應用t copula 與skew t copula函數於商品期貨風險管理

Han-Yang Lee; 李翰揚

請用此 Handle URI 來引用此文件： http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54340

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.advisor	葉小蓁(Hsiao-Chen Yeh)
dc.contributor.author	Han-Yang Lee	en
dc.contributor.author	李翰揚	zh_TW
dc.date.accessioned	2021-06-16T02:51:23Z	-
dc.date.available	2017-07-23
dc.date.copyright	2015-07-23
dc.date.issued	2015
dc.date.submitted	2015-07-14
dc.identifier.citation	1. Aas, K. and Haff, I.(2006), “The generalized hyperbolic skew student’s t distribution', Journal of financial econometrics 4, No.2: 275-309. 2.Berkowitz, J. and O’Brien, J. (2002)” How Accurate Are Value-at-Risk Models at Commercial Banks?”, The Journal of Finance, Vol.57, No.3. 3.Clemen, R. T. and Reilly, T(1997),”Correlations and copula for decision and risk analysis.”, Management Science, Vol.45, No.2, 208. 4.Culp, C., Miller, M. and Neves, A.(1998),” Value at risk: Uses and abuses”, Journal of Applied Corporate Finance, Vol. 10, Issue. 4, 26-38. 5.Demarta, S. and McNeil, A. J. (2004),”The t Copula and Related Copulas”, 2-10. 6.Hu, W. and A, Kercheval.(2007), “Risk management with generalized hyperbolic distributions”,Working paper,Florida State University, Tallahassee, USA. 7.J.P. Morgan.(1995), ”RiskMetrics”, Third Edition, J.P. Morgan. 8.Lin, J.L. and Liou, Z.K.(2009), “The dynamic t Copula with analytic estimation of degree of freedom in risk management of commodity futures portfolio.”,Taiwan futures and derivative products journal,Vol.9,No.1, 1-35. 9.McNeil, A. J., Frey, P. and Embrechts, P.(2005),”Quantitative risk Management: Concepts,Techniques and Tools”,184-186. 10.Nieppola, O.(2009),”Backtesting Value-at-risk Models”,17-28. 11.Romano, C(2002), “Applying copula function to risk management.”,Working paper. 12.Yen, Y. Z.(2010),”Nonparametric Statistics”,NTU College of Management,325-332. 13.Yeh, H.C.(2009),”Advanced Statistics”, NTU College of Management, 231-234.
dc.identifier.uri	http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54340	-
dc.description.abstract	評價多資產衍生性標的，在理論推導和計算上相當複雜，尤其當投資組合標的資產個數很大時，幾乎無法準確找出聯合機率分配。直到copula 方法的提出，我們方可簡化處理上述的問題，配適出更符合實際的聯合機率分配。本篇研究分別採用了skew t copula 及 t copula 關聯結構搭配指數加權平均法估計相關性進而估計某一商品期貨投資組合的風險值。我們發現兩模型皆通過了回朔測試並且也在壓力測試中，也快速地反映了左尾極端事件造成的影響。最後，我們針對此一期貨投資組合內各類別報酬率的相關性進行探討，發現相關性幾乎為正，尤其是在2008金融海嘯後此現象更加明顯。	zh_TW
dc.description.provenance	Made available in DSpace on 2021-06-16T02:51:23Z (GMT). No. of bitstreams: 1 ntu-104-R02723057-1.pdf: 1333010 bytes, checksum: 9dec6df2c6f41b3ad7bfc9b2c1520293 (MD5) Previous issue date: 2015	en
dc.description.tableofcontents	1.Introduction……………………………………………………………..….....………...1 2.Literature Review………………………………………………….….....………………3 3.Data………………………………………………………………………………...............5 4.Methodology…………………………………………………………...……….....……...7 4.1 Basic concepts…………………………………………..……………….....…..…7 4.1.1 Copula function…………………………………...…………….....……….7 4.1.2 Sklar’s theorem……………………………………..……………......…..7 4.1.3 The multivariate skew t distribution…….......8 4.1.4 The multivariate t distribution………………........9 4.2 Calculating the VaR………………….…………………………………….....…9 4.3 The tests of backward testing and correlation….14 4.3.1Kupeic’s test…………………………………………….…………...........14 4.3.2Chrisofferson’s test…………………………………....….……………..15 4.3.3Spearman’s rank correlation and Hotelling Pabst’s test...............................................17 4.3.4 Kendall’s rank correlation test…………..….…………….18 5.Empirical result…………………………………………………………......…….……20 5.1 Backward testing……………………………………………........………………20 5.2 Stress testing…………………………………...……….…...…………………..25 5.3 Correlation…………………………………………….........……………………..29 6.Conclution………………………………………………..........………………………….35 Reference…………………………………………………...........…………………………..38 Appendix…………………………………………………............…………………………..40
dc.language.iso	en
dc.subject	偏態t分布	zh_TW
dc.subject	指數加權平均法	zh_TW
dc.subject	關聯結構	zh_TW
dc.subject	關聯結構	zh_TW
dc.subject	風險值	zh_TW
dc.subject	風險值	zh_TW
dc.subject	偏態t分布	zh_TW
dc.subject	指數加權平均法	zh_TW
dc.subject	copula	en
dc.subject	VaR	en
dc.subject	copula	en
dc.subject	skew t distribution	en
dc.subject	Exponentially Weighted Moving Average	en
dc.subject	VaR	en
dc.subject	skew t distribution	en
dc.subject	Exponentially Weighted Moving Average	en
dc.title	應用t copula 與skew t copula函數於商品期貨風險管理	zh_TW
dc.title	Application of t copula and skew t copula function in risk management	en
dc.type	Thesis
dc.date.schoolyear	103-2
dc.description.degree	碩士
dc.contributor.oralexamcommittee	蘇永成(Yung-Cheng Su),許耀文(Yao-Wen Hsu)
dc.subject.keyword	風險值,關聯結構,偏態t分布,指數加權平均法,	zh_TW
dc.subject.keyword	VaR,copula,skew t distribution,Exponentially Weighted Moving Average,	en
dc.relation.page	44
dc.rights.note	有償授權
dc.date.accepted	2015-07-14
dc.contributor.author-college	管理學院	zh_TW
dc.contributor.author-dept	財務金融學研究所	zh_TW
顯示於系所單位：	財務金融學系

文件中的檔案：

檔案	大小	格式
ntu-104-1.pdf 未授權公開取用	1.3 MB	Adobe PDF

顯示文件簡單紀錄

系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。