nautilus_analysis/statistics/
sharpe_ratio.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2025 Posei Systems Pty Ltd. All rights reserved.
3//  https://poseitrader.io
4//
5//  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
6//  You may not use this file except in compliance with the License.
7//  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
8//
9//  Unless required by applicable law or agreed to in writing, software
10//  distributed under the License is distributed on an "AS IS" BASIS,
11//  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12//  See the License for the specific language governing permissions and
13//  limitations under the License.
14// -------------------------------------------------------------------------------------------------
15
16use crate::{Returns, statistic::PortfolioStatistic};
17
18#[repr(C)]
19#[derive(Debug)]
20#[cfg_attr(
21    feature = "python",
22    pyo3::pyclass(module = "posei_trader.core.nautilus_pyo3.analysis")
23)]
24pub struct SharpeRatio {
25    period: usize,
26}
27
28impl SharpeRatio {
29    /// Creates a new [`SharpeRatio`] instance.
30    #[must_use]
31    pub fn new(period: Option<usize>) -> Self {
32        Self {
33            period: period.unwrap_or(252),
34        }
35    }
36}
37
38impl PortfolioStatistic for SharpeRatio {
39    type Item = f64;
40
41    fn name(&self) -> String {
42        stringify!(SharpeRatio).to_string()
43    }
44
45    fn calculate_from_returns(&self, raw_returns: &Returns) -> Option<Self::Item> {
46        if !self.check_valid_returns(raw_returns) {
47            return Some(f64::NAN);
48        }
49
50        let returns = self.downsample_to_daily_bins(raw_returns);
51        let mean = returns.values().sum::<f64>() / returns.len() as f64;
52        let std = self.calculate_std(&returns);
53
54        if std < f64::EPSILON {
55            return Some(f64::NAN);
56        }
57
58        let annualized_ratio = (mean / std) * (self.period as f64).sqrt();
59
60        Some(annualized_ratio)
61    }
62}
63
64#[cfg(test)]
65mod tests {
66    use std::collections::BTreeMap;
67
68    use nautilus_core::UnixNanos;
69    use rstest::rstest;
70
71    use super::*;
72
73    fn create_returns(values: Vec<f64>) -> BTreeMap<UnixNanos, f64> {
74        let mut new_return = BTreeMap::new();
75        let one_day_in_nanos = 86_400_000_000_000;
76        let start_time = 1_600_000_000_000_000_000;
77
78        for (i, &value) in values.iter().enumerate() {
79            let timestamp = start_time + i as u64 * one_day_in_nanos;
80            new_return.insert(UnixNanos::from(timestamp), value);
81        }
82
83        new_return
84    }
85
86    #[rstest]
87    fn test_empty_returns() {
88        let ratio = SharpeRatio::new(None);
89        let returns = create_returns(vec![]);
90        let result = ratio.calculate_from_returns(&returns);
91        assert!(result.is_some());
92        assert!(result.unwrap().is_nan());
93    }
94
95    #[rstest]
96    fn test_zero_std_dev() {
97        let ratio = SharpeRatio::new(None);
98        let returns = create_returns(vec![0.01; 10]);
99        let result = ratio.calculate_from_returns(&returns);
100        assert!(result.is_some());
101        assert!(result.unwrap().is_nan());
102    }
103
104    #[rstest]
105    fn test_valid_sharpe_ratio() {
106        let ratio = SharpeRatio::new(Some(252));
107        let returns = create_returns(vec![0.01, -0.02, 0.015, -0.005, 0.025]);
108        let result = ratio.calculate_from_returns(&returns);
109        assert!(result.is_some());
110        assert_eq!(result.unwrap(), 4.48998886412873);
111    }
112
113    #[rstest]
114    fn test_name() {
115        let ratio = SharpeRatio::new(None);
116        assert_eq!(ratio.name(), "SharpeRatio");
117    }
118}
nautilus_analysis/statistics/sharpe_ratio.rs

nautilus_analysis/statistics/
sharpe_ratio.rs
