nautilus_analysis/python/statistics/
sortino_ratio.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
18use pyo3::prelude::*;
19
20use super::transform_returns;
21use crate::{statistic::PortfolioStatistic, statistics::sortino_ratio::SortinoRatio};
22
23#[pymethods]
24#[pyo3_stub_gen::derive::gen_stub_pymethods]
25impl SortinoRatio {
26    /// Calculates the Sortino ratio for portfolio returns.
27    ///
28    /// The Sortino ratio is a variation of the Sharpe ratio that only penalizes downside
29    /// volatility, making it more appropriate for strategies with asymmetric return distributions.
30    ///
31    /// Formula: `Mean Return / Downside Deviation * sqrt(period)`
32    ///
33    /// Where downside deviation is calculated as:
34    /// `sqrt(sum(negative_returns^2) / total_observations)`
35    ///
36    /// Note: Uses total observations count (not just negative returns) as per Sortino's methodology.
37    ///
38    /// # References
39    ///
40    /// - Sortino, F. A., & van der Meer, R. (1991). "Downside Risk". *Journal of Portfolio Management*, 17(4), 27-31.
41    /// - Sortino, F. A., & Price, L. N. (1994). "Performance Measurement in a Downside Risk Framework".
42    ///   *Journal of Investing*, 3(3), 59-64.
43    #[new]
44    #[pyo3(signature = (period=None))]
45    fn py_new(period: Option<usize>) -> Self {
46        Self::new(period)
47    }
48
49    fn __repr__(&self) -> String {
50        self.to_string()
51    }
52
53    #[getter]
54    #[pyo3(name = "name")]
55    fn py_name(&self) -> String {
56        self.name()
57    }
58
59    #[pyo3(name = "calculate_from_returns")]
60    #[expect(clippy::needless_pass_by_value)]
61    fn py_calculate_from_returns(&mut self, raw_returns: BTreeMap<u64, f64>) -> Option<f64> {
62        self.calculate_from_returns(&transform_returns(&raw_returns))
63    }
64
65    #[pyo3(name = "calculate_from_realized_pnls")]
66    fn py_calculate_from_realized_pnls(&mut self, _realized_pnls: Vec<f64>) -> Option<f64> {
67        None
68    }
69
70    #[pyo3(name = "calculate_from_positions")]
71    fn py_calculate_from_positions(&mut self, _positions: Vec<Py<PyAny>>) -> Option<f64> {
72        None
73    }
74}
nautilus_analysis/python/statistics/sortino_ratio.rs

nautilus_analysis/python/statistics/
sortino_ratio.rs
