ezyquant.reader.SETDataReader.get_adjust_factor#

SETDataReader.get_adjust_factor(symbol_list: List[str] | None = None, start_date: str | None = None, end_date: str | None = None, ca_type_list: List[str] | None = None) → DataFrame#

Data from table ADJUST_FACTOR.

Parameters:

  • symbol_list (Optional[List[str]] = None) – N_SECURITY in symbol_list (must be unique).

  • start_date (Optional[str] = None) – start of effect_date (D_EFFECT).

  • end_date (Optional[str] = None) – end of effect_date (D_EFFECT).

  • ca_type_list (Optional[List[str]] = None) –

    Corporate action type (N_CA_TYPE).

    • ’ ‘

    • ’CR’ - Capital Reduction

    • ’PC’ - Par Change

    • ’RC’ - Ratio Change

    • ’SD’ - Stock Dividend

    • ’XR’ - Rights

Returns:

adjust factor dataframe contain columns:

  • symbol: str - SECURITY.N_SECURITY

  • effect_date: date - D_EFFECT

  • ca_type: str - N_CA_TYPE

  • adjust_factor: float - R_ADJUST_FACTOR

Return type:

pd.DataFrame

Examples

>>> from ezyquant import SETDataReader
>>> sdr = SETDataReader()
>>> sdr.get_adjust_factor(symbol_list=["RAM"])
  symbol effect_date ca_type  adjust_factor
0    RAM  2019-06-17      PC           0.05
1    RAM  2021-11-09      PC           0.20