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研究生:吳英杰
研究生(外文):Ying-chieh Wu
論文名稱:跳躍擴散模型與風險值之應用
論文名稱(外文):Study on Diffusion-Jump Models and their Applications on VaR
指導教授:黃銘欽黃銘欽引用關係
指導教授(外文):Min-Ching Huang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:統計學系碩博士班
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:37
中文關鍵詞:跳躍擴散模型擔保維持率信用交易風險值
外文關鍵詞:Diffusion-Jump ModelMargin ratioMargin tradingVaR
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本論文主要以風險值的觀點探討現行信用交易120%最低擔保維持率之適切性。利用跳躍擴散模型捕捉股價報酬率偏態與高狹峰的特性,常態擴散-均勻跳躍模型為配適較佳的股價報酬率模型;根據常態擴散-均勻跳躍模型進一步分析現行最低擔保維持率的適切性,實證發現各類股指數在持有期間兩天的擔保維持率臨界值皆低於現行的120%最低擔保維持率,表示台灣現行的最低擔保維持率足以涵蓋證券金融公司面對信用戶的違約風險。
This thesis explores the rational for the 120% lowest margin ratio on securities margin trading using VaR. Firstly, we apply diffusion- jump model to catch skewness and leptokurtic feature for returns. The normal-diffusion with uniform-jump model has better capability to fit the distribution of returns. This thesis also utilizes the normal-diffusion with uniform-jump model to carry out feasibility studies under the current lowest margin ratio. The empirical results show that 120% cash position holding can cover the default risk of financial institutions.
目錄………………………………………………………………………I
表目錄…………………………………………………………………III
圖目錄…………………………………………………………………IV
第一章 緒論……………………………………………………………1
第一節 研究背景………………………………………………………1
第二節 研究動機與目的………………………………………………1
第三節 論文結構………………………………………………………3
第四節 研究流程………………………………………………………4
第二章 文獻回顧………………………………………………………5
第一節 風險值概述……………………………………………………5
第二節 風險值相關文獻………………………………………………6
第三節 信用交易………………………………………………………6
第四節 資產報酬分配…………………………………………………7
第三章 研究方法………………………………………………………9
第一節 模型介紹………………………………………………………9
一、一般擴散過程………………………………………………………9
二、跳躍擴散過程……………………………………………………10
三、跳躍大小- 對數常態分配………………………………………11
四、跳躍大小- 對數均勻分配………………………………………12
五、模型比較…………………………………………………………12
第二節 風險值…………………………………………………………13
一、風險值基本概念…………………………………………………13
二、風險值與擔保維持率臨界值之轉換……………………………14
第四章 實證分析………………………………………………………15
第一節 資料來源與基本統計量分析…………………………………15
第二節 參數估計與模型比較…………………………………………16
第三節 風險值與擔保維持率…………………………………………22
第五章 結論與建議……………………………………………………24
第一節 結論……………………………………………………………24
第二節 建議……………………………………………………………24
參考文獻………………………………………………………………26
附錄(A)………………………………………………………………29
附錄(B)………………………………………………………………31
附錄(C)………………………………………………………………34
一、中文
1.王儷容、鄭思因,我國證券市場信用交易制度,中華經濟研究院,民國九十年十月。
2.方文碩、孫穎慶(2000),融資、融券與股票市場關聯性探討,臺灣銀行季刊,51(3),216-245。
3.李訓民(1996),揭開美國保證金交易制度之面紗—兼論我國信用交易制度之比較研究,證交資料,410,20-31。
4.周恆志(2002),以涉險值模型初步探討風險值台灣股票市場信用交易的最低擔保維持率,華岡經濟論叢,2(1),1-27。
5.姚海青、杜化宇、陳盛源(1999),我國股票市場融資比率與融券保證金成數調整對股價波動性影響之研究,證券市場發展季刊,11(2),129-154。
6.陳逸君(2003),以風險值的觀點探討現行信用交易之最低擔保維持率,淡江大學企業管理學系碩士論文。
7.蘇松欽(1999),美、日、中證券信用交易制度之比較,台研金融與投資,12,28-43。

二、英文
1.Akaike, H. (1981), “Likelihood of a Model and Information Criteria,” Journal of Econometrics 16, 3-14.
2.Akgiray, V. and G. Booth, (1986), “Stock Price Processes with Discontinuous Time Paths: An Empirical Examination,” Financial Review, Vol. 21, pp.163-184.
3.Bali, T. G. and N. Cakici, (2004), ”Value at Risk and Expected Stock Returns,” Financial Analysts Journal, Vol.60, pp.57-73.
4.Ball, C. A. and W. N. Torous, (1985), ”On Jump in Common Stock Prices and Their Impact on Call Option Pricing,” The Journal of Finance, 40(1), 155-173.
5.Beder, T. S. (1995), ”VAR: Seductive but Dangerous,” Financial Analysts Journal, Vol.51, Iss.5, pp.12-24.
6.Bollerslev, T. (1987a), “A Conditional Heteroskedasticity Time Series Model for Speculative Prices and Rate of Return,” Review of Economic and Statistics 69, 542-547.
7.Bollerslev, T. (1987b), “On the Correlation Structure for the Generalized Autoregressive Conditional Heteroskedasticity Process,” Journal of Time Series Analysis, 9:2, 21-131.
8.Duffie, D. and J. Pan, (2001), “Analytical Value at Risk with Jumps and Credit Risk,” Finance and Stochastics, 5(2), 155-180.
9.Engle, R. F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation,” Econometrica, 50, 987-1008.
10.Fama, E. F. (1965), “The Behavior of Stock Market Prices,” Journal of Business, Vol. 38, pp. 34-105.
11.Hanson, F. B. and Z. Zhu, (2004), “Comparison of Market Parameters for Jump-Diffusion Distributions Using Multinomial Maximum Likelihood Estimation,” Proceedings of 43nd IEEE conference on Decision and Control, pp. 3913-3924.
12.Black, F. and M. Scholes, (1973), “The Pricing of Options and Corporate Liabilities,” Journal of Political Economy, Vol.81, 637-659.
13.Fornari, F. and A. Mele, (1995), “Sign- and Volatility-Switching ARCH Models:Theory and Applications to International Stock Markets,” University of Paris X, Working Paper, No. 251.
14.Glosten, L.,R. Jagannathan, and D. Runkle, (1993), “On the Relation Between the Expected Value and the Volatility on the Nominal Excess Returns on Stocks,” Journal of Finance, 48, 1779-1801.
15.Yan, G. and F. B. Hanson, (2006), “Option Pricing for a Stochastic Volatility Jump-Diffusion Model with Log-Uniform Jump-Amplitudes,” Proc. Amer. Control Conf., pp.2989-2994.
16.Jorion, P. (1996), “Risk2:Measuring the Risk in Value at Risk,” Financial Analysis Journal, 52, 47-56.
17.Ju, X. and N. D. Pearson, (2000), “Using Value-at-Risk to Control Risk Taking:How Wrong Can You Be,” Journal of Risk, Vol1.1, pp.5-36.
18.Kon, S. J., (1984), “Models of Stock Returns: A Comparison,” Journal of Finance, Vol. 39, pp. 147-165.
19.Liu, S. M. and B. W. Brorsen, (1992), “Maximum Likelihood Estimation of the Stable Distribution with a Time-Varying Scale Parameter,” mimeo, Department of Economics, Oklahoma State University.
20.Mandelbrot, B. (1963), “New Method in Statistical Economics,” Journal of Political Economy, Vol. 71, pp. 421-440.
21.McDonald, J. B. and Y. J. Xu, (1995), “A Generalization of the Beta Distribution with Applications,” Journal of Econometrics, 66, 133-152.
22.Merton, R. C. (1976), “Option Pricing When Underlying Stock Returns Are Discontinuous,” Journal of Financial Economics, Vol. 3, pp. 125-144.
23.Nelson, D. (1991) “Conditional Heteroskedasticity in Asset Returns:A New Approach,” Econometrica, 59, 347-70.
24.Wang, K. L., C. Fawson, C. B. Barrett, and J. McDonald, (2001), “A Flexible Parametric GARCH Model with an Application to Exchange Rates,” Journal of Applied Econometrics, 16:4, 521-536.
25.Zakoian, J. M. (1994) “Threshold Heteroskedastic Models,” Journal of Economic Dynamics and Control 18, 931-955.
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