portfolio_toolkit.asset.optimization package

Submodules

portfolio_toolkit.asset.optimization.optimization_asset module

class portfolio_toolkit.asset.optimization.optimization_asset.OptimizationAsset(ticker: str, prices: pandas.core.series.Series, info: Dict, currency: str | None = None, quantity: float = 0.0, expected_return: float = 0.0)[fuente]

Bases: MarketAsset

quantity: float = 0.0

expected_return: float = 0.0

returns: Series

log_returns: Series

mean_return: float

volatility: float

classmethod to_dataframe(assets: List[OptimizationAsset]) → DataFrame[fuente]: Convert a list of OptimizationAsset objects to a pandas DataFrame.

__init__(ticker: str, prices: Series, info: Dict, currency: str | None = None, quantity: float = 0.0, expected_return: float = 0.0) → None

ticker: str

prices: pd.Series

info: Dict

sector: str

country: str

Module contents

class portfolio_toolkit.asset.optimization.OptimizationAsset(ticker: str, prices: pandas.core.series.Series, info: Dict, currency: str | None = None, quantity: float = 0.0, expected_return: float = 0.0)[fuente]

Bases: MarketAsset

__init__(ticker: str, prices: Series, info: Dict, currency: str | None = None, quantity: float = 0.0, expected_return: float = 0.0) → None

expected_return: float = 0.0

quantity: float = 0.0

classmethod to_dataframe(assets: List[OptimizationAsset]) → DataFrame[fuente]: Convert a list of OptimizationAsset objects to a pandas DataFrame.

returns: Series

log_returns: Series

mean_return: float

volatility: float

ticker: str

prices: pd.Series

info: Dict

sector: str

country: str