美式選擇權之數值演算法

碩士 === 輔仁大學 === 金融研究所 === 89 === Abstract This article proposes a new numerical algorithm for American option, adopting the concept of Broadie and Glasserman [1997]. For the reason that there is no unbiased simulation estimator of American option values, we use the confidence intervals th...

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Main Author: 邱紀尊
Other Authors: 李泰明
Format: Others
Language:zh-TW
Published: 2001
Online Access:http://ndltd.ncl.edu.tw/handle/15646357570145580333
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spelling ndltd-TW-089FJU002140062016-07-06T04:10:41Z http://ndltd.ncl.edu.tw/handle/15646357570145580333 美式選擇權之數值演算法 邱紀尊 碩士 輔仁大學 金融研究所 89 Abstract This article proposes a new numerical algorithm for American option, adopting the concept of Broadie and Glasserman [1997]. For the reason that there is no unbiased simulation estimator of American option values, we use the confidence intervals that are generated by two estimates, one biased high and the other biased low, of assets price based on random samples of future state trajectories, and these confidence intervals would cover the correct option values. This article implements the ideal of finite difference method which uses the grid points to replace the whole tree model, and integrates the branches structure of the tree system. Combining finite difference method with tree model, simulation time can be shortened substantially. We obtain close results, and evaluate American option successfully. At the same time, we can compute the option prices of all the gird points, which is distinguishable from other usual simulation tree obtaining only one option price. For path-dependent American option, we adopt the nature of time reverse of Brownian motion to overcome this problem. However, the key point of accuracy is the exploitation of interpolation. If we use two-point interpolation, the numerical results show a potential error caused by approximation. Moreover, this error will accumulate in backward-simulation process, and cause high and low estimates increase abnormally. This property also influences the accuracy of confidence intervals and point estimates. Especially after adopting common random number, although it can shorten simulation time dramatically, it also makes the error from two-point interpolation accumulate over time. If we change two-point interpolation into cubic spline interpolation, we can improve preceding error and our model can accommodate both speed and accuracy. 李泰明 蔡麗茹 2001 學位論文 ; thesis 0 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 輔仁大學 === 金融研究所 === 89 === Abstract This article proposes a new numerical algorithm for American option, adopting the concept of Broadie and Glasserman [1997]. For the reason that there is no unbiased simulation estimator of American option values, we use the confidence intervals that are generated by two estimates, one biased high and the other biased low, of assets price based on random samples of future state trajectories, and these confidence intervals would cover the correct option values. This article implements the ideal of finite difference method which uses the grid points to replace the whole tree model, and integrates the branches structure of the tree system. Combining finite difference method with tree model, simulation time can be shortened substantially. We obtain close results, and evaluate American option successfully. At the same time, we can compute the option prices of all the gird points, which is distinguishable from other usual simulation tree obtaining only one option price. For path-dependent American option, we adopt the nature of time reverse of Brownian motion to overcome this problem. However, the key point of accuracy is the exploitation of interpolation. If we use two-point interpolation, the numerical results show a potential error caused by approximation. Moreover, this error will accumulate in backward-simulation process, and cause high and low estimates increase abnormally. This property also influences the accuracy of confidence intervals and point estimates. Especially after adopting common random number, although it can shorten simulation time dramatically, it also makes the error from two-point interpolation accumulate over time. If we change two-point interpolation into cubic spline interpolation, we can improve preceding error and our model can accommodate both speed and accuracy.
author2 李泰明
author_facet 李泰明
邱紀尊
author 邱紀尊
spellingShingle 邱紀尊
美式選擇權之數值演算法
author_sort 邱紀尊
title 美式選擇權之數值演算法
title_short 美式選擇權之數值演算法
title_full 美式選擇權之數值演算法
title_fullStr 美式選擇權之數值演算法
title_full_unstemmed 美式選擇權之數值演算法
title_sort 美式選擇權之數值演算法
publishDate 2001
url http://ndltd.ncl.edu.tw/handle/15646357570145580333
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