Moving averages

Overview

All moving average functions accept a source argument - either a ctx.* accessor, an input.source() result, or any (offset?) => number | null function. They return a scalar at the current bar.

Functions

`ta.sma(source, length)` - Simple moving average

Arithmetic mean over length bars.

onBar(() => {
  plot("SMA20", ta.sma(ctx.close, 20));
});

`ta.ema(source, length)` - Exponential moving average

Exponentially weighted, with factor α = 2 / (length + 1). Faster to react than SMA.

onBar(() => {
  plot("EMA9",  ta.ema(ctx.close, 9));
  plot("EMA21", ta.ema(ctx.close, 21));
});

`ta.rma(source, length)` - Wilder smoothing

EMA with α = 1 / length. Also known as Wilder’s Moving Average (RMA). Used internally by ta.rsi and ta.atr.

onBar(() => {
  const gain = math.max(ctx.close() - ctx.close(1), 0);
  plot("Smoothed gain", ta.rma(() => gain, 14));
});

`ta.wma(source, length)` - Weighted moving average

Linearly weighted - most recent bar has the highest weight.

onBar(() => {
  plot("WMA14", ta.wma(ctx.close, 14));
});

`ta.hma(source, length)` - Hull moving average

Reduces lag by combining WMAs. HMA = WMA(2*WMA(n/2) - WMA(n), sqrt(n)).

onBar(() => {
  plot("HMA20", ta.hma(ctx.close, 20));
});

`ta.vwma(source, volume, length)` - Volume-weighted moving average

Weights each bar by its volume.

onBar(() => {
  plot("VWMA20", ta.vwma(ctx.close, ctx.volume, 20));
});

`ta.alma(source, length, offset?, sigma?)` - Arnaud Legoux moving average

Gaussian-weighted. offset controls the phase (default 0.85), sigma controls smoothing (default 6).

onBar(() => {
  plot("ALMA", ta.alma(ctx.close, 20, 0.85, 6));
});

`ta.swma(source)` - Symmetrically weighted moving average

Fixed-length 4-bar average with weights [1, 2, 2, 1] / 6.

onBar(() => {
  plot("SWMA", ta.swma(ctx.close));
});

`ta.linreg(source, length)` - Linear regression value

Returns the current value on the linear regression line fitted to the last length bars.

onBar(() => {
  plot("LinReg20", ta.linreg(ctx.close, 20));
});

Ribbon example

const lengths = [8, 13, 21, 34, 55];

plot("EMA8",  null, { color: "#22c55eFF" });
plot("EMA13", null, { color: "#84cc16FF" });
plot("EMA21", null, { color: "#eab308FF" });
plot("EMA34", null, { color: "#f97316FF" });
plot("EMA55", null, { color: "#ef4444FF" });

onBar(() => {
  plot("EMA8",  ta.ema(ctx.close, 8));
  plot("EMA13", ta.ema(ctx.close, 13));
  plot("EMA21", ta.ema(ctx.close, 21));
  plot("EMA34", ta.ema(ctx.close, 34));
  plot("EMA55", ta.ema(ctx.close, 55));
});

Oscillators

RSI, MACD, Stochastic and more.

Crossovers

Detect when two MAs cross.

Bar context

Source function shape reference.

Getting Started

Core Concepts

Plotting

Drawing Entities

Technical Analysis

Utility Namespaces

Examples

Reference

Moving averages

Overview

Functions

`ta.sma(source, length)` - Simple moving average

`ta.ema(source, length)` - Exponential moving average

`ta.rma(source, length)` - Wilder smoothing

`ta.wma(source, length)` - Weighted moving average

`ta.hma(source, length)` - Hull moving average

`ta.vwma(source, volume, length)` - Volume-weighted moving average

`ta.alma(source, length, offset?, sigma?)` - Arnaud Legoux moving average

`ta.swma(source)` - Symmetrically weighted moving average

`ta.linreg(source, length)` - Linear regression value

Ribbon example

Oscillators

Crossovers

Bar context

​Overview

​Functions

​ta.sma(source, length) - Simple moving average

​ta.ema(source, length) - Exponential moving average

​ta.rma(source, length) - Wilder smoothing

​ta.wma(source, length) - Weighted moving average

​ta.hma(source, length) - Hull moving average

​ta.vwma(source, volume, length) - Volume-weighted moving average

​ta.alma(source, length, offset?, sigma?) - Arnaud Legoux moving average

​ta.swma(source) - Symmetrically weighted moving average

​ta.linreg(source, length) - Linear regression value

​Ribbon example

​Related pages

Oscillators

Crossovers

Bar context

Overview

Functions

`ta.sma(source, length)` - Simple moving average

`ta.ema(source, length)` - Exponential moving average

`ta.rma(source, length)` - Wilder smoothing

`ta.wma(source, length)` - Weighted moving average

`ta.hma(source, length)` - Hull moving average

`ta.vwma(source, volume, length)` - Volume-weighted moving average

`ta.alma(source, length, offset?, sigma?)` - Arnaud Legoux moving average

`ta.swma(source)` - Symmetrically weighted moving average

`ta.linreg(source, length)` - Linear regression value

Ribbon example

Related pages