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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17617完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 呂育道(Yuh-Dauh Lyuu) | |
| dc.contributor.author | Kuan-Lin Huang | en |
| dc.contributor.author | 黃冠霖 | zh_TW |
| dc.date.accessioned | 2021-06-08T00:25:37Z | - |
| dc.date.copyright | 2013-07-26 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-07-15 | |
| dc.identifier.citation | [1] Amdahl, G.. M., “Validity of The Single Processor Approach to Achieving Large-Scale Computing Capabilities”, AFIPS Conference Proceedings, No. 30, pp. 483–485, Spring 1967.
[2] Barraquand, J., Martineau, D., “Numerical Valuation of High Dimensional Multivariate American Securities”, Journal of Financial and Quantitative Analysis, Vol. 30, No. 3, pp. 383–405, 1995 Fall. [3] Black, F., Scholes, M., “The Pricing of Options and Corporate Liabilities”, Journal of Political Economy, Vol. 81, No. 3, pp. 637–654, 1973. [4] Boyle, P. P., “Options: A Monte Carlo approach”, Journal of Financial Economics, Vol. 4, No. 3, pp. 323–338, 1977. [5] Choudhury, A. R., King, A., Kumar, S., Sabharwal, Y., “Optimizations in Financial Engineering: The Least-Squares Monte Carlo method of Longstaff and Schwartz”, 23rd IEEE International Parallel & Distributed Processing Symposium, pp. 1–11, 2008. [6] Clement, E., Lamberton, D., Protter, P., “An Analysis of a Least Squares Regression Method for American Option Pricing”, Finance and Stochastics, Vol. 6, pp. 449–471, 2002. [7] Cox, J. C., Ross, S., Rubinstein, M., “Option Pricing: A Simplified Approach”, Journal of Financial Economics, No. 7, pp. 229–264, 1979. [8] Eager, D. L., Lazowska, E. D., Zahorjan, J., “Speedup versus Efficiency in Parallel Systems”, IEEE Transactions on Computers, Vol. 38, No. 3, pp. 408–423, March 1989. [9] Hull, J., Options Futures and Other Derivatives eighth edition, Pearson College Div, 2012. [10] Hull, J., White, A., “Efficient Procedures for Valuing European and American Path-dependent Options”, The Journal of Derivatives, Vol. 1, No. 1, pp. 21–31, 1993 Fall. [11] Longstaff, F. A., Schwartz, E. S., “Valuing American Options by Simulation: A Simple Least-Squares Approach”, Review of Financial Studies, Vol. 13, No. 1, pp. 113–147, 2001 spring. [12] Merton, R. C., “Theory of Rational Option Pricing”, The Bell Journal of Economics and Management Science, Vol. 4, No. 1, pp. 141–183, 1973. [13] Raymar, S. B., Zwecher, M. J., “Monte Carlo Estimation of American Call Options on the Maximum of Several Stocks”, The Journal of Derivatives, Vol. 5, No. 1, pp. 7–23, 1997 Fall. [14] Stentoft, L., “Convergence of The Least Squares Monte Carlo Approach to American Option Valuation”, Management Science, Vol. 50, No. 9, pp. 1193–1203, September 2004. [15] Tilley, J. A., “Valuing American Options in a Path Simulation Model”, Transactions on the Society of Actuaries, Vol. 45, pp. 83–104, 1993. [16] White, L. H., Asymptotic Theory for Econometricians, Academic Press, New York, 1984. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17617 | - |
| dc.description.abstract | Option pricing is an important issue in financial computing. However, the early-exercise feature of American options makes their pricing more difficult than European options. To price American options using simulation, Longstaff and Schwartz presented a simple yet powerful simulation technique, named the least-squares Monte Carlo method. Least-squares Monte Carlo simulation involves huge amounts of path simulation, which makes it difficult to compute the price in a short amount of time. To solve this problem, this thesis divides the computation paths into threads and then compares the numerical results of the strategy, the original version and the trinomial tree. The outcome shows that the division strategy does not have much impact on the prices. After the numerical evaluation of the division strategy, the least-square Monte Carlo method is parallelized and evaluated on the speedup and efficiency. The results show that the parallelization of the least-squares Monte Carlo method provides considerable speedup without sacrificing numerical accuracy. The Longstaff-Schwartz algorithm is thus amenable to parallelism. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T00:25:37Z (GMT). No. of bitstreams: 1 ntu-102-R00922018-1.pdf: 2913170 bytes, checksum: 095022bfddea7674656ac32e5819df54 (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | 謝辭 i
內容摘要 ii Abstract iii 目錄 iv 圖目錄 vi 表目錄 vii 第1章 選擇權簡介 1 1.1 選擇權 1 1.2 美式選擇權評價 4 第2章 文獻回顧 6 2.1 蒙地卡羅模擬法 6 2.2 蒙地卡羅模擬法於美式選擇權上的應用 8 2.3 最小平方蒙地卡羅法 9 2.4 最小平方蒙地卡羅法的實例 13 第3章 實驗設計 19 3.1 路徑模擬 19 3.2 最小平方蒙地卡羅法實作 20 3.3 最小平方法 20 3.4 平行處理 23 第4章 實驗結果 26 4.1 分散工作運算結果評估 26 4.1.1 一次多項式回歸 27 4.1.2 二次多項式回歸 29 4.1.3 三次多項式回歸 32 4.1.4 實驗結果討論 35 4.2 平行化加速程度評估 36 第5章 研究結論 54 參考文獻 56 | |
| dc.language.iso | zh-TW | |
| dc.title | 最小平方蒙地卡羅法之平行化效能評估 | zh_TW |
| dc.title | Evaluation of Parallelization of the Least-Squares Monte Carlo Method | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 金國興,王釧茹 | |
| dc.subject.keyword | 最小平方蒙地卡羅法,平行化, | zh_TW |
| dc.subject.keyword | Least-squares Monte Carlo,parallelization,trinomial Tree, | en |
| dc.relation.page | 57 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2013-07-15 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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