Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model

博士 === 國立臺北大學 === 企業管理學系 === 92 === Although the profitability of contrarian is obviously related to the Mean-Reverting Behavior of return, few theses have explored it in terms of dynamic time series but elaborated on where it comes forth, how winner-loser investment combinations are successfully se...

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Main Authors: Lu, Chih-Chiang, 盧智強
Other Authors: Goo, Yeong-Jia
Format: Others
Language:zh-TW
Published: 2004
Online Access:http://ndltd.ncl.edu.tw/handle/33486572309531669580
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spelling ndltd-TW-092NTPU01211322015-10-13T13:27:33Z http://ndltd.ncl.edu.tw/handle/33486572309531669580 Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model 報酬率均值不對稱反轉型態、跨市場效應與反向投資策略之研究-ANST-GARCH模型 Lu, Chih-Chiang 盧智強 博士 國立臺北大學 企業管理學系 92 Although the profitability of contrarian is obviously related to the Mean-Reverting Behavior of return, few theses have explored it in terms of dynamic time series but elaborated on where it comes forth, how winner-loser investment combinations are successfully set up, or why difference persists in return calculation. This paper stands out in that it adopts time series ANST-GARCH model, which features a leverage effect in both conditional mean and conditional variance equations, to investigate whether asymmetric reverting pattern can be developed in monthly, weekly, and daily excess return and in volatility dynamic process of TSEC, OTC, TAIEX future markets, to examine the factors behind it, and to further established it as one of the sources of contrarian. In this paper, a great effort also goes to fashion a bivariate ANST-GARCH model to analyze if, in each two of the 3 markets, the dynamic process of daily excess return exhibits autocorrelation or volatility asymmetric reverting pattern and if this pattern exists in inter-market transmission and volatility spillover. The results are as follows: 1.All monthly, weekly, and daily excess returns for both TSEC and OTC show persistent asymmetric reverting pattern while only daily excess return for TAIEX future shows the same pattern. Besides, leverage effect goes with the volatility of all series except for monthly excess return of TAIEX future. 2.Under time varying rational expectation hypothesis, the daily excess return for both TSEC and OTC and the weekly excess return for listed stocks still display asymmetric reverting pattern. The asymmetric return pattern of daily excess return for all three markets and the weekly return for OTC can be explained by rational expectation hypothesis. 3.The empirical relationship between data frequency interval and volatility effect is highly sensitive, where the dynamic process speed varies with the interval. 4.When factors like Jan. & Feb. effect, the day-of-the-week effect or trade volume rate is considered, the asymmetric reverting pattern varies with data frequency interval and market efficiency. 5.A month-interval is recommended for contrarian in TSEC and OTC, whereas a shorter daily strategy is preferred for TAIEX future operation. 6.When contrarian is practiced on a daily basis, the inter-market data transmission and spillover effect on asymmetry can still be a reference although with less strength and speed than on a monthly or weekly basis. When TSEC is targeted the prior TAIEX future return over positive information can serve as a leading indicator. As for TAIEX future investment the explainability (predictability) of return asymmetry over either positive or negative information for TSEC and OTC can be put into consideration. Goo, Yeong-Jia 古永嘉 2004 學位論文 ; thesis 163 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 博士 === 國立臺北大學 === 企業管理學系 === 92 === Although the profitability of contrarian is obviously related to the Mean-Reverting Behavior of return, few theses have explored it in terms of dynamic time series but elaborated on where it comes forth, how winner-loser investment combinations are successfully set up, or why difference persists in return calculation. This paper stands out in that it adopts time series ANST-GARCH model, which features a leverage effect in both conditional mean and conditional variance equations, to investigate whether asymmetric reverting pattern can be developed in monthly, weekly, and daily excess return and in volatility dynamic process of TSEC, OTC, TAIEX future markets, to examine the factors behind it, and to further established it as one of the sources of contrarian. In this paper, a great effort also goes to fashion a bivariate ANST-GARCH model to analyze if, in each two of the 3 markets, the dynamic process of daily excess return exhibits autocorrelation or volatility asymmetric reverting pattern and if this pattern exists in inter-market transmission and volatility spillover. The results are as follows: 1.All monthly, weekly, and daily excess returns for both TSEC and OTC show persistent asymmetric reverting pattern while only daily excess return for TAIEX future shows the same pattern. Besides, leverage effect goes with the volatility of all series except for monthly excess return of TAIEX future. 2.Under time varying rational expectation hypothesis, the daily excess return for both TSEC and OTC and the weekly excess return for listed stocks still display asymmetric reverting pattern. The asymmetric return pattern of daily excess return for all three markets and the weekly return for OTC can be explained by rational expectation hypothesis. 3.The empirical relationship between data frequency interval and volatility effect is highly sensitive, where the dynamic process speed varies with the interval. 4.When factors like Jan. & Feb. effect, the day-of-the-week effect or trade volume rate is considered, the asymmetric reverting pattern varies with data frequency interval and market efficiency. 5.A month-interval is recommended for contrarian in TSEC and OTC, whereas a shorter daily strategy is preferred for TAIEX future operation. 6.When contrarian is practiced on a daily basis, the inter-market data transmission and spillover effect on asymmetry can still be a reference although with less strength and speed than on a monthly or weekly basis. When TSEC is targeted the prior TAIEX future return over positive information can serve as a leading indicator. As for TAIEX future investment the explainability (predictability) of return asymmetry over either positive or negative information for TSEC and OTC can be put into consideration.
author2 Goo, Yeong-Jia
author_facet Goo, Yeong-Jia
Lu, Chih-Chiang
盧智強
author Lu, Chih-Chiang
盧智強
spellingShingle Lu, Chih-Chiang
盧智強
Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
author_sort Lu, Chih-Chiang
title Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
title_short Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
title_full Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
title_fullStr Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
title_full_unstemmed Investigating Asymmetric Mean-Reversion of Stock Return, Inter-market Effect and Contrarian Strategy-Using ANST GARCH Model
title_sort investigating asymmetric mean-reversion of stock return, inter-market effect and contrarian strategy-using anst garch model
publishDate 2004
url http://ndltd.ncl.edu.tw/handle/33486572309531669580
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