Date of Award:
5-1995
Document Type:
Dissertation
Degree Name:
Doctor of Philosophy (PhD)
Department:
Economics and Finance
Department name when degree awarded
Economics
Committee Chair(s)
Chris Fawson
Committee
Chris Fawson
Committee
Dwight Israelsen
Committee
Basudeb Biswas
Committee
Donald Sisson
Committee
Terry F. Glover
Abstract
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.
Checksum
995cb123f5ae9f386fc30dcfea574068
Recommended Citation
Chang, Tsangyao, "An Application of Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays" (1995). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 3916.
https://digitalcommons.usu.edu/etd/3916
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