nautilus_analysis/python/statistics/
expectancy.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::expectancy::Expectancy};
24
25#[pymethods]
26#[pyo3_stub_gen::derive::gen_stub_pymethods]
27impl Expectancy {
28    /// Calculates the expectancy of a trading strategy based on realized PnLs.
29    ///
30    /// Expectancy is defined as: `(Average Win × Win Rate) + (Average Loss × Loss Rate)`
31    /// This metric provides insight into the expected profitability per trade and helps
32    /// evaluate the overall edge of a trading strategy.
33    ///
34    /// A positive expectancy indicates a profitable system over time, while a negative
35    /// expectancy suggests losses.
36    ///
37    /// # References
38    ///
39    /// - Tharp, V. K. (1998). *Trade Your Way to Financial Freedom*. McGraw-Hill.
40    /// - Elder, A. (1993). *Trading for a Living*. John Wiley & Sons.
41    /// - Vince, R. (1992). *The Mathematics of Money Management*. John Wiley & Sons.
42    #[new]
43    fn py_new() -> Self {
44        Self {}
45    }
46
47    fn __repr__(&self) -> String {
48        self.to_string()
49    }
50
51    #[getter]
52    #[pyo3(name = "name")]
53    fn py_name(&self) -> String {
54        self.name()
55    }
56
57    #[pyo3(name = "calculate_from_realized_pnls")]
58    #[expect(clippy::needless_pass_by_value)]
59    fn py_calculate_from_realized_pnls(&mut self, realized_pnls: Vec<f64>) -> Option<f64> {
60        self.calculate_from_realized_pnls(&realized_pnls)
61    }
62
63    #[pyo3(name = "calculate_from_returns")]
64    #[allow(unused_variables)] // Pattern preserved for consistency across statistics
65    fn py_calculate_from_returns(&mut self, _returns: BTreeMap<u64, f64>) -> Option<f64> {
66        None
67    }
68
69    #[pyo3(name = "calculate_from_positions")]
70    fn py_calculate_from_positions(&mut self, _positions: Vec<Position>) -> Option<f64> {
71        None
72    }
73}
nautilus_analysis/python/statistics/expectancy.rs

nautilus_analysis/python/statistics/
expectancy.rs
