nautilus_analysis/python/statistics/
win_rate.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2026 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 std::collections::BTreeMap;
17
18#[allow(unused_imports)] // Used in template pattern for returns conversion
19use nautilus_core::UnixNanos;
20use nautilus_model::position::Position;
21use pyo3::prelude::*;
22
23use crate::{statistic::PortfolioStatistic, statistics::win_rate::WinRate};
24
25#[pymethods]
26#[pyo3_stub_gen::derive::gen_stub_pymethods]
27impl WinRate {
28    /// Calculates the win rate of a trading strategy based on realized PnLs.
29    ///
30    /// Win rate is the percentage of profitable trades out of total trades:
31    /// `Count(Trades with PnL > 0) / Total Trades`
32    ///
33    /// Returns a value between 0.0 and 1.0, where 1.0 represents 100% winning trades.
34    ///
35    /// Note: While a high win rate is desirable, it should be considered alongside
36    /// average win/loss sizes and profit factor for complete system evaluation.
37    ///
38    /// # References
39    ///
40    /// - Standard trading performance metric across the industry
41    /// - Tharp, V. K. (1998). *Trade Your Way to Financial Freedom*. McGraw-Hill.
42    /// - Kaufman, P. J. (2013). *Trading Systems and Methods* (5th ed.). Wiley.
43    #[new]
44    fn py_new() -> Self {
45        Self {}
46    }
47
48    fn __repr__(&self) -> String {
49        self.to_string()
50    }
51
52    #[getter]
53    #[pyo3(name = "name")]
54    fn py_name(&self) -> String {
55        self.name()
56    }
57
58    #[pyo3(name = "calculate_from_realized_pnls")]
59    #[expect(clippy::needless_pass_by_value)]
60    fn py_calculate_from_realized_pnls(&mut self, realized_pnls: Vec<f64>) -> Option<f64> {
61        self.calculate_from_realized_pnls(&realized_pnls)
62    }
63
64    #[pyo3(name = "calculate_from_returns")]
65    #[allow(unused_variables)] // Pattern preserved for consistency across statistics
66    fn py_calculate_from_returns(&mut self, _returns: BTreeMap<u64, f64>) -> Option<f64> {
67        None
68    }
69
70    #[pyo3(name = "calculate_from_positions")]
71    fn py_calculate_from_positions(&mut self, _positions: Vec<Position>) -> Option<f64> {
72        None
73    }
74}
nautilus_analysis/python/statistics/win_rate.rs

nautilus_analysis/python/statistics/
win_rate.rs
