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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅承德(Cheng-Der Fuh) | |
| dc.contributor.author | Hao-Hsiang Chang | en |
| dc.contributor.author | 張皓翔 | zh_TW |
| dc.date.accessioned | 2021-06-17T05:03:11Z | - |
| dc.date.available | 2023-08-01 | |
| dc.date.copyright | 2018-08-01 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-07-24 | |
| dc.identifier.citation | [1] Adrian, T. and Brunnermeier, M. K., CoVaR. American Economic Review,
Vol. 106, No. 7, 2016. [2] Andrews, L. C., Special Functions of Mathematics for Engineers, 1998 (Oxford University Press). [3] Bucklew, J. A., Introduction to Rare Event Simulation, 2004 (Springer-Verlag: New York). [4] Fuh, C. D. and Hu, I., Efficient importance sampling for events of moderate deviations with applications. Biometrika 91 (2), 471–490, 2004. [5] Fuh, C. D., Hu, I., Hsu, Y. H. and Wang, R. H., Efficient simulation of value at risk with heavy-tailed risk factors. Operations Research, 59, 1395–1406, 2011. [6] Fuh, C. D. and Wang, C. J., Efficient Simulation for Portfolio Credit Risk in Normal Mixture Copula Models. arXiv:1711.03744, 2017. [7] Glasserman, P., Monte Carlo Methods in Financial Engineering, 2004 (Springer: New York). [8] Glasserman, P., Heidelberger, P., and Shahabuddin, P., Portfolio Value-at- Risk with heavy-tailed risk factors. Mathematical Finance, 12: 239-269, 2002. [9] Glasserman, P., Heidelberger, P., and Shahabuddin, P., Variance reduction techniques for estimating Value-at-Risk. Management Science, 46: 1349-1364, 2000. [10] Glynn, P. W., Importance sampling for Monte Carlo estimation of quantiles. In Mathematical Methods in Stochastic Simulation and Experimental Design: Proc. 2nd St. Petersburg Workshop on Simulation, Publishing House of Saint Petersburg, 180–185, 1996. [11] Hall, P. and Martin, M. A., Exact convergence rate of bootstrap quantile variance estimator. Probability Theory Related Fields, 80, 261–268, 1988. [12] Hull, J., Options, Futures, and Other Derivatives, 2013 (Pearson Education). [13] Liu, J., and Yang, X., The convergence rate and asymptotic distribution of the bootstrap quantile variance estimator for importance sampling. Advances in Applied Probability, 44, 815–841, 2012. [14] Magnus, J.A. and Neudecker, H., Matrix Differential Calculus with Applications in Statistics and Econometrics, 2007 (John Wiley & Sons Ltd). [15] Mainik, G. and Schaanning, E., On dependence consistency of CoVaR and some other systemic risk measures. arXiv:1207.3464, 2012. [16] Ross, S.M., Simulation, 2013 (Academic Press: New York). [17] Teng, H.W., Fuh, C.D., and Chen, C.C., On an automatic and optimal importance sampling approach with applications in finance. Quantitative Finance, 16 (8), 1259–1271, 2016. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71291 | - |
| dc.description.abstract | 本論文將基於邊際和聯合機率進行 CoVaR 的模擬。此外，將提出重要抽樣法的最佳參數與分位數之間的二次模式，這可以幫助我們更有效率地找到所要估計的分位數。 | zh_TW |
| dc.description.abstract | In this thesis, a simulation of CoVaR based on the marginal and the joint probability would be presented. Also, a quadratic pattern between the optimal parameters of importance sampling and the quantiles will be proposed, which may help us to find the quantiles of interest more efficiently. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T05:03:11Z (GMT). No. of bitstreams: 1 ntu-107-R05246008-1.pdf: 1006004 bytes, checksum: 9c831c18d964e1729ba975d0729f896c (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 口試委員審定書i
致謝ii 摘要iii Abstract iv 1 Introduction 1 2 Preliminaries 4 2.1 VaR and CoVaR . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Importance Sampling and Exponential Tilting . . . . . . . . . . . . 6 2.3 Delta-Gamma Approximation . . . . . . . . . . . . . . . . . . . . . 8 3 Simulation under Normal Distribution 11 3.1 Model Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Alternative Distribution . . . . . . . . . . . . . . . . . . . . . . . . 13 3.3 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4 Simulation under t-Distribution 20 4.1 Model Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.2 Alternative Distribution . . . . . . . . . . . . . . . . . . . . . . . . 24 4.3 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 5 Numerical Results 29 6 Conclusion Remarks and Further Research 40 | |
| dc.language.iso | en | |
| dc.subject | 條件風險值 | zh_TW |
| dc.subject | delta-gamma 近似 | zh_TW |
| dc.subject | 稀有事件 | zh_TW |
| dc.subject | 重要抽樣法 | zh_TW |
| dc.subject | 風險值 | zh_TW |
| dc.subject | delta-gamma approximation | en |
| dc.subject | rare events | en |
| dc.subject | conditional value at risk | en |
| dc.subject | importance sampling | en |
| dc.subject | value at risk | en |
| dc.title | CoVaR 之蒙地卡羅模擬 | zh_TW |
| dc.title | Monte Carlo Simulation on CoVaR | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 江金倉(Chin-Tsang Chiang) | |
| dc.contributor.oralexamcommittee | 陳宏(Hung Chen),韓傳祥(Chuan-Hsiang Han) | |
| dc.subject.keyword | 風險值,條件風險值,重要抽樣法,稀有事件,delta-gamma 近似, | zh_TW |
| dc.subject.keyword | value at risk,conditional value at risk,importance sampling,rare events,delta-gamma approximation, | en |
| dc.relation.page | 42 | |
| dc.identifier.doi | 10.6342/NTU201801699 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-07-24 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 應用數學科學研究所 | zh_TW |
| 顯示於系所單位： | 應用數學科學研究所 | |
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