Pro Trading Signals - Trend + S/R + Risk// ============================================
// PROFESSIONAL TRADING STRATEGY NOTES
// ============================================
// === WHAT THIS STRATEGY DOES ===
// 1. TREND ANALYSIS: Uses multiple EMAs (9, 21, 50, 200) to identify trend direction
// 2. SUPPORT/RESISTANCE: Automatically detects key price levels
// 3. RISK MANAGEMENT: Calculates stop loss and take profit with 2:1+ R:R ratio
// 4. SIGNAL SCORING: Only trades high-quality setups (60/100+ score)
// 5. ENTRY TYPES: Pullbacks, support/resistance bounces, breakouts
// === KEY IMPROVEMENTS FROM BASIC SIGNALS ===
// ✓ Trend alignment required (no counter-trend trades)
// ✓ Support/resistance confirmation
// ✓ Volume and momentum filters
// ✓ Automatic stop loss and take profit levels
// ✓ Signal quality scoring (filters out weak signals)
// ✓ Risk:Reward ratio enforcement (minimum 2:1)
// ✓ Volatility filter (avoids choppy markets)
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Keltner Channel Enhanced [DCAUT]█ Keltner Channel Enhanced
📊 ORIGINALITY & INNOVATION
The Keltner Channel Enhanced represents an important advancement over standard Keltner Channel implementations by introducing dual flexibility in moving average selection for both the middle band and ATR calculation. While traditional Keltner Channels typically use EMA for the middle band and RMA (Wilder's smoothing) for ATR, this enhanced version provides access to 25+ moving average algorithms for both components, enabling traders to fine-tune the indicator's behavior to match specific market characteristics and trading approaches.
Key Advancements:
Dual MA Algorithm Flexibility: Independent selection of moving average types for middle band (25+ options) and ATR smoothing (25+ options), allowing optimization of both trend identification and volatility measurement separately
Enhanced Trend Sensitivity: Ability to use faster algorithms (HMA, T3) for middle band while maintaining stable volatility measurement with traditional ATR smoothing, or vice versa for different trading strategies
Adaptive Volatility Measurement: Choice of ATR smoothing algorithm affects channel responsiveness to volatility changes, from highly reactive (SMA, EMA) to smoothly adaptive (RMA, TEMA)
Comprehensive Alert System: Five distinct alert conditions covering breakouts, trend changes, and volatility expansion, enabling automated monitoring without constant chart observation
Multi-Timeframe Compatibility: Works effectively across all timeframes from intraday scalping to long-term position trading, with independent optimization of trend and volatility components
This implementation addresses key limitations of standard Keltner Channels: fixed EMA/RMA combination may not suit all market conditions or trading styles. By decoupling the trend component from volatility measurement and allowing independent algorithm selection, traders can create highly customized configurations for specific instruments and market phases.
📐 MATHEMATICAL FOUNDATION
Keltner Channel Enhanced uses a three-component calculation system that combines a flexible moving average middle band with ATR-based (Average True Range) upper and lower channels, creating volatility-adjusted trend-following bands.
Core Calculation Process:
1. Middle Band (Basis) Calculation:
The basis line is calculated using the selected moving average algorithm applied to the price source over the specified period:
basis = ma(source, length, maType)
Supported algorithms include EMA (standard choice, trend-biased), SMA (balanced and symmetric), HMA (reduced lag), WMA, VWMA, TEMA, T3, KAMA, and 17+ others.
2. Average True Range (ATR) Calculation:
ATR measures market volatility by calculating the average of true ranges over the specified period:
trueRange = max(high - low, abs(high - close ), abs(low - close ))
atrValue = ma(trueRange, atrLength, atrMaType)
ATR smoothing algorithm significantly affects channel behavior, with options including RMA (standard, very smooth), SMA (moderate smoothness), EMA (fast adaptation), TEMA (smooth yet responsive), and others.
3. Channel Calculation:
Upper and lower channels are positioned at specified multiples of ATR from the basis:
upperChannel = basis + (multiplier × atrValue)
lowerChannel = basis - (multiplier × atrValue)
Standard multiplier is 2.0, providing channels that dynamically adjust width based on market volatility.
Keltner Channel vs. Bollinger Bands - Key Differences:
While both indicators create volatility-based channels, they use fundamentally different volatility measures:
Keltner Channel (ATR-based):
Uses Average True Range to measure actual price movement volatility
Incorporates gaps and limit moves through true range calculation
More stable in trending markets, less prone to extreme compression
Better reflects intraday volatility and trading range
Typically fewer band touches, making touches more significant
More suitable for trend-following strategies
Bollinger Bands (Standard Deviation-based):
Uses statistical standard deviation to measure price dispersion
Based on closing prices only, doesn't account for intraday range
Can compress significantly during consolidation (squeeze patterns)
More touches in ranging markets
Better suited for mean-reversion strategies
Provides statistical probability framework (95% within 2 standard deviations)
Algorithm Combination Effects:
The interaction between middle band MA type and ATR MA type creates different indicator characteristics:
Trend-Focused Configuration (Fast MA + Slow ATR): Middle band uses HMA/EMA/T3, ATR uses RMA/TEMA, quick trend changes with stable channel width, suitable for trend-following
Volatility-Focused Configuration (Slow MA + Fast ATR): Middle band uses SMA/WMA, ATR uses EMA/SMA, stable trend with dynamic channel width, suitable for volatility trading
Balanced Configuration (Standard EMA/RMA): Classic Keltner Channel behavior, time-tested combination, suitable for general-purpose trend following
Adaptive Configuration (KAMA + KAMA): Self-adjusting indicator responding to efficiency ratio, suitable for markets with varying trend strength and volatility regimes
📊 COMPREHENSIVE SIGNAL ANALYSIS
Keltner Channel Enhanced provides multiple signal categories optimized for trend-following and breakout strategies.
Channel Position Signals:
Upper Channel Interaction:
Price Touching Upper Channel: Strong bullish momentum, price moving more than typical volatility range suggests, potential continuation signal in established uptrends
Price Breaking Above Upper Channel: Exceptional strength, price exceeding normal volatility expectations, consider adding to long positions or tightening trailing stops
Price Riding Upper Channel: Sustained strong uptrend, characteristic of powerful bull moves, stay with trend and avoid premature profit-taking
Price Rejection at Upper Channel: Momentum exhaustion signal, consider profit-taking on longs or waiting for pullback to middle band for reentry
Lower Channel Interaction:
Price Touching Lower Channel: Strong bearish momentum, price moving more than typical volatility range suggests, potential continuation signal in established downtrends
Price Breaking Below Lower Channel: Exceptional weakness, price exceeding normal volatility expectations, consider adding to short positions or protecting against further downside
Price Riding Lower Channel: Sustained strong downtrend, characteristic of powerful bear moves, stay with trend and avoid premature covering
Price Rejection at Lower Channel: Momentum exhaustion signal, consider covering shorts or waiting for bounce to middle band for reentry
Middle Band (Basis) Signals:
Trend Direction Confirmation:
Price Above Basis: Bullish trend bias, middle band acts as dynamic support in uptrends, consider long positions or holding existing longs
Price Below Basis: Bearish trend bias, middle band acts as dynamic resistance in downtrends, consider short positions or avoiding longs
Price Crossing Above Basis: Potential trend change from bearish to bullish, early signal to establish long positions
Price Crossing Below Basis: Potential trend change from bullish to bearish, early signal to establish short positions or exit longs
Pullback Trading Strategy:
Uptrend Pullback: Price pulls back from upper channel to middle band, finds support, and resumes upward, ideal long entry point
Downtrend Bounce: Price bounces from lower channel to middle band, meets resistance, and resumes downward, ideal short entry point
Basis Test: Strong trends often show price respecting the middle band as support/resistance on pullbacks
Failed Test: Price breaking through middle band against trend direction signals potential reversal
Volatility-Based Signals:
Narrow Channels (Low Volatility):
Consolidation Phase: Channels contract during periods of reduced volatility and directionless price action
Breakout Preparation: Narrow channels often precede significant directional moves as volatility cycles
Trading Approach: Reduce position sizes, wait for breakout confirmation, avoid range-bound strategies within channels
Breakout Direction: Monitor for price breaking decisively outside channel range with expanding width
Wide Channels (High Volatility):
Trending Phase: Channels expand during strong directional moves and increased volatility
Momentum Confirmation: Wide channels confirm genuine trend with substantial volatility backing
Trading Approach: Trend-following strategies excel, wider stops necessary, mean-reversion strategies risky
Exhaustion Signs: Extreme channel width (historical highs) may signal approaching consolidation or reversal
Advanced Pattern Recognition:
Channel Walking Pattern:
Upper Channel Walk: Price consistently touches or exceeds upper channel while staying above basis, very strong uptrend signal, hold longs aggressively
Lower Channel Walk: Price consistently touches or exceeds lower channel while staying below basis, very strong downtrend signal, hold shorts aggressively
Basis Support/Resistance: During channel walks, price typically uses middle band as support/resistance on minor pullbacks
Pattern Break: Price crossing basis during channel walk signals potential trend exhaustion
Squeeze and Release Pattern:
Squeeze Phase: Channels narrow significantly, price consolidates near middle band, volatility contracts
Direction Clues: Watch for price positioning relative to basis during squeeze (above = bullish bias, below = bearish bias)
Release Trigger: Price breaking outside narrow channel range with expanding width confirms breakout
Follow-Through: Measure squeeze height and project from breakout point for initial profit targets
Channel Expansion Pattern:
Breakout Confirmation: Rapid channel widening confirms volatility increase and genuine trend establishment
Entry Timing: Enter positions early in expansion phase before trend becomes overextended
Risk Management: Use channel width to size stops appropriately, wider channels require wider stops
Basis Bounce Pattern:
Clean Bounce: Price touches middle band and immediately reverses, confirms trend strength and entry opportunity
Multiple Bounces: Repeated basis bounces indicate strong, sustainable trend
Bounce Failure: Price penetrating basis signals weakening trend and potential reversal
Divergence Analysis:
Price/Channel Divergence: Price makes new high/low while staying within channel (not reaching outer band), suggests momentum weakening
Width/Price Divergence: Price breaks to new extremes but channel width contracts, suggests move lacks conviction
Reversal Signal: Divergences often precede trend reversals or significant consolidation periods
Multi-Timeframe Analysis:
Keltner Channels work particularly well in multi-timeframe trend-following approaches:
Three-Timeframe Alignment:
Higher Timeframe (Weekly/Daily): Identify major trend direction, note price position relative to basis and channels
Intermediate Timeframe (Daily/4H): Identify pullback opportunities within higher timeframe trend
Lower Timeframe (4H/1H): Time precise entries when price touches middle band or lower channel (in uptrends) with rejection
Optimal Entry Conditions:
Best Long Entries: Higher timeframe in uptrend (price above basis), intermediate timeframe pulls back to basis, lower timeframe shows rejection at middle band or lower channel
Best Short Entries: Higher timeframe in downtrend (price below basis), intermediate timeframe bounces to basis, lower timeframe shows rejection at middle band or upper channel
Risk Management: Use higher timeframe channel width to set position sizing, stops below/above higher timeframe channels
🎯 STRATEGIC APPLICATIONS
Keltner Channel Enhanced excels in trend-following and breakout strategies across different market conditions.
Trend Following Strategy:
Setup Requirements:
Identify established trend with price consistently on one side of basis line
Wait for pullback to middle band (basis) or brief penetration through it
Confirm trend resumption with price rejection at basis and move back toward outer channel
Enter in trend direction with stop beyond basis line
Entry Rules:
Uptrend Entry:
Price pulls back from upper channel to middle band, shows support at basis (bullish candlestick, momentum divergence)
Enter long on rejection/bounce from basis with stop 1-2 ATR below basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Downtrend Entry:
Price bounces from lower channel to middle band, shows resistance at basis (bearish candlestick, momentum divergence)
Enter short on rejection/reversal from basis with stop 1-2 ATR above basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Trend Management:
Trailing Stop: Use basis line as dynamic trailing stop, exit if price closes beyond basis against position
Profit Taking: Take partial profits at opposite channel, move stops to basis
Position Additions: Add to winners on subsequent basis bounces if trend intact
Breakout Strategy:
Setup Requirements:
Identify consolidation period with contracting channel width
Monitor price action near middle band with reduced volatility
Wait for decisive breakout beyond channel range with expanding width
Enter in breakout direction after confirmation
Breakout Confirmation:
Price breaks clearly outside channel (upper for longs, lower for shorts), channel width begins expanding from contracted state
Volume increases significantly on breakout (if using volume analysis)
Price sustains outside channel for multiple bars without immediate reversal
Entry Approaches:
Aggressive: Enter on initial break with stop at opposite channel or basis, use smaller position size
Conservative: Wait for pullback to broken channel level, enter on rejection and resumption, tighter stop
Volatility-Based Position Sizing:
Adjust position sizing based on channel width (ATR-based volatility):
Wide Channels (High ATR): Reduce position size as stops must be wider, calculate position size using ATR-based risk calculation: Risk / (Stop Distance in ATR × ATR Value)
Narrow Channels (Low ATR): Increase position size as stops can be tighter, be cautious of impending volatility expansion
ATR-Based Risk Management: Use ATR-based risk calculations, position size = 0.01 × Capital / (2 × ATR), use multiples of ATR (1-2 ATR) for adaptive stops
Algorithm Selection Guidelines:
Different market conditions benefit from different algorithm combinations:
Strong Trending Markets: Middle band use EMA or HMA, ATR use RMA, capture trends quickly while maintaining stable channel width
Choppy/Ranging Markets: Middle band use SMA or WMA, ATR use SMA or WMA, avoid false trend signals while identifying genuine reversals
Volatile Markets: Middle band and ATR both use KAMA or FRAMA, self-adjusting to changing market conditions reduces manual optimization
Breakout Trading: Middle band use SMA, ATR use EMA or SMA, stable trend with dynamic channels highlights volatility expansion early
Scalping/Day Trading: Middle band use HMA or T3, ATR use EMA or TEMA, both components respond quickly
Position Trading: Middle band use EMA/TEMA/T3, ATR use RMA or TEMA, filter out noise for long-term trend-following
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing parameters is essential for adapting Keltner Channel Enhanced to specific trading approaches.
Source Parameter:
Close (Most Common): Uses closing price, reflects daily settlement, best for end-of-day analysis and position trading, standard choice
HL2 (Median Price): Smooths out closing bias, better represents full daily range in volatile markets, good for swing trading
HLC3 (Typical Price): Gives more weight to close while including full range, popular for intraday applications, slightly more responsive than HL2
OHLC4 (Average Price): Most comprehensive price representation, smoothest option, good for gap-prone markets or highly volatile instruments
Length Parameter:
Controls the lookback period for middle band (basis) calculation:
Short Periods (10-15): Very responsive to price changes, suitable for day trading and scalping, higher false signal rate
Standard Period (20 - Default): Represents approximately one month of trading, good balance between responsiveness and stability, suitable for swing and position trading
Medium Periods (30-50): Smoother trend identification, fewer false signals, better for position trading and longer holding periods
Long Periods (50+): Very smooth, identifies major trends only, minimal false signals but significant lag, suitable for long-term investment
Optimization by Timeframe: 1-15 minute charts use 10-20 period, 30-60 minute charts use 20-30 period, 4-hour to daily charts use 20-40 period, weekly charts use 20-30 weeks.
ATR Length Parameter:
Controls the lookback period for Average True Range calculation, affecting channel width:
Short ATR Periods (5-10): Very responsive to recent volatility changes, standard is 10 (Keltner's original specification), may be too reactive in whipsaw conditions
Standard ATR Period (10 - Default): Chester Keltner's original specification, good balance between responsiveness and stability, most widely used
Medium ATR Periods (14-20): Smoother channel width, ATR 14 aligns with Wilder's original ATR specification, good for position trading
Long ATR Periods (20+): Very smooth channel width, suitable for long-term trend-following
Length vs. ATR Length Relationship: Equal values (20/20) provide balanced responsiveness, longer ATR (20/14) gives more stable channel width, shorter ATR (20/10) is standard configuration, much shorter ATR (20/5) creates very dynamic channels.
Multiplier Parameter:
Controls channel width by setting ATR multiples:
Lower Values (1.0-1.5): Tighter channels with frequent price touches, more trading signals, higher false signal rate, better for range-bound and mean-reversion strategies
Standard Value (2.0 - Default): Chester Keltner's recommended setting, good balance between signal frequency and reliability, suitable for both trending and ranging strategies
Higher Values (2.5-3.0): Wider channels with less frequent touches, fewer but potentially higher-quality signals, better for strong trending markets
Market-Specific Optimization: High volatility markets (crypto, small-caps) use 2.5-3.0 multiplier, medium volatility markets (major forex, large-caps) use 2.0 multiplier, low volatility markets (bonds, utilities) use 1.5-2.0 multiplier.
MA Type Parameter (Middle Band):
Critical selection that determines trend identification characteristics:
EMA (Exponential Moving Average - Default): Standard Keltner Channel choice, Chester Keltner's original specification, emphasizes recent prices, faster response to trend changes, suitable for all timeframes
SMA (Simple Moving Average): Equal weighting of all data points, no directional bias, slower than EMA, better for ranging markets and mean-reversion
HMA (Hull Moving Average): Minimal lag with smooth output, excellent for fast trend identification, best for day trading and scalping
TEMA (Triple Exponential Moving Average): Advanced smoothing with reduced lag, responsive to trends while filtering noise, suitable for volatile markets
T3 (Tillson T3): Very smooth with minimal lag, excellent for established trend identification, suitable for position trading
KAMA (Kaufman Adaptive Moving Average): Automatically adjusts speed based on market efficiency, slow in ranging markets, fast in trends, suitable for markets with varying conditions
ATR MA Type Parameter:
Determines how Average True Range is smoothed, affecting channel width stability:
RMA (Wilder's Smoothing - Default): J. Welles Wilder's original ATR smoothing method, very smooth, slow to adapt to volatility changes, provides stable channel width
SMA (Simple Moving Average): Equal weighting, moderate smoothness, faster response to volatility changes than RMA, more dynamic channel width
EMA (Exponential Moving Average): Emphasizes recent volatility, quick adaptation to new volatility regimes, very responsive channel width changes
TEMA (Triple Exponential Moving Average): Smooth yet responsive, good balance for varying volatility, suitable for most trading styles
Parameter Combination Strategies:
Conservative Trend-Following: Length 30/ATR Length 20/Multiplier 2.5, MA Type EMA or TEMA/ATR MA Type RMA, smooth trend with stable wide channels, suitable for position trading
Standard Balanced Approach: Length 20/ATR Length 10/Multiplier 2.0, MA Type EMA/ATR MA Type RMA, classic Keltner Channel configuration, suitable for general purpose swing trading
Aggressive Day Trading: Length 10-15/ATR Length 5-7/Multiplier 1.5-2.0, MA Type HMA or EMA/ATR MA Type EMA or SMA, fast trend with dynamic channels, suitable for scalping and day trading
Breakout Specialist: Length 20-30/ATR Length 5-10/Multiplier 2.0, MA Type SMA or WMA/ATR MA Type EMA or SMA, stable trend with responsive channel width
Adaptive All-Conditions: Length 20/ATR Length 10/Multiplier 2.0, MA Type KAMA or FRAMA/ATR MA Type KAMA or TEMA, self-adjusting to market conditions
Offset Parameter:
Controls horizontal positioning of channels on chart. Positive values shift channels to the right (future) for visual projection, negative values shift left (past) for historical analysis, zero (default) aligns with current price bars for real-time signal analysis. Offset affects only visual display, not alert conditions or actual calculations.
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Keltner Channel Enhanced provides improvements over standard implementations while maintaining proven effectiveness.
Response Characteristics:
Standard EMA/RMA Configuration: Moderate trend lag (approximately 0.4 × length periods), smooth and stable channel width from RMA smoothing, good balance for most market conditions
Fast HMA/EMA Configuration: Approximately 60% reduction in trend lag compared to EMA, responsive channel width from EMA ATR smoothing, suitable for quick trend changes and breakouts
Adaptive KAMA/KAMA Configuration: Variable lag based on market efficiency, automatic adjustment to trending vs. ranging conditions, self-optimizing behavior reduces manual intervention
Comparison with Traditional Keltner Channels:
Enhanced Version Advantages:
Dual Algorithm Flexibility: Independent MA selection for trend and volatility vs. fixed EMA/RMA, separate tuning of trend responsiveness and channel stability
Market Adaptation: Choose configurations optimized for specific instruments and conditions, customize for scalping, swing, or position trading preferences
Comprehensive Alerts: Enhanced alert system including channel expansion detection
Traditional Version Advantages:
Simplicity: Fewer parameters, easier to understand and implement
Standardization: Fixed EMA/RMA combination ensures consistency across users
Research Base: Decades of backtesting and research on standard configuration
When to Use Enhanced Version: Trading multiple instruments with different characteristics, switching between trending and ranging markets, employing different strategies, algorithm-based trading systems requiring customization, seeking optimization for specific trading style and timeframe.
When to Use Standard Version: Beginning traders learning Keltner Channel concepts, following published research or trading systems, preferring simplicity and standardization, wanting to avoid optimization and curve-fitting risks.
Performance Across Market Conditions:
Strong Trending Markets: EMA or HMA basis with RMA or TEMA ATR smoothing provides quicker trend identification, pullbacks to basis offer excellent entry opportunities
Choppy/Ranging Markets: SMA or WMA basis with RMA ATR smoothing and lower multipliers, channel bounce strategies work well, avoid false breakouts
Volatile Markets: KAMA or FRAMA with EMA or TEMA, adaptive algorithms excel by automatic adjustment, wider multipliers (2.5-3.0) accommodate large price swings
Low Volatility/Consolidation: Channels narrow significantly indicating consolidation, algorithm choice less impactful, focus on detecting channel width contraction for breakout preparation
Keltner Channel vs. Bollinger Bands - Usage Comparison:
Favor Keltner Channels When: Trend-following is primary strategy, trading volatile instruments with gaps, want ATR-based volatility measurement, prefer fewer higher-quality channel touches, seeking stable channel width during trends.
Favor Bollinger Bands When: Mean-reversion is primary strategy, trading instruments with limited gaps, want statistical framework based on standard deviation, need squeeze patterns for breakout identification, prefer more frequent trading opportunities.
Use Both Together: Bollinger Band squeeze + Keltner Channel breakout is powerful combination, price outside Bollinger Bands but inside Keltner Channels indicates moderate signal, price outside both indicates very strong signal, Bollinger Bands for entries and Keltner Channels for trend confirmation.
Limitations and Considerations:
General Limitations:
Lagging Indicator: All moving averages lag price, even with reduced-lag algorithms
Trend-Dependent: Works best in trending markets, less effective in choppy conditions
No Direction Prediction: Indicates volatility and deviation, not future direction, requires confirmation
Enhanced Version Specific Considerations:
Optimization Risk: More parameters increase risk of curve-fitting historical data
Complexity: Additional choices may overwhelm beginning traders
Backtesting Challenges: Different algorithms produce different historical results
Mitigation Strategies:
Use Confirmation: Combine with momentum indicators (RSI, MACD), volume, or price action
Test Parameter Robustness: Ensure parameters work across range of values, not just optimized ones
Multi-Timeframe Analysis: Confirm signals across different timeframes
Proper Risk Management: Use appropriate position sizing and stops
Start Simple: Begin with standard EMA/RMA before exploring alternatives
Optimal Usage Recommendations:
For Maximum Effectiveness:
Start with standard EMA/RMA configuration to understand classic behavior
Experiment with alternatives on demo account or paper trading
Match algorithm combination to market condition and trading style
Use channel width analysis to identify market phases
Combine with complementary indicators for confirmation
Implement strict risk management using ATR-based position sizing
Focus on high-quality setups rather than trading every signal
Respect the trend: trade with basis direction for higher probability
Complementary Indicators:
RSI or Stochastic: Confirm momentum at channel extremes
MACD: Confirm trend direction and momentum shifts
Volume: Validate breakouts and trend strength
ADX: Measure trend strength, avoid Keltner signals in weak trends
Support/Resistance: Combine with traditional levels for high-probability setups
Bollinger Bands: Use together for enhanced breakout and volatility analysis
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Keltner Channel Enhanced has limitations and should not be used as the sole basis for trading decisions. While the flexible moving average selection for both trend and volatility components provides valuable adaptability across different market conditions, algorithm performance varies with market conditions, and past characteristics do not guarantee future results.
Key considerations:
Always use multiple forms of analysis and confirmation before entering trades
Backtest any parameter combination thoroughly before live trading
Be aware that optimization can lead to curve-fitting if not done carefully
Start with standard EMA/RMA settings and adjust only when specific conditions warrant
Understand that no moving average algorithm can eliminate lag entirely
Consider market regime (trending, ranging, volatile) when selecting parameters
Use ATR-based position sizing and risk management on every trade
Keltner Channels work best in trending markets, less effective in choppy conditions
Respect the trend direction indicated by price position relative to basis line
The enhanced flexibility of dual algorithm selection provides powerful tools for adaptation but requires responsible use, thorough understanding of how different algorithms behave under various market conditions, and disciplined risk management.
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced
📊 ORIGINALITY & INNOVATION
The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles.
Key Improvements:
Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre)
Maintains backward compatibility with traditional Stochastic calculations through SMA default setting
Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics
Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition
Comprehensive alert system covering crossovers and zone entries for systematic trade management
Differentiation from Traditional Stochastic:
Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs.
📐 MATHEMATICAL FOUNDATION
Core Stochastic Calculation:
The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period:
Step 1: Raw %K Calculation
%K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low)
Where:
Close = Current closing price
Lowest Low = Lowest low over the %K Length period
Highest High = Highest high over the %K Length period
Result ranges from 0 (close at period low) to 100 (close at period high)
Step 2: Smoothed %K Calculation
%K = MA(%K_raw, K Smoothing Period, MA Type)
Where:
MA = Selected moving average algorithm (SMA, EMA, etc.)
K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic
Traditional Fast Stochastic uses %K_raw directly without smoothing
Step 3: Signal Line %D Calculation
%D = MA(%K, D Smoothing Period, MA Type)
Where:
%D acts as a signal line and moving average of %K
D Smoothing typically set to 3 periods in traditional implementations
Both %K and %D use the same MA algorithm for consistent behavior
Available Smoothing Algorithms (21 Options):
Standard Moving Averages:
SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics
EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting
RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA
WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness
VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity
Advanced Moving Averages:
HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period
ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction
LSMA (Least Squares): Linear regression based, fits trend line to data points
DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique
TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation
ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive
TMA (Triangular): Double-smoothed SMA, very smooth but slower response
Adaptive & Intelligent Filters:
T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness
FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges
KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes
McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws
Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering
Advanced Digital Filters:
Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag
Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics
Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis
Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively
📊 COMPREHENSIVE SIGNAL ANALYSIS
Absolute Level Interpretation (%K Line):
%K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries
%K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing
%K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend
%K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend
%K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing
%K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries
Crossover Signal Analysis:
%K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level
%K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level
Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis
Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move
Advanced Divergence Patterns (%K Line vs Price):
Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone
Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone
Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation
Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation
Momentum Strength Analysis (%K Line Slope):
Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk
Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals
Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing
%K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following
🎯 STRATEGIC APPLICATIONS
Mean Reversion Strategy (Range-Bound Markets):
Identify ranging market conditions using price action or Bollinger Bands
Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold)
Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20)
Set profit targets near opposite extreme or midline (50 level)
Use tight stop-loss above recent swing high/low to protect against breakout scenarios
Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction
Trend Following with Momentum Confirmation:
Identify primary trend direction using higher timeframe analysis or moving averages
Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend
Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend)
Use wider stops to accommodate normal trend volatility
Add to position on subsequent pullbacks showing similar Stochastic pattern
Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence
Divergence-Based Reversal Strategy:
Scan for divergence between price and Stochastic at swing highs/lows
Confirm divergence with at least two price pivots showing divergent Stochastic readings
Wait for %K to cross %D in direction of anticipated reversal as entry trigger
Enter position in divergence direction with stop beyond recent swing extreme
Target profit at key support/resistance levels or Fibonacci retracements
Scale out as Stochastic reaches opposite extreme zone
Multi-Timeframe Momentum Alignment:
Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias
Switch to lower timeframe (1H or 15M) for precise entry timing
Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction
Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe
Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe
Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses
Zone Transition Strategy:
Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.)
Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish
Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish
Use zone midpoint (50) as dynamic support/resistance for position management
Trail stops as Stochastic advances through favorable zones
Exit when Stochastic fails to maintain momentum and reverses back into prior zone
📋 DETAILED PARAMETER CONFIGURATION
%K Length (Default: 14):
Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping
Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies
Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction
Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis
%K Smoothing (Default: 3):
Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise
Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard
Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing
Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+
%D Smoothing (Default: 3):
Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering
Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications
Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading
Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only
Smoothing Type Algorithm Selection:
For Trending Markets:
ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves
HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise
EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability
For Ranging/Choppy Markets:
Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points
Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges
T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification
For Adaptive Market Conditions:
KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions
FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty
McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges
For Conservative Long-Term Analysis:
SMA: Traditional choice, predictable behavior, widely understood characteristics
RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions
Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely
Source Selection:
Close (Default): Standard choice using closing prices, most common and widely tested
HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior
HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges
Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
Traditional SMA-Based Stochastic:
Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods
Equal treatment of trending and ranging markets, no adaptation to volatility changes
Predictable behavior but suboptimal in varying market regimes
Enhanced Version with Adaptive Algorithms:
KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges
ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels
Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA
Performance improvements vary by algorithm selection and market conditions
Signal Quality Improvements:
Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically
Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies
Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing
Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals
Comparison with Standard Implementations:
Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles
Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification
Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets
Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments
Flexibility Advantages:
Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants
Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends)
Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture
Backtesting capability with algorithm as optimization parameter for strategy development
Limitations and Considerations:
Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data
Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable
Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions
Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation
Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios
Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends
Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm
Divergence patterns require confirmation from price action or additional indicators before trading
Past indicator characteristics and backtested results do not guarantee future performance
Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation
Test selected algorithm on historical data of specific instrument and timeframe before live trading
Market regime changes may require algorithm adjustment for optimal performance
The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
1m Scalping ATR (with SL & Zones)A universal ATR indicator that anchors volatility to your stop-loss.
Read any market (FX, JPY pairs, Gold/Silver, indices, crypto) consistently—regardless of pip/point conventions and timeframe.
Why this indicator?
Classic ATR is absolute (pips/points) and feels different across markets/TFs. ATR Takeoff normalizes ATR to your stop-loss in pips and highlights clear zones for “quiet / ideal / too volatile,” so you instantly know if a 10-pip SL fits current conditions.
Key features
Auto pip detection (FX, JPY, XAU/XAG, indices, BTC/ETH).
Selectable ATR source: chart timeframe or fixed ATR TF (e.g., “15”, “30”, “60”).
Display modes:
Percent of SL – ATR relative to SL in %, great for M1 (typical 10–30%).
Multiple of SL – ATR as a multiple of SL (e.g., 0.6× / 1.0× / 1.2×).
Panel zones:
Green = “Ready for takeoff” (≤ Low), Yellow = reference (Mid), Red = too volatile (≥ High).
Status badge (top-right): Quiet / ATR ok / Wild, current ATR/SL value, ATR TF used.
Direction-agnostic: Works the same for longs and shorts.
Inputs (at a glance)
Length / Smoothing (RMA/SMA/EMA/WMA): ATR base settings.
Your Stop-Loss (Pips): Reference SL (e.g., 10).
ATR Timeframe (empty = chart): Use chart TF or a fixed TF.
Display Mode: “Percent of SL” or “Multiple of SL.”
Low/Mid/High (Percent Mode): Zone thresholds in % of SL.
Low/Mid/High (Multiple Mode): Zone thresholds in ×SL.
Recommended defaults
Length 14, Smoothing RMA, SL 10 pips
Display Mode: Percent of SL
Low/Mid/High (%): 15 / 20 / 25
ATR Timeframe: empty (= chart) for reactive, or “30” for smoother M30 context with M1 entries.
How to use
Set SL (pips). 2) Choose display mode. 3) Optionally pick ATR TF.
Interpretation:
≤ Low (green): setups allowed.
≈ Mid (yellow): neutral reference.
≥ High (red): too volatile → adjust SL/size or wait.
Note: Auto-pip relies on common ticker naming; verify on exotic symbols.
Disclaimer: For research/education. Not financial advice.
Session-Conditioned Regime ATRWhy this exists
Classic ATR is great—until the open. The first few bars often inherit overnight gaps and 24-hour noise that have nothing to do with the intraday regime you actually trade. That inflates early ATR, scrambles thresholds, and invites hyper-recency bias (“today is crazy!”) when it’s just the open being the open.
This tool was built to:
Separate session reality from 24h noise. Measure volatility only inside your defined session (e.g., NYSE 09:30–16:00 ET).
Judge candles against the current regime, not the last 2–3 bars. A rolling statistic from the last N completed sessions defines what “typical” means right now.
Label “large” and “small” objectively. Bars are colored only when True Range meaningfully departs from the session regime—no gut feel, no open-bar distortion (gap inclusion optional).
Overview
Purpose: objectively identify unusually big or small candles within the active trading session, compared to the recent session regime.
Use cases: volatility filters, entry/exit confirmation, session bias detection, adaptive sizing.
This indicator replaces generic ATR with a session-conditioned, regime-aware measure. It colors candles only when their True Range (TR) is abnormally large/small versus the last N completed sessions of the same session window.
How it works
Session gating: Only bars inside the selected session are evaluated (presets for NYSE, CME RTH, FX NY; custom supported).
Per-bar TR: TR = max(high, prevRef) − min(low, prevRef).
prevRef is the prior close for in-session bars.
First bar of the session can include the overnight gap (optional; default off).
Regime statistic: For any bar in session k, aggregate all in-session TRs from the previous N completed sessions (k−N … k−1), then compute Median (default) or Mean.
Today’s anchor: Running statistic from today’s session start → current bar (for context and the on-chart ratio).
Color logic:
Big if TR ≥ bigMult × RegimeStat
Small if TR ≤ smallMult × RegimeStat
Colored states: big bull, big bear, small bull, small bear.
Non-triggering bars retain the chart’s native colors.
Panel (top-right by default)
Regime ATR (Nd): session-conditioned statistic over the past N completed sessions.
Today ATR (anchored): running statistic for the current session.
Ratio (Today/Regime): intraday volatility vs regime.
Sample size n: number of bars used in the regime calculation.
Inputs
Session Preset: NYSE (09:30–16:00 ET), CME RTH (08:30–15:00 CT), FX NY (08:00–17:00 ET), Custom (session + IANA timezone).
Regime Window: number of completed sessions (default 5).
Statistic: Median (robust) or Mean.
Include Open Gap: include overnight gap in the first in-session bar’s TR (default off).
Big/Small thresholds: multipliers relative to RegimeStat (defaults: Big=1.5×, Small=0.67×).
Colors: four independent colors for big/small × bull/bear.
Panel position & text size.
Hidden outputs: expose RegimeStat, TodayStat, Ratio, and Z-score to other scripts.
Alerts
RegimeATR: BIG bar — triggers when a bar meets the “Big” condition.
RegimeATR: SMALL bar — triggers when a bar meets the “Small” condition.
Hidden outputs (for strategies/screeners)
RegimeATR_stat, TodayATR_stat, Today_vs_Regime_Ratio, BarTR_Zscore.
Notes & limitations
No look-ahead: calculations only use information available up to that bar. Historical colors reflect what would have been known then.
Warm-up: colors begin once there are at least N completed sessions; before that, regime is undefined by design.
Changing inputs (session window, multipliers, median/mean, gap toggle) recomputes the full series using the same rolling regime logic per bar.
Designed for standard candles. Styling respects existing chart colors when no condition triggers.
Practical tips
For a broader or tighter notion of “unusual,” adjust Big/Small multipliers.
Prefer Median in markets prone to outliers; use Mean if you want Z-score alignment with the panel’s regime mean/std.
Use the Ratio readout to spot compression/expansion days quickly (e.g., <0.7× = compressed session, >1.3× = expanded).
Roadmap
More session presets:
24h continuous (crypto, index CFDs).
23h/Globex futures (CME ETH with a 60-minute maintenance break).
Regional equities (LSE, Xetra, TSE), Asia/Europe/NY overlaps for FX.
Half-day/holiday templates and dynamic calendars.
Multi-regime comparison: track multiple overlapping regimes (e.g., RTH vs ETH for futures) and show separate stats/ratios.
Robust stats options: trimmed mean, MAD/Huber alternatives; optional percentile thresholds instead of fixed multipliers.
Subpanel visuals: rolling TodayATR and Ratio plots; optional Z-score ribbon.
Screener/strategy hooks: export boolean series for BIG/SMALL, plus a lightweight strategy template for backtesting entries/exits conditioned on regime volatility.
Performance/QOL: per-symbol presets, smarter warm-up, and finer control over sample caps for ultra-low TF charts.
Changelog
v0.9b (Beta)
Session presets (NYSE/CME RTH/FX NY/Custom) with timezone handling.
Panel enhancements: ratio + sample size n.
Four-state bar coloring (big/small × bull/bear).
Alerts for BIG/SMALL bars.
Hidden Z-score stream for downstream use.
Gap-in-TR toggle for the first in-session bar.
Disclaimer
For educational purposes only. Not investment advice. Validate thresholds and session settings across symbols/timeframes before live use.
Market Structure ICT Screener [TradingFinder] BoS ChoCh🔵 Introduction
Market Structure is the foundation of every Smart Money and ICT based trading model. It describes how price moves through a sequence of highs and lows, forming clear phases of expansion, retracement and reversal. Understanding this structure allows traders to read institutional order flow and align their positions with the true direction of liquidity.
Two of the most critical components in Market Structure are the Break of Structure (BOS) and Change of Character (CHOCH). A BOS represents trend continuation, confirming strength within the current direction. In contrast, CHOCH also known as a Market Structure Shift (MSS) signals the first sign of a trend reversal or liquidity shift where order flow begins to change from bullish to bearish or vice versa.
Because the market is fractal, structure can exist at multiple levels known as Major (External) and Minor (Internal). Major structure defines the overall trend on higher timeframes while minor or internal structure reveals short term swings and early reversals within that larger move.
🔵 How to Use
Understanding Market Structure starts with identifying how price interacts with previous swing highs and swing lows. Every trend in the market, whether bullish or bearish, is built from a sequence of impulsive and corrective moves. Impulsive legs show strong displacement in the direction of liquidity flow, while corrective legs represent temporary pullbacks as the market rebalances before the next expansion. Recognizing these sequences is essential for reading the story of price and anticipating what may happen next.
A Break of Structure (BOS) occurs when price decisively moves beyond a previous structural point by breaking above the last high in an uptrend or falling below the last low in a downtrend. This event confirms that the current trend remains intact and that liquidity has been successfully taken from one side of the market. A BOS acts as confirmation of continuation and reflects strength within the existing directional bias.
A Change of Character (CHOCH) appears when price violates structure in the opposite direction of the prevailing trend. This is the first signal that market sentiment and order flow may be shifting. For example, during a downtrend if price breaks above a previous high, it indicates that sellers are losing control and a potential bullish reversal may be developing. In an uptrend, when price drops below a recent low, it suggests a possible bearish transition.
Because the market is fractal, structure exists across multiple layers. Major structure reflects the dominant movement visible on higher timeframes and defines the broader directional bias. Minor or internal structure represents smaller swings within that move and helps identify early transitions before they appear on the higher timeframe. When internal and external structures align, they offer a high probability signal for trend continuation or reversal.
By observing BOS and CHOCH across both internal and external structures, traders can clearly visualize when the market is expanding, contracting or preparing to shift direction. This structured understanding of price movement forms the foundation for precise trend analysis and high quality decision making in any Smart Money or ICT based trading approach.
🔵 Settings
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 20 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
Pivot Period : Set the length used to detect swing highs and lows. Shorter values increase sensitivity, longer ones focus on major structures.
🔵 Conclusion
Mastering Market Structure and understanding the relationship between BOS and CHOCH allows traders to see the market with greater clarity and confidence. These two elements reveal how liquidity moves through different phases of expansion and retracement and how institutional order flow shifts between accumulation and distribution.
By analyzing both internal and external structures, traders can align short term and long term perspectives and anticipate where price is most likely to react. The ability to read these structural shifts helps identify continuation points, reversals and areas where liquidity is engineered or collected.
Incorporating Market Structure into a consistent trading process transforms the way a trader views the chart. Instead of reacting to random movements, each swing, break and shift becomes part of a logical framework that reflects the true behavior of the market. Understanding BOS and CHOCH is not just a concept but a complete language of price that guides every professional decision in Smart Money and ICT based trading.
LA - EMA Bands with MTF DashboardDetailed Explanation of the LA - EMA Bands with MTF Dashboard Indicator
This custom Pine Script v6 indicator, designed for Trading View, overlays EMA-based price channels on the chart while incorporating a multi-timeframe (MTF) dashboard for broader market context. It focuses on visualizing trend direction and momentum through three sets of EMA bands, each representing different time horizons, and extends this with a tabular dashboard that summarizes signals across user-selected timeframes. The bands help identify support, resistance, and trend shifts, while the dashboard provides at-a-glance alignment across multiple periods, aiding in confirming trades or spotting divergences. Unlike volatility-based channels (e.g., Bollinger or Keltner), it relies solely on EMAs for simplicity and lag-reduced responsiveness.
Inputs Section
The script begins with user-configurable options grouped for ease. A timeframe input allows specifying a resolution for the EMA bands' data fetching, defaulting to the chart's timeframe if left empty—this enables higher-timeframe overlays on lower charts for context.
Next, a shared source input defines the price data for all midlines, defaulting to the midpoint of high and low (hl2) but customizable to close, open, or others.
The EMA bands have dedicated toggles and length inputs for each of the three sets: the first (long-term) defaults to 144 periods, the second (medium-term) to 72, and the third (short-term) to 12. These are inlined for compact settings panels, with minimum lengths of 1 to prevent errors.
A boolean toggle controls the visibility of the MTF dashboard. Following this are nine pairs of inputs for dashboard timeframes: each pair includes a show/hide toggle and an editable timeframe string (e.g., '1' for 1-minute, 'D' for daily). Defaults progress from short (1, 3, 5 minutes) to longer (15, 30, 60 minutes, daily, weekly, monthly), grouped in inlines for organization. Only enabled and non-empty timeframes appear in the dashboard.
Helpers Section
Two utility functions are defined here. The first computes an EMA on any source series over a specified length using Trading View's built-in function, reused throughout for midlines and bands.
The second function generates a signal string ("B" for buy/bullish, "S" for sell/bearish, or "-" for neutral) based on the direction of an EMA applied to high prices. It compares the current EMA value to the previous one, mirroring the band fill logic for consistency in the dashboard.
Core Components per Band Set:
Midline: An EMA calculated on a user-selectable source price (default: hl2, which is the midpoint between high and low prices). This acts as the central trend line.
Upper Band: An EMA applied directly to the high prices of each bar.
Lower Band: An EMA applied to the low prices of each bar.
These form a channel that captures the smoothed range of price action, highlighting potential support (lower band), resistance (upper band), and overall trend direction (midline).
Multiple Band Sets: The indicator includes three independent EMA band sets, each with its own length parameter for customization:
EMA1 (default length: 144) – Focuses on long-term trends.
EMA2 (default length: 72) – Targets medium-term trends.
EMA3 (default length: 12) – Emphasizes short-term momentum.
Each set can be toggled on or off via input checkboxes, allowing users to reduce chart clutter if needed.
Visual Elements:
Midline Plot: Displayed as a line colored based on its direction compared to the previous bar: green for rising (bullish), red for falling (bearish), and black for neutral (flat).
Band Fill: The area between the upper and lower bands is filled with a semi-transparent color indicating the trend of the upper band: light green for rising (suggesting expanding highs/upward momentum) and light pink for falling (contracting highs/downward pressure). The bands themselves are plotted in blue with a thin linewidth.
Multi-Timeframe Support: Users can input a custom timeframe (e.g., 'D' for daily), and the indicator fetches data from that resolution. This enables higher-timeframe context on lower-timeframe charts, such as viewing daily EMA bands on a 1-hour chart.
Calculation Mechanics:
All EMAs are computed using Trading View's built-in ta.ema() function.
Data is retrieved in a single request.security() call for efficiency, with lookahead enabled to avoid repainting.
No multipliers or volatility adjustments are included, making it a simple EMA-based envelope rather than a true volatility channel.
In practice, this indicator helps traders identify trend strength, potential breakouts (price crossing bands), or mean-reversion opportunities (price bouncing within bands). It's particularly useful for swing or position trading where multi-period alignment (e.g., all midlines green) signals conviction.
Pros
Multi-Period Insight: By combining short (12), medium (72), and long (144) periods, it offers a layered view of trends across time horizons, helping confirm alignments or divergences without needing multiple separate indicators.
Visual Clarity: Color-coded trends and fills make it easy to spot bullish/bearish shifts at a glance, reducing analysis time.
Flexibility: Custom timeframe input allows for multi-timeframe analysis, while shared source and toggles provide user control.
Simplicity and Efficiency: Purely EMA-based, it's computationally light and avoids overcomplication, making it accessible for beginners while still useful for spotting channel-based setups like squeezes or expansions.
No Repainting: With lookahead, plots are stable once bars close.
Cons
Lagging Nature: EMAs inherently lag price action, especially longer ones like 144-period, which may cause delayed signals in fast-moving or ranging markets.
Lack of Volatility Adjustment: Unlike Keltner Channels or Bollinger Bands, it doesn't incorporate ATR or standard deviation, so bands may not accurately reflect true volatility—potentially leading to false breakouts in high-volatility environments.
Chart Clutter: Displaying all three band sets simultaneously can overcrowd the chart, particularly on lower timeframes or volatile assets.
Subjective Interpretation: Color changes and band interactions require trader discretion; there's no built-in alerting or quantitative signals, which might lead to inconsistent results.
Market Dependency: Defaults may not suit all assets (e.g., stocks vs. crypto); shorter periods like 12 could whipsaw in noisy markets, while 144 might be too slow for intraday trading.
Justification for Default Values (12, 72, and 144)
The default lengths of 12, 72, and 144 are not arbitrary but draw from established trading principles, particularly W.D. Gann's geometric and numerical theories, as well as Fibonacci sequences, to create a harmonic progression for short-, medium-, and long-term analysis. Here's the rationale:
12 (Short-Term): This is a common period for capturing recent momentum in technical indicators, often seen in setups like the MACD (which uses 12- and 26-day EMAs). It aligns with natural cycles, such as the 12 months in a year, and in Gann theory, 12 serves as a base unit for squaring price and time (e.g., in the "Square of 12" where multiples like 12, 24, etc., measure cycles in days, weeks, or months). At 12 periods, the EMA reacts quickly to price changes without excessive noise, making it ideal for short-term trend detection.
72 (Medium-Term): This acts as an intermediate bridge, derived from Gann's divisions of the 360-degree circle (a key Gann concept representing a full cycle). Specifically, 72 is 360/5 (relating to pentagonal geometry and natural harmonics) and appears in Gann's time cycle measurements (e.g., as a multiple in the Square of 12: 12×6=72). It's roughly half of 144, providing a balanced midpoint for medium-term trends without overlapping too closely with the others. In practice, 72 periods smooth out short-term fluctuations while still responding to developing trends.
144 (Long-Term): This is a powerhouse number in trading lore, being both 12 squared (12×12=144, central to Gann's "Square of 144" for monthly charts and major cycle turns, as there are 12 months in a year) and a Fibonacci sequence value (1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144...). Fibonacci periods are popular in moving averages for their alignment with natural growth patterns in markets, and 144 is often used for long-term regime definition (e.g., confirming trends over 144 bars). It helps identify major support/resistance in extended cycles.
Overall, these values form a geometric/harmonic series (12, 72=12×6, 144=12×12), promoting alignment with market cycles as per Gann and Fibonacci principles, rather than generic lengths like 50 or 200. They can be adjusted based on the asset or timeframe, but the defaults provide a starting point rooted in time-tested trading numerology for balanced multi-period analysis.
Please use this along with other indicators (eg. Pivot, MACD, etc) for better results.
Relative Strength index 2xRelative Strength Index 2×
The RSI*2 by AZly is an advanced dual-RSI indicator that allows traders to analyze momentum from two distinct perspectives — short-term and medium-term — on a single chart. It combines RSI precision with multi-timeframe flexibility, giving a clear view of both immediate and underlying momentum trends.
⚙️ How It Works
This indicator calculates and plots two fully independent RSI lines, each with customizable settings:
RSI 1 (Main RSI) : Captures medium-term momentum, ideal for trend and context.
RSI 2 (Fast RSI) : Reacts quickly to short-term moves, identifying overbought and oversold conditions.
Both RSIs include:
Custom timeframe, source, and smoothing method (SMA, EMA, WMA, VWMA, HMA, SMMA).
Gradient zones to visualize momentum strength and reversals.
Adjustable levels and colors for clear chart presentation.
📘 Andrew Cardwell Zones (RSI 1)
RSI 1 uses Andrew Cardwell’s “range rules” to distinguish bullish and bearish momentum phases:
Bullish Range: RSI holds between 40–80, finding support around 40–45.
Bearish Range: RSI stays between 20–60, with rallies capped near 55–60.
A breakout from one range into another often signals a trend phase transition — marking potential trend beginnings or endings.
⚡ Overbought/Oversold Zones (RSI 2)
RSI 2 is designed for fast reactions and reversal detection:
95–100: Extreme overbought zone — potential exhaustion and short setup.
5–0: Extreme oversold zone — potential exhaustion and long setup.
Crossing these levels highlights short-term momentum exhaustion , often preceding pullbacks or strong price reversals.
💡 Why It’s Better
Compared to traditional RSI indicators, this version provides superior control and insight:
Dual independent RSIs with separate timeframes and smoothing.
Cardwell-style range recognition for better context of trend strength.
Extreme bands for fast RSI 2 to time entries with precision.
Dynamic gradient zones for intuitive visual interpretation.
Multi-timeframe flexibility that adapts to any trading style.
🎯 Trading Concepts
Trend Confirmation:
RSI 1 above 50 (bullish range) confirms uptrend bias; below 50 (bearish range) confirms downtrend.
Reversal Setup:
RSI 2 hitting extreme zones (above 95 or below 5) while RSI 1 stays steady often signals exhaustion and reversal setups.
Divergence Confirmation:
When RSI 2 diverges from price and RSI 1 supports the direction, it strengthens reversal probability.
Range Transition:
A shift in RSI 1’s range (from bearish to bullish or vice versa) confirms a major change in market structure.
🕒 Trade Timing (Entry Ideas)
Timing is one of the indicator’s strongest features.
Wait for RSI 2 to reach an extreme zone (above 95 or below 5).
Then confirm the direction with RSI 1 — trades are most effective when RSI 1’s range aligns with the anticipated move.
Buy Setup:
RSI 1 in bullish range + RSI 2 rebounds upward from the 5 zone.
Sell Setup:
RSI 1 in bearish range + RSI 2 turns down from the 95 zone.
Best Timing:
Enter when RSI 2 crosses back inside the 10–90 range in the same direction as RSI 1’s trend.
This captures momentum just as it resumes — avoiding early or late entries.
🔷 M & W Patterns (RSI 2)
RSI 2 also reveals short-term exhaustion structures:
“ M ” Formation: Two RSI peaks near 95–100 — bearish reversal setup.
“ W ” Formation: Two RSI troughs near 0–5 — bullish reversal setup.
These shapes often appear before price reversals, offering early momentum clues.
⚠️ Important Trading Guidance
It is strongly recommended not to trade against the prevailing trend or attempt to pick exact tops or bottoms. The indicator works best when used in alignment with trend direction. Counter-trend entries carry higher risk and lower probability.
📊 Recommended Use
Ideal for momentum traders, scalpers, and multi-timeframe analysts seeking precise timing and context. Works on all markets — forex, crypto, stocks, indexes, and commodities.
Multi-Confluence MTF S/R Signal5 Confluences:
RSI - Detects oversold/overbought conditions with momentum
MACD - Confirms trend direction and momentum shifts
Moving Average Trend - Validates price position relative to 50 SMA and 20 EMA
Volume - Ensures strong participation (1.5x average volume)
Price Action - Confirms breakout (higher high for buys, lower low for sells)
Features:
Green triangles below bars = BUY signal (all 5 confluences bullish)
Red triangles above bars = SELL signal (all 5 confluences bearish)
Background coloring when signals occur
Real-time dashboard showing each confluence status
Built-in alerts you can enable
Customizable parameters for all indicators
Multi-Timeframe Features:
Higher Timeframe Analysis (Default: 60 min)
HTF Trend - Checks if price is above/below moving averages on higher timeframe
HTF MACD - Confirms momentum direction
HTF RSI - Validates not overbought/oversold
Signal Types:
Strong Signals (Full triangles with text)
✅ All 5 current timeframe confluences aligned
✅ Higher timeframe confirmation (2 of 3 HTF conditions)
GREEN "BUY" or RED "SELL" labels
Weak Signals (Small transparent triangles with "?")
✅ All 5 current timeframe confluences aligned
❌ NO higher timeframe confirmation
Use with caution - may signal counter-trend trades
Dashboard Updates:
Shows Current Timeframe section (all 5 confluences)
Shows HTF status (your chosen higher timeframe)
Displays final signal strength
Customizable Settings:
Enable/Disable MTF - Toggle multi-timeframe confirmation
Higher Timeframe - Choose any timeframe (15m, 60m, 4H, D, etc.)
Require HTF - Force HTF confirmation or allow weak signals
Alerts:
Strong Buy/Sell - Full confirmation
Weak Buy/Sell - No HTF confirmation
Natural Gas Intraday Strategy [15m] with Partial Profit & TrailBuy when:
1. Close > EMA 100 and EMA 20 > EMA 100
2. MACD (8,21,5) > Signal and histogram rising
3. RSI > 60
4. ATR > threshold (avoid flat market)
Sell when:
1. Close < EMA 100 and EMA 20 < EMA 100
2. MACD (8,21,5) < Signal and histogram falling
3. RSI < 40
4. ATR > threshold
Exit:
• SL = recent swing ± 0.5 ATR
• TP1 = 1 ATR, trail rest with EMA 20
VWAP / ORB / VP & POCThis is an all-in-one technical analysis tool designed to give you a comprehensive view of the market on a single chart. It combines three powerful indicators—VWAP, Opening Range, and Volume Profile—to help you identify key price levels, understand intraday trends, and spot areas of high liquidity.
What It Does
The indicator plots three distinct components on your chart:
Volume-Weighted Average Price (VWAP): A benchmark that shows the average price a security has traded at throughout the day, based on both price and volume. It's often used by institutional traders to gauge whether they are getting a good price. The script also plots standard deviation or percentage-based bands around the VWAP line, which can act as dynamic support and resistance.
Opening Range Breakout (ORB): A tool that highlights the high and low of the initial trading period of a session (e.g., the first 15 minutes). The script draws lines for the opening price, range high, and range low for the rest of the session. It also colors the chart with zones to visually separate price action above, below, and within this critical opening range.
Volume Profile (VP): A powerful study that shows trading activity over a set number of bars at specific price levels. Unlike traditional volume that is plotted over time, this is plotted on the price axis. It helps you instantly see where the most and least trading has occurred, identifying significant levels like the Point of Control (POC)—the single price with the most volume—and the Value Area (VA), where the majority of trading took place.
How to Use It for Trading
The real strength of this indicator comes from finding confluence, where two or more of its components signal the same key level.
Identifying Support & Resistance: The POC, VWAP bands, Opening Range high/low, and session open price are all powerful levels to watch. When price approaches one of these levels, you can anticipate a potential reaction (a bounce or a breakout).
Gauging Intraday Trend: A simple rule of thumb is to consider the intraday trend bullish when the price is trading above the VWAP and bearish when it is trading below the VWAP.
Finding High-Value Zones: The Volume Profile’s Value Area (VA) shows you where the market has accepted a price. Trading within the VA is considered "fair value," while prices outside of it are "unfair." Reversals often happen when the price tries to re-enter the Value Area from the outside.
Settings:
Here’s a breakdown of all the settings you can change to customize the indicator to your liking.
Volume Profile Settings:
Number of Bars: How many of the most recent bars to use for the calculation. A higher number gives a broader profile.
Row Size: The number of price levels (rows) in the profile. Higher numbers give a more detailed, granular view.
Value Area Volume %: The percentage of total volume to include in the Value Area (standard is 70%).
Horizontal Offset: Moves the Volume Profile further to the right to avoid overlapping with recent price action.
Colors & Styles: Customize the colors for the POC line, Value Area, and the up/down volume bars.
VWAP Settings:
Anchor Period: Resets the VWAP calculation at the start of a new Session, Week, Month, Year, etc. You can even anchor it to corporate events like Earnings or Splits.
Source: The price source used in the calculation (default is hlc3, the average of the high, low, and close).
Bands Calculation Mode:
Standard Deviation: The bands are based on statistical volatility.
Percentage: The bands are a fixed percentage away from the VWAP line.
Bands Multiplier: Sets the distance of the bands from the VWAP. You can enable and configure up to three sets of bands.
ORB Settings (Opening Range)
Opening Range Timeframe: The duration of the opening range (e.g., 15 for 15 minutes, 60 for the first hour).
Market Session & Time Zone: Crucial for ensuring the range is calculated at the correct time for the asset you're trading.
Line & Zone Styles: Full customization for the colors, thickness, and style (Solid, Dashed, Dotted) of the High, Low, and Opening Price lines, as well as the background colors for the zones above, below, and within the range.
RSI Cloud v1.0 [PriceBlance] RSI Cloud v1.0 — Ichimoku-style Cloud on RSI(14), not on price.
Recalibrated baselines: EMA9 (Tenkan) for speed, WMA45 (Kijun) for stability.
Plus ADX-on-RSI to grade strength so you know when momentum persists or fades.
1. Introduction
RSI Cloud v1.0 applies an Ichimoku Cloud directly on RSI(14) to reveal momentum regimes earlier and cleaner than price-based views. We replaced Tenkan with EMA9 (faster, more responsive) and Kijun with WMA45 (slower, more stable) to fit a bounded oscillator (0–100). Forward spans (+26) and a lagging line (−26) provide a clear framework for trend bias and transitions.
To qualify signals, the indicator adds ADX computed on RSI—highlighting whether strength is weak, strong, or very strong, so you can decide when to follow, fade, or stand aside.
2. Core Mapping (Hook + Bullets)
At a glance: Ichimoku on RSI(14) with recalibrated baselines for a bounded oscillator.
Source: RSI(14)
Tenkan → EMA9(RSI) (fast, responsive)
Kijun → WMA45(RSI) (slow, stable)
Span A: classic Ichimoku midline, displaced +26
Span B: classic Ichimoku baseline, displaced +26
Lagging line: RSI shifted −26
3. Key Benefits (Why traders care)
Momentum regimes on RSI: position vs. Cloud = bull / bear / transition at a glance.
Cleaner confirmations: EMA9/WMA45 pairing cuts noise vs. raw 30/70 flips.
Earlier warnings: Cloud breaks on RSI often lead price-based confirmations.
4. ADX on RSI (Enhanced Strength Normalization)
Grade strength inside the RSI domain using ADX from ΔRSI:
ADX ≤ 20 → Weak (transparency = 60)
ADX ≤ 40 → Strong (transparency = 15)
ADX > 40 → Very strong (transparency = 0)
Use these tiers to decide when to trust, fade, or ignore a signal.
5. How to Read (Quick rules)
Bias / Regime
Bullish: RSI above Cloud and RSI > WMA45
Bearish: RSI below Cloud and RSI < WMA45
Neutral / Transition: all other cases
6. Settings (Copy & use)
RSI Length: 14 (default)
Tenkan: EMA9 on RSI · Kijun: WMA45 on RSI
Displacement: +26 (Span A/B) · −26 (Lagging)
Theme: PriceBlance Dark/Light
Visibility toggles: Cloud, Baselines, Lagging, labels/panel, Overbought/Oversold, Divergence, ADX-on-RSI (via transparency coloring)
7. Credits & License
Author/Brand: PriceBlance
Version: v1.0 (Free)
Watermark: PriceBlance • RSI Cloud v1.0
Disclaimer: Educational content; not financial advice.
8. CTA
If this helps, please ⭐ Star and Follow for updates & new tools.
Feedback is welcome—comment what you’d like added next (alerts, presets, visuals).
Stoch + RSI DashboardIndicator Description
MTF Stochastic + RSI Dashboard FLEX with STRONG Alerts
A compact, multi-timeframe dashboard that shows Stochastic %K/%D, RSI and signal states across user-defined timeframes. Columns can be toggled on/off to keep the panel as small as you need. Signal texts and colors are fully customizable. The table can be placed in any chart corner, and the background color & opacity are adjustable for perfect readability.
What it shows
• For each selected timeframe: %K, %D, a signal cell (Bullish/Bearish/Strong), RSI value, and RSI state (Overbought/Oversold/Neutral).
• Timeframes are displayed as friendly labels (e.g., 60 → 1h, W → 1w, 3D → 3d).
Signals & logic
• Bullish/Bearish when %K and %D show a sufficient gap (or an optional confirmed cross).
• Strong Bullish when both %K and %D are below the “Strong Bullish max” threshold.
• Strong Bearish when both %K and %D are above the “Strong Bearish min” threshold.
• Optional confirmation: RSI < 30 for Strong Bullish, RSI > 70 for Strong Bearish.
Alerts
• Global alerts for any selected timeframes when a STRONG BULLISH or STRONG BEARISH event occurs.
Key options
• Column visibility toggles (TF, %K, %D, Signal, RSI, RSI Status).
• Custom signal texts & colors.
• Dashboard position: top-left / top-right / bottom-left / bottom-right.
• Table background color + opacity (0 = opaque, 100 = fully transparent).
• Sensitivity (minimum %K–%D gap) and optional “cross-only” mode.
• Customizable timeframes for display and for alerts.
Default settings
• Stochastic: K=5, D=3, SmoothK=3
• RSI length: 14
• Decimals: 1
• Strong Bullish max: 20
• Strong Bearish min: 80
• Default TFs & alerts: 3m, 15m, 1h, 3h, 6h, 12h, 1d, 3d, 1w
Swing Dashboard - Pro Trader Metrics with MTF & Enhanced VolumeDESCRIPTION:
A comprehensive real-time dashboard designed for swing traders and active investors trading US equities. Displays all critical metrics in one customizable panel overlay - no need to clutter your chart with multiple indicators.
KEY FEATURES:
📊 Relative Strength Analysis:
Stock vs Market (SPY/QQQ/IWM/DIA)
Stock vs Sector (automatic sector ETF detection)
Sector vs Market comparison
Customizable lookback period (5-60 days)
📈 Price & Range Metrics:
Daily range, change, and gap percentages
Distance from SMA20, SMA50, VWAP
52-week position percentage
ATR% and ADR% for volatility assessment
Range/ADR ratio for breakout detection
💪 Advanced Volume Analysis:
RVOL (full day volume vs 20-day average)
Volume Strength (bar-by-bar analysis)
Volume Trend (5-day vs 20-day momentum)
Customizable RVOL alert thresholds
Non-repainting volume calculations
⚙️ Multi-Timeframe (MTF) Mode:
View daily charts with 5-min or 15-min metric updates
Perfect for monitoring positions without switching timeframes
All calculations remain accurate across timeframes
🎨 Fully Customizable:
Choose which metrics to display
9 position options for the dashboard
Adjustable text size and colors
Toggle individual metrics on/off
Sector-specific ETF mapping for accurate RS calculations
TECHNICAL SPECIFICATIONS:
✅ Non-repainting - all calculations use confirmed bar data
✅ No lookahead bias or future data
✅ Optimized for US stocks with proper sector mapping
✅ Works on any timeframe (best on 5m-Daily)
✅ Pine Script v6 with best practices
✅ Handles edge cases and missing data gracefully
IDEAL FOR:
Swing traders monitoring multiple positions
Day traders needing quick metric overview
Investors tracking relative strength and momentum
Anyone who wants institutional-grade metrics in one place
SECTOR ETF MAPPING:
Automatically maps to correct sector ETFs: XLK, XLF, XLV, XLY, XLP, XLE, XLB, XLI, XLRE, XLC, XLU
HOW TO USE:
Green = Positive/Strong | Red = Negative/Weak | White = Neutral
RS > 0 = Outperforming benchmark/sector
RVOL > 1.5x = High volume day
VWAP% negative = Price below VWAP (mean reversion opportunity)
R/ADR > 100% = Extended range (potential exhaustion)
Perfect for traders who need professional-grade analysis without chart clutter.
TAGS:
dashboard, swing, relativestrengrh, sectoranalysis, volume, rvol, multitimeframe, mtf, tradingdashboard, metrics, daytrading, swingtrading, momentum, vwap, atr, volatility, volumeanalysis
Relative Strength Index_ShRelative Strength Index updated to keep upper level at 60 while lower at 40
RSI Momentum ScalperOverview
The "RSI Momentum Scalper" is a Pine Script v5 strategy crafted for trading highly volatile markets, with a special focus on newly listed cryptocurrencies. This strategy harnesses the Relative Strength Index (RSI) alongside volume analysis and momentum thresholds to pinpoint short-term trading opportunities. It supports both long and short trades, managed with customizable take profit, stop loss, and trailing stop levels, which are visually plotted on the chart for easy tracking.
Why I Created This Strategy
I developed the "RSI Momentum Scalper" because I was seeking a reliable trading strategy tailored to newly listed, highly volatile cryptocurrencies. These assets often experience rapid price fluctuations, rendering traditional strategies less effective. I aimed to create a tool that could exploit momentum and volume spikes while managing risk through adaptable exit parameters. This strategy is designed to address that need, offering a flexible approach for traders in dynamic crypto markets.
How It Works
The strategy utilizes RSI to identify momentum shifts, combined with volume confirmation, to trigger long or short entries. Trades are controlled with take profit, stop loss, and trailing stop levels, which adjust dynamically as the price moves in your favor. The trailing stop helps lock in profits, while the plotted exit levels provide clear visual cues for trade management.
Customizable Settings
The script is highly customizable, allowing you to adjust it to various market conditions and trading styles. Here’s a brief overview of the key settings:
Trade Mode: Select "Both," "Long Only," or "Short Only" to determine the trade direction.
(Default: Both)
RSI Length: Sets the lookback period for the RSI calculation (2 to 30).
(Default: 8)
A shorter length increases RSI sensitivity, suitable for volatile assets.
RSI Overbought: Defines the upper RSI threshold (60 to 99) for short entries.
(Default: 90)
Higher values signal stronger overbought conditions.
RSI Oversold: Defines the lower RSI threshold (1 to 40) for long entries.
(Default: 10)
Lower values indicate stronger oversold conditions.
RSI Momentum Threshold: Sets the minimum RSI momentum change (1 to 15) to trigger entries.
(Default: 14)
Adjusts the sensitivity to price momentum.
Volume Multiplier: Multiplies the volume moving average to filter high-volume bars (1.0 to 3.0).
(Default: 1)
Higher values require stronger volume confirmation.
Volume MA Length: Sets the lookback period for the volume moving average (5 to 50).
(Default: 13)
Influences the volume trend sensitivity.
Take Profit %: Sets the profit target as a percentage of the entry price (0.1 to 10.0).
(Default: 4.15)
Determines when to close a winning trade.
Stop Loss %: Sets the loss limit as a percentage of the entry price (0.1 to 6.0).
(Default: 1.85)
Protects against significant losses.
Trailing Stop %: Sets the trailing stop distance as a percentage (0.1 to 4.0).
(Default: 2.55)
Locks in profits as the price moves favorably.
Visual Features
Exit Levels: Take profit (green), fixed stop loss (red), and trailing stop (orange) levels are plotted when in a position.
Performance Table: Displays win rate, total trades, and net profit in the top-right corner.
How to Use
Add the strategy to your chart in TradingView.
Adjust the input settings based on the cryptocurrency and timeframe you’re trading.
Monitor the plotted exit levels for trade management.
Use the performance table to assess the strategy’s performance over time.
Notes
Test the strategy on a demo account or with historical data before live trading.
The strategy is optimized for short-term scalping; adjust settings for longer timeframes if needed.
Dr.Yazdani V063 Session OR + A-Lines
**ACD Indicator: Mark Fisher's Opening Range Breakout Strategy**
**Overview**
The ACD system, developed by legendary trader Mark Fisher in his book *The Logical Trader*, is a powerful methodology for identifying high-probability trade setups based on the market's opening range (OR). This indicator automates Layers 1 and 2 of the ACD strategy, helping you spot breakout opportunities, trend direction, and key support/resistance levels. Perfect for day traders, scalpers, and swing traders in forex, stocks, futures, or crypto.
**How It Works**
1. **Opening Range (OR)**: Calculated from the high/low of the first X minutes (default: 30-60 min) of major sessions (e.g., Tokyo, London, New York).
2. **A Levels**: Drawn at a percentage (default: 0.5% of OR range or ATR-based) above/below the OR. A breakout above A-Up signals a bullish setup; below A-Down signals bearish.
3. **C Levels**: Wider levels (default: 1-2% or ATR multiplier) for stronger confirmation. Breakouts here confirm trend strength and filter fakeouts.
4. **Pivot Ranges**: Includes daily and N-day pivots to gauge overall market bias (above pivots = bullish; below = bearish).
**Key Features**
- **Customizable Sessions**: Tokyo (00:00-01:00 GMT), London (08:00-09:00 GMT), New York (13:30-14:30 GMT) – adjustable.
- **ATR Integration**: Uses Average True Range for dynamic A/C levels (period: 14 by default).
- **Visual Alerts**: Color-coded lines (green for bullish, red for bearish) + optional labels for breakouts.
- **Pivot Display**: Show/hide daily or multi-day pivots with customizable colors.
- **Risk Management**: Built-in stop-loss suggestions based on OR width.
**Trading Rules**
- **Bullish Setup**: Price breaks and holds above A-Up → Enter long at C-Up confirmation. Target: Next pivot or 1:2 risk-reward.
- **Bearish Setup**: Price breaks below A-Down → Enter short at C-Down.
- **Avoid Fakeouts**: Wait for stabilization (e.g., close above/below level).
- **Trend Filter**: Combine with PMA (Pivot Moving Average) for Layer 3 confirmation (search "ACD PMA" in TradingView).
**Settings Guide**
- **OR Timeframe**: Session start time and duration (e.g., 30 min).
- **A Multiplier (%)**: Distance for A levels (default: 0.5).
- **C Multiplier (%)**: Distance for C levels (default: 1.0).
- **ATR Period**: For volatility-based levels (default: 14).
- **Show Pivots**: Toggle daily/N-day ranges.
This indicator balances supply/demand by analyzing volume and price action within the opening range. Backtest on your favorite pairs (e.g., EURUSD, BTCUSD) and adjust for your style. Not financial advice – always use proper risk management!
**Inspired by**: Mark Fisher's ACD Methodology. Open-source for community review. Questions? Comment below!
#ACD #OpeningRange #Breakout #DayTrading #FisherStrategy
Smart Money Support/Resistance — LiteSmart Money Support/Resistance — Lite
Overview & Methodology
This indicator identifies support and resistance as zones derived from concentrated buying and selling pressure, rather than relying solely on traditional swing highs/lows. Its design focuses on transparency: how data is sourced, how zones are computed, and how the on‑chart display should be interpreted.
Lower‑Timeframe (LTF) Data
The script requests Up Volume, Down Volume, and Volume Delta from a lower timeframe to expose intrabar order‑flow structure that the chart’s native timeframe cannot show. In practical terms, this lets you see where buyers or sellers briefly dominated inside the body of a higher‑timeframe bar.
bool use_custom_tf_input = input.bool(true, title="Use custom lower timeframe", tooltip="Override the automatically chosen lower timeframe for volume calculations.", group=grpVolume)
string custom_tf_input = input. Timeframe("1", title="Lower timeframe", tooltip="Lower timeframe used for up/down volume calculations (default 5 seconds).", group=grpVolume)
import TradingView/ta/10 as tvta
resolve_lower_tf(useCustom, customTF) =>
useCustom ? customTF :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
get_up_down_volume(lowerTf) =>
= tvta.requestUpAndDownVolume(lowerTf)
var float upVolume = na
var float downVolume = na
var float deltaVolume = na
string lower_tf = resolve_lower_tf(use_custom_tf_input, custom_tf_input)
= get_up_down_volume(lower_tf)
upVolume := u_tmp
downVolume := d_tmp
deltaVolume := dl_tmp
• Data source: TradingView’s ta.requestUpAndDownVolume(lowerTf) via the official TA library.
• Plan capabilities: higher‑tier subscriptions unlock seconds‑based charts and allow more historical bars per chart. This expands both the temporal depth of LTF data and the precision of short‑horizon analysis, while base tiers provide minute‑level data suitable for day/short‑swing studies.
• Coverage clarity: a small on‑chart Coverage Panel reports the active lower timeframe, the number of bars covered, and the latest computed support/resistance ranges so you always know the bounds of valid LTF input.
Core Method
1) Data acquisition (LTF)
The script retrieves three series from the chosen lower timeframe:
– Up Volume (buyers)
– Down Volume (sellers)
– Delta (Up – Down)
2) Rolling window & extrema
Over a user‑defined lookback (Global Volume Period), the algorithm builds rolling arrays of completed bars and scans for extrema:
– Buyers_max / Buyers_min from Up Volume
– Sellers_max / Sellers_min from Down Volume
Only completed bars are considered; the current bar is excluded for stability.
3) Price mapping
The extrema are mapped back to their source candles to obtain price bounds:
– For “maximum” roles the algorithm uses the relevant candle highs.
– For “minimum” roles it uses the relevant candle lows.
These pairs define candidate resistance (max‑based) and support (min‑based) zones or vice versa.
4) Zone construction & minimum width
To ensure practicality on all symbols, zones enforce a minimum vertical thickness of two ticks. This prevents visually invisible or overly thin ranges on instruments with tight ticks.
5) Vertical role resolution
When both max‑ and min‑based zones exist, the script compares their midpoints. If, due to local price structure, the min‑based zone sits above the max‑based zone, display roles are swapped so the higher zone is labeled Resistance and the lower zone Support. Colors/widths are updated accordingly to keep the visual legend consistent.
6) Rendering & panel
Two horizontal lines and a filled box represent each active zone. The Coverage Panel (bottom‑right by default) prints:
– Lower‑timeframe in use
– Number of bars covered by LTF data
– Current Support and Resistance ranges
If the two zones overlap, an additional “Range Market” note is shown.
Key Inputs
• Global Volume Period: shared lookback window for the extrema search.
• Lower timeframe: user‑selectable override of the automatically resolved lower timeframe.
• Visualization toggles: independent show/hide controls and colors for maximum (resistance) and minimum (support) zones.
• Coverage Panel: enable/disable the single‑cell table and its readout.
Operational Notes
• The algorithm aligns all lookups to completed bars (no peeking). Price references are shifted appropriately to avoid using the still‑forming bar in calculations.
• Second‑based lower timeframes improve granularity for scalping and very short‑term entries. Minute‑based lower timeframes provide broader coverage for intraday and short‑swing contexts.
• Use the Coverage Panel to confirm the true extent of available LTF history on your symbol/plan before drawing conclusions from very deep lookbacks.
Visual Walkthrough
A step‑by‑step image sequence accompanies this description. Each figure demonstrates how the indicator reads LTF volume, locates extrema, builds price‑mapped zones, and updates labels/colors when vertical order requires it.
Chart Interpretation
This chart illustrates two distinct perspectives of the Smart Money Support/Resistance — Lite indicator, each derived from different lookback horizons and lower-timeframe (LTF) resolutions.
1- Short-term view (43 bars, 10-second LTF)
Using the most recent 43 completed bars with 10-second intrabar data, the algorithm detects that both maximum and minimum volume extrema fall within a narrow range. The result is a clearly identified range market: resistance between 178.15–184.55 and support between 175.02–179.38.
The Coverage Panel (bottom-right) confirms the scope of valid input: the lower timeframe used, number of bars covered, and the resulting zones. This short-term scan highlights how the indicator adapts to limited data depth, flagging sideways structure where neither side dominates.
2 - Long-term view (120 bars, 30-second LTF)
Over a wider 120-bar lookback with higher-granularity 30-second data, broader supply and demand zones emerge.
– The long-term resistance zone captures the concentration of buyers and sellers at the upper boundary of recent price history.
– The long-term support zone anchors to the opposite side of the distribution, derived from maxima and minima of both buying and selling pressure.
These zones reflect deeper structural levels where market participants previously committed significant volume.
Combined Perspective
By aligning the short-term and long-term outputs, the chart shows how the indicator distinguishes immediate consolidation (range market) from more durable support and resistance levels derived from extended history. This dual resolution approach makes clear that support and resistance are not static lines but dynamic zones, dependent on both timeframe depth and the resolution of intrabar volume data.
MA“5 / 10 / 20 / 60 / 240 Moving Averages, with a red background automatically highlighted when MA5 > MA10 > MA20.”
BOCS AdaptiveBOCS Adaptive Strategy - Automated Volatility Breakout System
WHAT THIS STRATEGY DOES:
This is an automated trading strategy that detects consolidation patterns through volatility analysis and executes trades when price breaks out of these channels. Take-profit and stop-loss levels are calculated dynamically using Average True Range (ATR) to adapt to current market volatility. The strategy closes positions partially at the first profit target and exits the remainder at the second target or stop loss.
TECHNICAL METHODOLOGY:
Price Normalization Process:
The strategy begins by normalizing price to create a consistent measurement scale. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). The current close price is then normalized using the formula: (close - lowest_low) / (highest_high - lowest_low). This produces values between 0 and 1, allowing volatility analysis to work consistently across different instruments and price levels.
Volatility Detection:
A 14-period standard deviation is applied to the normalized price series. Standard deviation measures how much prices deviate from their average - higher values indicate volatility expansion, lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() functions to track when volatility reaches peaks and troughs over the detection length period (default 14 bars).
Channel Formation Logic:
When volatility crosses from a high level to a low level, this signals the beginning of a consolidation phase. The strategy records this moment using ta.crossover(upper, lower) and begins tracking the highest and lowest prices during the consolidation. These become the channel boundaries. The duration between the crossover and current bar must exceed 10 bars minimum to avoid false channels from brief volatility spikes. Channels are drawn using box objects with the recorded high/low boundaries.
Breakout Signal Generation:
Two detection modes are available:
Strong Closes Mode (default): Breakout occurs when the candle body midpoint math.avg(close, open) exceeds the channel boundary. This filters out wick-only breaks.
Any Touch Mode: Breakout occurs when the close price exceeds the boundary.
When price closes above the upper channel boundary, a bullish breakout signal generates. When price closes below the lower boundary, a bearish breakout signal generates. The channel is then removed from the chart.
ATR-Based Risk Management:
The strategy uses request.security() to fetch ATR values from a specified timeframe, which can differ from the chart timeframe. For example, on a 5-minute chart, you can use 1-minute ATR for more responsive calculations. The ATR is calculated using ta.atr(length) with a user-defined period (default 14).
Exit levels are calculated at the moment of breakout:
Long Entry Price = Upper channel boundary
Long TP1 = Entry + (ATR × TP1 Multiplier)
Long TP2 = Entry + (ATR × TP2 Multiplier)
Long SL = Entry - (ATR × SL Multiplier)
For short trades, the calculation inverts:
Short Entry Price = Lower channel boundary
Short TP1 = Entry - (ATR × TP1 Multiplier)
Short TP2 = Entry - (ATR × TP2 Multiplier)
Short SL = Entry + (ATR × SL Multiplier)
Trade Execution Logic:
When a breakout occurs, the strategy checks if trading hours filter is satisfied (if enabled) and if position size equals zero (no existing position). If volume confirmation is enabled, it also verifies that current volume exceeds 1.2 times the 20-period simple moving average.
If all conditions are met:
strategy.entry() opens a position using the user-defined number of contracts
strategy.exit() immediately places a stop loss order
The code monitors price against TP1 and TP2 levels on each bar
When price reaches TP1, strategy.close() closes the specified number of contracts (e.g., if you enter with 3 contracts and set TP1 close to 1, it closes 1 contract). When price reaches TP2, it closes all remaining contracts. If stop loss is hit first, the entire position exits via the strategy.exit() order.
Volume Analysis System:
The strategy uses ta.requestUpAndDownVolume(timeframe) to fetch up volume, down volume, and volume delta from a specified timeframe. Three display modes are available:
Volume Mode: Shows total volume as bars scaled relative to the 20-period average
Comparison Mode: Shows up volume and down volume as separate bars above/below the channel midline
Delta Mode: Shows net volume delta (up volume - down volume) as bars, positive values above midline, negative below
The volume confirmation logic compares breakout bar volume to the 20-period SMA. If volume ÷ average > 1.2, the breakout is classified as "confirmed." When volume confirmation is enabled in settings, only confirmed breakouts generate trades.
INPUT PARAMETERS:
Strategy Settings:
Number of Contracts: Fixed quantity to trade per signal (1-1000)
Require Volume Confirmation: Toggle to only trade signals with volume >120% of average
TP1 Close Contracts: Exact number of contracts to close at first target (1-1000)
Use Trading Hours Filter: Toggle to restrict trading to specified session
Trading Hours: Session input in HHMM-HHMM format (e.g., "0930-1600")
Main Settings:
Normalization Length: Lookback bars for high/low calculation (1-500, default 100)
Box Detection Length: Period for volatility peak/trough detection (1-100, default 14)
Strong Closes Only: Toggle between body midpoint vs close price for breakout detection
Nested Channels: Allow multiple overlapping channels vs single channel at a time
ATR TP/SL Settings:
ATR Timeframe: Source timeframe for ATR calculation (1, 5, 15, 60, etc.)
ATR Length: Smoothing period for ATR (1-100, default 14)
Take Profit 1 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 2.0)
Take Profit 2 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 3.0)
Stop Loss Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 1.0)
Enable Take Profit 2: Toggle second profit target on/off
VISUAL INDICATORS:
Channel boxes with semi-transparent fill showing consolidation zones
Green/red colored zones at channel boundaries indicating breakout areas
Volume bars displayed within channels using selected mode
TP/SL lines with labels showing both price level and distance in points
Entry signals marked with up/down triangles at breakout price
Strategy status table showing position, contracts, P&L, ATR values, and volume confirmation status
HOW TO USE:
For 2-Minute Scalping:
Set ATR Timeframe to "1" (1-minute), ATR Length to 12, TP1 Multiplier to 2.0, TP2 Multiplier to 3.0, SL Multiplier to 1.5. Enable volume confirmation and strong closes only. Use trading hours filter to avoid low-volume periods.
For 5-15 Minute Day Trading:
Set ATR Timeframe to match chart or use 5-minute, ATR Length to 14, TP1 Multiplier to 2.0, TP2 Multiplier to 3.5, SL Multiplier to 1.2. Volume confirmation recommended but optional.
For Hourly+ Swing Trading:
Set ATR Timeframe to 15-30 minute, ATR Length to 14-21, TP1 Multiplier to 2.5, TP2 Multiplier to 4.0, SL Multiplier to 1.5. Volume confirmation optional, nested channels can be enabled for multiple setups.
BACKTEST CONSIDERATIONS:
Strategy performs best during trending or volatility expansion phases
Consolidation-heavy or choppy markets produce more false signals
Shorter timeframes require wider stop loss multipliers due to noise
Commission and slippage significantly impact performance on sub-5-minute charts
Volume confirmation generally improves win rate but reduces trade frequency
ATR multipliers should be optimized for specific instrument characteristics
COMPATIBLE MARKETS:
Works on any instrument with price and volume data including forex pairs, stock indices, individual stocks, cryptocurrency, commodities, and futures contracts. Requires TradingView data feed that includes volume for volume confirmation features to function.
KNOWN LIMITATIONS:
Stop losses execute via strategy.exit() and may not fill at exact levels during gaps or extreme volatility
request.security() on lower timeframes requires higher-tier TradingView subscription
False breakouts inherent to breakout strategies cannot be completely eliminated
Performance varies significantly based on market regime (trending vs ranging)
Partial closing logic requires sufficient position size relative to TP1 close contracts setting
RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance of this or any strategy does not guarantee future results. This strategy is provided for educational purposes and automated backtesting. Thoroughly test on historical data and paper trade before risking real capital. Market conditions change and strategies that worked historically may fail in the future. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions.
ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by AlgoAlpha in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns and sharing this innovative technique with the TradingView community. The enhancements added to the original concept include automated trade execution, multi-timeframe ATR-based risk management, partial position closing by contract count, volume confirmation filtering, and real-time position monitoring.
Anchored EMA/VWAP### Anchored EMA/VWAP Indicator
**Description:**
The **Anchored EMA/VWAP Indicator** is a powerful and versatile tool designed for traders seeking to analyze price trends and momentum from a user-defined anchor point in time. Built for TradingView using Pine Script v6, this indicator calculates and displays multiple **Exponential Moving Averages (EMAs)**, **Volume-Weighted Exponential Moving Averages (VWEMAs)**, and a **Volume-Weighted Average Price (VWAP)**, all anchored to a specific date and time chosen by the user. By anchoring these calculations, traders can focus on price action relative to significant market events, such as news releases, earnings reports, or key support/resistance levels.
The indicator supports multi-timeframe (MTF) analysis, allowing users to compute EMAs, VWEMAs, and VWAP on a higher or custom timeframe (e.g., 5-minute, 1-hour, daily) while overlaying the results on the current chart. It also includes customizable cross signals for EMA and VWEMA pairs, marked with distinct shapes (circles, diamonds, squares) to highlight potential trend changes or reversals. These features make the indicator ideal for trend-following, momentum trading, and identifying key price levels across various markets, including stocks, forex, cryptocurrencies, and commodities.
**Key Features:**
- **Anchored Calculations**: EMAs, VWEMAs, and VWAP start calculations from a user-specified anchor time, enabling analysis relative to significant market moments.
- **Multi-Timeframe Support**: Compute indicators on any timeframe (e.g., 60-minute, daily) and display them on the chart’s timeframe for flexible analysis.
- **Customizable EMAs and VWEMAs**: Four EMAs and four VWEMAs with adjustable lengths (default: 9, 21, 50, 100) and colors, with options to show or hide each.
- **Volume-Weighted Metrics**: VWAP and VWEMAs incorporate volume data, providing a more robust representation of market activity compared to standard EMAs.
- **Cross Signals**: Visual markers (circles, diamonds, squares) for crossovers between EMA and VWEMA pairs, with customizable visibility to highlight bullish (up) or bearish (down) signals.
- **User-Friendly Interface**: Organized input groups for General, EMA, VWEMA, VWAP, Arrow Settings, and Cross Visibility, with intuitive inline inputs for length and color customization.
- **Visual Clarity**: Overlaid on the price chart with distinct colors and line styles (dotted for EMAs, dashed for VWEMAs, solid for VWAP) to ensure easy interpretation.
**How to Use:**
1. **Set the Anchor Time**: Click a specific bar or enter a date/time (default: June 1, 2025) to start calculations from a significant market event.
2. **Select Timeframe**: Choose a timeframe (e.g., "5" for 5-minute, "D" for daily) to compute the indicators, allowing alignment with your trading strategy.
3. **Customize EMAs and VWEMAs**: Adjust lengths and colors for up to four EMAs and VWEMAs, and toggle their visibility to focus on relevant lines.
4. **Enable VWAP**: Display the anchored VWAP to identify volume-weighted price levels, useful as dynamic support/resistance.
5. **Monitor Cross Signals**: Enable cross visibility for specific EMA or VWEMA pairs to spot potential trend changes. Bullish crosses (e.g., shorter EMA crossing above longer EMA) are marked with green shapes below the bar, while bearish crosses are marked with red shapes above the bar.
6. **Interpret Signals**: Use EMA/VWEMA crossovers for trend confirmation, VWAP as a mean-reversion level, and volume-weighted VWEMAs for momentum analysis in high-volume markets.
**Use Cases:**
- **Trend Trading**: Identify trend direction using EMA and VWEMA crossovers, with shorter lengths (e.g., 9, 21) for faster signals and longer lengths (e.g., 50, 100) for trend confirmation.
- **Mean Reversion**: Use the anchored VWAP as a dynamic support/resistance level to trade pullbacks or breakouts.
- **Event-Based Analysis**: Anchor the indicator to significant events (e.g., earnings, economic data releases) to analyze price behavior post-event.
- **Multi-Timeframe Strategies**: Combine higher timeframe EMAs/VWAPs with lower timeframe price action for high-probability setups.
**Settings:**
- **Anchor Time**: Set the starting point for calculations (default: June 1, 2025).
- **Timeframe**: Choose the timeframe for calculations (default: 5-minute).
- **EMA/VWEMA Lengths**: Default lengths of 9, 21, 50, and 100 for both EMAs and VWEMAs, adjustable per user preference.
- **Colors**: Customizable colors with slight transparency for visual clarity.
- **Cross Visibility**: Toggle specific EMA and VWEMA cross signals (e.g., EMA1/EMA2, VWEMA1/VWEMA3) to reduce chart clutter.
- **Arrow Colors**: Green for bullish crosses, red for bearish crosses.
**Notes:**
- The indicator is overlaid on the price chart, ensuring seamless integration with price action analysis.
- VWEMAs and VWAP are volume-sensitive, making them particularly effective in markets with significant volume fluctuations.
- Ensure the anchor time is set to a valid historical or future bar to avoid calculation errors.
- Cross signals are conditional on non-NA values to prevent false positives during initialization.
**Author**: NEPOLIX
**Version**: 6 (Pine Script v6)
**Published**: For TradingView Community
This indicator is a must-have for traders looking to combine anchored, volume-weighted, and multi-timeframe analysis into a single, customizable tool. Whether you're a day trader, swing trader, or long-term investor, the Anchored EMA/VWAP Indicator provides actionable insights for informed trading decisions.
Opening ATR + High Momentum (10/30/60)this is a custom momentum indicator using atr
A fixed, compiling Pine v5 script is below with the three issues corrected: no plots in local scope, a ≤10-character shorttitle, and cleaned ternaries/formatting that remove the “end of line without line continuation” error.
Foresight Cone (HoltxF1xVWAP) [KedArc Quant]Description:
This is a time-series forecasting indicator that estimates the next bar (F1) and projects a path a few bars ahead. It also draws a confidence cone based on how accurate the recent forecasts have been. You can optionally color the projection only when price agrees with VWAP.
Why it’s different
* One clear model: Everything comes from Holt’s trend-aware forecasting method—no mix of unrelated indicators.
* Transparent visuals: You see the next-bar estimate (F1), the forward projection, and a cone that widens or narrows based on recent forecast error.
* Context, not signals: The VWAP option only changes colors. It doesn’t add trade rules.
* No look-ahead: Accuracy is measured using the forecast made on the previous bar versus the current bar.
Inputs (what they mean)
* Source: Price series to forecast (default: Close).
* Preset: Quick profiles for fast, smooth, or momentum markets (see below).
* Alpha (Level): How fast the model reacts to new prices. Higher = faster, twitchier.
* Beta (Trend): How fast the model updates the slope. Higher = faster pivots, more flips in chop.
* Horizon: How many bars ahead to project. Bigger = wider cone.
* Residual Window: How many bars to judge recent accuracy. Bigger = steadier cone.
* Confidence Z: How wide the cone should be (typical setting ≈ “95% style” width).
* Show Bands / Draw Forward Path: Turn the cone and forward lines on/off.
* Color only when aligned with VWAP: Highlights projections only when price agrees with the trend side of VWAP.
* Colors / Show Panel: Styling plus a small panel with RMSE, MAPE, and trend slope.
Presets (when to pick which)
* Scalp / Fast (1-min): Very responsive; best for quick moves. More twitch in chop.
* Smooth Intraday (1–5 min): Calmer and steadier; a good default most days.
* Momentum / Breakout: Quicker slope tracking during strong pushes; may over-react in ranges.
* Custom: Set your own values if you know exactly what you want.
What is F1 here?
F1 is the model’s next-bar fair value. Crosses of price versus F1 can hint at short-term momentum shifts or mean-reversion, especially when viewed with VWAP or the cone.
How this helps
* Gives a baseline path of where price may drift and a cone that shows normal wiggle room.
* Helps you tell routine noise (inside cone) from information (edges or breaks outside the cone).
* Keeps you aware of short-term bias via the trend slope and F1.
How to use (step by step)
1. Add to chart → choose a Preset (start with Smooth Intraday).
2. Set Horizon around 8–15 bars for intraday.
3. (Optional) Turn on VWAP alignment to color only when price agrees with the trend side of VWAP.
4. Watch where price sits relative to the cone and F1:
* Inside = normal noise.
* At edges = stretched.
* Outside = possible regime change.
5. Check the panel: if RMSE/MAPE spike, expect a wider cone; consider a smoother preset or a higher timeframe.
6. Tweak Alpha/Beta only if needed: faster for momentum, slower for chop.
7. Combine with your own plan for entries, exits, and risk.
Accuracy Panel — what it tells you
Preset & Horizon: Shows which preset you’re using and how many bars ahead the projection goes. Longer horizons mean more uncertainty.
RMSE (error in price units): A “typical miss” measured in the chart’s currency (e.g., ₹).
Lower = tighter fit and a usually narrower cone. Rising = conditions getting noisier; the cone will widen.
MAPE (error in %): The same idea as RMSE but in percent.
Good for comparing different symbols or timeframes. Sudden spikes often hint at a regime change.
Slope T: The model’s short-term trend reading.
Positive = gentle up-bias; negative = gentle down-bias; near zero = mostly flat/drifty.
How to read it at a glance
Calm & directional: RMSE/MAPE steady or falling + Slope T positive (or negative) → trends tend to respect the cone’s mid/upper (or mid/lower) area.
Choppy/uncertain: RMSE/MAPE climbing or jumping → expect more whipsaw; rely more on the cone edges and higher-TF context.
Flat tape: Slope T near zero → mean-revert behavior is common; treat cone edges as stretch zones rather than breakout zones.
Warm-up & tweaks
Warm-up: Right after adding the indicator, the panel may be blank for a short time while it gathers enough bars.
Too twitchy? Switch to Smooth Intraday or increase the Residual Window.
Too slow? Use Scalp/Fast or Momentum/Breakout to react quicker.
Timeframe tips
* 1–3 min: Scalp/Fast or Momentum/Breakout; horizon \~8–12.
* 5–15 min: Smooth Intraday; horizon \~12–15.
* 30–60 min+: Consider a larger residual window for a steadier cone.
FAQ
Q: Is this a strategy or an indicator?
A: It’s an indicator only. It does not place orders, TP/SL, or run backtests.
Q: Does it repaint?
A: The next-bar estimate (F1) and the cone are calculated using only information available at that time. The forward path is a projection drawn on the last bar and will naturally update as new bars arrive. Historical bars aren’t revised with future data.
Q: What is F1?
A: F1 is the indicator’s best guess for the next bar.
Price crossing above/below F1 can hint at short-term momentum shifts or mean-reversion.
Q: What do “Alpha” and “Beta” do?
A: Alpha controls how fast the indicator reacts to new prices
(higher = faster, twitchier). Beta controls how fast the slope updates (higher = quicker pivots, more flips in chop).
Q: Why does the cone width change?
A: It reflects recent forecast accuracy. When the market gets noisy, the cone widens. When the tape is calm, it narrows.
Q: What does the Accuracy Panel tell me?
A:
* Preset & Horizon you’re using.
* RMSE: typical forecast miss in price units.
* MAPE: typical forecast miss in percent.
* Slope T: short-term trend reading (up, down, or flat).
If RMSE/MAPE rise, expect a wider cone and more whipsaw.
Q: The panel shows “…” or looks empty. Why?
A: It needs a short warm-up to gather enough bars. This is normal after you add the indicator or change settings/timeframes.
Q: Which timeframe is best?
A:
* 1–3 min: Scalp/Fast or Momentum/Breakout, horizon \~8–12.
* 5–15 min: Smooth Intraday, horizon \~12–15.
Higher timeframes work too; consider a larger residual window for steadier cones.
Q: Which preset should I start with?
A: Start with Smooth Intraday. If the market is trending hard, try Momentum/Breakout.
For very quick tapes, use Scalp/Fast. Switch back if things get choppy.
Q: What does the VWAP option do?
A: It only changes colors (highlights when price agrees with the trend side of VWAP).
It does not add or remove signals.
Q: Are there alerts?
A: Yes—alerts for price crossing F1 (up/down). Use “Once per bar close” to reduce noise on fast charts.
Q: Can I use this on stocks, futures, crypto, or FX?
A: Yes. It works on any symbol/timeframe. You may want to adjust Horizon and the Residual Window based on volatility.
Q: Can I use it with Heikin Ashi or other non-standard bars?
A: You can, but remember you’re forecasting the synthetic series of those bars. For pure price behavior, use regular candles.
Q: The cone feels too wide/too narrow. What do I change?
A:
* Too wide: lower Alpha/Beta a bit or increase the Residual Window.
* Too narrow (misses moves): raise Alpha/Beta slightly or try Momentum/Breakout.
Q: Why do results change when I switch timeframe or symbol?
A: Different noise levels and trends. The accuracy stats reset per chart, so the cone adapts to each context.
Q: Any limits or gotchas?
A: Extremely large Horizon may hit TradingView’s line-object limits; reduce Horizon or turn
off extra visuals if needed. Big gaps or news spikes will widen errors—expect the cone to react.
Q: Can this predict exact future prices?
A: No. It provides a baseline path and context. Always combine with your own rules and risk management.
Glossary
* TS (Time Series): Data over time (prices).
* Holt’s Method: A forecasting approach that tracks a current level and a trend to predict the next bars.
* F1: The indicator’s best guess for the next bar.
* F(h): The projected value h bars ahead.
* VWAP: Volume-Weighted Average Price—used here for optional color alignment.
* RMSE: Typical forecast miss in price units (how far off, on average).
* MAPE: Typical forecast miss in percent (scale-free, easy to compare).
Notes & limitations
* The panel needs a short warm-up; stats may be blank at first.
* The cone reflects recent conditions; sudden volatility changes will widen it.
* This is a tool for context. It does not place trades and does not promise results.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
