A Robust Estimation of the CAPM with a Heavy-tailed Distribution
A Robust Estimation of the CAPM with a Heavy-tailed Distribution
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具有重尾分布的 CAPM 稳健估计
DOI：
10.11114/ijsss.v5i5.2362
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Chikashi Tsuji
中科院分区：
文献类型：
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作者：
Chikashi Tsuji;Chikashi Tsuji;Chikashi Tsuji;Chikashi Tsuji;Chikashi Tsuji;Chikashi Tsuji
本研究以10家美国代表性的芬兰公司的股票月收益率为研究对象，对线性标准资本资产定价模型（CAPM）和非线性CAPM进行了定量研究。通过极大似然估计，我们得到了以下有用的发现。(1)首先，当股票收益分布是厚尾的，我们的非线性CAPM应用是非常有效的。由于我们的非线性CAPM参数很好地捕捉了厚尾收益的行为，因此非线性CAPM估计比标准线性CAPM更可靠。(2)其次，基于标准线性CAPM估计量和非线性CAPM估计量进行Wald检验，阐明当股票收益率分布呈厚尾时，基于非线性CAPM估计量的Wald检验结果比基于标准线性CAPM估计量的Wald检验结果更可靠。
This study quantitatively explores the linear standard capital asset pricing model (CAPM) and a non-linear CAPM by using ten US representative finns' monthly stock returns. By the maximum likelihood estimation, we derive the following useful findings.(1) First, when the stock return distribution is fat-tailed, our non-linear CAPM application is highly effective. Because our non-linear CAPM parameters very well capture the behavior of fat-tailed returns, the non-linear CAPM estimation derives more reliable beta value estimates than the standard linear CAPM.(2) Second, conducting the Wald tests based on both the standard linear CAPM and non-linear CAPM estimators, we clarify that when the stock return distribution is fat-tailed, the Wald test result based on the non-linear CAPM estimators is more reliable than that based on the standard linear CAPM estimators.