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題名 A vg-ngarch model for impacts of extreme events on stock returns 作者 陳麗霞
Kao, Lie-Jane
Chen, Li-Shya
Lee, Cheng-Few貢獻者 統計系 日期 2015-01 上傳時間 8-Aug-2017 16:40:37 (UTC+8) 摘要 This article compares two types of GARCH models, namely, the VG-NGARCH and the GARCH-jump model with autoregressive conditional jump intensity, i.e., the GARJI model, to make inferences on the log of stock returns when there are irregular substantial price fluctuations. The VG-NGARCH model imposes a nonlinear asymmetric structure on the conditional shape parameters in a variance-gamma process, which describes the arrival rates for news with different degrees of influence on price movements and provides an ex ante probability for the occurrence of large price movements. On the other hand, the GARJI model, a mixed GARCH-jump model proposed by Chan and Maheu (Journal of Business & Economic Statistics 20:377-389, 2002), adopts two independent autoregressive processes to model the variances corresponding to moderate and large price movements, respectively. An empirical study using daily stock prices of four major banks, namely, Bank of America, J.P. Morgan Chase, Citigroup, and Wells Fargo, from 2006 to 2009 is performed to compare the two models. The goodness of fit of the VG-NGARCH model vs. the GARJI model is demonstrated. © Springer Science+Business Media New York 2015. 關聯 Handbook of Financial Econometrics and Statistics, 2263-2279 資料類型 book/chapter DOI http://dx.doi.org/10.1007/978-1-4614-7750-1_82 dc.contributor 統計系 zh_Tw dc.creator (作者) 陳麗霞 zh_TW dc.creator (作者) Kao, Lie-Jane en_US dc.creator (作者) Chen, Li-Shya en_US dc.creator (作者) Lee, Cheng-Few en_US dc.date (日期) 2015-01 en_US dc.date.accessioned 8-Aug-2017 16:40:37 (UTC+8) - dc.date.available 8-Aug-2017 16:40:37 (UTC+8) - dc.date.issued (上傳時間) 8-Aug-2017 16:40:37 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111671 - dc.description.abstract (摘要) This article compares two types of GARCH models, namely, the VG-NGARCH and the GARCH-jump model with autoregressive conditional jump intensity, i.e., the GARJI model, to make inferences on the log of stock returns when there are irregular substantial price fluctuations. The VG-NGARCH model imposes a nonlinear asymmetric structure on the conditional shape parameters in a variance-gamma process, which describes the arrival rates for news with different degrees of influence on price movements and provides an ex ante probability for the occurrence of large price movements. On the other hand, the GARJI model, a mixed GARCH-jump model proposed by Chan and Maheu (Journal of Business & Economic Statistics 20:377-389, 2002), adopts two independent autoregressive processes to model the variances corresponding to moderate and large price movements, respectively. An empirical study using daily stock prices of four major banks, namely, Bank of America, J.P. Morgan Chase, Citigroup, and Wells Fargo, from 2006 to 2009 is performed to compare the two models. The goodness of fit of the VG-NGARCH model vs. the GARJI model is demonstrated. © Springer Science+Business Media New York 2015. en_US dc.format.extent 612381 bytes - dc.format.mimetype application/pdf - dc.relation (關聯) Handbook of Financial Econometrics and Statistics, 2263-2279 en_US dc.title (題名) A vg-ngarch model for impacts of extreme events on stock returns en_US dc.type (資料類型) book/chapter dc.identifier.doi (DOI) 10.1007/978-1-4614-7750-1_82 dc.doi.uri (DOI) http://dx.doi.org/10.1007/978-1-4614-7750-1_82
