Distance Estimator

A distance estimator estimates the codependence and distance matrix 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 codependence and distance matrix in its codependence_ and distance_ attributes.

X can be any array-like structure (numpy array, pandas DataFrame, etc.)

Available estimators are:

• PearsonDistance

• KendallDistance

• SpearmanDistance

• CovarianceDistance

• DistanceCorrelation

• MutualInformation

Example:

from skfolio.datasets import load_sp500_dataset
from skfolio.distance import PearsonDistance
from skfolio.preprocessing import prices_to_returns

prices = load_sp500_dataset()
X = prices_to_returns(prices)

model = PearsonDistance()
model.fit(X)
print(model.codependence_)
print(model.distance_)