use std::fmt::Display;
use nautilus_model::position::Position;
use crate::{Returns, statistic::PortfolioStatistic};
#[repr(C)]
#[derive(Debug, Clone, Default)]
#[cfg_attr(
feature = "python",
pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis", from_py_object)
)]
#[cfg_attr(
feature = "python",
pyo3_stub_gen::derive::gen_stub_pyclass(module = "nautilus_trader.analysis")
)]
pub struct RiskReturnRatio {}
impl RiskReturnRatio {
#[must_use]
pub fn new() -> Self {
Self {}
}
}
impl Display for RiskReturnRatio {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
write!(f, "Risk Return Ratio")
}
}
impl PortfolioStatistic for RiskReturnRatio {
type Item = f64;
fn name(&self) -> String {
self.to_string()
}
fn calculate_from_returns(&self, raw_returns: &Returns) -> Option<Self::Item> {
if !self.check_valid_returns(raw_returns) {
return Some(f64::NAN);
}
let returns = self.downsample_to_daily_bins(raw_returns);
let mean = returns.values().sum::<f64>() / returns.len() as f64;
let std = self.calculate_std(&returns);
if std < f64::EPSILON || std.is_nan() {
Some(f64::NAN)
} else {
Some(mean / std)
}
}
fn calculate_from_realized_pnls(&self, _realized_pnls: &[f64]) -> Option<Self::Item> {
None
}
fn calculate_from_positions(&self, _positions: &[Position]) -> Option<Self::Item> {
None
}
}
#[cfg(test)]
mod tests {
use std::collections::BTreeMap;
use nautilus_core::{UnixNanos, approx_eq};
use rstest::rstest;
use super::*;
fn create_returns(values: &[f64]) -> Returns {
let mut new_return = BTreeMap::new();
let one_day_in_nanos = 86_400_000_000_000;
let start_time = 1_600_000_000_000_000_000;
for (i, &value) in values.iter().enumerate() {
let timestamp = start_time + i as u64 * one_day_in_nanos;
new_return.insert(UnixNanos::from(timestamp), value);
}
new_return
}
#[rstest]
fn test_empty_returns() {
let ratio = RiskReturnRatio::new();
let returns = create_returns(&[]);
let result = ratio.calculate_from_returns(&returns);
assert!(result.is_some());
assert!(result.unwrap().is_nan());
}
#[rstest]
fn test_zero_std_dev() {
let ratio = RiskReturnRatio::new();
let returns = create_returns(&[0.05; 10]);
let result = ratio.calculate_from_returns(&returns);
assert!(result.is_some());
assert!(result.unwrap().is_nan());
}
#[rstest]
fn test_valid_risk_return_ratio() {
let ratio = RiskReturnRatio::new();
let returns = create_returns(&[0.1, -0.05, 0.2, -0.1, 0.15]);
let result = ratio.calculate_from_returns(&returns);
assert!(result.is_some());
assert!(approx_eq!(
f64,
result.unwrap(),
0.46360044557175345,
epsilon = 1e-9
));
}
#[rstest]
fn test_name() {
let ratio = RiskReturnRatio::new();
assert_eq!(ratio.name(), "Risk Return Ratio");
}
}