An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays

In this dissertation, three essays are presented that apply recent advances in time-series methods to the analysis of inflation and stock market index data for Taiwan. Specifically, ARCH and GARCH methodologies are used to investigate claims of increased volatility in economic time-series data since...

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Main Author: Chang, Tsangyao
Format: Others
Published: DigitalCommons@USU 1995
Subjects:
Online Access:http://digitalcommons.usu.edu/etd/4040
http://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=5061&context=etd
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spelling ndltd-UTAHS-oai-digitalcommons.usu.edu-etd-50612015-02-21T04:51:14Z An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays Chang, Tsangyao In this dissertation, three essays are presented that apply recent advances in time-series methods to the analysis of inflation and stock market index data for Taiwan. Specifically, ARCH and GARCH methodologies are used to investigate claims of increased volatility in economic time-series data since 1980. In the first essay, analysis that accounts for structural change reveals that the fundamental relationship between inflation and its variability was severed by policies implemented during economic liberalization in Taiwan in the early 1980s. Furthermore, if residuals are corrected for serial correlation, evidence in favor of ARCH effects is weakened. In the second essay, dynamic linkages between daily stock returns and daily trading volume are explored. Both linear and nonlinear dependence are evaluated using Granger causality tests and GARCH modelling. Results suggest significant unidirectional Granger causality from stock returns to trading volume. In the third essay, comparative analysis of the frequency structure of the Taiwan stock index data is conducted using daily, weekly, and monthly data. Results demonstrate that the relationship between mean return and its conditional standard deviation is positive and significant only for high-frequency daily data. 1995-01-01T08:00:00Z text application/pdf http://digitalcommons.usu.edu/etd/4040 http://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=5061&context=etd Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu). All Graduate Theses and Dissertations DigitalCommons@USU Autoregressive Conditional Heteroskedasticity Autoregressive Conditional Heteroskedasticity Taiwan's Time-Series Data Economics
collection NDLTD
format Others
sources NDLTD
topic Autoregressive Conditional Heteroskedasticity
Autoregressive Conditional Heteroskedasticity
Taiwan's Time-Series Data
Economics
spellingShingle Autoregressive Conditional Heteroskedasticity
Autoregressive Conditional Heteroskedasticity
Taiwan's Time-Series Data
Economics
Chang, Tsangyao
An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
description In this dissertation, three essays are presented that apply recent advances in time-series methods to the analysis of inflation and stock market index data for Taiwan. Specifically, ARCH and GARCH methodologies are used to investigate claims of increased volatility in economic time-series data since 1980. In the first essay, analysis that accounts for structural change reveals that the fundamental relationship between inflation and its variability was severed by policies implemented during economic liberalization in Taiwan in the early 1980s. Furthermore, if residuals are corrected for serial correlation, evidence in favor of ARCH effects is weakened. In the second essay, dynamic linkages between daily stock returns and daily trading volume are explored. Both linear and nonlinear dependence are evaluated using Granger causality tests and GARCH modelling. Results suggest significant unidirectional Granger causality from stock returns to trading volume. In the third essay, comparative analysis of the frequency structure of the Taiwan stock index data is conducted using daily, weekly, and monthly data. Results demonstrate that the relationship between mean return and its conditional standard deviation is positive and significant only for high-frequency daily data.
author Chang, Tsangyao
author_facet Chang, Tsangyao
author_sort Chang, Tsangyao
title An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
title_short An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
title_full An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
title_fullStr An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
title_full_unstemmed An Application of Autoregressive Conditional Heteroskedasticity (Arch) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
title_sort application of autoregressive conditional heteroskedasticity (arch) and generalized autoregressive conditional heteroskedasticity (garch) modelling on taiwan's time-series data: three essays
publisher DigitalCommons@USU
publishDate 1995
url http://digitalcommons.usu.edu/etd/4040
http://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=5061&context=etd
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