Source code for skfolio.moments.expected_returns._base

"""Base Expected returns estimators."""

# Copyright (c) 2023-2026
# Author: Hugo Delatte <hugo.delatte@skfoliolabs.com>
# SPDX-License-Identifier: BSD-3-Clause
# Implementation derived from:
# scikit-learn, Copyright (c) 2007-2010 David Cournapeau, Fabian Pedregosa, Olivier
# Grisel Licensed under BSD 3 clause.

from __future__ import annotations

from abc import ABC, abstractmethod

import sklearn.base as skb

from skfolio.typing import ArrayLike, FloatArray, StrArray




class BaseMu(skb.BaseEstimator, ABC):
    """Base class for all expected returns estimators in skfolio.

    Notes
    -----
    All estimators should specify all the parameters that can be set
    at the class level in their `__init__` as explicit keyword
    arguments (no `*args` or `**kwargs`).
    """

    mu_: FloatArray
    n_features_in_: int
    feature_names_in_: StrArray

    @abstractmethod
    def __init__(self) -> None: ...



    @abstractmethod
    def fit(self, X: ArrayLike, y: None = None) -> BaseMu:
        """Fit the expected returns estimator.

        Parameters
        ----------
        X : array-like of shape (n_observations, n_assets)
            Price returns of the assets.

        y : Ignored
            Not used, present for API consistency by convention.

        Returns
        -------
        self : BaseMu
            Fitted estimator.
        """
        ...