| 研究生: |
林怡廷 I-Ting Lin |
|---|---|
| 論文名稱: |
降低變異數演算法在不同選擇權評價上的應用 Variance Reduction Algorithm for Pricing Various Options |
| 指導教授: |
張傳章
Chuang-Chang Chang |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
理學院 - 統計研究所 Graduate Institute of Statistics |
| 畢業學年度: | 96 |
| 語文別: | 英文 |
| 論文頁數: | 40 |
| 中文關鍵詞: | 重設選擇權 、障礙選擇權 、偏誤縮減 、最小平方蒙地卡羅法 |
| 外文關鍵詞: | barrier option, bias reduction, least squares Monte Carlo simulation, reset option |
| 相關次數: | 點閱:11 下載:0 |
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本篇論文是結合Longstaff and Schwartz (2001) 提出的最小平方法與Huge and Rom-Poulsen (2004) 提出降低變異數 (variance reduction) 的技巧來評價美式選擇權。Longstaff and Schwartz (2001) 使用最小平方法估計美式選擇權的持有價值,Huge and Rom-Poulsen (2004) 則是利用最小平方法計算標的資產的價格。當標的資產須用蒙地卡羅的方式模擬時,計算選擇權的報酬會產生偏誤的現象。我們應用這個演算法分別去估計標的資產為債券的障礙選擇權 (barrier option) 與重設選擇權 (reset option) 的價格,並且以數值模擬的結果呈現出降低變異數的效果。
This paper develops an algorithm that combines the Longstaff and Schwartz (2001) simulation algorithm and the variance reduction technique proposed in Huge and Rom-Poulsen (2004) to simulate American-style option prices on securities such that their prices can be found by the Monte Carlo simulations. Longstaff and Schwartz (2001) used the least squares method to estimate the optimal exercise boundary of American options, Huge and Rom-Poulsen (2004) used the same method to calculate the price of underlying security. In this paper, we apply this algorithm to value various options, such as barrier option and reset option. Bias reduction is also involved in algorithm, since we know that using simulated prices of the underlying security to compute option payoff causes an upward bias in option prices. We use numerical results to show that this algorithm can provide significant improvement on efficiency and accuracy for pricing barrier bond option and reset bond option.
[1] Andersen, L., “A Simple Approach to the Pricing of Bermudan Swaptions in the Multi-Factor Libor Market Model”, Journal of Computational Finance, Vol. 3, No. 2, pp. 5-32, 2001.
[2] Barone-Adesi, G. and R. Whaley, “Efficient Analytic Approximation of American Option Values”, Journal of Finance, Vol. 42, pp. 301-320, 1987.
[3] Barraquand J. and D. Martineau, “Numerical Valuation of High Dimensional Multivariate American Securities”, Journal of Financial and Quantitative Analysis, Vol. 30, No. 3, pp. 383-405, 1995.
[4] Black, F. and M. Scholes, “The Pricing of Options and Corporate Liabilities”, Journal of Political Economy, Vol. 81, No. 3, pp. 637-654, 1973.
[5] Boyle, P. P., “A Monte Carlo Approach”, Journal of Financial Economics, Vol. 4, pp. 323-338, 1977.
[6] Boyle, P., J. Evnine and S. Gibbs, “Numerical Evaluation of Multivariate Contingent Claims”, Review of Financial Studies, Vol. 2, pp. 241-250, 1989.
[7] Brennan, M. and E. Schwartz, “Finite Difference Methods and Jump Processes Arising in the Pricing of the Contingent Claims: A Synthesis”, Journal of Financial and Quantitative Analysis, Vol. 13, No. 3, pp. 461-474, 1978.
[8] Broadie,M. and P. Glasserman, “Estimating Security Price Derivatives Using Simulation”, Management Science, Vol. 42, No. 2, pp. 269-285, 1996.
[9] Broadie, M. and P. Glasserman, “Pricing American-Style Securities Using Simulation”, Journal of Economic Dynamics and Control, Vol. 21, pp. 1323-1352, 1997.
[10] Broadie, M., P. Glasserman and S. Kou, “A Continuity Correction for Discrete Barrier Options”, Mathematical Finance, Vol. 7, No.4, pp. 325-248, 1997
[11] Carriere, J. F., “Valuation of Early-Exercise Price of Options Using Simulations and nonparametric regression”, Insurance: Mathematics and Economics, Vol. 19, pp. 19-30, 1996.
[12] Carverhill, A. and K. Pang, “Efficient and Flexible Bond Option Valuation in the Heath-Jarrow-Morton framework”, Journal of Fixed Income, Vol. 5, No. 2, pp. 70-77, 1995.
[13] Cox, J., J. Ingersoll and S. Ross, “An Intertemporal General Equilibrium Model of Asset Price”, Econometrica, Vol. 53, No. 2, pp. 363-384, 1985
[14] Cox, J., S. Ross, and M. Rubinstein, “Option Pricing: A Simplified Approach”, Journal of Financial Economics, Vol. 7, No. 3, pp. 229-264, 1979.
[15] Clewlow,L. and A. Carverhill, “On the Simulation of Contingent Claims”, Journal of Derivatives, Vol. 2, No. 2, pp. 66-74, 1994.
[16] Fishman,G. and B. Huang, “Antithetic Variates Revisited”, Communications of the ACM, Vol. 26, No. 11, pp. 964-971, 1983.
[17] Gamba, A. and L. Trigeorgis, “A Log-Transformed Binomial Lattice Extension for Multi-Dimensional Option Problems”, Conference Proceedings, 5th Annual International Conference on Peal Options, 2001.
[18] Glasserman, P., Monte Carlo Methods in Financial Engineering.1st ed., Springer-Verlag New York, 2004.
[19] Glasserman,P. and J. Staum, “Conditioning on one-step survival for barrier option simulations”, Operations Research, Vol. 49, No. 6, pp. 923-937, 2001.
[20] Glasserman,P., P. Heidelberger, and P. Shahabuddin, “Asymptotically Optimal Importance Sampling and Stratification for Path-Dependent Options”, Mathematical Finance, Vol. 9, No. 2, pp. 117-152, 1999.
[21] Glasserman,P., P. Heidelberger, and P. Shahabuddin, “Importance Sampling in the Heath-Jarrow-Morton Framework”, Journal of Derivatives, Vol. 7, No. 1, pp. 32-50, 1999.
[22] Hilliard,J., A. Schwartz, and A. Tucker, “Bivariate Binomial Options Pricing with Generalized Interest Rate Processes”, Journal of Financial Research, Vol. XIX, No. 4, pp 585-602, 1996.
[23] Huge, B. and N. Rom-Poulsen, “Bias Reduction in European Option Pricing”, Working Paper, Copenhagen Business School, 2004.
[24] Huge, B. and N. Rom-Poulsen, “An Algorithm for Simulating Bermudan Option Prices on Simulated Asset Prices”, Journal of Derivatives, Vol. 14, No. 4, pp. 64-85, 2007.
[25] Hull, J. and A. White, “The Pricing of Options on Assets with Stochastic Volatilities”, Journal of Finance, Vol. 42, No. 2, pp. 281-300, 1987.
[26] Kemna, A. and A. Vorst, “A Pricing Method for Options Based on Average Asset Values”, Journal of Banking and Finance, Vol. 14, No. 1, pp. 113-129, 1990.
[27] Longstaff, F. and E. Schwartz, “Valuing American Options by Simulation: A Simple Least-Squares Approach”, The Review of Financial Studies, Vol. 14, No. 1, pp. 113-147, 2001.
[28] MacMillan, L. W., “Analytic Approximation for the American Put Option”, Advances in Futures and Options Research, Vol. 1, pp. 119-139, 1986.
[29] Rubinstein, R., G. Samorodnitsky, and M. Shaked, “Antithetic Variates, Multivariate Dependence and Simulation of Stochastic Systems”, Management Science, Vol. 31, No. 1, pp. 66-77, 1985.
[30] Tilley, J. A., “Valuing American Options in a Path Simulation Model”, Transactions of the Society of Actuaries, Vol. 45, pp. 83-104, 1993.
[31] Trigeorgis, L., “A Log-Transformed Binomial Numerical Analysis Method for Valuing Complex Multi-Option Investments”, Journal of Financial and Quantitative Analysis, Vol. 26, pp. 309-326, 1991.
[32] Tsitsiklis, J. and B. Van Roy, “Regression Methods for Pricing Complex American-Style Options”, IEEE Transactions on Neural Network, Vol. 12, No. 4, pp. 694-703, 2001.