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Type	Master's Thesis
Scope	Discipline-based scholarship
Title	Do Uncertainty Indices Matter for Asset Pricing — A Machine-Learning Approach
Organization Unit	Financial Engineering (Markus Leippold)
Authors	Yongjie Chen
Supervisors	Nikola Vasiljevic Markus Leippold
Language	English
Institution	University of Zurich
Faculty	Faculty of Business, Economics and Informatics
Date	2020
Abstract Text	Large amounts of statistical signiﬁcant predictors in asset pricing make testing new factors chal-lenging. The aim of this paper is to adopt the post-double-selection LASSO and use it to test the signiﬁcance of uncertainty indices in asset pricing. Our test shows that all the uncertainty factors are statistically not signiﬁcant in predicting cross-section of expected returns. In addition, we found out that the post-double-selection LASSO does diﬀerentiate with post-single-selection LASSO. However, the result with diﬀerent missing values imputations and test assets are not stable.
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