portfolio_toolkit.asset.portfolio.portfolio_asset module

class portfolio_toolkit.asset.portfolio.portfolio_asset.PortfolioAsset(ticker: str, prices: pandas.core.series.Series, info: Dict, currency: Optional[str] = None, transactions: List[portfolio_toolkit.asset.portfolio.portfolio_asset_transaction.PortfolioAssetTransaction] = <factory>)

Bases: MarketAsset

transactions: List[PortfolioAssetTransaction]

classmethod from_ticker(data_provider: DataProvider, ticker: str, currency: str | None = None) → PortfolioAsset

Create a PortfolioAsset from a ticker.

classmethod to_dataframe(assets: List[PortfolioAsset]) → DataFrame

Convert a list of PortfolioAsset objects to a pandas DataFrame.

add_transaction(transaction: PortfolioAssetTransaction)

Adds a transaction to the portfolio asset.

add_transaction_from_dict(transaction_dict: dict)

Adds a transaction to the account from a dictionary.

add_split(split_dict: dict) → float

Adds a stock split to the portfolio asset by simulating sell all + buy equivalent. Creates a sell transaction for all held shares and a buy transaction for split-adjusted quantity.

Parameters:

split_dict – Dictionary containing split information with keys: - date: Split date (str) - split_factor: Split ratio as float (e.g., 2.0 for 2:1 split, 0.1 for 1:10 reverse split)

Returns:

Cash amount to be added to account due to fractional shares sold

(only applies to reverse splits where shares are lost)

Return type:

float

__init__(ticker: str, prices: ~pandas.core.series.Series, info: ~typing.Dict, currency: str | None = None, transactions: ~typing.List[~portfolio_toolkit.asset.portfolio.portfolio_asset_transaction.PortfolioAssetTransaction] = <factory>) → None

ticker: str

prices: pd.Series

info: Dict

sector: str

country: str