Struct MaxDrawdown 

#[repr(C)]
pub struct MaxDrawdown {}

Calculates the Maximum Drawdown for returns.

Maximum Drawdown is the maximum observed loss from a peak to a trough, before a new peak is attained. It is an indicator of downside risk over a specified time period.

Formula: Max((Peak - Trough) / Peak) for all peak-trough sequences

The equity curve compounds returns from a starting value of 1.0, and the result is reported as a negative fraction (e.g. -0.20 is a 20% drawdown).

References

• Bacon, C. R. (2008). Practical Portfolio Performance Measurement and Attribution (2nd ed.). Wiley.

Implementations

impl MaxDrawdown

pub fn new() -> Self

Creates a new MaxDrawdown instance.

Trait Implementations

impl Clone for MaxDrawdown

fn clone(&self) -> MaxDrawdown

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MaxDrawdown

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for MaxDrawdown

fn default() -> MaxDrawdown

Returns the “default value” for a type.

impl PortfolioStatistic for MaxDrawdown

type Item = f64

fn name(&self) -> String

Returns the name of this statistic for display and identification purposes.

fn calculate_from_returns( &self, returns: &BTreeMap<UnixNanos, f64>, ) -> Option<Self::Item>

Calculates the statistic from time-indexed returns data.

fn calculate_from_realized_pnls( &self, _realized_pnls: &[f64], ) -> Option<Self::Item>

Calculates the statistic from realized profit and loss values.

fn calculate_from_positions( &self, _positions: &[Position], ) -> Option<Self::Item>

Calculates the statistic from position data.

fn calculate_from_orders( &self, orders: Vec<Box<dyn Order>>, ) -> Option<Self::Item>

Calculates the statistic from order data.

fn calculate_from_returns_with_benchmark( &self, returns: &Returns, benchmark: &Returns, ) -> Option<Self::Item>

Calculates the statistic from time-indexed strategy returns relative to a benchmark.

fn align_returns(&self, a: &Returns, b: &Returns) -> (Vec<f64>, Vec<f64>)

Aligns two returns series onto a common daily grid.

fn check_valid_returns(&self, returns: &Returns) -> bool

Validates that returns data is not empty.

fn downsample_to_daily_bins(&self, returns: &Returns) -> Returns

Downsamples high-frequency returns to daily bins by geometric compounding.

fn calculate_std(&self, returns: &Returns) -> f64

Calculates the standard deviation of returns with Bessel’s correction.