portfolio_toolkit.optimization.optimization module

class portfolio_toolkit.optimization.optimization.Optimization(name: str, currency: str, assets: List[OptimizationAsset], data_provider: DataProvider, period: str = '1y', returns: DataFrame | None = None, covariance_matrix: DataFrame | None = None, means: Series | None = None, weights: Series | None = None, expected_returns: Series | None = None)[source]

Bases: object

Class to represent and manage an asset optimization.

name: str

currency: str

assets: List[OptimizationAsset]

data_provider: DataProvider

period: str = '1y'

returns: DataFrame | None = None

covariance_matrix: DataFrame | None = None

means: Series | None = None

weights: Series | None = None

expected_returns: Series | None = None

classmethod from_dict(data: dict, data_provider: DataProvider) → Optimization[source]

get_var() → float[source]

get_efficient_frontier(num_points: int)[source]

__init__(name: str, currency: str, assets: List[OptimizationAsset], data_provider: DataProvider, period: str = '1y', returns: DataFrame | None = None, covariance_matrix: DataFrame | None = None, means: Series | None = None, weights: Series | None = None, expected_returns: Series | None = None) → None