Exponential Moving Average (EMA)

Summary

Exponential moving average that weights recent prices more heavily via a recursive smoothing factor. A core building block seeding or composing many other indicators. Reacts faster than SMA; price above/below EMA suggests up/down trend.

Chart

Reference data (CSV) · Chart (SVG)

Chart metadata i

Outputs

outReal: line

Formula

k = 2 / (period + 1); EMA_t = (price_t - EMA_{t-1}) * k + EMA_{t-1}. Seed: EMA = SMA of first period bars.

Notes

A period of 1 performs no smoothing: the output is a copy of the input. Allowed since 0.6.5 (issues #48/#59).

Inputs

inReal — price/data series to smooth

Outputs

outReal — the exponential moving average

Parameters

Parameter	Type	Default	Accepted values	Description
`optInTimePeriod`	integer	30	1–100000	Number of bars in the average; sets smoothing k = 2/(period+1)

Properties

Numerical Stability: Initial Unstable Period


✅ Overlap Input i
☐ Independent Y-Axis
☐ Candlestick
☐ Display Shift


☐ Can Output NaN or ±Inf
✅ Identity at Period 1 i
☐ Uses Transcendental
☐ Input Must Be Positive

Example

#include <stdio.h>
#include <ta_libc.h>

int n = 252;
double series[252]; /* your data, oldest first */
double out[252];
int outBegIdx, outNBElement;

TA_Initialize();
TA_EMA( 0, n - 1, series, 30, &outBegIdx, &outNBElement, out );
printf( "%d values from bar %d; last out = %f\n", outNBElement, outBegIdx, out[outNBElement - 1] );

Rust

use ta_lib::Core;

let series = vec![0.0; 252]; // your data, oldest first
let mut out = vec![0.0; 252];

let core = Core::new();
let range = core.ema(0, series.len() - 1, &series, 30, &mut out)?;
println!("{} values from bar {}; last out = {}", range.count, range.beg_idx, out[range.count - 1]);

Java

import io.github.talib.Core;
import io.github.talib.OutRange;

double[] series = new double[252]; // your data, oldest first
double[] out = new double[252];

Core core = Core.DEFAULT;
OutRange r = core.ema(0, series.length - 1, series, 30, out);
System.out.println(r.count() + " values from bar " + r.begIdx() + "; last out = " + out[r.count() - 1]);

using System;
using TALib;

var series = new double[252]; // your data, oldest first
var outReal = new double[252];

var core = Core.Default;
OutRange r = core.Ema(0, series.Length - 1, series, 30, outReal);
Console.WriteLine($"{r.Count} values from bar {r.BegIdx}; last outReal = {outReal[r.Count - 1]}");

TypeScript

import { ema } from 'ta-lib';

const series = new Float64Array(252); // your data, oldest first

const { begIdx, values } = ema(series, { timePeriod: 30 });
console.log(values.length + ' values from bar ' + begIdx + '; last values = ' + values[values.length - 1]);

Implementation

Added in 0.4.0.

TA-Lib Definition: ema.c · ema.yaml

Native	File
C	`ta_EMA.c`
Rust	`ema.rs`
Java	`Core_EMA.java`
C#	`Core_EMA.cs`
TypeScript	`ema.ts`

Python: talib.EMA, see ta-lib-python.

TA-Lib is also available for R and more using a wrapper.

Aliases

Exponential Moving Average, Exponentially Weighted Moving Average, EWMA