An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks
碩士 === 國立交通大學 === 資訊管理研究所 === 86 === Traditionally, the Black-Scholes model is a useable evaluation method for optionpricing. However, there exist some impractical assumptions in the Black-Scholes Model. Therefore, the evaluated prices would be reconsider...
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ndltd-TW-086NCTU03960172015-10-13T11:06:15Z http://ndltd.ncl.edu.tw/handle/75916254603267408126 An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks 運用類神經網路預測選擇權評價模式中股票價格波動率之實證研究 Chung, Chenz-Chi 鍾澄吉 碩士 國立交通大學 資訊管理研究所 86 Traditionally, the Black-Scholes model is a useable evaluation method for optionpricing. However, there exist some impractical assumptions in the Black-Scholes Model. Therefore, the evaluated prices would be reconsidered that may generated from the practiced data. Usually, in all input variables considered from B-S model, the volatility is the most difficulty part to understand. Thus, if a practical model would be applied, the volatility should be precisely estimated as the first step to be done.However recent studies of the field in the artificial intelligence reflect that neural networks have the ability of learning and performing high-speed calculations. Also with it''s parallel processing and tolerance of faults, it''s prediction ability has become gradually an accepted level. So this research will attempt to forecast the future volatility of prices by neural networks.This empirical research is to simulate options transactions that randomly selected from 30 companies in Taiwan. In this research, the neural network with genetic algorithm should be applied to forecast the volatility of each stock and the result would be compared with the output from the traditional B-S method. The research periods is starting from 1995 to 1997 three years.The research shows that the output from the forecast module by the neural network is superior to that from the traditional B-S method no matter in interpreter capability or in practical hedge strategy operation. This means that the new method provided in this thesis can assist the investor to make more precisely investment decision and hedge strategy. An-Pin Chen 陳安斌 1998 學位論文 ; thesis 60 zh-TW |
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碩士 === 國立交通大學 === 資訊管理研究所 === 86 === Traditionally, the Black-Scholes model is a useable evaluation
method for optionpricing. However, there exist some impractical
assumptions in the Black-Scholes Model. Therefore, the evaluated
prices would be reconsidered that may generated from the
practiced data. Usually, in all input variables considered from
B-S model, the volatility is the most difficulty part to
understand. Thus, if a practical model would be applied, the
volatility should be precisely estimated as the first step to be
done.However recent studies of the field in the artificial
intelligence reflect that neural networks have the ability of
learning and performing high-speed calculations. Also with it''s
parallel processing and tolerance of faults, it''s prediction
ability has become gradually an accepted level. So this research
will attempt to forecast the future volatility of prices by
neural networks.This empirical research is to simulate options
transactions that randomly selected from 30 companies in Taiwan.
In this research, the neural network with genetic algorithm
should be applied to forecast the volatility of each stock and
the result would be compared with the output from the
traditional B-S method. The research periods is starting from
1995 to 1997 three years.The research shows that the output from
the forecast module by the neural network is superior to that
from the traditional B-S method no matter in interpreter
capability or in practical hedge strategy operation. This means
that the new method provided in this thesis can assist the
investor to make more precisely investment decision and hedge
strategy.
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author2 |
An-Pin Chen |
author_facet |
An-Pin Chen Chung, Chenz-Chi 鍾澄吉 |
author |
Chung, Chenz-Chi 鍾澄吉 |
spellingShingle |
Chung, Chenz-Chi 鍾澄吉 An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
author_sort |
Chung, Chenz-Chi |
title |
An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
title_short |
An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
title_full |
An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
title_fullStr |
An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
title_full_unstemmed |
An Empirical Study on Forecasting the Stock Volatility in the Option Pricing Model by Using the Neural Networks |
title_sort |
empirical study on forecasting the stock volatility in the option pricing model by using the neural networks |
publishDate |
1998 |
url |
http://ndltd.ncl.edu.tw/handle/75916254603267408126 |
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