nautilus_analysis/python/statistics/returns_volatility.rs
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14// -------------------------------------------------------------------------------------------------
15
16use std::collections::BTreeMap;
17
18use pyo3::prelude::*;
19
20use super::transform_returns;
21use crate::{statistic::PortfolioStatistic, statistics::returns_volatility::ReturnsVolatility};
22
23#[pymethods]
24#[pyo3_stub_gen::derive::gen_stub_pymethods]
25impl ReturnsVolatility {
26 /// Calculates the annualized volatility (standard deviation) of portfolio returns.
27 ///
28 /// Volatility is calculated as the standard deviation of returns, annualized by
29 /// multiplying the daily standard deviation by the square root of the period:
30 /// `Standard Deviation * sqrt(period)`
31 ///
32 /// Uses Bessel's correction (ddof=1) for sample standard deviation.
33 /// This provides a measure of the portfolio's risk or uncertainty of returns.
34 ///
35 /// # References
36 ///
37 /// - CFA Institute Level I Curriculum: Quantitative Methods
38 /// - Hull, J. C. (2018). *Options, Futures, and Other Derivatives* (10th ed.). Pearson.
39 /// - Fabozzi, F. J., et al. (2002). *The Handbook of Financial Instruments*. Wiley.
40 #[new]
41 #[pyo3(signature = (period=None))]
42 fn py_new(period: Option<usize>) -> Self {
43 Self::new(period)
44 }
45
46 fn __repr__(&self) -> String {
47 self.to_string()
48 }
49
50 #[getter]
51 #[pyo3(name = "name")]
52 fn py_name(&self) -> String {
53 self.name()
54 }
55
56 #[pyo3(name = "calculate_from_returns")]
57 #[expect(clippy::needless_pass_by_value)]
58 fn py_calculate_from_returns(&mut self, raw_returns: BTreeMap<u64, f64>) -> Option<f64> {
59 self.calculate_from_returns(&transform_returns(&raw_returns))
60 }
61
62 #[pyo3(name = "calculate_from_realized_pnls")]
63 fn py_calculate_from_realized_pnls(&mut self, _realized_pnls: Vec<f64>) -> Option<f64> {
64 None
65 }
66
67 #[pyo3(name = "calculate_from_positions")]
68 fn py_calculate_from_positions(&mut self, _positions: Vec<Py<PyAny>>) -> Option<f64> {
69 None
70 }
71}