nautilus_analysis/statistics/
calmar_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
16//! Calmar Ratio statistic.
17
18use std::collections::BTreeMap;
19
20use nautilus_core::UnixNanos;
21use nautilus_model::position::Position;
22
23use crate::{
24    statistic::PortfolioStatistic,
25    statistics::{cagr::CAGR, max_drawdown::MaxDrawdown},
26};
27
28/// Calculates the Calmar Ratio for returns.
29///
30/// The Calmar Ratio is a function of the fund's average compounded annual rate
31/// of return versus its maximum drawdown. The higher the Calmar ratio, the better
32/// it performed on a risk-adjusted basis during the given time frame.
33///
34/// Formula: Calmar Ratio = CAGR / |Max Drawdown|
35///
36/// Reference: Young, T. W. (1991). "Calmar Ratio: A Smoother Tool". Futures, 20(1).
37#[repr(C)]
38#[derive(Debug, Clone)]
39#[cfg_attr(
40    feature = "python",
41    pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis", from_py_object)
42)]
43#[cfg_attr(
44    feature = "python",
45    pyo3_stub_gen::derive::gen_stub_pyclass(module = "nautilus_trader.analysis")
46)]
47pub struct CalmarRatio {
48    /// The number of periods per year for CAGR calculation (e.g., 252 for trading days).
49    pub period: usize,
50}
51
52impl CalmarRatio {
53    /// Creates a new [`CalmarRatio`] instance.
54    #[must_use]
55    pub fn new(period: Option<usize>) -> Self {
56        Self {
57            period: period.unwrap_or(252),
58        }
59    }
60}
61
62impl PortfolioStatistic for CalmarRatio {
63    type Item = f64;
64
65    fn name(&self) -> String {
66        format!("Calmar Ratio ({} days)", self.period)
67    }
68
69    fn calculate_from_returns(&self, returns: &BTreeMap<UnixNanos, f64>) -> Option<Self::Item> {
70        if returns.is_empty() {
71            return Some(f64::NAN);
72        }
73
74        // Calculate CAGR
75        let cagr_stat = CAGR::new(Some(self.period));
76        let cagr = cagr_stat.calculate_from_returns(returns)?;
77
78        // Calculate Max Drawdown
79        let max_dd_stat = MaxDrawdown::new();
80        let max_dd = max_dd_stat.calculate_from_returns(returns)?;
81
82        // Calmar = CAGR / |Max Drawdown|
83        // Max Drawdown is already negative, so we use abs
84        // When no drawdown exists, the ratio is undefined
85        if max_dd.abs() < f64::EPSILON {
86            return Some(f64::NAN);
87        }
88
89        let calmar = cagr / max_dd.abs();
90
91        if calmar.is_finite() {
92            Some(calmar)
93        } else {
94            Some(f64::NAN)
95        }
96    }
97    fn calculate_from_realized_pnls(&self, _realized_pnls: &[f64]) -> Option<Self::Item> {
98        None
99    }
100
101    fn calculate_from_positions(&self, _positions: &[Position]) -> Option<Self::Item> {
102        None
103    }
104}
105
106#[cfg(test)]
107mod tests {
108    use rstest::rstest;
109
110    use super::*;
111
112    fn create_returns(values: &[f64]) -> BTreeMap<UnixNanos, f64> {
113        let mut returns = BTreeMap::new();
114        let nanos_per_day = 86_400_000_000_000;
115        let start_time = 1_600_000_000_000_000_000;
116
117        for (i, &value) in values.iter().enumerate() {
118            let timestamp = start_time + i as u64 * nanos_per_day;
119            returns.insert(UnixNanos::from(timestamp), value);
120        }
121
122        returns
123    }
124
125    #[rstest]
126    fn test_name() {
127        let ratio = CalmarRatio::new(Some(252));
128        assert_eq!(ratio.name(), "Calmar Ratio (252 days)");
129    }
130
131    #[rstest]
132    fn test_empty_returns() {
133        let ratio = CalmarRatio::new(Some(252));
134        let returns = BTreeMap::new();
135        let result = ratio.calculate_from_returns(&returns);
136        assert!(result.is_some());
137        assert!(result.unwrap().is_nan());
138    }
139
140    #[rstest]
141    fn test_no_drawdown() {
142        let ratio = CalmarRatio::new(Some(252));
143        // Only positive returns, no drawdown
144        let returns = create_returns(&vec![0.01; 252]);
145        let result = ratio.calculate_from_returns(&returns);
146
147        // Should be NaN when no drawdown (undefined ratio)
148        assert!(result.is_some());
149        assert!(result.unwrap().is_nan());
150    }
151
152    #[rstest]
153    fn test_positive_ratio() {
154        let ratio = CalmarRatio::new(Some(252));
155        // Simulate a year with 20% CAGR and 10% max drawdown
156        // Daily return for 20% annual: (1.20)^(1/252) - 1
157        let mut returns_vec = vec![0.001; 200]; // Small positive returns
158        // Add a drawdown period
159        returns_vec.extend(vec![-0.002; 52]); // Small negative returns
160
161        let returns = create_returns(&returns_vec);
162        let result = ratio.calculate_from_returns(&returns).unwrap();
163
164        // Calmar should be positive (CAGR / |Max DD|)
165        assert!(result > 0.0);
166    }
167
168    #[rstest]
169    fn test_high_calmar_better() {
170        let ratio = CalmarRatio::new(Some(252));
171
172        // Strategy A: Higher return, same drawdown
173        let returns_a = create_returns(&vec![0.002; 252]);
174        let calmar_a = ratio.calculate_from_returns(&returns_a);
175
176        // Strategy B: Lower return
177        let returns_b = create_returns(&vec![0.001; 252]);
178        let calmar_b = ratio.calculate_from_returns(&returns_b);
179
180        // Higher CAGR should give higher Calmar (assuming same drawdown pattern)
181        // This test just verifies both calculate successfully
182        assert!(calmar_a.is_some());
183        assert!(calmar_b.is_some());
184    }
185}
nautilus_analysis/statistics/calmar_ratio.rs

nautilus_analysis/statistics/
calmar_ratio.rs
