BBr1 Candle Range Volitility Gap IndicatorModified Candle Range Volatility Gap Indicator
1. Useful to analyze bars body and wicks and volatility of security.
2. Added a Percentage Option - easier to analyze across different securities.
2. Added a Standard Deviation ("1 std dev= 68.2%, 2 std dev=95.4%, 3 std dev=99.7%, etc") based upon user defined lookback period.
3. Added the ability to include Gaps in Analysis. (Gaps are when the prior closing cost does not equal opening price)
4. Possible Uses setting up stop losses, trailing entries/exits (inside range or outside range).
5. Use it with other indicators in determining if to make an entry or close entry.
Reposted Original Description by © ka66 Kamal Advani
Visually shows the Body Range (open to close) and Candle Range (high to low).
Semi-transparent overlapping area is the full Candle Range, and fully-opaque smaller area is the Body Range. For aesthetics and visual consistency, Candle Range follows the direction of the Body Range, even though technically it's always positive (high - low).
The different plots for each range type also means the UI will allow deselecting one or the other as needed. For example, some strategies may care only about the Body Range, rather than the entire Candle Range, so the latter can be hidden to reduce noise.
Threshold horizontal lines are plotted, so the trader can modify these high and low levels as needed through the user interface. These need to be configured to match the instrument's price range levels for the timeframe. The defaults are pretty arbitrary for +/- 0.0080 (80 pips in a 4-decimal place forex pair). Where a range reaches or exceeds a threshold, it's visually marked as well with a shape at the Body or Candle peak, to assist with quicker visual potential setup scanning, for example, to anticipate a following reversal or continuation.
Ketidakstabilan
Sharpe Ratio ScreenerThe original code was created by tim_amblard , and the modifications were made by Mr_Rakun for the purpose of adapting the script into a screener format.
The Sharpe ratio is a popular metric used to measure the risk-adjusted return of an asset or portfolio, which allows traders and investors to assess whether the returns they are receiving are worth the risk they are taking. In this script, the Sharpe ratio is calculated over a 180-day period (approximately 6 months), and several valuation zones are defined based on the ratio to help assess whether an asset is overvalued, undervalued, or critically undervalued.
Key Features:
1. Risk-Free Rate Input: The user can define the risk-free rate (usually the return of government bonds or a similar safe asset) for Sharpe ratio calculation.
2. Lookback Period (180 Days): The default lookback period is set to 180 days (approximately 6 months) to calculate the mean and standard deviation of the asset’s daily returns.
3. Valuation Zones:
• Overvalued Zone: If the Sharpe ratio is greater than 5.
• Undervalued Zone: If the Sharpe ratio is between -1 and 5.
• Critically Undervalued Zone: If the Sharpe ratio is below -3.
• Neutral Zone: If the Sharpe ratio does not meet any of the above conditions.
4. Table View: The script pulls a list of symbols from the user (e.g., cryptocurrency or stock tickers) and displays their latest price, Sharpe ratio, and whether they are in an overvalued, undervalued, or neutral zone in a table format.
5. Custom Symbol Input: The user can input a list of symbols (separated by commas) to track.
6. Daily Timeframe Check: The script warns the user to ensure they are using a daily timeframe, as this indicator is designed specifically for it.
How It Works:
• The script calculates the daily returns for each symbol over the specified lookback period.
• It then calculates the mean and standard deviation of the returns to derive the Sharpe ratio.
• The Sharpe ratio is annualized, and it’s compared to the defined thresholds to categorize the symbol into different valuation zones.
• A table is generated on the chart to show the symbols, their current prices, and their Sharpe ratios, with color-coded background to easily identify whether they are overvalued (red), undervalued (green), or critically undervalued (blue).
This tool is useful for screening multiple assets for their Sharpe ratio to find investment opportunities with optimal risk-adjusted returns.
Original code credit: This code was originally written by tim_amblard and modified by Mr_Rakun for use as a screener.
Türkçe Açıklama:
Orijinal kod tim_amblard tarafından yazılmıştır ve Mr_Rakun tarafından, bu script’in tarayıcı formatına dönüştürülmesi amacıyla değiştirilmiştir.
Sharpe oranı, bir varlığın veya portföyün risk düzeltilmiş getirisini ölçmek için yaygın olarak kullanılan bir metriktir. Bu metrik, yatırımcıların aldıkları risk karşılığında aldıkları getirinin ne kadar verimli olduğunu değerlendirmelerine olanak tanır. Bu script’te, Sharpe oranı 180 günlük bir periyot (yaklaşık 6 ay) boyunca hesaplanır ve oranı baz alarak varlıkların değerleme bölgeleri tanımlanır: aşırı değerli, değerli ve kritik şekilde değersiz.
Ana Özellikler:
1. Risk-Free Rate (Risk-Free Oranı) Girişi: Kullanıcı, Sharpe oranı hesaplaması için risk-free (risksiz) oranı (genellikle devlet tahvilleri veya benzeri güvenli bir varlık getirisi) tanımlayabilir.
2. Lookback (Geribildirim) Periyodu (180 Gün): Varsayılan geribildirim periyodu, varlığın günlük getirilerinin ortalama ve standart sapmalarını hesaplamak için 180 gün (yaklaşık 6 ay) olarak ayarlanmıştır.
3. Değerleme Bölgeleri:
• Aşırı Değerli Bölge: Sharpe oranı 5’ten büyükse.
• Değerli Bölge: Sharpe oranı -1 ile 5 arasında ise.
• Kritik Derecede Değersiz Bölge: Sharpe oranı -3’ten küçükse.
• Nötr Bölge: Sharpe oranı yukarıdaki hiçbir koşulu karşılamıyorsa.
4. Tablo Görünümü: Script, kullanıcıdan alınan semboller listesine göre (örneğin, kripto para veya hisse senedi sembolleri) her bir sembolün son fiyatını, Sharpe oranını ve değerleme bölgesini tablo şeklinde gösterir.
5. Özel Sembol Girişi: Kullanıcı, izlemek istediği semboller listesini (virgülle ayrılmış) girebilir.
6. Günlük Zaman Çerçevesi Kontrolü: Script, kullanıcının doğru sonuçlar almak için günlük zaman çerçevesinde işlem yapması gerektiğini hatırlatır.
Nasıl Çalışır:
• Script, her sembol için belirtilen geribildirim periyodu boyunca günlük getirileri hesaplar.
• Ardından, getirilerin ortalama ve standart sapmasını hesaplayarak Sharpe oranını çıkarır.
• Sharpe oranı yıllıklaştırılır ve tanımlanan eşiklerle karşılaştırılarak sembol, farklı değerleme bölgelerine kategorize edilir.
• Grafik üzerinde, semboller, mevcut fiyatları ve Sharpe oranları gösteren bir tablo oluşturulur. Bu tablo, hangi sembollerin aşırı değerli (kırmızı), değerli (yeşil) veya kritik derecede değersiz (mavi) olduğunu kolayca görmek için renk kodlu arka planlar kullanır.
Bu araç, yatırım fırsatlarını daha verimli bir şekilde değerlendirebilmek için risk düzeltilmiş getiri açısından optimal fırsatları bulmak için birden fazla varlığın Sharpe oranlarını taramak için kullanışlıdır.
ATR Percentages BoxThis custom indicator provides a quick visual reference for volatility-based price ranges, directly on your TradingView charts. It calculates and displays three ranges derived from the Daily Average True Range (ATR) with a standard 14-period setting:
5 Min (3% ATR): Ideal for very short-term scalping and quick intraday moves.
1 Hour (5% ATR): Useful for hourly setups, short-term trades, and intraday volatility assessment.
Day (10% ATR): Perfect for daily volatility context, swing trades, or placing stops and targets.
The ranges are clearly shown in a compact box at the top-right corner, providing traders immediate insights into realistic price movements, helping to optimise entries, stops, and profit targets efficiently.
Liquidity Market Seeking SwiftEdgeThis indicator is designed to identify potential liquidity levels on the chart by detecting swing highs and lows, which are often areas where stop-loss orders or significant orders accumulate. It visualizes these levels with horizontal lines and labels on the right side of the chart, color-coded based on volume to help traders understand where the market might seek liquidity.
How It Works
Swing Highs and Lows: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant swing points over a user-defined lookback period (Swing Length). These points are considered potential liquidity levels where stop-loss orders might be placed.
Volume Analysis: The indicator compares the volume at each swing point to the average volume over a specified period (Volume Average Length). Levels with above-average volume are colored red, indicating higher liquidity, while levels with below-average volume are colored green.
Liquidity Visualization: Horizontal dashed lines are drawn at each identified level, extending across the chart. Labels on the right side display the estimated liquidity amount (simulated based on volume and a multiplier, Volume Multiplier for Liquidity).
Sell Signal: A "SELL NOW" label appears when the price approaches a liquidity level after an uptrend (detected using a simple moving average crossover). This suggests a potential reversal as the market may target liquidity at that level.
Strategy Concept: Market Seeking Liquidity
The indicator is based on the concept that markets often move toward areas of high liquidity, such as clusters of stop-loss orders or significant order accumulations. These liquidity pools are typically found around swing highs and lows, where traders place their stop-losses or large orders. By identifying these levels and highlighting those with higher volume (red lines), the indicator aims to show where the market might move to "grab" this liquidity. For example, after an uptrend, the market may reverse at a swing high to take out stop-losses above that level, providing liquidity for larger players to enter or exit positions.
Settings
Swing Length: The number of bars to look back for detecting swing highs and lows. Default is 20.
Liquidity Threshold: The price threshold for merging nearby levels to avoid duplicates. Default is 0.001.
Volume Average Length: The period for calculating the average volume to compare against. Default is 20.
Volume Multiplier for Liquidity: A multiplier to scale the volume into a simulated liquidity amount (displayed as "K"). Default is 1000.
Usage Notes
Use this indicator on any timeframe, though it may be more effective on higher timeframes (e.g., 1H, 4H) where swing points are more significant.
Red lines indicate levels with higher volume, suggesting stronger liquidity pools that the market might target.
Green lines indicate levels with lower volume, which may be less significant.
The "SELL NOW" signal is a basic example of how to use liquidity levels for trading decisions. It appears when the price approaches a liquidity level after an uptrend, but it should be used in conjunction with other analysis.
Adjust the Volume Multiplier for Liquidity to scale the displayed liquidity amounts based on your instrument (e.g., forex pairs may need a higher multiplier than indices).
Extreme Areas with MTF Screener by QTX Algo SystemsStatistically Extreme Areas with MTF Screener by QTX Algo Systems
Overview
This indicator is designed to automatically highlight zones where prices become statistically overextended, signaling potential reversal opportunities. Enhanced with a Multi Time Frame (MTF) Screener, it verifies these extremes across several timeframes for a comprehensive, multi-dimensional view of market conditions.
How It Works
Baseline Statistical Analysis:
The indicator establishes a baseline price range using historical data through a statistical percentile approach. This baseline reflects typical price extremes over time.
Volatility and Momentum Filters:
It incorporates a Bollinger Band Width Percentile (BBWP) to measure real-time volatility and combines this with a double‐smoothed SMI and a Price – Moving Average Ratio (PMARP) to assess short-term momentum. This dual-filter system ensures that signals are generated only when both volatility and momentum conditions are satisfied.
Directional Oscillator (BBO) Analysis:
A Bollinger Band Oscillator (BBO) is used to evaluate the slopes of the upper and lower bands, adding an extra layer of confirmation for identifying true market extremes.
MTF Screener Integration:
The added MTF Screener scans multiple timeframes, confirming that the statistically extreme conditions are not isolated events. This cross-verification provides a more robust signal, ensuring that the identified reversal zones are consistent across the market.
Customizable Visual Alerts:
The indicator allows for customizable color coding for various conditions (e.g., extreme low warnings, extreme high warnings, and potential reversals), offering clear, visual guidance for traders.
Why It’s Different and Valuable
This tool is more than just a simple merger of common indicators—it’s a carefully integrated system that validates price extremes across several dimensions. By combining statistical analysis with real-time volatility, momentum verification, and multi-timeframe confirmation, it provides a dynamic framework that helps traders identify high-probability reversal zones while minimizing false signals. The added MTF Screener ensures that these signals are consistent and reliable across different market views, enhancing the overall decision-making process.
How to Use
Monitor Visual Cues: Look for the color-coded signals that indicate statistically extreme price levels.
Confirm Across Timeframes: Use the MTF Screener component to ensure that the extreme conditions appear consistently across various timeframes.
Integrate with Your Strategy: Use this indicator alongside other technical tools to refine entry, exit, and stop-loss decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and conduct your own analysis before trading.
Volatility Based Momentum with MTF Screener by QTX Algo SystemsVolatility Based Momentum with MTF Screener by QTX Algo Systems
Overview
This indicator builds on our original Volatility Based Momentum tool by integrating a Multi Time Frame (MTF) Screener that provides real-time, cross-market momentum analysis. It dynamically adjusts momentum signals using adaptive volatility measurements, ensuring that signals reflect true market strength across various timeframes and assets.
How It Works
Core Momentum Analysis:
The indicator uses a double‐smoothed SMI combined with a Price – Moving Average Ratio (PMARP) to assess short-term momentum. These metrics filter out noise and generate per-candle signals based on sustained market energy.
Adaptive Volatility Measurement:
An adaptive volatility factor—derived from a Bollinger Band Width Percentile (BBWP) calculation—scales the momentum readings, ensuring that only strong signals in a sufficiently volatile market are considered.
MTF Screener Integration:
The MTF Screener scans multiple timeframes simultaneously, confirming that a momentum signal is consistent across different market views. This extra layer of screening reduces false signals and helps ensure that the detected momentum is robust and reliable.
Real-Time Visual Feedback:
Dynamic visual cues, such as color changes and signal markers, indicate when the momentum and volatility align, providing a clear, actionable overview.
Why It’s Different and Valuable
This indicator isn’t just a simple overlay of standard momentum and volatility measures—it’s a multi-layered system that verifies signals across multiple timeframes. The integrated MTF Screener provides broader context and cross-validation, making it a more dependable tool for confirming trend strength. This level of depth in analysis offers enhanced clarity and helps traders make more confident decisions compared to using conventional indicators in isolation.
How to Use
Review Per-Candle Signals: Observe the momentum signals generated on your chart and note when they are confirmed by the adaptive volatility measure.
Cross-Check with MTF Screener: Ensure that signals appear consistently across multiple timeframes before taking action.
Adjust Settings for Your Style: Customize the volatility threshold, and MTF settings to match your specific trading approach.
Integrate with Your Strategy: Use the insights from this indicator alongside other analysis tools to optimize your entry and exit points.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always apply proper risk management and conduct your own analysis before trading.
Continuation Opportunity with MTF Screener by QTX Algo SystemsContinuation Opportunity Indicator with MTF Screener by QTX Algo Systems
Overview
This enhanced indicator is designed to pinpoint key moments when an established trend is likely to continue. By combining traditional momentum analysis with dual volatility measures—and now integrating a powerful Multi Time Frame (MTF) Screener—it offers a multi-dimensional view of trend behavior. This tool not only detects when a pullback is simply a temporary consolidation (characterized by reduced volatility) but also confirms that the overall trend is poised to resume, validated across several timeframes.
How It Works
Core Methodology:
The base indicator uses a double‐smoothed Stochastic Momentum Index (SMI) combined with a Price – Moving Average Ratio (PMARP) to detect momentum crossovers that signal trend continuation. It also uses volatility filters to ensure that the signals occur only when market activity is strong.
Dual Volatility Analysis:
A Bollinger Band Width Percentile (BBWP) measure and historical volatility metrics work together to ensure that only meaningful pullbacks trigger signals—distinguishing between noise and genuine consolidation.
MTF Screener Integration:
The new MTF Screener feature extends the analysis beyond a single timeframe. It scans multiple assets and timeframes concurrently, confirming that a detected pullback or resumption signal appears consistently across the broader market view. This cross-verification minimizes false signals and provides traders with confidence that the trend continuation is robust.
Enhanced Visual Cues:
Color-coded backgrounds and well-defined signal triggers help traders quickly interpret when a pullback is likely just a consolidation phase and when increased volatility signals the trend’s resumption.
Why It’s Different and Valuable
Unlike a simple combination of separate indicators, this tool integrates each element in a systematic, layered approach. The MTF Screener adds an extra dimension by validating signals across different timeframes—ensuring that traders are not basing decisions on isolated, potentially misleading data. This cohesive design enhances overall accuracy and provides actionable insights that are more robust than what individual indicators would offer on their own.
How to Use
Monitor Visual Signals: Look for color-coded cues and momentum crossovers that appear after a pullback.
Validate Across Timeframes: Use the MTF Screener’s output to confirm that the continuation signal is consistent across various timeframes.
Integrate with Other Tools: Combine these signals with your existing technical analysis methods to refine your entry and exit points.
Disclaimer
This indicator is provided for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Dynamic Price ImpulseThis indicator is designed to capture price momentum without the lag typically found in traditional oscillators.
Core Mechanics
Instead of using simple price differences, the indicator normalizes changes relative to the average true range (ATR), making it adaptive to different volatility regimes.
By squaring the normalized change while preserving its sign, the indicator responds more aggressively to stronger price moves while remaining sensitive to smaller ones.
The indicator identifies periods when volatility is expanding, which often precede significant price movements.
Trading Strategy Applications
1. Momentum Signals:
o When the indicator crosses above zero, look for long entries
o When it crosses below zero, look for short entries
o The stronger the impulse (farther from zero), the stronger the signal
2. Early Trend Detection:
o Volatility expansion markers (yellow circles) often appear at the beginning of new trends
o Use these as early warning signals to prepare for potential entries
3. Trend Continuation:
o Strong readings in the direction of the trend suggest continuation
o Weakening readings suggest the trend may be losing steam
4. Counter-Trend Opportunities:
o Look for divergences between price and the indicator for potential reversals
o When price makes a new high but the indicator doesn't, consider potential shorts (and vice versa)
Fine-Tuning
• Length (14): Controls the lookback period for ATR calculation. Lower values make it more responsive but noisier.
• Threshold (1.5): Determines how much volatility needs to expand to trigger the volatility expansion signal.
• Smoothing (3): Reduces noise in the signal. Higher values reduce false signals but introduce more lag.
MSB BOS Market Structure [FTB]Track Market Structure Breaks (MSB) and Breaks of Structure (BOS) on your charts. This indicator does exactly that without clutter and with easy-to-spot.
🔑 Features:
MSB (Market Structure Break): Shows when price flips and breaks the previous high/low — possible start of a new trend.
BOS (Break of Structure): Highlights key structural breakouts in line with the existing trend.
✅ Pivot-Based Analysis (Body Focused)
Uses candle body-based pivot highs and lows to find clean market structure points (no wicks confusion here!).
Adjustable pivot strength — control how many candles you want on either side to define a swing.
✅ Clean Visual Markings
MSB and BOS lines with optional labels so you see exactly where breaks happen.
Customizable line style (Solid, Dashed, Dotted) to match your chart aesthetic.
Optional pivot markers to show minor swing highs/lows.
✅ Alerts Ready
Set alerts for any MSB or BOS, or filter to specific bullish/bearish breaks — never miss a key level again
💡 How to Use This Indicator:
Identify Trend Shifts: Use MSB to spot early trend reversals — when a previous structure breaks against the trend.
Catch Continuations: Watch for BOS to confirm trend continuation — great for riding the trend!
⚙️ Settings You Can Adjust:
Pivot Strength: How many candles to look back and forward for swing points (default: 3).
Show Pivots: Optional — highlight swing highs and lows for extra clarity.
Victor the Predictor - Gold Advanced Analytics Suite by SK v 2.0Victor the Predictor - Gold Advanced Analytics Suite by SK v2.0
Overview:
Victor the Predictor is a powerful trading indicator designed for advanced market analysis, combining classic technical indicators with volatility-based metrics and machine learning-based predictions. This suite is specifically optimized for trading gold (XAUUSD) but can be used effectively in other markets as well.
Key Features:
✅ Swing Levels & Trend Channels: Automatically detects key support and resistance levels, along with trend channels, to help identify optimal entry and exit points.
✅ Technical Indicators: Includes RSI, MACD, and ATR for trend strength assessment and momentum-based trading decisions.
✅ Machine Learning Forecasting: Implements a predictive algorithm that analyzes historical price action, volatility, and volume to provide directional forecasts.
✅ Smart Volatility Filtering: Avoids false signals by analyzing ATR-based volatility spikes and filtering out unstable market conditions.
✅ Candle Coloring & Signal Markers: Highlights strong bullish and bearish signals based on confluence criteria, making trade opportunities visually clear.
✅ Customizable Settings: Offers full flexibility to adjust indicator parameters for different trading styles and risk preferences.
How It Works:
🔹 Support & Resistance Zones: The script calculates the highest high and lowest low within a given period to define swing levels. The mid-point between these levels serves as a potential pivot area.
🔹 Trend Analysis: The indicator overlays trend channels using EMA (50) and ATR-based deviation bands, helping traders gauge market direction and volatility expansion.
🔹 Momentum & Volume Analysis: RSI and MACD are used to confirm trade entries, while volume percentile ranks help assess market participation.
🔹 Machine Learning Predictions: A simplified ML-based approach aggregates various technical indicators into a weighted prediction score, which is normalized and projected over a short-term horizon.
🔹 Trade Signals:
BUY Signal: RSI crosses above 50, MACD is bullish, price is above EMA-14, and volatility conditions are favorable.
SELL Signal: RSI crosses below 50, MACD is bearish, price is below EMA-14, and volatility conditions are favorable.
Strong signals appear only when volatility filters confirm a stable environment.
Visualization & Alerts:
Colored Candles: Green for strong bullish signals, red for strong bearish signals.
Support & Resistance Zones: Automatically plotted key price levels.
Trend Channels: Highlight areas of expected price movement.
ML Forecast Line: A projected trend based on historical data analysis.
Buy/Sell Markers: Clear trade signals displayed directly on the chart.
Usage & Optimization:
Works best on gold (XAUUSD) but can be applied to forex, indices, and commodities.
Ideal for swing traders and day traders who use technical confluence.
Recommended timeframes: 15M, 1H, 4H, Daily.
Adjust RSI, MACD, ATR, and ML sensitivity to fine-tune signals according to market conditions.
📌 Important Note:
This indicator does not guarantee future performance and should be used alongside proper risk management strategies. Always backtest before using it in live trading.
FTB Smart Trader System — Market Maker Levels, EMAs & VectorsThe FTB Trade Engine is an indicator suite I built for myself as a crypto trader. It's designed specifically for trading Institution levels, EMAs, PVSRA Volume Candles, and Session Timings. It helps me spot high probability trade setups without overcomplicating things.
🔑 Features of this Indicator
📌 🔥 Key Session Levels (extend lines in settings as needed)
✅ Weekly High & Low (HOW/LOW) — Automatically plots the previous week's high and low
✅ Daily High & Low (HOD/LOD) — Marks the prior day's range
✅ Asia Session High & Low — Plots the Asian session’s high and low, helping you detect potential breakouts or fakeouts, as Asia often sets the initial high and low of the day.
✅ 50% Asia Level — Automatically calculates and displays the midpoint between Asia’s high and low, an important level for intraday trading.
📌 🔥 Advanced EMA Suite
✅ Includes 10, 20, 50, 200, and 800 EMAs — providing key zones of support, resistance, and trend direction.
👀 Good to know: the break of the 50EMA WITH a vector candle is significant for reversals.
📌 🔥 PVSRA Candles
(👀 IMPORTANT: To properly view PVSRA candles, make sure to UNCHECK all default candle settings — Color Bars, Body, Borders, and Wick — in your chart's candle settings.)
✅ Price, Volume, Support & Resistance Analysis (PVSRA) Candles — These special candles combine price action with volume analysis, color-coded to highlight areas potentially influenced by market makers, institutions, and large players. Perfect for identifying key volume zones and quickly analyzing any coin or pair without switching tools.
Candle Colors Explained:
Bullish Candles:
🟢 Green — 200% increase in volume on bullish moves (strong buyer presence).
🔵 Blue — 150% increase in bullish volume, but may also indicate fatigue or possible reversal.
⚪ White — Normal bullish volume (standard green candles).
Bearish Candles:
🔴 Red — 200% increase in bearish volume compared to the last 10 candles (strong selling).
🟣 Magenta — 150% increase in bearish volume, signaling possible continuation or exhaustion.
⚫ Gray — Normal bearish volume (standard red candles).
Triple Doji SequenceThe Triple Doji Sequence indicator helps traders identify consecutive Doji candlestick patterns, allowing them to choose between spotting single, double, or triple Dojis. A Doji is detected when the candle's body is small relative to its wicks, with either the upper or lower wick being significantly larger. Users can customize their own Doji criteria by adjusting the body size and wick dominance settings. The indicator ensures that consecutive Dojis align in the same direction before confirming a valid pattern, making it easier to identify market indecision or potential trend reversals.
When the chosen Doji sequence is detected, the indicator plots a star (*) above bearish Dojis (upper wick dominant) and below bullish Dojis (lower wick dominant). It also sends alerts when a valid sequence is confirmed at the close of the bar. This tool helps traders refine their strategy by spotting repeated Doji formations, which may indicate key turning points or continuation patterns in price action.
How to Use the Triple Doji Sequence Indicator?
Apply the Indicator:
Add the Triple Doji Sequence indicator to your TradingView chart.
It will automatically scan for Doji patterns based on your settings.
Customize Your Doji Criteria:
Adjust the body size and wick dominance settings to define what qualifies as a Doji.
Choose whether to detect single, double, or triple Doji sequences.
Interpret the Signals:
A star (*) above a candle signals a bearish Doji (upper wick dominant).
A star (*) below a candle signals a bullish Doji (lower wick dominant).
Set Up Alerts:
Enable alerts to receive notifications when a Doji sequence is confirmed at bar close.
Choose alert frequency based on your trading strategy (e.g., once per bar, once per bar close).
Use in Trading Strategy:
Doji sequences can indicate trend reversals or market indecision.
Combine this indicator with support/resistance levels, volume, or other indicators to confirm signals.
PS: Good luck in finding a Triple Doji :)
Volatility BandsThe Volatility Bands script is a custom indicator designed to help traders visualize volatility levels in the market. It calculates dynamic bands around a central moving average, providing insights into potential support and resistance levels based on recent price action.
The script calculates multiple volatility bands (u0, u1, u2, d0, d1, d2) that adjust based on recent price movements. The outer bands (u2 and d2) represent extreme volatility levels, while the inner bands (u0, u1, d0, d1) indicate more immediate support and resistance.
Look for price reactions at the band levels. A touch of the upper bands may indicate overbought conditions, while a touch of the lower bands may indicate oversold conditions.
Central Moving Average: A smoothed moving average that adapts to price changes, providing a clear trend direction.
The script has no input parameters.
Script Functions:
erf(x): Calculates the error function for a given input x. Used in the calculation of the smoothing factor for the UMA.
uma(input): Provides a smoothed average that adapts to recent price changes, reducing lag compared to traditional moving averages.
dev(input, mu): Used to calculate the volatility bands around the central moving average.
MTF ATR BandsA simple but effective MTF ATR bands indicator.
The script calculate and display ATR bands low and high of the current timeframe using high, low inputs and an RMA moving average, adding to it ATR of the period multiplied with the user multiplier, default is set to 1.5.
Than is calculated a smoothed average of the range and the color of it based on its slope, same color is used to fill the atr bands.
Than the higher timeframe bands are calculated and displayed on the chart.
How can be used ?
The higher timeframe average and bands can give you long term direction of the trend and the current timeframes moving average and filling short term trend, for example using the 15 min chart with a 4h HTF bands, or an 1h with a daily, or a daily with an weekly or weekly with bi-monthly atr bands.
Also can be used as a stop loss indicator.
Hope you will like it, any question send me a PM.
Clustering Volatility (ATR-ADR-ChaikinVol) [Sam SDF-Solutions]The Clustering Volatility indicator is designed to evaluate market volatility by combining three widely used measures: Average True Range (ATR), Average Daily Range (ADR), and the Chaikin Oscillator.
Each indicator is normalized using one of the available methods (MinMax, Rank, or Z-score) to create a unified metric called the Score. This Score is further smoothed with an Exponential Moving Average (EMA) to reduce noise and provide a clearer view of market conditions.
Key Features:
Multi-Indicator Integration: Combines ATR, ADR, and the Chaikin Oscillator into a single Score that reflects overall market volatility.
Flexible Normalization: (Supports three normalization methods)
MinMax: Scales values between the observed minimum and maximum.
Rank: Normalizes based on the relative rank within a moving window.
Z-score: Standardizes values using mean and standard deviation.
Dynamic Window Selection: Offers an automatic window selection option based on a specified lookback period, or a fixed window size can be used.
Customizable Weights: Allows the user to assign individual weights to ATR, ADR, and the Chaikin Oscillator. Optionally, weights can be normalized to sum to 1.
Score Smoothing: Applies an EMA to the computed Score to smooth out short-term fluctuations and reduce market noise.
Cluster Visualization: Divides the smoothed Score into a number of clusters, each represented by a distinct color. These colors can be applied to the price bars (if enabled) for an immediate visual indication of the current volatility regime.
How It Works:
Input & Window Setup: Users set parameters for indicator periods, normalization methods, weights, and window size. The indicator can automatically determine the analysis window based on the number of lookback days.
Calculation of Metrics: The indicator computes the ATR, ADR (as the average of bar ranges), and the Chaikin Oscillator (based on the difference between short and long EMAs of the Accumulation/Distribution line).
Normalization & Scoring: Each indicator’s value is normalized and then weighted to form a raw Score. This raw Score is scaled to a range using statistics from the chosen window.
Smoothing & Clustering: The raw Score is smoothed using an EMA. The resulting smoothed Score is then multiplied by the number of clusters to assign a cluster index, which is used to choose a color for visual signals.
Visualization: The smoothed Score is plotted on the chart with a color that changes based on its value (e.g., lime for low, red for high, yellow for intermediate values). Optionally, the price bars are colored according to the assigned cluster.
_____________
This indicator is ideal for traders seeking a quick and clear assessment of market volatility. By integrating multiple volatility measures into one comprehensive Score, it simplifies analysis and aids in making more informed trading decisions.
For more detailed instructions, please refer to the guide here:
Clustering & Divergences (RSI-Stoch-CCI) [Sam SDF-Solutions]The Clustering & Divergences (RSI-Stoch-CCI) indicator is a comprehensive technical analysis tool that consolidates three popular oscillators—Relative Strength Index (RSI), Stochastic, and Commodity Channel Index (CCI)—into one unified metric called the Score. This Score offers traders an aggregated view of market conditions, allowing them to quickly identify whether the market is oversold, balanced, or overbought.
Functionality:
Oscillator Clustering: The indicator calculates the values of RSI, Stochastic, and CCI using user-defined periods. These oscillator values are then normalized using one of three available methods: MinMax, Z-Score, or Z-Bins.
Score Calculation: Each normalized oscillator value is multiplied by its respective weight (which the user can adjust), and the weighted values are summed to generate an overall Score. This Score serves as a single, interpretable metric representing the combined oscillator behavior.
Market Clustering: The indicator performs clustering on the Score over a configurable window. By dividing the Score range into a set number of clusters (also configurable), the tool visually represents the market’s state. Each cluster is assigned a unique color so that traders can quickly see if the market is trending toward oversold, balanced, or overbought conditions.
Divergence Detection: The script automatically identifies both Regular and Hidden divergences between the price action and the Score. By using pivot detection on both price and Score data, the indicator marks potential reversal signals on the chart with labels and connecting lines. This helps in pinpointing moments when the price and the underlying oscillator dynamics diverge.
Customization Options: Users have full control over the indicator’s behavior. They can adjust:
The periods for each oscillator (RSI, Stochastic, CCI).
The weights applied to each oscillator in the Score calculation.
The normalization method and its manual boundaries.
The number of clusters and whether to invert the cluster order.
Parameters for divergence detection (such as pivot sensitivity and the minimum/maximum bar distance between pivots).
Visual Enhancements:
Depending on the user’s preference, either the Score or the Cluster Index (derived from the clustering process) is plotted on the chart. Additionally, the script changes the color of the price bars based on the identified cluster, providing an at-a-glance visual cue of the current market regime.
Logic & Methodology:
Input Parameters: The script starts by accepting user inputs for clustering settings, oscillator periods, weights, divergence detection, and manual boundary definitions for normalization.
Oscillator Calculation & Normalization: It computes RSI, Stochastic, and CCI values from the price data. These values are then normalized using either the MinMax method (scaling between a lower and upper band) or the Z-Score method (standardizing based on mean and standard deviation), or using Z-Bins for an alternative scaling approach.
Score Computation: Each normalized oscillator is multiplied by its corresponding weight. The sum of these products results in the overall Score that represents the combined oscillator behavior.
Clustering Algorithm: The Score is evaluated over a moving window to determine its minimum and maximum values. Using these values, the script calculates a cluster index that divides the Score into a predefined number of clusters. An option to invert the cluster calculation is provided to adjust the interpretation of the clustering.
Divergence Analysis: The indicator employs pivot detection (using left and right bar parameters) on both the price and the Score. It then compares recent pivot values to detect regular and hidden divergences. When a divergence is found, the script plots labels and optional connecting lines to highlight these key moments on the chart.
Plotting: Finally, based on the user’s selection, the indicator plots either the Score or the Cluster Index. It also overlays manual boundary lines (for the chosen normalization method) and adjusts the bar colors according to the cluster to provide clear visual feedback on market conditions.
_________
By integrating multiple oscillator signals into one cohesive tool, the Clustering & Divergences (RSI-Stoch-CCI) indicator helps traders minimize subjective analysis. Its dynamic clustering and automated divergence detection provide a streamlined method for assessing market conditions and potentially enhancing the accuracy of trading decisions.
For further details on using this indicator, please refer to the guide available at:
CAM | Comparison and Normalisation Indicator Description: "CAM | Comparison and Normalisation" 🌟
Overview 📊
The "CAM | Comparison and Normalisation" indicator is a must-have tool for forex traders! 🚀 It analyzes the strength of a currency pair’s base and quote currencies against the pair’s price movement, using automatic detection, composite calculations, and normalization—all wrapped in a colorful, easy-to-read package. 🎨
How It Works 🛠️
- 🔍 **Automatic Currency Detection**: Instantly spots the base (e.g., EUR in EURUSD) and quote (e.g., USD) currencies—no manual setup needed!
- 💪 **Composite Strength Calculation**: Measures each currency’s power by averaging its rate against 9 major currencies (GBP, EUR, CHF, USD, AUD, CAD, NZD, JPY, NOK). A true strength test! 🏋️♂️
- 📏 **Normalization**: Scales everything with a smart formula (price minus moving average, divided by standard deviation) so base, quote, and pair prices play on the same field. ⚖️
- 🎨 **Dynamic Visualization**:
- Plots 3 normalized lines with unique colors:
- **Base Composite** (e.g., purple for GBP, blue for EUR)
- **Quote Composite** (e.g., green for USD, yellow for JPY)
- **Actual Pair** (⚪ white)
- Adds labels on the last bar (e.g., "Base: GBP" in purple). 🏷️
- 📊 **Performance Histogram**: Shows the base vs. quote strength gap with a green (👍) or red (👎) area chart—adjusted by the pair’s price.
- ⚙️ **Customizable Settings**: Adjust Scaling Period (50), Histogram Scale (0.5), and Levels (1, -1) to fit your style! 🎚️
Benefits 🌈
- 🧠 **Simplified Analysis**: Normalized data cuts through the noise, making trends crystal clear.
- ✅ **Enhanced Decisions**: Colorful lines and histograms spotlight trading signals fast.
- ⏱️ **Time-Saver**: No setup—just drop it on a chart and go!
- 🌍 **Versatile**: Works on any supported pair, with colors adapting automatically (e.g., orange AUD on AUDCAD).
- 👀 **Eye-Catching**: Currency-specific colors (like purple GBP from pound notes) make it fun and easy to follow.
How It Helps Traders 💡
- 📈 **Spot Trends**: See if the base is flexing 💪 or the quote is fading 📉, and how it ties to the pair’s price.
- ⚠️ **Catch Divergences**: Histogram flags when currency strength and price don’t match—hello, opportunity! 🚨
- 🛡️ **Manage Risk**: Normalized values and levels help gauge overbought/oversold zones for smarter stops.
- **Big Picture**: Compare currency strength to pair price for strategic edge, whether scalping or swinging.
Example in Action 🎬
- **GBPUSD Chart**:
- purple GBP line climbs, greenUSD dips, histogram turns green 👍—GBP’s gaining! If the white pair line rises too, it’s a bullish hint.
Conclusion ✨
"CAM | Comparison and Normalisation" turns forex complexity into clear, actionable insights. With its auto-detection, vibrant visuals, and trader-friendly design, it’s your shortcut to smarter trades! 📈💰
Statistically Extreme Areas by QTX Algo SystemsStatistically Extreme Areas by QTX Algo Systems
Overview
This indicator helps traders pinpoint potential reversal zones by detecting when prices become statistically overextended. By combining advanced statistical analysis with volatility and momentum metrics—including BBWP, SMI, PMARP, and Bollinger Band Oscillator (BBO) slope analysis—it provides clear visual cues for identifying market extremes and managing risk.
How It Works
Baseline Statistical Calculation:
The indicator starts by establishing a baseline price range using historical data through a statistical percentile approach. This captures the typical extremes over a significant period and forms the foundation for further analysis.
Volatility Adjustment:
A Bollinger Band Width Percentile (BBWP) measure is used to assess recent price variability. This dynamic volatility factor adjusts the baseline, ensuring that signals are only generated when overall market volatility exceeds a minimum threshold.
Momentum and Trend Verification:
A double‐smoothed Stochastic Momentum Index (SMI) captures short-term momentum, while a Price – Moving Average Ratio (PMARP) confirms the prevailing trend's strength. Additionally, a Bollinger Band Oscillator (BBO) calculates the slopes of the upper and lower bands to further refine the detection of extreme conditions without relying solely on a simple mashup of standard indicators.
Why It's Different
Rather than merely merging common indicators, this tool integrates distinct layers of analysis to produce a cohesive and dynamic framework. The synthesis of statistical extremes, real-time volatility adjustments, and momentum/trend verification helps filter out noise and false signals, offering traders a robust method to identify reversal zones and set precise stop-loss levels. This multi-dimensional approach delivers actionable insights that go beyond what traditional support/resistance or momentum indicators can offer on their own.
How to Use
Interpret the Visual Cues:
Watch for the color-coded background changes that signal statistically extreme conditions.
Integrate with Your Analysis:
Use these visual alerts alongside other technical tools to refine your entry and exit decisions and to enhance your overall risk management.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Statistical Price Bands with Trend Filtering by QTX Algo SystemsStatistical Price Bands with Trend Filtering by QTX Algo Systems
Overview
This indicator generates adaptive support and resistance bands by fusing statistical analysis with real-time volatility and trend measurements. It highlights areas where prices appear overextended, providing traders with clear visual cues for potential reversals or risk management adjustments.
How It Works
Baseline Statistical Calculation:
The indicator begins by deriving a baseline price range from historical data using a statistical percentile approach. This percentile reflects the typical extremes observed over a significant period, forming the foundation for the bands.
Volatility Adjustment:
A dynamic volatility factor is then calculated by comparing the moving standard deviation of price to its moving average. This factor adjusts the baseline, ensuring that the bands reflect current market variability. The use of both a long-term dispersion measure and a short-term percentile-based volatility metric helps confirm that overall market volatility remains above a minimum threshold.
Trend Filtering:
In parallel, the indicator assesses trend direction by comparing the current price to a volume-weighted moving average (VWMA). This trend component shifts the bands in the direction of the prevailing market bias—moving the bands upward during uptrends and downward during downtrends.
Why It’s Different
Unlike traditional static support/resistance tools, this indicator integrates multiple layers of analysis—statistical extremes, real-time volatility, and trend direction—to create bands that continuously adapt to market conditions. This synthesis produces a dynamic framework that not only identifies potential overextended price areas but also provides practical stop loss levels, setting it apart from other basic band or moving average models.
How to Use
Customize the baseline statistical setting to match your trading style. Use the dynamically adjusted bands as visual cues for potential reversal zones or as guides for setting stop losses. Combine these insights with other technical tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Volatility Based SMI with Dynamic Bands by QTX Algo SystemsVolatility Based SMI with Dynamic Bands by QTX Algo Systems
Overview
This advanced oscillator redefines the classic Stochastic Momentum Index (SMI) by incorporating adaptive volatility scaling and dynamically tilting its overbought and oversold levels based on market trends. The result is a context-sensitive momentum tool that adjusts its thresholds in real time, helping traders identify potential reversals or trend continuations more effectively.
How It Works
Enhanced SMI Calculation:
The indicator starts by computing a double‐smoothed SMI. Two layers of exponential moving averages—controlled by the “Smoothing K” and “Smoothing D” inputs—are applied to both the relative price range and the overall range (difference between the highest high and lowest low) over a fixed period. This process reduces short-term noise and isolates the underlying momentum.
Adaptive Volatility Scaling:
A normalized volatility measure is derived using a fixed Bollinger Band Width Percentile (BBWP) approach. This volatility metric is used to create an adaptive adjustment factor that scales the SMI, ensuring that the oscillator’s sensitivity reflects current market conditions without being distorted by temporary extremes.
Dynamic Threshold Adjustment:
The indicator then calculates trend strength using a lookback period (set by the “Trend Lookback Period” input) that compares the current price to a volume-weighted moving average (VWMA). This trend strength is used to adjust the base overbought and oversold levels (fixed at 50 and –50) through two mechanisms:
Band Tilt Strengths:
The “Upper Band Tilt Strength” and “Lower Band Tilt Strength” inputs determine how aggressively the respective thresholds are shifted in response to the prevailing trend. In an uptrend, for example, the oversold level is raised more noticeably, while in a downtrend, the overbought level is lowered.
Opposite Band Compression:
The “Opposite Band Compression Strength” input further refines this adjustment by accelerating the contraction of the opposite band during trend reversals, enhancing the indicator’s responsiveness.
How to Use and Input Adjustments
Smoothing K & Smoothing D:
Adjust these to control the degree of smoothing in the SMI calculation. Lower values provide quicker, albeit noisier, responses, while higher values yield smoother signals.
SMI EMA Length:
This sets the sensitivity of the moving average applied to the SMI, affecting how promptly crossover signals are generated.
Trend Lookback Period:
Defines the historical window for assessing trend strength. A longer period gives a more stable trend, while a shorter period increases responsiveness.
Upper/Lower Band Tilt Strength:
These parameters determine how much the overbought and oversold levels shift in response to the market’s trend. Increasing these values results in more pronounced threshold adjustments.
Opposite Band Compression Strength:
This setting influences how quickly the opposite band compresses during trend reversals, thereby fine-tuning the dynamic nature of the oscillator’s thresholds.
What Makes It Proprietary
Traditional SMI indicators typically rely on fixed thresholds for overbought and oversold conditions. Our approach is proprietary because it seamlessly integrates adaptive volatility scaling with dynamic, trend-based threshold adjustments. This fusion produces an oscillator that is acutely sensitive to current market conditions, offering a more nuanced and context-aware view of momentum that stands apart from conventional methods.
How to Use
Monitor the oscillator for crossovers between the SMI and its EMA, which serve as potential signals for reversals or confirmations of trend continuation. Fine-tune the input parameters to match your market conditions and trading style, and use the dynamically adjusted thresholds in conjunction with other technical analysis tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
CAM| Bar volatility and statsCAPRICORN ASSETS MANAGEMENT
⸻
CAM | Bar Volatility and Stats Indicator
The CAM | Bar Volatility and Stats indicator is designed to track historical price movements, analyzing bar volatility and key statistical trends in financial instruments. By evaluating past bars, it provides insights into market dynamics, helping traders assess volatility, trend strength, and momentum patterns.
Key Features & Functionality:
✅ Volatility Analysis – Measures historical volatility by calculating the average price range per bar and displaying it in pips.
✅ Bull & Bear Bar Statistics – Tracks the number of bullish and bearish bars within a given lookback period, including their respective percentages.
✅ Consecutive Bar Sequences – Identifies and records the longest streaks of consecutive bullish or bearish bars, providing insights into market trends.
✅ Average Volatility by Trend – Computes separate volatility values for bullish and bearish bars, helping traders understand trend-based price behavior.
✅ Real-Time Labeling – Displays a live statistics summary directly on the chart, updating dynamically with each new bar.
Benefits for Traders:
📊 Enhanced Market Insight – Quickly assess market conditions, determining whether volatility is increasing or decreasing.
📈 Trend Strength Identification – Identify strong bullish or bearish sequences to improve trade timing and strategy development.
⏳ Better Risk Management – Use historical volatility metrics to fine-tune stop-loss and take-profit levels.
🛠 Customizable Analysis – Adjustable lookback period and display options allow traders to focus on the data that matters most.
This indicator is an essential tool for traders looking to refine their decision-making process by leveraging volatility-based statistics. Whether trading Forex, stocks, or commodities, it provides valuable insights into price action trends and market conditions.
⸻
AI Adaptive Oscillator [PhenLabs]📊 Algorithmic Adaptive Oscillator
Version: PineScript™ v6
📌 Description
The AI Adaptive Oscillator is a sophisticated technical indicator that employs ensemble learning and adaptive weighting techniques to analyze market conditions. This innovative oscillator combines multiple traditional technical indicators through an AI-driven approach that continuously evaluates and adjusts component weights based on historical performance. By integrating statistical modeling with machine learning principles, the indicator adapts to changing market dynamics, providing traders with a responsive and reliable tool for market analysis.
🚀 Points of Innovation:
Ensemble learning framework with adaptive component weighting
Performance-based scoring system using directional accuracy
Dynamic volatility-adjusted smoothing mechanism
Intelligent signal filtering with cooldown and magnitude requirements
Signal confidence levels based on multi-factor analysis
🔧 Core Components
Ensemble Framework : Combines up to five technical indicators with performance-weighted integration
Adaptive Weighting : Continuous performance evaluation with automated weight adjustment
Volatility-Based Smoothing : Adapts sensitivity based on current market volatility
Pattern Recognition : Identifies potential reversal patterns with signal qualification criteria
Dynamic Visualization : Professional color schemes with gradient intensity representation
Signal Confidence : Three-tiered confidence assessment for trading signals
🔥 Key Features
The indicator provides comprehensive market analysis through:
Multi-Component Ensemble : Integrates RSI, CCI, Stochastic, MACD, and Volume-weighted momentum
Performance Scoring : Evaluates each component based on directional prediction accuracy
Adaptive Smoothing : Automatically adjusts based on market volatility
Pattern Detection : Identifies potential reversal patterns in overbought/oversold conditions
Signal Filtering : Prevents excessive signals through cooldown periods and minimum change requirements
Confidence Assessment : Displays signal strength through intuitive confidence indicators (average, above average, excellent)
🎨 Visualization
Gradient-Filled Oscillator : Color intensity reflects strength of market movement
Clear Signal Markers : Distinct bullish and bearish pattern signals with confidence indicators
Range Visualization : Clean representation of oscillator values from -6 to 6
Zero Line : Clear demarcation between bullish and bearish territory
Customizable Colors : Color schemes that can be adjusted to match your chart style
Confidence Symbols : Intuitive display of signal confidence (no symbol, +, or ++) alongside direction markers
📖 Usage Guidelines
⚙️ Settings Guide
Color Settings
Bullish Color
Default: #2b62fa (Blue)
This setting controls the color representation for bullish movements in the oscillator. The color appears when the oscillator value is positive (above zero), with intensity indicating the strength of the bullish momentum. A brighter shade indicates stronger bullish pressure.
Bearish Color
Default: #ce9851 (Amber)
This setting determines the color representation for bearish movements in the oscillator. The color appears when the oscillator value is negative (below zero), with intensity reflecting the strength of the bearish momentum. A more saturated shade indicates stronger bearish pressure.
Signal Settings
Signal Cooldown (bars)
Default: 10
Range: 1-50
This parameter sets the minimum number of bars that must pass before a new signal of the same type can be generated. Higher values reduce signal frequency and help prevent overtrading during choppy market conditions. Lower values increase signal sensitivity but may generate more false positives.
Min Change For New Signal
Default: 1.5
Range: 0.5-3.0
This setting defines the minimum required change in oscillator value between consecutive signals of the same type. It ensures that new signals represent meaningful changes in market conditions rather than minor fluctuations. Higher values produce fewer but potentially higher-quality signals, while lower values increase signal frequency.
AI Core Settings
Base Length
Default: 14
Minimum: 2
This fundamental setting determines the primary calculation period for all technical components in the ensemble (RSI, CCI, Stochastic, etc.). It represents the lookback window for each component’s base calculation. Shorter periods create a more responsive but potentially noisier oscillator, while longer periods produce smoother signals with potential lag.
Adaptive Speed
Default: 0.1
Range: 0.01-0.3
Controls how quickly the oscillator adapts to new market conditions through its volatility-adjusted smoothing mechanism. Higher values make the oscillator more responsive to recent price action but potentially more erratic. Lower values create smoother transitions but may lag during rapid market changes. This parameter directly influences the indicator’s adaptiveness to market volatility.
Learning Lookback Period
Default: 150
Minimum: 10
Determines the historical data range used to evaluate each ensemble component’s performance and calculate adaptive weights. This setting controls how far back the AI “learns” from past performance to optimize current signals. Longer periods provide more stable weight distribution but may be slower to adapt to regime changes. Shorter periods adapt more quickly but may overreact to recent anomalies.
Ensemble Size
Default: 5
Range: 2-5
Specifies how many technical components to include in the ensemble calculation.
Understanding The Interaction Between Settings
Base Length and Learning Lookback : The base length determines the reactivity of individual components, while the lookback period determines how their weights are adjusted. These should be balanced according to your timeframe - shorter timeframes benefit from shorter base lengths, while the lookback should generally be 10-15 times the base length for optimal learning.
Adaptive Speed and Signal Cooldown : These settings control sensitivity from different angles. Increasing adaptive speed makes the oscillator more responsive, while reducing signal cooldown increases signal frequency. For conservative trading, keep adaptive speed low and cooldown high; for aggressive trading, do the opposite.
Ensemble Size and Min Change : Larger ensembles provide more stable signals, allowing for a lower minimum change threshold. Smaller ensembles might benefit from a higher threshold to filter out noise.
Understanding Signal Confidence Levels
The indicator provides three distinct confidence levels for both bullish and bearish signals:
Average Confidence (▲ or ▼) : Basic signal that meets the minimum pattern and filtering criteria. These signals indicate potential reversals but with moderate confidence in the prediction. Consider using these as initial alerts that may require additional confirmation.
Above Average Confidence (▲+ or ▼+) : Higher reliability signal with stronger underlying metrics. These signals demonstrate greater consensus among the ensemble components and/or stronger historical performance. They offer increased probability of successful reversals and can be traded with less additional confirmation.
Excellent Confidence (▲++ or ▼++) : Highest quality signals with exceptional underlying metrics. These signals show strong agreement across oscillator components, excellent historical performance, and optimal signal strength. These represent the indicator’s highest conviction trade opportunities and can be prioritized in your trading decisions.
Confidence assessment is calculated through a multi-factor analysis including:
Historical performance of ensemble components
Degree of agreement between different oscillator components
Relative strength of the signal compared to historical thresholds
✅ Best Use Cases:
Identify potential market reversals through oscillator extremes
Filter trade signals based on AI-evaluated component weights
Monitor changing market conditions through oscillator direction and intensity
Confirm trade signals from other indicators with adaptive ensemble validation
Detect early momentum shifts through pattern recognition
Prioritize trading opportunities based on signal confidence levels
Adjust position sizing according to signal confidence (larger for ++ signals, smaller for standard signals)
⚠️ Limitations
Requires sufficient historical data for accurate performance scoring
Ensemble weights may lag during dramatic market condition changes
Higher ensemble sizes require more computational resources
Performance evaluation quality depends on the learning lookback period length
Even high confidence signals should be considered within broader market context
💡 What Makes This Unique
Adaptive Intelligence : Continuously adjusts component weights based on actual performance
Ensemble Methodology : Combines strength of multiple indicators while minimizing individual weaknesses
Volatility-Adjusted Smoothing : Provides appropriate sensitivity across different market conditions
Performance-Based Learning : Utilizes historical accuracy to improve future predictions
Intelligent Signal Filtering : Reduces noise and false signals through sophisticated filtering criteria
Multi-Level Confidence Assessment : Delivers nuanced signal quality information for optimized trading decisions
🔬 How It Works
The indicator processes market data through five main components:
Ensemble Component Calculation :
Normalizes traditional indicators to consistent scale
Includes RSI, CCI, Stochastic, MACD, and volume components
Adapts based on the selected ensemble size
Performance Evaluation :
Analyzes directional accuracy of each component
Calculates continuous performance scores
Determines adaptive component weights
Oscillator Integration :
Combines weighted components into unified oscillator
Applies volatility-based adaptive smoothing
Scales final values to -6 to 6 range
Signal Generation :
Detects potential reversal patterns
Applies cooldown and magnitude filters
Generates clear visual markers for qualified signals
Confidence Assessment :
Evaluates component agreement, historical accuracy, and signal strength
Classifies signals into three confidence tiers (average, above average, excellent)
Displays intuitive confidence indicators (no symbol, +, ++) alongside direction markers
💡 Note:
The AI Adaptive Oscillator performs optimally when used with appropriate timeframe selection and complementary indicators. Its adaptive nature makes it particularly valuable during changing market conditions, where traditional fixed-weight indicators often lose effectiveness. The ensemble approach provides a more robust analysis by leveraging the collective intelligence of multiple technical methodologies. Pay special attention to the signal confidence indicators to optimize your trading decisions - excellent (++) signals often represent the most reliable trade opportunities.
SigmaTrend Prime | QuantEdgeBIntroducing SigmaTrend Prime (STP) by QuantEdgeB
🛠️ Overview
SigmaTrend Prime (STP) is an advanced trend-following indicator that combines double exponential moving averages (DEMA) with a volatility-adjusted SuperTrend framework.
Unlike traditional ATR-based SuperTrends, STP dynamically adjusts trend thresholds using a standard deviation filter derived from price percentiles. This ensures that the trend signals remain highly adaptive, filtering out short-term noise while maintaining robustness across different market conditions.
By leveraging a DEMA core, STP minimizes lag while preserving strong trend identification, making it a powerful tool for traders looking to capture directional moves with enhanced precision.
_____
✨ Key Features
🔹 DEMA-Driven Trend Filtering
SigmaTrend Prime minimizes lag and enhances responsiveness using a double exponential moving average (DEMA) core.
🔹 Volatility-Adaptive SuperTrend
STP applies a percentile-based price smoothing technique, ensuring that the trend filter dynamically adjusts to market conditions.
🔹 Standard Deviation (SD) Filtering for Noise Reduction
By applying a rolling standard deviation derived from smoothed price action, STP eliminates false breakouts and enhances trend clarity.
🔹 Customizable Visual & Signal Settings
Includes multiple color modes, backtest metrics, and signal labels, making it highly adaptable for different trading styles.
📊 How It Works
1️⃣ DEMA-Based Trend Smoothing
SigmaTrend Prime uses DEMA (Double Exponential Moving Average) as its trend foundation, offering a smoother and more responsive trend structure:
🔹 Why DEMA?
✔ Minimizes lag compared to standard EMA.
✔ Maintains trend sensitivity while reducing market noise.
✔ Stronger confirmation of directional moves in volatile environments.
2️⃣ Adaptive Volatility Filtering with Standard Deviation (SD)
Unlike conventional SuperTrend indicators that rely on ATR for trend filtering, SigmaTrend Prime applies an SD-based smoothing mechanism.
📌 How it Works?
✔ Price Percentile Calculation → Uses percentile price ranking for better trend representation.
✔ Rolling Standard Deviation Calculation → Applies a volatility-adjusted filter to prevent false signals.
✔ Dynamic Trend Band Expansion → Factors (Factor1 & Factor2) multipliers to adjust trend sensitivity based on current price behavior.
🔹 Why SD-Based Filtering?
✔ More adaptive to different volatility regimes.
✔ Improves trend accuracy in both trending and ranging markets.
✔ Avoids excessive whipsaws common with ATR-based models.
3️⃣ Signal Generation & Trend Confirmation
SigmaTrend Prime detects trend shifts based on SD-filtered breakouts:
✅ Long Signal → Triggered when price crosses above the SuperTrend upper band.
❌ Short Signal → Triggered when price crosses below the SuperTrend lower band.
📌 Additional Features:
✔ Adaptive Signal Labels → Shows "Long" or "Short" trade signals dynamically.
✔ Trend-Following Mode → Stays in position until a confirmed reversal signal occurs.
✔ Customizable Sensitivity → Traders can adjust Factor1 & Factor2 multipliers and other settings to refine signal responsiveness.
👥 Who Should Use It?
✅ Trend Traders & Momentum Followers → Identify strong directional trends with greater accuracy.
✅ Swing & Position Traders → Gain precise trend confirmation signals for optimized entries/exits.
✅ Volatility-Aware Traders → Benefit from adaptive trend filtering based on real-time market conditions.
✅ Systematic & Quant Traders → Implement STP within automated trading systems for improved trend detection.
⚙️ Customization & Default Settings
🔧 Key Custom Inputs:
• DEMA Source (Default: HLC3) → Defines the price input for DEMA calculations.
• DEMA Length (Default: 30) → Controls the smoothing period for trend calculation.
• Percentile SD Length (Default: 10) → Determines historical percentile ranking for volatility
assessment.
• Volatility SD Length (Default: 30) → Defines rolling SD length for dynamic filtering.
• Trend Sensitivity Factors:
🔹 Factor1 (Default: 25) → Adjusts lower SD band responsiveness.
🔹 Factor2 (Default: 40) → Controls upper SD band expansion.
• Visual Customizations → Multiple color modes, backtest metrics, and trend labels available.
🚀 By default, STP is optimized for adaptive trend-following while remaining flexible for customization.
_____
📌 How to Use SigmaTrend Prime in Trading
1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when STP confirms a bullish trend shift above its upper trend band.
✔ Enter short positions when STP confirms a bearish trend shift below its lower trend band.
✔ Stay in trades as long as STP maintains trend direction, filtering out false reversals.
2️⃣ Volatility-Adaptive Strategy (Dynamic Trend Adjustments)
✔ Use Factor1 & Factor2 adjustments to fine-tune STP’s sensitivity to price movements.
✔ Increase Factor1 for slower trend shifts and reduce Factor2 for more aggressive trend detection.
📌 Why?
• In high-volatility conditions, adjust trend bands wider to prevent whipsaws.
• In low-volatility conditions, tighten trend bands for faster signal responsiveness.
_____
📊 Backtest Mode
SigmaTrend Prime includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions.
🔹 Backtest Metrics Displayed:
• Equity Max Drawdown → Largest historical loss from peak equity.
• Profit Factor → Ratio of total profits to total losses, measuring system efficiency.
• Sharpe Ratio → Assesses risk-adjusted return performance.
• Sortino Ratio → Focuses on downside risk-adjusted returns.
• Omega Ratio → Evaluates return consistency & performance asymmetry.
• Half Kelly → Optimal position sizing based on risk/reward analysis.
• Total Trades & Win Rate → Assess STP’s historical success rate.
📌 Disclaimer:
Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
🚀 Why This Matters?
✅ Strategy Validation → Gain insight into historical trend accuracy.
✅ Customization Insights → See how different STP settings impact performance.
✅ Risk Awareness → Understand potential drawdowns before deploying capital.
_____
📌 Conclusion
SigmaTrend Prime (STP) is an advanced trend-following solution that merges DEMA-based trend smoothing with standard deviation-adaptive filtering. By utilizing percentile-based price smoothing, STP enhances trend accuracy while ensuring that signals remain adaptive to different market environments.
🔹 Key Takeaways:
1️⃣ Lag-Minimized Trend Filtering – DEMA enhances trend responsiveness while reducing noise.
2️⃣ SD-Based Volatility Adaptation – More reliable than ATR-based trend models, reducing false breakouts.
3️⃣ Customizable & Dynamic – Easily fine-tune sensitivity settings for various market conditions.
📌 Master the market with precision and confidence | QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
IU Gap Fill StrategyThe IU Gap Fill Strategy is designed to capitalize on price gaps that occur between trading sessions. It identifies gaps based on a user-defined percentage threshold and executes trades when the price fills the gap within a day. This strategy is ideal for traders looking to take advantage of market inefficiencies that arise due to overnight or session-based price movements. An ATR-based trailing stop-loss is incorporated to dynamically manage risk and lock in profits.
USER INPUTS
Percentage Difference for Valid Gap - Defines the minimum gap size in percentage terms for a valid trade setup. ( Default is 0.2 )
ATR Length - Sets the lookback period for the Average True Range (ATR) calculation. (default is 14 )
ATR Factor - Determines the multiplier for the trailing stop-loss, helping in risk management. ( Default is 2.00 )
LONG CONDITION
A gap-up occurs, meaning the current session opens above the previous session’s close.
The price initially dips below the previous session's close but then recovers and closes above it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
SHORT CONDITION
A gap-down occurs, meaning the current session opens below the previous session’s close.
The price initially moves above the previous session’s close but then closes below it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
LONG EXIT
An ATR-based trailing stop-loss is set below the entry price and dynamically adjusts upwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
SHORT EXIT
An ATR-based trailing stop-loss is set above the entry price and dynamically adjusts downwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
WHY IT IS UNIQUE
Precision in Identifying Gaps - The strategy focuses on real price gaps rather than minor fluctuations.
Dynamic Risk Management - Uses ATR-based trailing stop-loss to secure profits while allowing the trade to run.
Versatility - Works on stocks, indices, forex, and any market that experiences session-based gaps.
Optimized Entry Conditions - Ensures entries are taken only when the price attempts to fill the gap, reducing false signals.
HOW USERS CAN BENEFIT FROM IT
Enhance Trade Timing - Captures high-probability trade setups based on market inefficiencies caused by gaps.
Minimize Risk - The ATR trailing stop-loss helps protect gains and limit losses.
Works in Different Market Conditions - Whether markets are trending or consolidating, the strategy adapts to potential gap fill opportunities.
Fully Customizable - Users can fine-tune gap percentage, ATR settings, and stop-loss parameters to match their trading style.
