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    题名: Risk Evaluations with Robust Approximate Factor Models
    作者: 顏佑銘
    Chou, Ray Yeutien;Yen, Tso-Jung;Yen, Yu-Min
    贡献者: 國貿系
    关键词: Approximate factor model;PCA;Norm penalty;Common factor;Idiosyncratic risk;VaR
    日期: 2016-05
    上传时间: 2017-04-17 12:21:05 (UTC+8)
    摘要: Approximate factor models 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 common components. In this paper we propose a new method for robustly estimating the approximate factor models and use it in risk assessments. We consider a class of 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 uncommon components are rare, we develop an estimation procedure to simultaneously disentangle and estimate the common and uncommon components. We then use the proposed method to investigate whether risks from the latent factors are priced for expected returns of Fama and French 100 size and book-to-market ratio portfolios. We find that while the risk from the common factor is priced for the 100 portfolios, the risks from the idiosyncratic factors are not. However, we find that model uncertainty risks of the idiosyncratic factors are priced, suggesting that with effective diversifications, only the predictable idiosyncratic risks can be reduced, but the unpredictable ones may still exist. We also illustrate how the proposed method can be adopted on evaluating value at risk (VaR) and find it can delivery comparable results as the conventional methods on VaR evaluations.
    關聯: Journal of Banking and Finance,未刊登
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1016/j.jbankfin.2016.05.008
    DOI: 10.1016/j.jbankfin.2016.05.008
    显示于类别:[國際經營與貿易學系 ] 期刊論文

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