Expected Return Estimator#
An expected return estimator estimates the expected returns (mu
) of
the assets.
It follows the same API as scikit-learn’s estimator
: the fit
method takes X
as
the assets returns and stores the expected returns in its mu_
attribute.
X
can be any array-like structure (numpy array, pandas DataFrame, etc.)
- Available estimators are:
Example:
from skfolio.datasets import load_sp500_dataset
from skfolio.moments import EmpiricalMu
from skfolio.preprocessing import prices_to_returns
prices = load_sp500_dataset()
X = prices_to_returns(prices)
model = EmpiricalMu()
model.fit(X)
print(model.mu_)