QuanTAlib/docs/indicators.md

Indicator Catalog

QuanTAlib provides technical indicators organized into mathematical families. Understanding these families helps choose the right tool for the analytical problem you're actually solving.

Full Category Table

Category	What It Measures	Representative Indicators	When You Need It
Trends	Direction and strength of price movement through smoothing and filtering	SMA, EMA, WMA, HMA, JMA, KAMA, ALMA, DEMA, TEMA, T3	Starting point for most analysis. Simpler variants (SMA, EMA) work for trend identification. Exotic ones (Jurik, Ehlers) trade CPU cycles for reduced lag.
Volatility	Size and variability of price movements	ATR, StdDev, Bollinger Bands, Keltner Channels, Historical Volatility	Position sizing, stop-loss placement, and understanding market regime. ATR tells you how much instruments typically move.
Momentum	Speed and magnitude of price changes	RSI, Stochastic, CCI, Williams %R, MACD, Momentum, ROC	Identifying overbought/oversold conditions and divergences. RSI oscillates between 0-100 by construction.
Volume	Trading activity and price-volume relationships	OBV, VWAP, Volume ROC, A/D, MFI	Confirming price movements with volume participation. VWAP shows where institutional traders executed.
Channels	Price boundaries and range definitions	Donchian Channels, Keltner Channels, Price Channels	Breakout strategies and range-bound trading. Donchian Channels mark highest high and lowest low.
Statistics	Mathematical relationships between price series	Correlation, Covariance, Beta, Z-Score, Linear Regression	Portfolio analysis, pairs trading, and statistical arbitrage. Correlation measures how two instruments move together.
Numerics	Mathematical transformations and signal processing	Convolution, Filters, Integration, Differentiation, Smoothing	Custom indicator development and advanced signal processing. Toolkit for building indicators rather than using them.
Errors	Measurement accuracy and model fit quality	MAE, RMSE, Residuals, R-Squared	Model validation and forecast quality assessment. Critical for anyone building quantitative strategies.
Forecasts	Future price prediction and projection	Linear Regression Forecast, Moving Average Projection	Predictive modeling. Projects price based on historical patterns.
Cycles	Periodic patterns and dominant frequencies	Hilbert Transform, Dominant Cycle, Instantaneous Phase, Sine Wave	Identifying and trading cyclical market behavior. Works beautifully when markets are cyclical.

When to Use Each Category

The categories aren't rigid boundaries—many indicators could fit multiple categories. KAMA is both a trend indicator and uses momentum calculations. Keltner Channels combine trends (moving average centerline) with volatility (ATR bands). The organization helps you understand what analytical problem each indicator solves rather than memorizing which arbitrary category someone assigned it to.

• New to TA? Start with Trends, Volatility, and Momentum. These provide the foundation most traders need.
• Building a Strategy? Use Statistics for pairs trading, Volume for confirmation, and Channels for breakouts.
• Advanced Quant? Numerics, Errors, and Cycles provide the raw mathematical tools for custom signal processing and model validation.

Mathematical Families Explanation

Moving Averages (Trends)

Moving averages are low-pass filters. They remove high-frequency noise (random price fluctuations) to reveal the underlying low-frequency signal (trend).

• SMA: Equal weight to all points. Slowest to react.
• EMA/WMA: More weight to recent data. Faster reaction.
• HMA/JMA/ALMA: Advanced math to reduce lag while maintaining smoothness.

Oscillators (Momentum)

Oscillators measure the velocity of price changes. They are typically bounded (e.g., 0-100) or centered around zero.

• RSI: Ratio of average gains to average losses.
• MACD: Difference between two moving averages (convergence/divergence).

Dispersion (Volatility)

These measure the spread of data points around the mean.

• StdDev: Standard statistical measure of variance.
• ATR: Volatility measure that accounts for gaps (high-low range).

Implemented Indicators

Momentum

• ADX - Average Directional Index
• ADXR - Average Directional Movement Rating
• AMAT - Archer Moving Averages Trends
• AO - Awesome Oscillator
• AROON - Aroon
• AROONOSC - Aroon Oscillator
• CFB - Jurik Composite Fractal Behavior
• DMX - Jurik Directional Movement Index
• RSX - Jurik Relative Strength Quality Index
• VEL - Jurik Velocity

Trends

• AFIRMA - Autoregressive FIR MA
• ALMA - Arnaud Legoux MA
• BESSEL - Bessel Filter
• BILATERAL - Bilateral Filter
• BLMA - Blackman Window MA
• BUTTER - Butterworth Filter
• CONV - Convolution MA
• DEMA - Double Exponential MA
• DWMA - Double Weighted MA
• EMA - Exponential MA
• HMA - Hull MA
• HTIT - Hilbert Transform Instantaneous Trend
• JMA - Jurik MA
• KAMA - Kaufman Adaptive MA
• LSMA - Least Squares MA
• MAMA - MESA Adaptive MA
• MGDI - McGinley Dynamic
• PWMA - Pascal Weighted MA
• RMA - wildeR MA
• SMA - Simple MA
• SSF - Ehlers Super Smooth Filter
• SUPER - SuperTrend
• T3 - Tillson T3 MA
• TEMA - Triple Exponential MA
• TRIMA - Triangular MA
• USF - Ehlers Ultimate Smoother Filter
• VIDYA - Variable Index Dynamic Average
• WMA - Weighted MA

Volatility

• ATR - Average True Range

Volume

• ADL - Accumulation/Distribution Line
• ADOSC - Chaikin A/D Oscillator

Statistics

• CMA - Cumulative Moving Average
• COVARIANCE - Covariance
• LINREG - Linear Regression Curve
• MEDIAN - Rolling Median
• SKEW - Skewness
• STDDEV - Standard Deviation
• SUM - Rolling Sum
• VARIANCE - Population and Sample Variance