题目：Estimation and Inference in Semiparametric Quantile Factor Models
报告人：Professor Shujie Ma (加州大学-Riverside分校)
In this talk, I will introduce an estimation methodology for a semiparametric quantile factor panel model. I will also talk about our proposed tools for inference that are robust to the existence of moments and to the form of weak cross-sectional dependence in the idiosyncratic error term. Specifically, we use sieve techniques to obtain preliminary estimators of the nonparametric beta functions, and use these to estimate the factor return vector at each time period. We then update the loading functions and factor returns sequentially. We derive the limiting properties of our estimated factor returns and factor loading functions under weak conditions on cross-section and temporal dependence. Lastly, I will talk about applications of our method to daily stock return data.
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