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TitleRisk Evaluations with Robust Approximate Factor Models
Creator顏佑銘
Chou, Ray Yeutien;Yen, Tso-Jung;Yen, Yu-Min
Contributor國貿系
Key WordsApproximate factor model; PCA; Norm penalty; Common factor; Idiosyncratic risk; VaR
Date2016-05
Date Issued17-Apr-2017 12:21:05 (UTC+8)
SummaryApproximate 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.
RelationJournal of Banking and Finance,未刊登
Typearticle
DOI http://dx.doi.org/10.1016/j.jbankfin.2016.05.008
dc.contributor 國貿系
dc.creator (作者) 顏佑銘zh_TW
dc.creator (作者) Chou, Ray Yeutien;Yen, Tso-Jung;Yen, Yu-Min
dc.date (日期) 2016-05
dc.date.accessioned 17-Apr-2017 12:21:05 (UTC+8)-
dc.date.available 17-Apr-2017 12:21:05 (UTC+8)-
dc.date.issued (上傳時間) 17-Apr-2017 12:21:05 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/108890-
dc.description.abstract (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.
dc.format.extent 2826792 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Journal of Banking and Finance,未刊登
dc.subject (關鍵詞) Approximate factor model; PCA; Norm penalty; Common factor; Idiosyncratic risk; VaR
dc.title (題名) Risk Evaluations with Robust Approximate Factor Models
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.jbankfin.2016.05.008
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.jbankfin.2016.05.008