Applying the Control Variate Technique to Numerical Option Pricing Models

碩士 === 國立中央大學 === 財務管理研究所 === 89 === For many complex options, analytical solutions are not available. In these cases a Monte Carlo simulation is an important numerical method. In its basic form, however, the Monte Carlo simulation is computationally inefficient, the control variate technique can be...

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Main Authors: Cheng-ming Chu, 屈誠銘
Other Authors: San-Lin Chang
Format: Others
Language:en_US
Published: 2001
Online Access:http://ndltd.ncl.edu.tw/handle/25161408985775228457
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spelling ndltd-TW-089NCU003050092016-01-29T04:28:17Z http://ndltd.ncl.edu.tw/handle/25161408985775228457 Applying the Control Variate Technique to Numerical Option Pricing Models 控制變數法在數值選擇權評價模型之應用分析 Cheng-ming Chu 屈誠銘 碩士 國立中央大學 財務管理研究所 89 For many complex options, analytical solutions are not available. In these cases a Monte Carlo simulation is an important numerical method. In its basic form, however, the Monte Carlo simulation is computationally inefficient, the control variate technique can be used to improve the efficiency of a Monte Carlo simulation. This paper presents a principle for finding better control variates when considering an option. A good control variate has to satisfy two conditions: The first is that a good control variate satisfies the same PDE satisfied by the target option. The second is that the boundary condition for the control variate is similar to the boundary condition for the target option. Options under consideration in this paper include American put options, barrier options, Asian options, and spread options. The result shows that a good control variate can improve the efficiency of the simulation dramatically and a good control variate can be differentiated from a bad control variate in a Monte Carlo simulation. San-Lin Chang 張森林 2001 學位論文 ; thesis 38 en_US
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description 碩士 === 國立中央大學 === 財務管理研究所 === 89 === For many complex options, analytical solutions are not available. In these cases a Monte Carlo simulation is an important numerical method. In its basic form, however, the Monte Carlo simulation is computationally inefficient, the control variate technique can be used to improve the efficiency of a Monte Carlo simulation. This paper presents a principle for finding better control variates when considering an option. A good control variate has to satisfy two conditions: The first is that a good control variate satisfies the same PDE satisfied by the target option. The second is that the boundary condition for the control variate is similar to the boundary condition for the target option. Options under consideration in this paper include American put options, barrier options, Asian options, and spread options. The result shows that a good control variate can improve the efficiency of the simulation dramatically and a good control variate can be differentiated from a bad control variate in a Monte Carlo simulation.
author2 San-Lin Chang
author_facet San-Lin Chang
Cheng-ming Chu
屈誠銘
author Cheng-ming Chu
屈誠銘
spellingShingle Cheng-ming Chu
屈誠銘
Applying the Control Variate Technique to Numerical Option Pricing Models
author_sort Cheng-ming Chu
title Applying the Control Variate Technique to Numerical Option Pricing Models
title_short Applying the Control Variate Technique to Numerical Option Pricing Models
title_full Applying the Control Variate Technique to Numerical Option Pricing Models
title_fullStr Applying the Control Variate Technique to Numerical Option Pricing Models
title_full_unstemmed Applying the Control Variate Technique to Numerical Option Pricing Models
title_sort applying the control variate technique to numerical option pricing models
publishDate 2001
url http://ndltd.ncl.edu.tw/handle/25161408985775228457
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