Struct Expectancy 

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

Calculates the expectancy of a trading strategy based on realized PnLs.

Expectancy is defined as: (Average Win × Win Rate) + (Average Loss × Loss Rate) This metric provides insight into the expected profitability per trade and helps evaluate the overall edge of a trading strategy.

A positive expectancy indicates a profitable system over time, while a negative expectancy suggests losses.

References

• Tharp, V. K. (1998). Trade Your Way to Financial Freedom. McGraw-Hill.
• Elder, A. (1993). Trading for a Living. John Wiley & Sons.
• Vince, R. (1992). The Mathematics of Money Management. John Wiley & Sons.

Trait Implementations

impl Clone for Expectancy

fn clone(&self) -> Expectancy

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Expectancy

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

Formats the value using the given formatter.

impl Display for Expectancy

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

Formats the value using the given formatter.

impl PortfolioStatistic for Expectancy

type Item = f64

fn name(&self) -> String

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

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

Calculates the statistic from realized profit and loss values.

fn calculate_from_returns(&self, _returns: &Returns) -> Option<Self::Item>

Calculates the statistic from time-indexed returns data.

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.