The Studies of Option Pricing with Stochastic Volatility Model

碩士 === 輔仁大學 === 金融研究所 === 93 === Abstract This study applies the efficient method of moments to estimate the parameters of stochastic volatility model. According to the estimate result, the study applies Monte Carlo simulation with common random number to do the Taiwan Index Option empiri...

Full description

Bibliographic Details
Main Authors: Lu I Liang, 呂一良
Other Authors: Tai-Ming Lee
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/12974699983940335366
id ndltd-TW-093FJU00214001
record_format oai_dc
spelling ndltd-TW-093FJU002140012016-06-13T04:17:14Z http://ndltd.ncl.edu.tw/handle/12974699983940335366 The Studies of Option Pricing with Stochastic Volatility Model 隨機波動模型之選擇權評價與實證 Lu I Liang 呂一良 碩士 輔仁大學 金融研究所 93 Abstract This study applies the efficient method of moments to estimate the parameters of stochastic volatility model. According to the estimate result, the study applies Monte Carlo simulation with common random number to do the Taiwan Index Option empirical analysis. The stochastic volatility models are divided into two parts: one is the independence between cash market price and volatility (applying the stochastic volatility model of Hull & White, 1987), the other is the dependence between cash market price and volatility which considers mean reverting effect. The empirical result shows that the performance of the independence between cash market price and volatility stochastic volatility model is better than Black-Scholes model, but the difference is little. On the other hand, the performance of the dependence between cash market price and volatility which considers mean reverting effect stochastic volatility model is much better than Black-Scholes model and the independence between cash market price and volatility stochastic volatility model. Tai-Ming Lee Li-Ju Tsai 李泰明 蔡麗茹 2005 學位論文 ; thesis 50 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 輔仁大學 === 金融研究所 === 93 === Abstract This study applies the efficient method of moments to estimate the parameters of stochastic volatility model. According to the estimate result, the study applies Monte Carlo simulation with common random number to do the Taiwan Index Option empirical analysis. The stochastic volatility models are divided into two parts: one is the independence between cash market price and volatility (applying the stochastic volatility model of Hull & White, 1987), the other is the dependence between cash market price and volatility which considers mean reverting effect. The empirical result shows that the performance of the independence between cash market price and volatility stochastic volatility model is better than Black-Scholes model, but the difference is little. On the other hand, the performance of the dependence between cash market price and volatility which considers mean reverting effect stochastic volatility model is much better than Black-Scholes model and the independence between cash market price and volatility stochastic volatility model.
author2 Tai-Ming Lee
author_facet Tai-Ming Lee
Lu I Liang
呂一良
author Lu I Liang
呂一良
spellingShingle Lu I Liang
呂一良
The Studies of Option Pricing with Stochastic Volatility Model
author_sort Lu I Liang
title The Studies of Option Pricing with Stochastic Volatility Model
title_short The Studies of Option Pricing with Stochastic Volatility Model
title_full The Studies of Option Pricing with Stochastic Volatility Model
title_fullStr The Studies of Option Pricing with Stochastic Volatility Model
title_full_unstemmed The Studies of Option Pricing with Stochastic Volatility Model
title_sort studies of option pricing with stochastic volatility model
publishDate 2005
url http://ndltd.ncl.edu.tw/handle/12974699983940335366
work_keys_str_mv AT luiliang thestudiesofoptionpricingwithstochasticvolatilitymodel
AT lǚyīliáng thestudiesofoptionpricingwithstochasticvolatilitymodel
AT luiliang suíjībōdòngmóxíngzhīxuǎnzéquánpíngjiàyǔshízhèng
AT lǚyīliáng suíjībōdòngmóxíngzhīxuǎnzéquánpíngjiàyǔshízhèng
AT luiliang studiesofoptionpricingwithstochasticvolatilitymodel
AT lǚyīliáng studiesofoptionpricingwithstochasticvolatilitymodel
_version_ 1718303481428705280