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    题名: The Extension from Independence to Dependence between Jump Frequency and Jump Size in Markov-modulated Jump Diffusion Models
    作者: 林士貴;彭金隆
    Lin, Shih-Kuei;Peng, Jin-Lung;Chao, Wei-Hsiung;Wu, An-Chi
    贡献者: 風管系;金融系
    关键词: Markov-modulated jump models;EM-gradient algorithm;SEM algorithm
    日期: 2016-07
    上传时间: 2016-06-16 14:30:22 (UTC+8)
    摘要: We set out in this study to investigate the relationship between jump frequency and jump size for the 30 component stocks of the Dow Jones Industrial Average (DJIA) index, extending the Markov-modulated jump diffusion model from independence to dependence between jump frequency and jump size. We propose an estimation method for the parameters of the Markov-modulated jump diffusion model based upon dependence between jump frequency and size, with our results indicating that when abnormal events occur, the Markov-modulated jump diffusion models with both state-independent jump sizes (MJMI) and state-dependent jump sizes (MJMD) outperform the pure jump diffusion (JD) model in terms of capturing the risks of jump frequency and jump size. Based upon Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC), our results further indicate that for 23 of the component stocks, the MJMD model may be better suited, as compared to the MJMI model. Finally, our empirical observations reveal that the behavior of jump risks in the stock markets, including jump frequency and jump size, is not independent, since these phenomena are found to coincide during both financial crisis periods and stock market crashes, with the largest jump size risks, during certain periods, being accompanied by either systematic or idiosyncratic risks.
    關聯: The North-American Journal of Economics and Finance, Volume 37, Pages 217–235
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1016/j.najef.2016.04.003
    DOI: 10.1016/j.najef.2016.04.003
    显示于类别:[金融學系] 期刊論文

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