NY Session (PIPNEXUS) Description:
This indicator, created for the PIPNEXUS Community, is designed to make backtesting easier and more efficient. It highlights the New York session, allowing you to clearly see when the market experiences the highest volume and liquidity. By using this tool, PIPNEXUS members can better identify peak trading hours, spot potential high-momentum moves, and optimize their trading strategy. Ideal for traders who want a precise and visual way to track the most active market periods.
การวิเคราะห์แนวโน้ม
RSI Divergence + Smoothed MA + Bollinger Bandadjust same settings as what you see on the pics.
imgur.com
ZoneRadar by Chaitu50cZoneRadar
ZoneRadar is a tool designed to detect and visualize hidden buy or sell pressures in the market. Using a Z-Score based imbalance model, it identifies areas where buyers or sellers step in with strong momentum and highlights them as dynamic supply and demand zones.
How It Works
Z-Score Imbalance : Calculates statistical deviations in order flow (bull vs. bear pressure).
Buy & Sell Triggers: Detects when imbalances cross predefined thresholds.
Smart Zones: Marks potential buy (green) or sell (red) zones directly on your chart.
Auto-Merge & Clean: Overlapping or noisy zones are automatically merged to keep the chart clean.
History Control: Keeps only the most recent and strongest zones for focus.
Key Features
Customizable Z-Score level and lookback period
Cooldown filter to avoid over-signaling
Smart zone merging to prevent clutter
Adjustable price tolerance for merging overlapping zones (ticks)
Extend zones into the future with right extensions
Fully customizable colors and display settings
Alert conditions for Buy Pressure and Sell Pressure
Why ZoneRadar?
Simplifies complex order flow into clear, tradable zones
Helps identify high-probability reversal or continuation levels
Avoids noise by keeping only the cleanest zones
Works across any timeframe or market (stocks, futures, forex, crypto)
Disclaimer
This tool is designed for educational and informational purposes only. It does not provide financial advice. Always test on demo and combine with your own trading strategy.
Strength by EGThis indicator from equitygurukul.in is designed to help traders identify key market trend phases using classic moving averages. It includes:
50, 150, 200-period MAs (user can choose SMA or EMA via dropdown).
A Custom MA (default length 21, user-adjustable).
Buy Signal Arrow when bullish alignment conditions are met.
Weak Label when price crosses below the Custom MA.
Strength Label when price crosses above the Custom MA and is also above the 50 MA.
Fully customizable colors, label display toggles, and arrow size options.
This tool allows traders to quickly visualize momentum shifts, long-term trend alignment, and strength/weakness signals on the chart.
⚠️ Disclaimer
This script is created for educational purposes under the brand equitygurukul.in. It is not financial advice. Trading and investing involve risk, and past performance does not guarantee future results. Please do your own research or consult a financial advisor before making investment decisions.
utt ohlc Pivot Linecheck only on day time frame and mark a line based on line u can plan a trade line above bullish below bearish ,its educational purpose only
Distance Between EMA'sThis indicator measures the distance between any two EMA's you choose. You can change the EMA's by clicking settings and change the inputs to the two that you choose
Rossgram
Script Name: ADMF: Rossgram Aggregated cumulative volume, volatility-dependent-parabolic-length, divergence-inverting EMA admf
Description:
This publication is a major revision by the original author. The script has been significantly improved to provide more accurate and timely signals by enhancing its core adaptive logic.
Key Improvements & Originality:
Enhanced Dynamic Calculation: The core algorithm now features a sophisticated volatility normalization mechanism. Instead of using a simple ATR, it calculates a normalized volatility index (volATR_admf) and dynamically adjusts the EMA length based on its position within a dynamically updated percentile range (2nd to 98th). This allows the indicator to be exceptionally responsive across different market regimes, from extreme volatility to calm conditions.
Advanced Percentile Anchoring: A dedicated initialization and update routine ensures robust calculation of volatility extremes. The script:
Initializes with safe defaults for the first 1000 bars.
After the 1000th bar, it calculates precise percentile levels (ta.percentile_nearest_rank) every 100 bars, ensuring the adaptive mechanism is always anchored to the most relevant recent market data rather than a fixed historical period. This is a unique approach to defining "extremes".
Multi-Exchange Data Aggregation (User-Configurable): The script is designed to aggregate volume data from multiple sources. This provides a more accurate picture of market activity than a single exchange. Users can manually configure a list of tickers for non-BTC assets in the settings, tailoring the data input to their specific trading instrument.
How It Works & How to Use:
The indicator plots a moving average that exponentially adjusts its sensitivity based on real-time market volatility. As volatility approaches historically high levels (98th percentile), the EMA length expands to filter out noise and help identify exhaustion. In low volatility (near the 2nd percentile), it contracts to become more responsive to new trends.
Usage: Add to the chart. For non-BTC assets, configure the tickers in settings.
Signal Interpretation: Look for the adaptive line to change direction, especially after it has been trending near one of the volatility extremes. This often anticipates sharp reversals.
Why Closed-Source? The specific implementation of the dynamic percentile-based anchoring, the volatility normalization formula, and the data aggregation logic are proprietary developments. Protecting the source code is necessary to safeguard the unique intellectual property behind this adaptive calculation method.
M/S Signal v2 - Multi-Zone Signal SystemM/S Signal v2 - Advanced Multi-Zone Breakout System
🔧 TECHNICAL INNOVATION
This indicator introduces a unique combination of adaptive zone confluence detection with multi-timeframe directional filtering that addresses specific limitations found in standard breakout indicators.
🎯 CORE ALGORITHM DIFFERENCES:
1. Adaptive Level Management:
Code
// Unlike static S/R indicators, levels update dynamically
if close > active_high:
active_high := current_high
active_low := current_low
generate_signal("BUY")
Traditional indicators use fixed pivot points. This system continuously adapts support/resistance levels based on actual price action.
2. Zone Confluence Mathematics:
Code
zones_match(level1, level2, tolerance_percent) =>
diff = math.abs(level1 - level2)
avg_price = (level1 + level2) / 2
tolerance = avg_price * tolerance_percent / 100
diff <= tolerance
This mathematical approach to zone alignment is not available in standard zone-based indicators.
3. Multi-Timeframe Signal Validation:
Code
htf_signal = request.security(symbol, htf_tf, get_last_signal_type())
allow_signal = current_tf_signal AND htf_allows_direction
The system tracks the last active signal from higher timeframes, not just current trend direction.
📊 UNIQUE FEATURES:
Triple Zone System:
Zone 1 (100-period): Macro trend identification
Zone 2 (60-period): Impulse movement detection
Zone 3 (20-period): Precise entry triggers
Dual Independent Filters:
Filter 1: Zone confluence with customizable tolerance (0.1% default)
Filter 2: Higher timeframe last signal direction
Each filter operates independently and can be toggled on/off
Dynamic Level Tracking: Unlike indicators that use predetermined levels, this system:
Updates support/resistance after each breakout
Prevents duplicate signals until new level formation
Tracks signal history to avoid repetitive alerts
📈 TECHNICAL SPECIFICATIONS:
Code Architecture:
PineScript v6 with optimized performance
45+ customizable parameters across 8 setting groups
Maximum 500 objects for stable operation
Overlay design with full visual control
Signal Generation Logic:
Monitor current support/resistance levels
Detect price breakouts above/below active levels
Apply zone confluence filter (if enabled)
Validate against higher timeframe direction (if enabled)
Generate final signal only when all conditions align
Visualization Components:
Three colored zone overlays with customizable fills
Active support/resistance level lines
BUY/SELL signal labels with price information
Key breakout candle highlighting
Real-time current price tracking
⚙️ SETTING GROUPS:
Zone Settings - Configure zone periods and colors
Zone Signal Filters - Control confluence detection
Higher Timeframe Filter - Set HTF validation rules
BUY Signal Configuration - Customize buy signal appearance
SELL Signal Configuration - Customize sell signal appearance
Alert System - Configure notification preferences
Visual Display - Control chart appearance elements
Level Management - Active support/resistance display
🎯 PRACTICAL APPLICATIONS:
For Scalping (M1-M5):
Disable HTF filter for faster signals
Use tight zone confluence tolerance (0.05%)
Focus on Zone 3 breakouts for quick entries
For Swing Trading (H1-H4):
Enable HTF filter with Daily timeframe
Use standard confluence tolerance (0.1%)
Combine all three zones for confirmation
For Position Trading (H4-Daily):
Set HTF filter to Weekly timeframe
Wider confluence tolerance (0.2%)
Focus on Zone 1 trend alignment
🔧 HOW TO USE:
Basic Setup: Use default parameters for most markets
Enable Filters: Turn on zone confluence for higher accuracy
Set HTF Filter: Choose appropriate higher timeframe for your strategy
Customize Signals: Adjust BUY/SELL signal appearance preferences
Configure Alerts: Set up notifications for real-time signal delivery
The indicator works by continuously monitoring price action against dynamically updated support and resistance levels, applying sophisticated filtering mechanisms to ensure only high-probability setups generate signals.
均线趋势过滤器 (MA_trend Signal/Noise Filter)双语简介
中文：
这款指标是一个基于“信噪比”思想的终极趋势过滤器。它通过比较快速和慢速EMA均线之间的差值（即信号）与ATR（平均真实波幅，代表噪音）来判断市场趋势。只有当信号的强度超过噪音的指定倍数时，才会确认趋势的有效性。该指标可帮助交易者过滤掉噪音，精确捕捉强势趋势，避免误操作。
English:
This indicator is the Ultimate Trend Filter based on the Signal-to-Noise ratio concept. It compares the difference between the fast and slow EMA (Signal) to the ATR (Noise) to determine market trends. A trend is confirmed only when the signal strength exceeds the noise by a specified multiplier. This indicator helps traders filter out noise and accurately capture strong trends, avoiding false signals.
High For Loop | MisinkoMasterThe High For Loop is a new Trend Following tool designed to give traders smooth and fast signals without being too complex, overfit or repainting.
It works by finding how many bars have a higher high than the current high, how many have a lower high, and scores it based on that. This provides users with easy and accurate signals, allowing for gaining a large edge in the market.
It is pretty simple but you can still play around with it pretty well and improve uppon your strategies.
For any backtests using strategies, I left many comments and tried to make it as easy as possible to backtest.
Enjoy G´s
MA-Median For Loop | MisinkoMasterThe MA-Median For Loop is a new Trend Following tool that gives the user smooth yet responsive trend signals, allowing you to see clear and accurate trends by combining the Moving Average & Median in a For Loop concept.
How does it work?
1. Select user defined inputs
=> Adjust it to your liking, everyone can set it to their liking.
2. Calculate the MA and the Median
=> Simple, but important
3. Calculate the For Loop
=> For every bar back where the median or ma of that bar is higher than the current median or ma subtract 0.5 from the trend score, and for every bar back where the current median/ma is higher than the previous one add 0.5 to the trend score.
This simple yet effective approach enhances speed, decreases noise, and produces accurate signals everyone can utilize to get an edge in the market
Enjoy G´s
HMA super trade by @arkancapMulti-HMA with five customizable moving averages: visual colors, transparency via picker, flexible line styles, and label/alert for HMA50↔HMA100 crossovers. Lightweight, readable, and ready for trading templates.
Мульти-HMA с пятью настраиваемыми скользящими: визуальные цвета, прозрачность через пикер, гибкие стили линий и метка/алерт для пересечений HMA50↔HMA100. Лёгкий, читабельный и готовый к торговым шаблонам.
Five Hull moving averages that show the trend and indicate key crossovers. Customize colors, thickness, and get accurate alerts. Suitable for scalping and multi-timeframes. Support for filling between moving averages to visually highlight areas of strength or weakness.
Пять Hull-скользящих, которые показывают тренд и подсказывают ключевые пересечения. Настраивай цвета, толщину и получай аккуратные алерты. Подходит для скальпа и мульти-таймфрейма. Поддержка заливки между скользящими для наглядного выделения зон силы или слабости.
DAILY WYCKOFF ATMWyckoff Confidence Dashboard
A clean, mobile-optimized Wyckoff phase and alignment dashboard built for serious traders.
This tool dynamically detects Accumulation, Distribution, Markup, and Markdown across multiple timeframes (1H/15M) and scores confidence based on:
• HTF trend direction
• Liquidity sweeps
• Fair Value Gap (FVG) presence
• Volume/OBV confirmation
• Multi-timeframe phase/action alignment
Includes smart alerts and a lightweight dashboard interface — no clutter, just actionable structure-based insight.
Great for SMC, Wyckoff, or price-action traders seeking high-confluence entries.
Statistical Mapping [Version 3]Edit Statistical Mapping (ESM) is a statistical technique used mainly in data validation, error detection, and imputation. It’s often applied in official statistics and large surveys. The method works by:
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
Smart Money Price Action ProSmart Money Price Action Pro - Smart Money and Price Action Dynamic Toolkit
The Smart Money Price Action Pro is designed to bring together multiple layers of market analysis into a single, cohesive framework, combining trend identification and consolidation detection in an actionable format. While individual indicators can provide useful insights, they often work in isolation. This toolkit integrates market flow detection, range analytics, and adaptive visualization into one system, allowing traders to see the bigger picture without piecing together multiple disconnected tools.
Building on principles from institutional trading behaviors, the toolkit gives traders a clearer picture of where “smart money” may be entering or exiting the market. Its design emphasizes confluence: signals from multiple independent modules overlap to create higher conviction setups, offering a structured edge when planning entries, exits, and risk levels.
At its core, the toolkit addresses the duality of market conditions: trending versus ranging. By offering a combination of trend-following signals and contrarian insights, it helps traders operate with a deeper understanding of market structure. While it provides actionable signals and visual guidance, it is intended as an assistive system, helping traders make more informed decisions rather than serving as a single source of truth.
Key Modules
1. Smart Money Signal Module
The Smart Money Signal Module identifies potential institutional activity by analyzing price swings and momentum shifts. Using configurable swing detection, it highlights potential reversal or continuation zones, expressed as adaptive zones around key market levels.
Signals are augmented with trend-colored candle overlays, offering immediate guidance on market bias. Bullish and bearish zones are clearly marked, while continuation and reversal markers help distinguish between trend shifts and market noise.
At its core, the engine applies swing detection combined with a sensitivity filter to track directional momentum across recent bars. This allows it to pinpoint bullish pivots (where downside momentum fades and strength returns) and bearish pivots (where upside momentum collapses). Once a pivot is confirmed, the system draws flow lines that map the breakout and classify it as either continuation or reversal, depending on broader market bias.
Momentum zones are then plotted to show areas where buyers stepped in with strength or sellers forced price lower. These levels extend forward dynamically, shifting in real time as new data forms. Zones change color the moment they break, visually confirming whether market structure has held or failed. Gradient shading highlights periods of extreme pressure, giving traders a clear visual of when momentum surges into overbought or oversold territory.
Instead of simply showing trend direction, this module also maps accumulation and distribution zones tied to institutional flows. When combined with the Range Module, these zones become more meaningful — for example, when institutional accumulation aligns with a breakout from consolidation.
Practical Use: Traders can use these signals to align trades with institutional flows. For example, entering a long position near a bullish accumulation zone or managing risk when bearish distribution areas form. By combining these insights with higher timeframe analysis, traders can filter out false signals and improve decision-making.
2. Range Detection Module
The Range Detection engine continuously monitors price action to flag when markets transition into consolidation phases. Ranges are defined not just by flat price action, but by a measurable contraction in volatility, repeated touches of boundary levels, and the clustering of traded volume around a central equilibrium point.
Once a valid range is identified, the system assigns a compression strength score (0–100). This score reflects how cleanly defined and structurally sound the consolidation is—higher scores indicate tighter boundaries and stronger evidence of accumulation or distribution.
Breakout tendencies are modeled dynamically. The system updates a forward-looking bias by incorporating:
Boundary time distribution – how often price presses against upper vs. lower edges
Historical breakout patterns – probability benchmarks derived from structurally similar ranges
Volume skew – whether traded volume leans toward buyers or sellers inside the range
Momentum alignment – auxiliary filters such as slope-based oscillators that indicate when energy is building for a directional move
The result is a live breakout forecast that evolves bar by bar as the range matures. Each active range carries a visual strength meter plotted above the consolidation zone, quantifying both compression and breakout potential in real time.
The module also supports range memory, preserving completed consolidations even after a breakout. This allows traders to review the prior structure for post-analysis or to track whether price respects the boundaries of the old range as support or resistance going forward.
Practical Use : Traders can use these ranges to anticipate breakout direction or step aside when conditions are unclear. A tight consolidation near a bullish zone, for instance, often signals a potential long opportunity, while overlapping bearish flows warn of false breakouts.
Integrated Workflow
The strength of the toolkit lies in its synergy. Each module is effective on its own, but the real advantage comes when their signals align.
A typical workflow may include:
Assessing the market trend using the Smart Money Signal Module and its trend-colored overlays
Identifying consolidation and breakout zones with the Range Detection Module
Watching for confluences: institutional accumulation aligning with range compression, or dashboard bias matching local setups
Executing trades with structured confidence, using these layered confirmations rather than relying on a single trigger
This integrated workflow streamlines decision-making and avoids the conflicting signals that can occur when combining unrelated indicators.
Additional Features
Adaptive Visualization : Dynamic zones and trend overlays adjust to volatility, keeping charts clear and focused
Analytics Dashboard : A compact summary panel shows active zones, bullish vs bearish flow counts, and current bias, giving context at a glance
Instead of simply adding more signals, the dashboard provides a meta-layer of analysis — context, bias, and flow strength — helping traders manage risk and stay aligned with broader market conditions.
Use Cases
Trend Confluence : Entering trades in line with prevailing smart money flows while filtering out counter-trend setups
Breakout Trading : Using the Range Detection Module to anticipate breakout zones and confirming direction with institutional flow signals
Contrarian Reversal Trades : Targeting accumulation/distribution zones where both modules indicate potential reversals
Each use case demonstrates how layered confluence creates clarity and conviction, making the toolkit a strong complement to other forms of technical analysis.
Conclusion
The Smart Money Signals Toolkit simplifies complex market analysis into actionable, visually intuitive insights. While standalone indicators provide value, this toolkit goes further by combining smart money flows, range detection, adaptive zones, and dashboard analytics into one cohesive system.
It doesn’t just generate buy/sell markers — it shows why a setup matters, where it is occurring, and how it aligns with broader conditions. This allows traders to operate with greater clarity, structure, and discipline.
Risk Disclaimer : This toolkit and its features are for educational and informational purposes only. Past performance does not guarantee future results. All suggested use cases are theoretical and should be applied with proper risk management.
Double Median ATR Bands | MisinkoMasterThe Double Median ATR Bands is a version of the SuperTrend that is designed to be smoother, more accurate while maintaining a good speed by combining the HMA smoothing technique and the median source.
How does it work?
Very simple!
1. Get user defined inputs:
=> Set them up however you want, for the result you want!
2. Calculate the Median of the source and the ATR
=> Very simple
3. Smooth the median with √length (for example if median length = 9, it would be smoothed over the length of 3 since 3x3 = 9)
4. Add ATR bands like so:
Upper = median + (atr*multiplier)
Lower = median - (atr*multiplier)
Trend Logic:
Source crossing over the upper band = uptrend
Source crossing below the lower band = downtrend
Enjoy G´s!
Cardwell RSI by TQ📌 Cardwell RSI – Enhanced Relative Strength Index
This indicator is based on Andrew Cardwell’s RSI methodology , extending the classic RSI with tools to better identify bullish/bearish ranges and trend dynamics.
In uptrends, RSI tends to hold between 40–80 (Cardwell bullish range).
In downtrends, RSI tends to stay between 20–60 (Cardwell bearish range).
Key Features :
Standard RSI with configurable length & source
Fast (9) & Slow (45) RSI Moving Averages (toggleable)
Cardwell Core Levels (80 / 60 / 40 / 20) – enabled by default
Base Bands (70 / 50 / 30) in dotted style
Optional custom levels (up to 3)
Alerts for MA crosses and level crosses
Data Window metrics: RSI vs Fast/Slow MA differences
How to Use :
Monitor RSI behavior inside Cardwell’s bullish (40–80) and bearish (20–60) ranges
Watch RSI crossovers with Fast (9) and Slow (45) MAs to confirm momentum or trend shifts
Use levels and alerts as confluence with your trading strategy
Default Settings :
RSI Length: 14
MA Type: WMA
Fast MA: 9 (hidden by default)
Slow MA: 45 (hidden by default)
Cardwell Levels (80/60/40/20): ON
Base Bands (70/50/30): ON
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.
Deadband Hysteresis Filter [BackQuant]Deadband Hysteresis Filter
What this is
This tool builds a “debounced” price baseline that ignores small fluctuations and only reacts when price meaningfully departs from its recent path. It uses a deadband to define how much deviation matters and a hysteresis scheme to avoid rapid flip-flops around the decision boundary. The baseline’s slope provides a simple trend cue, used to color candles and to trigger up and down alerts.
Why deadband and hysteresis help
They filter micro noise so the baseline does not react to every tiny tick.
They stabilize state changes. Hysteresis means the rule to start moving is stricter than the rule to keep holding, which reduces whipsaw.
They produce a stepped, readable path that advances during sustained moves and stays flat during chop.
How it works (conceptual)
At each bar the script maintains a running baseline dbhf and compares it to the input price p .
Compute a base threshold baseTau using the selected mode (ATR, Percent, Ticks, or Points).
Build an enter band tauEnter = baseTau × Enter Mult and an exit band tauExit = baseTau × Exit Mult where typically Exit Mult < Enter Mult .
Let diff = p − dbhf .
If diff > +tauEnter , raise the baseline by response × (diff − tauEnter) .
If diff < −tauEnter , lower the baseline by response × (diff + tauEnter) .
Otherwise, hold the prior value.
Trend state is derived from slope: dbhf > dbhf → up trend, dbhf < dbhf → down trend.
Inputs and what they control
Threshold mode
ATR — baseTau = ATR(atrLen) × atrMult . Adapts to volatility. Useful when regimes change.
Percent — baseTau = |price| × pctThresh% . Scale-free across symbols of different prices.
Ticks — baseTau = syminfo.mintick × tickThresh . Good for futures where tick size matters.
Points — baseTau = ptsThresh . Fixed distance in price units.
Band multipliers and response
Enter Mult — outer band. Price must travel at least this far from the baseline before an update occurs. Larger values reject more noise but increase lag.
Exit Mult — inner band for hysteresis. Keep this smaller than Enter Mult to create a hold zone that resists small re-entries.
Response — step size when outside the enter band. Higher response tracks faster; lower response is smoother.
UI settings
Show Filtered Price — plots the baseline on price.
Paint candles — colors bars by the filtered slope using your long/short colors.
How it can be used
Trend qualifier — take entries only in the direction of the baseline slope and skip trades against it.
Debounced crossovers — use the baseline as a stabilized surrogate for price in moving-average or channel crossover rules.
Trailing logic — trail stops a small distance beyond the baseline so small pullbacks do not eject the trade.
Session aware filtering — widen Enter Mult or switch to ATR mode for volatile sessions; tighten in quiet sessions.
Parameter interactions and tuning
Enter Mult vs Response — both govern sensitivity. If you see too many flips, increase Enter Mult or reduce Response. If turns feel late, do the opposite.
Exit Mult — widening the gap between Enter and Exit expands the hold zone and reduces oscillation around the threshold.
Mode choice — ATR adapts automatically; Percent keeps behavior consistent across instruments; Ticks or Points are useful when you think in fixed increments.
Timeframe coupling — on higher timeframes you can often lower Enter Mult or raise Response because raw noise is already reduced.
Concrete starter recipes
General purpose — ATR mode, atrLen=14 , atrMult=1.0–1.5 , Enter=1.0 , Exit=0.5 , Response=0.20 . Balanced noise rejection and lag.
Choppy range filter — ATR mode, increase atrMult to 2.0, keep Response≈0.15 . Stronger suppression of micro-moves.
Fast intraday — Percent mode, pctThresh=0.1–0.3 , Enter=1.0 , Exit=0.4–0.6 , Response=0.30–0.40 . Quicker turns for scalping.
Futures ticks — Ticks mode, set tickThresh to a few spreads beyond typical noise; start with Enter=1.0 , Exit=0.5 , Response=0.25 .
Strengths
Clear, explainable logic with an explicit noise budget.
Multiple threshold modes so the same tool fits equities, futures, and crypto.
Built-in hysteresis that reduces flip-flop near the boundary.
Slope-based coloring and alerts that make state changes obvious in real time.
Limitations and notes
All filters add lag. Larger thresholds and smaller response trade faster reaction for fewer false turns.
Fixed Points or Ticks can under- or over-filter when volatility regime shifts. ATR adapts, but will also expand bands during spikes.
On extremely choppy symbols, even a well tuned band will step frequently. Widen Enter Mult or reduce Response if needed.
This is a chart study. It does not include commissions, slippage, funding, or gap risks.
Alerts
DBHF Up Slope — baseline turns from down to up on the latest bar.
DBHF Down Slope — baseline turns from up to down on the latest bar.
Implementation details worth knowing
Initialization sets the baseline to the first observed price to avoid a cold-start jump.
Slope is evaluated bar-to-bar. The up and down alerts check for a change of slope rather than raw price crossings.
Candle colors and the baseline plot share the same long/short palette with transparency applied to the line.
Practical workflow
Pick a mode that matches how you think about distance. ATR for volatility aware, Percent for scale-free, Ticks or Points for fixed increments.
Tune Enter Mult until the number of flips feels appropriate for your timeframe.
Set Exit Mult clearly below Enter Mult to create a real hold zone.
Adjust Response last to control “how fast” the baseline chases price once it decides to move.
Final thoughts
Deadband plus hysteresis gives you a principled way to “only care when it matters.” With a sensible threshold and response, the filter yields a stable, low-chop trend cue you can use directly for bias or plug into your own entries, exits, and risk rules.
Rocket/Bomb PPO + SMI (confirmed, no repaint) — 1-liner labelsName: Rocket/Bomb PPO + SMI (confirmed, non-repaint)
What it does
Combines PPO (Percentage Price Oscillator) momentum with SMI (Stochastic Momentum Index) timing.
Prints a 🚀 “Rocket” buy label when PPO crosses up its signal and SMI crosses up its signal (momentum + timing agree).
Prints a 💣 “Bomb” sell label when PPO crosses down its signal and SMI crosses down its signal.
Labels are offset by ATR so they sit neatly above/below bars.
Why it’s clean (non-repaint)
Signals are gated by bar close confirmation (barstate.isconfirmed), so labels only appear after the bar closes—no flicker or back-filling.
Optional filter
“Strict SMI zone” filter: only allow buys when SMI < –Z and sells when SMI > +Z (default Z=20). This reduces noise in choppy markets.
Customization
PPO/SMI lengths, strict zone level, emoji vs arrows, label colors, icon size, and ATR offset are all configurable.
Alerts
Built-in alert conditions for Rocket (Long) and Bomb (Short) so you can automate notifications.
How to use (at a glance)
Trade in the direction of the Rocket/Bomb labels; the strict zone option helps avoid weak signals.
Best paired with basic trend or S/R context (e.g., higher-time-frame trend filter, recent swing levels) for entries/exits.
