class_docstr: Risk Model
  
  A risk model is used to estimate the covariance matrix of stock returns.
class_docstr_tok: ["Risk","Model","A","risk","model","is","used","to","estimate","the","covariance","matrix","of","stock","returns","."]
docstr: covariance estimation implementation
  
  This method should be overridden by child classes.
  
  By default, this method implements the empirical covariance estimation.
  
  Args:
      X (np.ndarray): data matrix containing multiple variables (columns) and observations (rows).
  
  Returns:
      np.ndarray: covariance matrix.
docstr_tok: ["covariance","estimation","implementation","This","method","should","be","overridden","by","child","classes",".","By","default",",","this","method","implements","the","empirical","covariance","estimation",".","Args",":","X","(","np.ndarray",")",":","data","matrix","containing","multiple","variables","(","columns",")","and","observations","(","rows",")",".","Returns",":","np.ndarray",":","covariance","matrix","."]
code: def _predict(self, X: np.ndarray) -> np.ndarray:
      """covariance estimation implementation
  
      This method should be overridden by child classes.
  
      By default, this method implements the empirical covariance estimation.
  
      Args:
          X (np.ndarray): data matrix containing multiple variables (columns) and observations (rows).
  
      Returns:
          np.ndarray: covariance matrix.
      """
      xTx = np.asarray(X.T.dot(X))
      N = len(X)
      if isinstance(X, np.ma.MaskedArray):
          M = 1 - X.mask
          N = M.T.dot(M)  # each pair has distinct number of samples
      return xTx / N
  
file_path: qlib/qlib/model/riskmodel/base.py
imports: import inspect
  import numpy
  import pandas
  from typing import Union
  from qlib.model.base import BaseModel
label_desc: Use image node_id 3 for calling the RiskModel obj's underlying member method code with example usage: obj._predict(X) and returns: unknown