Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets

Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets

碩士 === 國立雲林科技大學 === 財務金融系 === 90 === This study utilize White’s Reality Check bootstrap methodology (Sullivan, Timmermann, and White (1999)) to evaluate simple technical trading rules which quantifying the data-snooping bias and fully adjusting for its effect in the context of the two ful...

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Main Authors: Lin, Wei-luen, 林維倫
Other Authors: Chin-Sheng Huang
Format: Others
Language:zh-TW
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/49437852338181834999
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spelling ndltd-TW-090YUNTE3040142016-06-24T04:15:13Z http://ndltd.ncl.edu.tw/handle/49437852338181834999 Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets 技術分析、基因演算法與資料窺視─亞洲股市之實證研究 Lin, Wei-luen 林維倫 碩士 國立雲林科技大學 財務金融系 90 This study utilize White’s Reality Check bootstrap methodology (Sullivan, Timmermann, and White (1999)) to evaluate simple technical trading rules which quantifying the data-snooping bias and fully adjusting for its effect in the context of the two full universes (STW and GA rules) from which the trading rules were drawn and searched by using Genetic Algorithm. Hence, the paper presents a comprehensive test of performance across all technical trading rules examined. Apply the two group of trading rules to 31 years of daily data on the Taiwan Stock Exchange Capitalization Weighted Stock Index, and determine the effects of data-snooping. Also apply STW rules to 12 years of daily data on the Asian stock markets, and assess whether simple technical trading rules can perform better than holding cash in Asian markets. Chin-Sheng Huang 黃金生 2002 學位論文 ; thesis 72 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立雲林科技大學 === 財務金融系 === 90 === This study utilize White’s Reality Check bootstrap methodology (Sullivan, Timmermann, and White (1999)) to evaluate simple technical trading rules which quantifying the data-snooping bias and fully adjusting for its effect in the context of the two full universes (STW and GA rules) from which the trading rules were drawn and searched by using Genetic Algorithm. Hence, the paper presents a comprehensive test of performance across all technical trading rules examined. Apply the two group of trading rules to 31 years of daily data on the Taiwan Stock Exchange Capitalization Weighted Stock Index, and determine the effects of data-snooping. Also apply STW rules to 12 years of daily data on the Asian stock markets, and assess whether simple technical trading rules can perform better than holding cash in Asian markets.
author2 Chin-Sheng Huang
author_facet Chin-Sheng Huang
Lin, Wei-luen
林維倫
author Lin, Wei-luen
林維倫
spellingShingle Lin, Wei-luen
林維倫
Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
author_sort Lin, Wei-luen
title Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
title_short Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
title_full Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
title_fullStr Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
title_full_unstemmed Technical Trading Rule Performance, Genetic Algorithm, and Data Snooping: An Empirical Study of the Asian Stock Markets
title_sort technical trading rule performance, genetic algorithm, and data snooping: an empirical study of the asian stock markets
publishDate 2002
url http://ndltd.ncl.edu.tw/handle/49437852338181834999
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