QuanTAlib provides technical indicators organized into mathematical families. Understanding these families helps choose the right tool for the analytical problem at hand. Selecting an indicator without understanding its category leads to confusion at best, losses at worst.
## Category Reference
| Category | What It Measures | Representative Indicators | When to Reach for It |
| [**Trends (FIR)**](../lib/trends_FIR/_index.md) | Trend direction via finite impulse response filters | SMA, WMA, ALMA, HMA, LSMA | Trend identification with predictable lag and finite memory. Output depends only on a fixed window of past prices. |
| [**Trends (IIR)**](../lib/trends_IIR/_index.md) | Trend direction via infinite impulse response filters | EMA, DEMA, TEMA, JMA, KAMA, MAMA | Trend identification with recursive calculation and theoretically infinite memory. More responsive per unit of smoothness. |
| [**Filters**](../lib/filters/_index.md) | Signal processing filters for noise reduction | Bessel, Butterworth, Super Smoother | Removing noise while preserving trend structure. Designed by engineers, borrowed by traders. |
| [**Oscillators**](../lib/oscillators/_index.md) | Cyclical movement around a baseline | RSI, MACD, AO, UltOsc | Identifying overbought/oversold conditions and potential reversals. Bounded indicators that oscillate. |
| [**Dynamics**](../lib/dynamics/_index.md) | Trend strength and structural changes | ADX, Aroon, SuperTrend, Chop | Determining market regime (trending vs ranging) and measuring trend conviction. |
| [**Momentum**](../lib/momentum/_index.md) | Speed and magnitude of price changes | Momentum, ROC, Velocity | Measuring acceleration or deceleration in price. First derivative territory. |
| [**Volatility**](../lib/volatility/_index.md) | Size and variability of price movements | ATR, StdDev, Bollinger Bands | Position sizing, stop-loss placement, regime identification. How much prices move matters as much as direction. |
| [**Volume**](../lib/volume/_index.md) | Trading activity and price-volume relationships | OBV, VWAP, A/D | Confirming price movements with participation. Volume validates or contradicts price action. |
| [**Channels**](../lib/channels/_index.md) | Price boundaries and range definitions | Donchian, Keltner, Bollinger | Breakout strategies and range-bound trading. Defining "normal" so abnormal becomes visible. |
| [**Statistics**](../lib/statistics/_index.md) | Mathematical relationships between price series | Correlation, Covariance, Beta, Z-Score | Portfolio analysis, pairs trading, statistical arbitrage. Quantitative analysis beyond single instruments. |
| [**Numerics**](../lib/numerics/_index.md) | Mathematical transformations and signal processing | Convolution, Integration, Differentiation | Custom indicator development and advanced signal processing. Building blocks for novel indicators. |
| [**Errors**](../lib/errors/_index.md) | Measurement accuracy and model fit quality | MAE, RMSE, Residuals, R² | Model validation and forecast assessment. Quantifying wrongness before production quantifies losses. |
| [**Forecasts**](../lib/forecasts/_index.md) | Future price prediction and projection | Linear regression extrapolation, adaptive prediction | Projecting price based on historical patterns. Predictions that invite humility. |
**Beginning technical analysis?** Start with **Trends (FIR/IIR)**, **Volatility**, and **Oscillators**. SMA teaches moving average fundamentals. ATR teaches volatility measurement. RSI teaches bounded oscillators. These provide foundation for everything else.
**Building a trading strategy?** Add **Volume** for confirmation, **Channels** for breakouts, **Dynamics** for regime detection. Volume validates price moves. Channels define breakout boundaries. ADX distinguishes trending from ranging markets.
**Quantitative development?****Filters**, **Statistics**, **Numerics**, and **Errors** provide tools for signal processing, model validation, and custom indicator construction. Butterworth filters for noise reduction. Correlation for pairs trading. Error metrics for model selection.
## Implemented Indicators
### Trends (FIR)
Finite Impulse Response filters. Output depends only on a fixed window of inputs. Always stable. Predictable lag characteristics.
| Indicator | Full Name | Notes |
| :-------- | :-------- | :---- |
| [**ALMA**](../lib/trends_FIR/alma/Alma.md) | Arnaud Legoux MA | Gaussian-weighted with offset parameter |
| [**SGMA**](../lib/trends_FIR/sgma/Sgma.md) | Savitzky-Golay MA | Polynomial smoothing |
| [**SINEMA**](../lib/trends_FIR/sinema/Sinema.md) | Sine-Weighted MA | Sinusoidal weight distribution |
| [**SMA**](../lib/trends_FIR/sma/Sma.md) | Simple MA | Equal weights, the baseline |
| [**TRIMA**](../lib/trends_FIR/trima/Trima.md) | Triangular MA | Double-smoothed SMA |
| [**WMA**](../lib/trends_FIR/wma/Wma.md) | Weighted MA | Linear weight decay |
### Trends (IIR)
Infinite Impulse Response filters. Output depends on current input and past outputs. Recursive structure. More responsive but requires stability analysis.
| Indicator | Full Name | Notes |
| :-------- | :-------- | :---- |
| [**DEMA**](../lib/trends_IIR/dema/Dema.md) | Double Exponential MA | EMA of EMA with lag compensation |
| [**DSMA**](../lib/trends_IIR/dsma/Dsma.md) | Deviation-Scaled MA | Volatility-adaptive smoothing |
| [**EMA**](../lib/trends_IIR/ema/Ema.md) | Exponential MA | The fundamental IIR filter |
| [**FRAMA**](../lib/trends_IIR/frama/Frama.md) | Fractal Adaptive MA | Dimension-based adaptation |
| [**HEMA**](../lib/trends_IIR/hema/Hema.md) | Hull Exponential MA | Hull concept with EMA |
| [**STARCHANNEL**](../lib/channels/starchannel/starchannel.md) | Stoller Average Range Channel | SMA with ATR bands; similar to Keltner but uses SMA |
| [**SQRTTRANS**](../lib/numerics/sqrttrans/Sqrttrans.md) | Square Root Transform | √x; variance to standard deviation conversion |
### Errors
Error metrics and loss functions for model evaluation, forecast assessment, and strategy validation. Quantifying wrongness before production quantifies losses.
