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Co-authored-by: jose-donato <zmcdonato@gmail.com>
Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com>
Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
2023-10-30 21:01:29 +00:00

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title, description, keywords
title description keywords
ema A guide to understanding and using the Exponential Moving Average, a fundamental tool in technical analysis with a focus on its application.
Exponential Moving Average
technical analysis
moving average
EMA
cumulative calculation
data responsiveness
EMA use
EMA parameters

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

The Exponential Moving Average is a staple of technical analysis and is used in countless technical indicators. In a Simple Moving Average, each value in the time period carries equal weight, and values outside of the time period are not included in the average. However, the Exponential Moving Average is a cumulative calculation, including all data. Past values have a diminishing contribution to the average, while more recent values have a greater contribution. This method allows the moving average to be more responsive to changes in the data.

Usage

ema [-l N_LENGTH] [-o N_OFFSET]

Parameters

Name Description Default Optional Choices
n_length Window lengths. Multiple values indicated as comma separated values. 20, 50 True None
n_offset offset 0 True None

ema