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// -------------------------------------------------------------------------------------------------
// Copyright (C) 2015-2026 Nautech Systems Pty Ltd. All rights reserved.
// https://nautechsystems.io
//
// Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
// You may not use this file except in compliance with the License.
// You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// -------------------------------------------------------------------------------------------------
use std::collections::BTreeMap;
use nautilus_model::position::Position;
use pyo3::prelude::*;
use super::transform_returns;
use crate::{statistic::PortfolioStatistic, statistics::returns_skewness::ReturnsSkewness};
#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl ReturnsSkewness {
/// Calculates the skewness of portfolio returns.
///
/// Skewness measures the asymmetry of the return distribution about its mean. A
/// negative value indicates a longer left tail (downside outliers); a positive
/// value indicates a longer right tail.
///
/// Uses the bias-corrected sample skewness (adjusted Fisher-Pearson), matching
/// `pandas.Series.skew` and Excel `SKEW`:
///
/// `G1 = n / ((n - 1)(n - 2)) * sum(((x - mean) / s)^3)`
///
/// where `s` is the sample standard deviation (Bessel's correction, ddof=1).
/// Returns `NaN` for fewer than three returns or zero dispersion.
///
/// # References
///
/// - Joanes, D. N., & Gill, C. A. (1998). Comparing measures of sample skewness
/// and kurtosis. *Journal of the Royal Statistical Society: Series D*, 47(1), 183-189.
#[new]
fn py_new() -> Self {
Self::new()
}
fn __repr__(&self) -> String {
self.name()
}
#[getter]
#[pyo3(name = "name")]
fn py_name(&self) -> String {
self.name()
}
#[pyo3(name = "calculate_from_returns")]
#[expect(clippy::needless_pass_by_value)]
fn py_calculate_from_returns(&mut self, raw_returns: BTreeMap<u64, f64>) -> Option<f64> {
self.calculate_from_returns(&transform_returns(&raw_returns))
}
#[pyo3(name = "calculate_from_realized_pnls")]
fn py_calculate_from_realized_pnls(&mut self, _realized_pnls: Vec<f64>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_positions")]
fn py_calculate_from_positions(&mut self, _positions: Vec<Position>) -> Option<f64> {
None
}
}