nautilus_analysis/statistics/
win_rate.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2025 Nautech Systems Pty Ltd. All rights reserved.
3//  https://nautechsystems.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::statistic::PortfolioStatistic;
17
18#[repr(C)]
19#[derive(Debug)]
20#[cfg_attr(
21    feature = "python",
22    pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis")
23)]
24pub struct WinRate {}
25
26impl PortfolioStatistic for WinRate {
27    type Item = f64;
28
29    fn name(&self) -> String {
30        stringify!(WinRate).to_string()
31    }
32
33    fn calculate_from_realized_pnls(&self, realized_pnls: &[f64]) -> Option<Self::Item> {
34        if realized_pnls.is_empty() {
35            return Some(0.0);
36        }
37
38        let (winners, losers): (Vec<f64>, Vec<f64>) =
39            realized_pnls.iter().partition(|&&pnl| pnl > 0.0);
40
41        let total_trades = winners.len() + losers.len();
42        Some(winners.len() as f64 / total_trades.max(1) as f64)
43    }
44}
45
46#[cfg(test)]
47mod tests {
48    use super::*;
49
50    #[test]
51    fn test_empty_pnls() {
52        let win_rate = WinRate {};
53        let result = win_rate.calculate_from_realized_pnls(&[]);
54        assert!(result.is_some());
55        assert_eq!(result.unwrap(), 0.0);
56    }
57
58    #[test]
59    fn test_all_winning_trades() {
60        let win_rate = WinRate {};
61        let realized_pnls = vec![100.0, 50.0, 200.0];
62        let result = win_rate.calculate_from_realized_pnls(&realized_pnls);
63        assert!(result.is_some());
64        assert_eq!(result.unwrap(), 1.0);
65    }
66
67    #[test]
68    fn test_all_losing_trades() {
69        let win_rate = WinRate {};
70        let realized_pnls = vec![-100.0, -50.0, -200.0];
71        let result = win_rate.calculate_from_realized_pnls(&realized_pnls);
72        assert!(result.is_some());
73        assert_eq!(result.unwrap(), 0.0);
74    }
75
76    #[test]
77    fn test_mixed_trades() {
78        let win_rate = WinRate {};
79        let realized_pnls = vec![100.0, -50.0, 200.0, -100.0];
80        let result = win_rate.calculate_from_realized_pnls(&realized_pnls);
81        assert!(result.is_some());
82        assert_eq!(result.unwrap(), 0.5);
83    }
84
85    #[test]
86    fn test_name() {
87        let win_rate = WinRate {};
88        assert_eq!(win_rate.name(), "WinRate");
89    }
90}
nautilus_analysis/statistics/win_rate.rs

nautilus_analysis/statistics/
win_rate.rs
