – Like any responsive model, provisional intrabar states can appear before the bar closes. Use “bar close” alerts for finality.
Getting started (safe defaults you can adapt)
• Intraday bias – Shorter DM Length, modest span, moderately tight thresholds.
• Swing filter – Longer DM Length, wider span, stricter Long and sufficiently low Short.
• Conservative overlay – Keep thresholds firm and spans wide; use signals to scale risk rather than flip directions frequently.
Summary
DM Impulse Enhanced is a persistence-focused regime classifier built on directional-movement concepts. It answers a narrow question clearly “Risk-on or risk-off?” and stays with that answer until the evidence meaningfully changes. Use it as a bias switch, a portfolio risk overlay, or a gate for your existing entry logic, and size its spans/thresholds to the cadence of the market you trade.
Hammer Candle Finder [MQSXN]This script automatically scans your chart for hammer candlestick patterns and highlights them with fully customizable labels and markers. Hammers are classic price action signals that can suggest potential reversals or exhaustion in the current trend.
How it works:
- Detects candles with a small body near the top of the range, a long lower wick, and minimal upper wick.
- Separates bullish hammers (green close above open) from bearish hammers (red close below open).
- You can choose to display either type—or both—depending on your trading style.
Customizable options:
- Adjustable detection sensitivity (body % of range, wick-to-body ratio, top wick allowance).
- Toggle to show/hide bullish or bearish signals.
- Custom text, colors, label style, and positioning for the markers.
- Option to anchor labels above bars automatically or offset them by a set number of ticks.
Usage:
This tool is designed for traders who want a clear, visual way to spot hammer candles in real time or during historical chart analysis. Combine it with your own support/resistance zones, volume analysis, or confirmation indicators to build complete strategies.
Note:
This indicator does not provide buy/sell signals on its own—it’s meant to assist with candlestick recognition. Always confirm with your broader trading plan and risk management rules.
