nautilus_analysis/statistics/
returns_avg.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::fmt::Display;
17
18use nautilus_model::position::Position;
19
20use crate::{Returns, statistic::PortfolioStatistic};
21
22#[repr(C)]
23#[derive(Debug, Clone)]
24#[cfg_attr(
25    feature = "python",
26    pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis", from_py_object)
27)]
28#[cfg_attr(
29    feature = "python",
30    pyo3_stub_gen::derive::gen_stub_pyclass(module = "nautilus_trader.analysis")
31)]
32pub struct ReturnsAverage {}
33
34impl Display for ReturnsAverage {
35    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
36        write!(f, "Average (Return)")
37    }
38}
39
40impl PortfolioStatistic for ReturnsAverage {
41    type Item = f64;
42
43    fn name(&self) -> String {
44        self.to_string()
45    }
46
47    fn calculate_from_returns(&self, returns: &Returns) -> Option<Self::Item> {
48        if !self.check_valid_returns(returns) {
49            return Some(f64::NAN);
50        }
51
52        let sum: f64 = returns.values().sum();
53        let count = returns.len() as f64;
54
55        Some(sum / count)
56    }
57    fn calculate_from_realized_pnls(&self, _realized_pnls: &[f64]) -> Option<Self::Item> {
58        None
59    }
60
61    fn calculate_from_positions(&self, _positions: &[Position]) -> Option<Self::Item> {
62        None
63    }
64}
65
66#[cfg(test)]
67mod tests {
68    use std::collections::BTreeMap;
69
70    use nautilus_core::{UnixNanos, approx_eq};
71    use rstest::rstest;
72
73    use super::*;
74
75    fn create_returns(values: &[f64]) -> Returns {
76        let mut new_return = BTreeMap::new();
77        for (i, value) in values.iter().enumerate() {
78            new_return.insert(UnixNanos::from(i as u64), *value);
79        }
80        new_return
81    }
82
83    #[rstest]
84    fn test_empty_returns() {
85        let avg = ReturnsAverage {};
86        let returns = create_returns(&[]);
87        let result = avg.calculate_from_returns(&returns);
88        assert!(result.is_some());
89        assert!(result.unwrap().is_nan());
90    }
91
92    #[rstest]
93    fn test_all_zero() {
94        let avg = ReturnsAverage {};
95        let returns = create_returns(&[0.0, 0.0, 0.0]);
96        let result = avg.calculate_from_returns(&returns);
97        assert!(result.is_some());
98        // Average of [0.0, 0.0, 0.0] = 0.0
99        assert!(approx_eq!(f64, result.unwrap(), 0.0, epsilon = 1e-9));
100    }
101
102    #[rstest]
103    fn test_mixed_with_zeros() {
104        let avg = ReturnsAverage {};
105        let returns = create_returns(&[10.0, -20.0, 0.0, 30.0, -40.0]);
106        let result = avg.calculate_from_returns(&returns);
107        assert!(result.is_some());
108        // Average of [10.0, -20.0, 0.0, 30.0, -40.0] = -20 / 5 = -4.0
109        assert!(approx_eq!(f64, result.unwrap(), -4.0, epsilon = 1e-9));
110    }
111
112    #[rstest]
113    fn test_zeros_included_in_average() {
114        let avg = ReturnsAverage {};
115        let returns = create_returns(&[1.0, 0.0, 0.0]);
116        let result = avg.calculate_from_returns(&returns);
117        assert!(result.is_some());
118        // Average of [1.0, 0.0, 0.0] = 1.0 / 3 = 0.333...
119        assert!(approx_eq!(
120            f64,
121            result.unwrap(),
122            0.3333333333333333,
123            epsilon = 1e-9
124        ));
125    }
126
127    #[rstest]
128    fn test_name() {
129        let avg = ReturnsAverage {};
130        assert_eq!(avg.name(), "Average (Return)");
131    }
132}
nautilus_analysis/statistics/returns_avg.rs

nautilus_analysis/statistics/
returns_avg.rs
