Source code for frds.measures._kyle_lambda

import numpy as np

[docs] def kyle_lambda(returns: np.ndarray, signed_dollar_volume: np.ndarray) -> float: r""":doc:`/measures/kyle_lambda` Args: returns (np.ndarray): ``(n,)`` array of stock returns signed_dollar_volume (np.ndarray): ``(n,)`` array of signed dollar volume Returns: float: Kyle's lambda (*1000000) .. note:: The return value is the estimated coefficient of :math:`\lambda` in equation :math:numref:`kylelambda_regression` multiplied by 1,000,000. """ y = np.asarray(returns) x = np.asarray(signed_dollar_volume) x = x[:, np.newaxis] a, _, _, _ = np.linalg.lstsq(x, y, rcond=None) return a[0] * 1_000_000