Traditional Technical Indicators
In addition to the 27+ Comps Quant indicators, Comps also supports a wide range of traditional technical indicators. These can be used in Configuration mode to build custom strategies.
Trend Indicators:
SMA – Simple Moving Average
A basic moving average that calculates the average price over a specified number of periods. Commonly used periods include 20, 50, 100, and 200.
EMA – Exponential Moving Average
Similar to SMA but gives more weight to recent prices, making it more responsive to price changes. Commonly used for short to medium-term trend analysis.
WMA – Weighted Moving Average
A moving average that assigns different weights to prices, with more recent prices having higher weights. Provides a balance between SMA and EMA.
HMA – Hull Moving Average
A moving average that reduces lag while maintaining smoothness. Developed by Alan Hull, it uses weighted moving averages to reduce noise.
JMA – Jurik Moving Average
An adaptive moving average that adjusts its smoothing based on market volatility. Provides smooth signals with minimal lag.
Ichimoku Cloud
A comprehensive trend-following indicator that shows support/resistance levels, momentum, and trend direction using multiple components: Tenkan-sen, Kijun-sen, Senkou Span A/B, and Chikou Span.
SuperTrend
A trend-following indicator that uses ATR (Average True Range) to determine trend direction. Changes color when trend direction shifts.
Parabolic SAR
A trend-following indicator that appears as dots above or below price, indicating potential reversal points. Useful for setting trailing stop losses.
MACD
Moving Average Convergence Divergence - shows the relationship between two moving averages. Consists of MACD line, signal line, and histogram. Used to identify trend changes and momentum.
ADX
Average Directional Index - measures trend strength regardless of direction. Values above 25 indicate strong trends, below 20 indicate weak trends.
Keltner Channels
Volatility-based channels plotted above and below an EMA. Used to identify overbought/oversold conditions and potential breakout points.
Donchian Channels
Channels based on highest high and lowest low over a specified period. Useful for identifying breakouts and measuring volatility.
Regression Channels
Statistical channels based on linear regression that show the trend and expected price boundaries. Useful for identifying mean reversion opportunities.
Session High/Low
Identifies the highest and lowest prices during specific trading sessions (e.g., Asian, European, US sessions). Useful for intraday trading strategies.
Momentum / Oscillators:
RSI
Relative Strength Index - measures the speed and magnitude of price changes. Values above 70 indicate overbought conditions, below 30 indicate oversold conditions.
Stochastic
An oscillator that compares closing price to price range over a period. Used to identify overbought/oversold conditions and potential reversals.
Stochastic RSI
A combination of Stochastic and RSI that provides more sensitive overbought/oversold readings. Values above 0.8 are overbought, below 0.2 are oversold.
MACD Histogram
The difference between MACD line and signal line, displayed as a histogram. Shows momentum changes and potential trend shifts.
TSI
True Strength Index - a momentum oscillator that filters out market noise. Values above zero indicate bullish momentum, below zero indicate bearish momentum.
ROC
Rate of Change - measures the percentage change in price over a specified period. Used to identify momentum and potential trend reversals.
TRIX
Triple Exponential Average - a momentum oscillator that filters out minor price movements. Shows the rate of change of a triple-smoothed moving average.
Momentum
Measures the rate of change in price over a specified period. Positive values indicate upward momentum, negative values indicate downward momentum.
Fisher Transform
Transforms prices into a Gaussian normal distribution, making it easier to identify turning points. Values above +2 are overbought, below -2 are oversold.
QQE
Quantitative Qualitative Estimation - an RSI-based indicator that provides smoother signals with fewer false signals than traditional RSI.
WaveTrend
An oscillator that measures the relationship between price and its moving average. Provides clear overbought/oversold signals with trend confirmation.
Volatility Indicators:
ATR
Average True Range - measures market volatility by calculating the average of true ranges over a period. Higher values indicate higher volatility.
Bollinger Bands
Volatility bands plotted above and below a moving average. Bands expand during high volatility and contract during low volatility. Used to identify overbought/oversold conditions.
Bollinger Bands
Shows where price is relative to Bollinger Bands as a percentage. Values above 1.0 indicate price above upper band, below 0.0 indicate price below lower band.
Bandwidth
Measures the width of Bollinger Bands relative to the middle band. High bandwidth indicates high volatility, low bandwidth indicates low volatility (squeeze).
Standard Deviation
Measures the amount of variation in price movements. Higher values indicate greater price volatility and uncertainty.
Keltner Channel Width
Measures the width of Keltner Channels. Used to identify volatility expansion and contraction phases.
TTM Squeeze
Identifies periods when Bollinger Bands are inside Keltner Channels (squeeze), often followed by explosive moves.
Volatility Stop
A trailing stop based on volatility (ATR). Automatically adjusts stop distance based on market volatility conditions.
Volume Indicators:
OBV
On-Balance Volume - a cumulative volume indicator that adds volume on up days and subtracts on down days. Used to confirm price trends.
VWAP
Volume Weighted Average Price - calculates the average price weighted by volume. Often used as a reference point for intraday trading.
Volume Spike Detection
Identifies unusually high volume periods that may indicate significant price movements or institutional activity.
Chaikin Money Flow
Combines price and volume to measure buying and selling pressure. Values above zero indicate buying pressure, below zero indicate selling pressure.
Money Flow Index
A volume-weighted RSI that measures money flowing in and out of a security. Values above 80 are overbought, below 20 are oversold.
Volume Oscillator
Measures the difference between two volume moving averages. Used to identify volume trends and confirm price movements.
Volume Flow Indicator
Combines price action and volume to identify the flow of money. Positive values indicate buying pressure, negative values indicate selling pressure.
Klinger Volume Oscillator
Uses volume and price to predict price reversals. Combines volume force with trend direction to generate signals.
Pattern-Based Indicators:
Fibonacci Retracement
Draws horizontal lines at key Fibonacci levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) to identify potential support and resistance levels.
Fibonacci Extensions
Projects potential price targets beyond the original swing using Fibonacci ratios (127.2%, 161.8%, 261.8%).
Auto Pitchfork
Automatically draws Andrews' Pitchfork (a trend channel tool) based on three pivot points. Used to identify potential support and resistance levels.
Pivot Points
Calculates key support and resistance levels based on previous period's high, low, and close. Includes standard, Fibonacci, and Camarilla pivot points.
Support/Resistance Auto Zones
Automatically identifies support and resistance levels based on price action, volume, and time. Highlights key levels where price may reverse.
ZigZag
Filters out minor price movements to show only significant price swings. Useful for identifying major trends and chart patterns.
Elliott Wave Oscillator
A momentum indicator used in Elliott Wave analysis to confirm wave counts and identify potential wave completion points.
Gap Detection
Identifies gaps between trading sessions. Classifies gaps as common, breakaway, runaway, or exhaustion gaps for trading strategies.
Market Structure & Smart Money Indicators:
Fair Value Gaps (FVG)
Three-candle patterns that create imbalance areas. Price often returns to fill these gaps, creating trading opportunities.
Order Blocks
Identifies the last opposing candle before a strong directional move. These zones often act as support or resistance on retests.
Liquidity Zones
Areas where stop losses are likely clustered (equal highs/lows). Smart money often targets these zones before major moves.
Wyckoff Accumulation/Distribution
Identifies accumulation (smart money buying) and distribution (smart money selling) phases using volume and price action analysis.
Smart Money Index (SMI)
Measures the difference between buying and selling pressure from institutional traders. Helps identify smart money activity.
Break of Structure (BOS)
Identifies when price breaks a significant swing high or low, indicating potential trend continuation.
Change of Character (CHoCH)
Identifies when market structure shifts, potentially indicating trend reversal. Often occurs before a Break of Structure.
Statistical / Quant Indicators:
Z-score
Measures how many standard deviations price is from its mean. Values above +2 or below -2 indicate extreme price movements.
Hurst Exponent
Measures the long-term memory of a time series. Values above 0.5 indicate trending behavior, below 0.5 indicate mean-reverting behavior.
Kalman Filter MA
An adaptive moving average that uses Kalman filtering to reduce noise while maintaining responsiveness to trend changes.
Nadaraya-Watson Kernel Regression
A non-parametric regression method that creates smooth curves through price data. Useful for identifying trends without assuming linear relationships.
Mean Reversion Indicators
Identifies when price deviates significantly from its mean, suggesting potential reversal opportunities. Combines multiple statistical methods.
Correlation Coefficient
Measures the relationship between different assets or timeframes. Values range from -1 (inverse correlation) to +1 (perfect correlation).
Exotic / Advanced Indicators:
Gann Fan
Uses geometric angles to identify potential support and resistance levels. Based on W.D. Gann's trading theories.
Auto Market Profile
Creates a price histogram showing where most trading activity occurred. Identifies Value Area, Point of Control (POC), and volume nodes.
MESA
Maximum Entropy Spectral Analysis - a frequency domain indicator that identifies dominant cycles in price movements.
Jurik Adaptive Moving Average
An advanced moving average that adapts to market conditions using complex mathematical transformations to reduce lag and noise.
Neural Net Predictive Indicators
Uses artificial neural networks to predict future price movements based on historical patterns. Provides probability-based forecasts.
Best Practices
Combine with Comp Quant Indicators: Mix traditional indicators with AI-optimized Comp Quant indicators for stronger signals
Understand Indicator Strengths: Each indicator category works best in specific market conditions
Avoid Overloading: Using too many indicators can create conflicting signals - 2-5 indicators is typically optimal
Test Different Combinations: Experiment with different indicator combinations to find what works for your trading style
Consider Market Regime: Some indicators work better in trending markets, others in ranging markets
Last updated