【主讲】周雨田 教授 (台湾中央研究院)
【主题】Risk Evaluations with Robust Approximate Factor Models
【时间】2014年11月25日 (周二) 15：30-17：00
【地点】上海财经大学经济学院楼801室
【语言】英文
【摘要】We propose a new method on robustly estimating approximate factor models and apply the proposed method on risk evaluations. Approximate factor mod- els and their extensions are widely used in economic analysis and forecasting due to their ability to extracting useful information from a large number of relevant variables. In these models, candidate predictors are typically subject to some com- mon components. We consider to estimate approximate factor models in which the candidate predictors are additionally subject to idiosyncratic large uncommon components such as jumps or outliers. By assuming that occurrences of the uncom- mon components are rare, we propose an estimation procedure to simultaneously disentangle and estimate the common and uncommon components. Through in- tensive simulations, we compare nite-sample eciency of the proposed method and traditional PCA method. For empirical analysis, we use the proposed method on investigating whether the latent factors are priced for expected returns of Fama and French 100 size and book-to-market ratio portfolios. We nd evidence that for the 100 portfolios, risk from the common factor is priced but risks from the idiosyncratic factors are not. However, we also nd that model uncertainty risks of the idiosyncratic factors are priced, which suggests that with e ective diversica- tions, only the predictable idiosyncratic risks can be reduced and the unpredictable ones may still exist.
