nautilus_analysis/
statistic.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2025 Posei Systems Pty Ltd. All rights reserved.
3//  https://poseitrader.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, fmt::Debug};
17
18use nautilus_model::{orders::Order, position::Position};
19
20use crate::Returns;
21
22const IMPL_ERR: &str = "is not implemented for";
23
24/// Trait for portfolio performance statistics that can be calculated from different data sources.
25///
26/// This trait provides a flexible framework for implementing various financial performance
27/// metrics that can operate on returns, realized PnLs, orders, or positions data.
28/// Each statistic implementation should override the relevant calculation methods.
29#[allow(unused_variables)]
30pub trait PortfolioStatistic: Debug {
31    type Item;
32
33    /// Returns the name of this statistic for display and identification purposes.
34    fn name(&self) -> String;
35
36    /// Calculates the statistic from time-indexed returns data.
37    ///
38    /// # Panics
39    ///
40    /// Panics if this method is not implemented for the specific statistic.
41    fn calculate_from_returns(&self, returns: &Returns) -> Option<Self::Item> {
42        panic!("`calculate_from_returns` {IMPL_ERR} `{}`", self.name());
43    }
44
45    /// Calculates the statistic from realized profit and loss values.
46    ///
47    /// # Panics
48    ///
49    /// Panics if this method is not implemented for the specific statistic.
50    fn calculate_from_realized_pnls(&self, realized_pnls: &[f64]) -> Option<Self::Item> {
51        panic!(
52            "`calculate_from_realized_pnls` {IMPL_ERR} `{}`",
53            self.name()
54        );
55    }
56
57    /// Calculates the statistic from order data.
58    ///
59    /// # Panics
60    ///
61    /// Panics if this method is not implemented for the specific statistic.
62    #[allow(dead_code)]
63    fn calculate_from_orders(&self, orders: Vec<Box<dyn Order>>) -> Option<Self::Item> {
64        panic!("`calculate_from_orders` {IMPL_ERR} `{}`", self.name());
65    }
66
67    /// Calculates the statistic from position data.
68    ///
69    /// # Panics
70    ///
71    /// Panics if this method is not implemented for the specific statistic.
72    fn calculate_from_positions(&self, positions: &[Position]) -> Option<Self::Item> {
73        panic!("`calculate_from_positions` {IMPL_ERR} `{}`", self.name());
74    }
75
76    /// Validates that returns data is not empty.
77    fn check_valid_returns(&self, returns: &Returns) -> bool {
78        !returns.is_empty()
79    }
80
81    /// Downsamples high-frequency returns to daily bins for daily statistics calculation.
82    fn downsample_to_daily_bins(&self, returns: &Returns) -> Returns {
83        let nanos_per_day = 86_400_000_000_000; // Number of nanoseconds in a day
84        let mut daily_bins = BTreeMap::new();
85
86        for (&timestamp, &value) in returns {
87            // Calculate the start of the day in nanoseconds for the given timestamp
88            let day_start = timestamp - (timestamp.as_u64() % nanos_per_day);
89
90            // Sum returns for each day
91            *daily_bins.entry(day_start).or_insert(0.0) += value;
92        }
93
94        daily_bins
95    }
96
97    /// Calculates the standard deviation of returns with Bessel's correction.
98    fn calculate_std(&self, returns: &Returns) -> f64 {
99        let n = returns.len() as f64;
100        if n < 2.0 {
101            return f64::NAN;
102        }
103
104        let mean = returns.values().sum::<f64>() / n;
105
106        let variance = returns.values().map(|x| (x - mean).powi(2)).sum::<f64>() / (n - 1.0);
107
108        variance.sqrt()
109    }
110}
nautilus_analysis/statistic.rs

nautilus_analysis/
statistic.rs
