Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China

Factor models provide a cornerstone for understanding financial asset pricing; however, research on China’s stock market risk premia is still limited. Motivated by this, this paper proposes a four-factor model for China’s stock market that includes a market factor, a size factor, a value factor, and...

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Main Authors: Xi Sun, Yihao Chen, Yulin Chen, Zhusheng Lou, Lingfeng Tao, Yihao Zhang
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2021/6670378
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spelling doaj-bd3ad38f2b744dcb9f013614440ccf592021-06-14T00:16:54ZengHindawi LimitedDiscrete Dynamics in Nature and Society1607-887X2021-01-01202110.1155/2021/6670378Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from ChinaXi Sun0Yihao Chen1Yulin Chen2Zhusheng Lou3Lingfeng Tao4Yihao Zhang5Hanqing Advanced Institute of Economics and FinanceHanqing Advanced Institute of Economics and FinanceHanqing Advanced Institute of Economics and FinanceHanqing Advanced Institute of Economics and FinanceHanqing Advanced Institute of Economics and FinanceBusiness SchoolFactor models provide a cornerstone for understanding financial asset pricing; however, research on China’s stock market risk premia is still limited. Motivated by this, this paper proposes a four-factor model for China’s stock market that includes a market factor, a size factor, a value factor, and a liquidity factor. We compare our four-factor model with a set of prominent factor models based on newly developed likelihood-ratio tests and Bayesian methods. Along with the comparison, we also find supporting evidence for the alternative t-distribution assumption for empirical asset pricing studies. Our results show the following: (1) distributional tests suggest that the returns of factors and stock return anomalies are fat-tailed and therefore are better captured by t-distributions than by normality; (2) under t-distribution assumptions, our four-factor model outperforms a set of prominent factor models in terms of explaining the factors in each other, pricing a comprehensive list of stock return anomalies, and Bayesian marginal likelihoods; (3) model comparison results vary across normality and t-distribution assumptions, which suggests that distributional assumptions matter for asset pricing studies. This paper contributes to the literature by proposing an effective asset pricing factor model and providing factor model comparison tests under non-normal distributional assumptions in the context of China.http://dx.doi.org/10.1155/2021/6670378
collection DOAJ
language English
format Article
sources DOAJ
author Xi Sun
Yihao Chen
Yulin Chen
Zhusheng Lou
Lingfeng Tao
Yihao Zhang
spellingShingle Xi Sun
Yihao Chen
Yulin Chen
Zhusheng Lou
Lingfeng Tao
Yihao Zhang
Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
Discrete Dynamics in Nature and Society
author_facet Xi Sun
Yihao Chen
Yulin Chen
Zhusheng Lou
Lingfeng Tao
Yihao Zhang
author_sort Xi Sun
title Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
title_short Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
title_full Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
title_fullStr Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
title_full_unstemmed Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China
title_sort comparing asset pricing factor models under multivariate t-distribution: evidence from china
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1607-887X
publishDate 2021-01-01
description Factor models provide a cornerstone for understanding financial asset pricing; however, research on China’s stock market risk premia is still limited. Motivated by this, this paper proposes a four-factor model for China’s stock market that includes a market factor, a size factor, a value factor, and a liquidity factor. We compare our four-factor model with a set of prominent factor models based on newly developed likelihood-ratio tests and Bayesian methods. Along with the comparison, we also find supporting evidence for the alternative t-distribution assumption for empirical asset pricing studies. Our results show the following: (1) distributional tests suggest that the returns of factors and stock return anomalies are fat-tailed and therefore are better captured by t-distributions than by normality; (2) under t-distribution assumptions, our four-factor model outperforms a set of prominent factor models in terms of explaining the factors in each other, pricing a comprehensive list of stock return anomalies, and Bayesian marginal likelihoods; (3) model comparison results vary across normality and t-distribution assumptions, which suggests that distributional assumptions matter for asset pricing studies. This paper contributes to the literature by proposing an effective asset pricing factor model and providing factor model comparison tests under non-normal distributional assumptions in the context of China.
url http://dx.doi.org/10.1155/2021/6670378
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