arbitragelab.hedge_ratios.box_tiao

Hedge ratio estimation using Box-Tiao canonical decomposition on the assets dataframe.

Module Contents

Functions

get_box_tiao_hedge_ratio(→ Tuple[dict, ...)

Perform Box-Tiao canonical decomposition on the assets dataframe.
get_box_tiao_hedge_ratio(price_data: pandas.DataFrame, dependent_variable: str) → Tuple[dict, pandas.DataFrame, None, pandas.Series]

Perform Box-Tiao canonical decomposition on the assets dataframe.

The resulting ratios are the weightings of each asset in the portfolio. There are N decompositions for N assets, where each column vector corresponds to one portfolio. The order of the weightings corresponds to the descending order of the eigenvalues.

Parameters:

  • price_data – (pd.DataFrame) DataFrame with security prices.

  • dependent_variable – (str) Column name which represents the dependent variable (y).

Returns:

(Tuple) Hedge ratios, X, and fit residuals.