linearmodels.asset_pricing.results.GMMFactorModelResults¶

class GMMFactorModelResults(results)[source]¶

Attributes:

alphas: Mispricing estimates
betas: Estimated factor loadings
cov: Estimated covariance of parameters
cov_estimator: Type of covariance estimator used to compute covariance
full_summary: Complete summary including factor loadings and mispricing measures
iterations: Number of steps in GMM estimation
j_statistic: Model J statistic
name: Model type
nobs: Number of observations
params: Estimated parameters
pvalues: Parameter p-vals.
residual_ss: Residual sum of squares
risk_premia: Estimated factor risk premia (lambda)
risk_premia_se: Estimated factor risk premia standard errors
risk_premia_tstats: Risk premia t-statistics
rsquared: Coefficient of determination (R**2)
std_errors: Estimated parameter standard errors
summary: Model estimation summary.
total_ss: Total sum of squares
tstats: Parameter t-statistics

Methods

Properties

`alphas`	Mispricing estimates
`betas`	Estimated factor loadings
`cov`	Estimated covariance of parameters
`cov_estimator`	Type of covariance estimator used to compute covariance
`full_summary`	Complete summary including factor loadings and mispricing measures
`iterations`	Number of steps in GMM estimation
`j_statistic`	Model J statistic
`name`	Model type
`nobs`	Number of observations
`params`	Estimated parameters
`pvalues`	Parameter p-vals.
`residual_ss`	Residual sum of squares
`risk_premia`	Estimated factor risk premia (lambda)
`risk_premia_se`	Estimated factor risk premia standard errors
`risk_premia_tstats`	Risk premia t-statistics
`rsquared`	Coefficient of determination (R**2)
`std_errors`	Estimated parameter standard errors
`summary`	Model estimation summary.
`total_ss`	Total sum of squares
`tstats`	Parameter t-statistics