Struct ux_indicators::indicators::MovingAverageConvergenceDivergence[][src]

pub struct MovingAverageConvergenceDivergence { /* fields omitted */ }

Moving average converge divergence (MACD).

The MACD indicator (or “oscillator”) is a collection of three time series calculated from historical price data, most often the closing price. These three series are:

  • The MACD series proper
  • The “signal” or “average” series
  • The “divergence” series which is the difference between the two

The MACD series is the difference between a “fast” (short period) exponential moving average (EMA), and a “slow” (longer period) EMA of the price series. The average series is an EMA of the MACD series itself.

Formula

Parameters

  • fast_length - length for the fast EMA. Default is 12.
  • slow_length - length for the slow EMA. Default is 26.
  • signal_length - length for the signal EMA. Default is 9.

Example

use core::indicators::MovingAverageConvergenceDivergence as Macd;
use core::Next;

let mut macd = Macd::new(3, 6, 4).unwrap();

assert_eq!(round(macd.next(2.0)), (0.0, 0.0, 0.0));
assert_eq!(round(macd.next(3.0)), (0.21, 0.09, 0.13));
assert_eq!(round(macd.next(4.2)), (0.52, 0.26, 0.26));
assert_eq!(round(macd.next(7.0)), (1.15, 0.62, 0.54));
assert_eq!(round(macd.next(6.7)), (1.15, 0.83, 0.32));
assert_eq!(round(macd.next(6.5)), (0.94, 0.87, 0.07));

fn round(nums: (f64, f64, f64)) -> (f64, f64, f64) {
    let n0 = (nums.0 * 100.0).round() / 100.0;
    let n1 = (nums.1 * 100.0).round() / 100.0;
    let n2 = (nums.2 * 100.0).round() / 100.0;
    (n0, n1, n2)
}

Implementations

impl MovingAverageConvergenceDivergence[src]

pub fn new(
    fast_length: u32,
    slow_length: u32,
    signal_length: u32
) -> Result<Self>
[src]

Trait Implementations

impl Clone for MovingAverageConvergenceDivergence[src]

impl Debug for MovingAverageConvergenceDivergence[src]

impl Default for MovingAverageConvergenceDivergence[src]

impl Display for MovingAverageConvergenceDivergence[src]

impl<'a, T: Close> Next<&'a T> for MovingAverageConvergenceDivergence[src]

type Output = (f64, f64, f64)

impl Next<f64> for MovingAverageConvergenceDivergence[src]

type Output = (f64, f64, f64)

impl Reset for MovingAverageConvergenceDivergence[src]

Auto Trait Implementations

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized
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impl<T> Borrow<T> for T where
    T: ?Sized
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impl<T> BorrowMut<T> for T where
    T: ?Sized
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impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, 
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impl<T> ToOwned for T where
    T: Clone
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type Owned = T

The resulting type after obtaining ownership.

impl<T> ToString for T where
    T: Display + ?Sized
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impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
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type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.