Struct ta::indicators::ExponentialMovingAverage

pub struct ExponentialMovingAverage { /* fields omitted */ }

An exponential moving average (EMA), also known as an exponentially weighted moving average (EWMA), is a type of infinite impulse response filter that applies weighting factors which decrease exponentially. The weighting for each older datum decreases exponentially, never reaching zero.

Formula

Where:

• EMA_t - is the value of the EMA at any time period t.
• EMA_t-1 - is the value of the EMA at the previous period t-1.
• p_t - is the input value at a time period t.
• α - is the coefficient that represents the degree of weighting decrease, a constant smoothing factor between 0 and 1.

α is calculated with the following formula:

Where:

• n - number of periods

Parameters

• n - number of periods (integer greater than 0)

Example

use ta::indicators::ExponentialMovingAverage;
use ta::Next;

let mut ema = ExponentialMovingAverage::new(3).unwrap();
assert_eq!(ema.next(2.0), 2.0);
assert_eq!(ema.next(5.0), 3.5);
assert_eq!(ema.next(1.0), 2.25);
assert_eq!(ema.next(6.25), 4.25);

Links

• Exponential moving average, Wikipedia

Methods

impl ExponentialMovingAverage

fn new(n: u32) -> Result<Self>

Trait Implementations

impl Debug for ExponentialMovingAverage

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Clone for ExponentialMovingAverage

fn clone(&self) -> ExponentialMovingAverage

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Next<f64> for ExponentialMovingAverage

type Output = f64

fn next(&mut self, input: f64) -> Self::Output

impl<T: Close> Next<T> for ExponentialMovingAverage

type Output = f64

fn next(&mut self, input: T) -> Self::Output

impl Reset for ExponentialMovingAverage

fn reset(&mut self)

impl Default for ExponentialMovingAverage

fn default() -> Self

Returns the "default value" for a type.