UnconstrainedMeanVariancePortfolioOptimizer

QuantConnect.Algorithm.Framework.Portfolio.UnconstrainedMeanVariancePortfolioOptimizer

Provides an implementation of a portfolio optimizer with unconstrained mean variance.

optimize(
    historical_returns: List[float],
    expected_returns: List[float] = None,
    covariance: List[float] = None,
) -> List[float]

Perform portfolio optimization for a provided matrix of historical returns and an array of expected returns

Parameters:

Name	Type	Description	Default
`historical_returns`	`List[float]`	Matrix of historical returns where each column represents a security and each row returns for the given date/time (size: K x N).	required
`expected_returns`	`List[float]`	Array of double with the portfolio annualized expected returns (size: K x 1).	`None`
`covariance`	`List[float]`	Multi-dimensional array of double with the portfolio covariance of annualized returns (size: K x K).	`None`

Returns:

Type	Description
`List[float]`	Array of double with the portfolio weights (size: K x 1).