Struct ta::indicators::MovingAverageConvergenceDivergence [−][src]
pub struct MovingAverageConvergenceDivergence { /* fields omitted */ }
Expand description
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_period - period for the fast EMA. Default is 12.
- slow_period - period for the slow EMA. Default is 26.
- signal_period - period for the signal EMA. Default is 9.
Example
use ta::indicators::MovingAverageConvergenceDivergence as Macd; use ta::Next; let mut macd = Macd::new(3, 6, 4).unwrap(); assert_eq!(round(macd.next(2.0).into()), (0.0, 0.0, 0.0)); assert_eq!(round(macd.next(3.0).into()), (0.21, 0.09, 0.13)); assert_eq!(round(macd.next(4.2).into()), (0.52, 0.26, 0.26)); assert_eq!(round(macd.next(7.0).into()), (1.15, 0.62, 0.54)); assert_eq!(round(macd.next(6.7).into()), (1.15, 0.83, 0.32)); assert_eq!(round(macd.next(6.5).into()), (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
Trait Implementations
Auto Trait Implementations
impl Send for MovingAverageConvergenceDivergence
impl Sync for MovingAverageConvergenceDivergence
impl Unpin for MovingAverageConvergenceDivergence
Blanket Implementations
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