請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 葉小蓁(Hsiaw-Chan Yeh) | |
| dc.contributor.author | Wen-Hua Hsieh | en |
| dc.contributor.author | 謝文華 | zh_TW |
| dc.date.accessioned | 2021-06-08T05:57:26Z | - |
| dc.date.copyright | 2007-11-15 | |
| dc.date.issued | 2007 | |
| dc.date.submitted | 2007-10-31 | |
| dc.identifier.citation | References
[1] Carmona, R. A. (2004). Statistical Analysis of Financial Data in S-Plus. Springer. [2] Cherubini, U., Luciano, E., and Vecchiato, W. (2004). Copula Methods in Finance. John Wiley & Sons. [3] Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. [4] Davison, A. C. (1984). Modelling excesses over high thresholds, with application. In Tiago de Oliveira, J., editor, Statistical Extremes and Applications, pages 461-482. Reidel, Dordrecht. [5] Davison, A. C. & Smith, R. L. (1990). Models for exceedances over high thresholds (with discussion). Journal of the Royal Statistical Society, B52,393-442. [6] Deheuvels, P. (1978). Caractérisation Compléte des lois Extrêmes Multivariées et de la Convergence des Types Extrêmes. Publications de l'Institut de. Statistique de l’Université de Paris, 23, 1-36. [7] Durrett, R. (2005). Probability: Theory and Examples. Thomson Learning. [8] Embrechts, P., Klüppelberg, C., Mikosch, T. (1997). Modelling Extremal Events for Insurance and Finance. Springer. [9] Feller, W. (1968). An Introduction to Probability Theory and Its Applications, v.2, John Wiley & Sons. [10] Fisz, M. (1963). Probability theory and mathematical statistics. Wiley. [11] Frank, M. J. (1979). On the Simultaneous Associativity of f(x,y) and x+y-f(x,y). Aequationes Mathematiques, 19, 194-226. [12] Gumbel, E. J. (1960).Distributions des Valeurs Extrêmes en Plusiers Dimensions. Publications de l’Institut de. Statistique de l’Université de Paris, 9, 171-173. [13] Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press. [14] Heiberger, R. M., Holland, B. (2004). Statistical analysis and data display: an intermediate course with examples in S-plus, R, and SAS. Springer. [15] Hull, J. C. (2006). Options, Futures, And Other Derivatives, 6th ed. Pearson Prentice Hall. [16] Hull, J. C. (2007). Risk Management and Financial Institutions. Pearson Prentice Hall. [17] Joe, H. (1997). Multivariate Models and Dependence Concepts. Chapman & Hall, London. [18] Joe , H. and Xu, J. (1996). The Estimation Method of Inference Functions for Margins for Multivariate Models. Technical Report No. 166, Department of Statistics, University of British Columbia, Vancouver. [19] Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk, McGraw-Hill. [20] Khindanova, I., Rachev, S.T., and Schwartz, E. (2001). Stable Modeling of Value at Risk. Mathematical and Computer Modelling, 34, 1223-1259. [21] Kruskal, W. H. (1958). Ordinal measures of association. Journal of the American Statistical Association, 53, 814-861. [22] Mandelbrot, B. B. (1963). New Methods in Statistical Economics. J. of Political Economy, 71, 421-440. [23] McNeil, A. J., Frey, R., Embrechts, P. (2005). Quantitative Risk Management. Princeton University Press. [24] Neftci, S. N. (Spring 2000). Value at Risk Calculations, Extreme Events, and Tail Estimation. Journal of Derivatives v. 7 no. 3 p. 23-37 [25] Nelson, R. B. (1999). An Introduction to Copulas, Lecture Notes in Statistics. Springer-Verlag, New York. [26] Rachev, S. T., Schwartz, E., and Khindanova, I. (2003). Stable Modeling of Credit Risk. In Handbook of Heavy Tailed Distributions in Finance, ed. Rachev S. T., 249-328. Amsterdam: North Holland Handbooks of Finance. [27] Rachev, S. T., Menn, C., Fabozzi, F. J. (2005). Fat-Tailed and Skewed Asset Return Distributions. John Wiley & Sons. [28] Rachev, S. T., Stoyanov, S., Biglova, A., Fabozzi, F. J. (2005). An Empirical Examination of Daily Stock Return Distributions for U.S. Stocks. Data Analysis and Decision Support, Springer Series in Studies in Classification, Data Analysis and Knowledge Organization. eds. Decker, R., Schmidt-Thieme, L., and Baier, D., 269-281. [29] RiskMetrics (1995). RiskMetrics Technical Document. 3rd ed., J. P. Morgan, New York. [30] Shiryaev, A. N. (1999). Essentials of Stochastic Finance: Facts, Models, Theory. World Scientific. Singapore. [31] Smith, R. L. (1984). Threshold methods for sample extremes. In Tiago de Oliveira, J., editor, Statistical Extremes and Applications, pages 621-638. Reidel, Dordrecht. [32] Tsay, R. S. (2005). Analysis of Financial Time Series. John Wiley & Sons. [33] Zivot, E., Wang, J., (2006). Modeling financial time series with S-plus. Springer. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/24861 | - |
| dc.description.abstract | 在這篇論文中，我們應用連接函數與極端值理論配置AMD及XEROX兩間公司股票報酬的聯合分配。我們比較了一般化柏拉圖分配以及常態分配作為邊際分配的影響，並且計算95%, 99%, 99.5%, 99.9%, 99.95% 及99.99% 信賴水準的風險值。由連接函數及極端值理論所得到的風險值的估計值，不論在樣本內或樣本外的測試結果都很好。並且我們也發現風險值的估計值並不隨著柏拉圖分配門檻的選擇而有很大的變化。另一方面，常態分配作為邊際分配所得到的信賴水準99%以上的風險值則低估了實際的風險。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-08T05:57:26Z (GMT). No. of bitstreams: 1 ntu-96-R93221040-1.pdf: 1390031 bytes, checksum: aba9666e00a7d681824e3fe92f322f11 (MD5) Previous issue date: 2007 | en |
| dc.description.tableofcontents | Contents
CHAPTER 1: INTRODUCTION - 1 - CHAPTER 2: LITERATURE REVIEW - 2 - CHAPTER 3: RESEARCH METHOD - 5 - CHAPTER 4: EMPIRICAL STUDY - 27 - CHAPTER 5: CONCLUSIONS - 53 - REFERENCES - 55 - | |
| dc.language.iso | en | |
| dc.subject | 厚尾 | zh_TW |
| dc.subject | 連接函數 | zh_TW |
| dc.subject | 一般化柏拉圖分配 | zh_TW |
| dc.subject | 風險值 | zh_TW |
| dc.subject | Copula | en |
| dc.subject | Heavy Tail | en |
| dc.subject | Value at Risk | en |
| dc.subject | Generalized Pareto Distribution | en |
| dc.title | 應用Copula方法於厚尾財務資料及風險值之計算 | zh_TW |
| dc.title | The Application of Copula Methods to Heavy-Tailed Financial Data and the Computation of Value at Risk
The Application of Copula Methods to Heavy-Tailed Financial Data and the Computation of Value at Risk The Application of Copula Methods to Heavy-Tailed Financial Data and the Computation of Value at Risk | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 陳宜良(I-Liang Chern) | |
| dc.contributor.oralexamcommittee | 蘇永成(Yong-Chern Su),廖咸興(Hsien-Hsing Liao) | |
| dc.subject.keyword | 連接函數,一般化柏拉圖分配,風險值,厚尾, | zh_TW |
| dc.subject.keyword | Copula,Generalized Pareto Distribution,Value at Risk,Heavy Tail, | en |
| dc.relation.page | 57 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2007-10-31 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 數學研究所 | zh_TW |
| 顯示於系所單位： | 數學系 | |
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| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-96-1.pdf 未授權公開取用 | 1.36 MB | Adobe PDF |
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