Publication: Improved inference in financial factor models
Improved inference in financial factor models
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Beck, E., De Nard, G., & Wolf, M. (2023). Improved inference in financial factor models. International Review of Economics and Finance, 86, 364–379. https://doi.org/10.1016/j.iref.2023.03.009
Abstract
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Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama–French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In this paper, we show that using weighted least squares (WLS) or adaptive least squares (ALS) to estimate model parameters generally leads to smaller HC standard errors compared to ordinary least squares (OLS), which translates into improved inferen
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- Beck, Elliot
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Citations
Beck, E., De Nard, G., & Wolf, M. (2023). Improved inference in financial factor models. International Review of Economics and Finance, 86, 364–379. https://doi.org/10.1016/j.iref.2023.03.009
