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mirror of https://github.com/microsoft/qlib.git synced 2026-07-16 09:11:00 +08:00
Charles Young
2021-03-08 17:14:29 +08:00
parent 79c1142d3e
commit 4d5a30b30b

View File

@@ -36,21 +36,21 @@ class StructuredCovEstimator(RiskModel):
self, self,
factor_model: str = "pca", factor_model: str = "pca",
num_factors: int = 10, num_factors: int = 10,
assume_centered: bool = False, **kwargs
scale_return: bool = True,
nan_option: str = DEFAULT_NAN_OPTION
): ):
""" """
Args: Args:
factor_model (str): the latent factor models used to estimate the structured covariance (`pca`/`fa`). factor_model (str): the latent factor models used to estimate the structured covariance (`pca`/`fa`).
num_factors (int): number of components to keep. num_factors (int): number of components to keep.
assume_centered (bool): whether the data is assumed to be centered. kwargs: see `RiskModel` for more information
scale_return (bool): whether scale returns as percentage.
nan_option (str): nan handling option (`fill`).
""" """
assert nan_option in [self.DEFAULT_NAN_OPTION], "nan_option={} is not supported".format(nan_option) if 'nan_option' in kwargs.keys():
assert kwargs['nan_option'] in [self.DEFAULT_NAN_OPTION], \
"nan_option={} is not supported".format(kwargs['nan_option'])
else:
kwargs['nan_option'] = self.DEFAULT_NAN_OPTION
super().__init__(nan_option, assume_centered, scale_return) super().__init__(**kwargs)
assert factor_model in [ assert factor_model in [
self.FACTOR_MODEL_PCA, self.FACTOR_MODEL_PCA,