Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information

Efficient markets hypothesis (EMH) has been a debatable topic among market practitioners and researchers since 1970s. The widespread availability of high frequency financial data together with a series of new empirical findings imposes challenges to the definition of financial markets and it also le...

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Main Author:	Wong, Zhen Yao
Format:	Thesis
Published:	2016
Subjects:	HG4551-4598 Stock exchanges
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id	my-mmu-ep.6857
record_format	uketd_dc
spelling	my-mmu-ep.68572017-07-12T04:04:38Z Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information 2016-03 Wong, Zhen Yao HG4551-4598 Stock exchanges Efficient markets hypothesis (EMH) has been a debatable topic among market practitioners and researchers since 1970s. The widespread availability of high frequency financial data together with a series of new empirical findings imposes challenges to the definition of financial markets and it also leads to the proposal of various alternative market hypotheses. Inspired by the EMH and the heterogeneous markets hypothesis (HMH), this study first examines the dynamic behaviour of global stock markets using daily and high frequency information. The identified predictable components of stock market dynamics are then captured using econometric models available in the literature with the aim to produce accurate risk forecasts. One of the main applications in conditional volatility modelling and forecasting of financial assets is the value-at-risk (VaR) estimation, which is used by financial institutions to report on the daily capital in risk. It remains as a question, whether realized volatility (RV) models that incorporate intraday data produce better VaR forecasts compared to methodologies which solely based on daily returns. Thus, this study provides extensive comparison of the out-of-sample volatility and the VaR forecast performance on global equity market indices: S&P500, FTSE100, and DAX30 by using 21 risk models which consist of 5 conventional GARCH specifications and 16 RV (ARFIMA and HAR) specifications. 2016-03 Thesis http://shdl.mmu.edu.my/6857/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php masters Multimedia University Faculty of Management
institution	Multimedia University
collection	MMU Institutional Repository
topic	HG4551-4598 Stock exchanges
spellingShingle	HG4551-4598 Stock exchanges Wong, Zhen Yao Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
description	Efficient markets hypothesis (EMH) has been a debatable topic among market practitioners and researchers since 1970s. The widespread availability of high frequency financial data together with a series of new empirical findings imposes challenges to the definition of financial markets and it also leads to the proposal of various alternative market hypotheses. Inspired by the EMH and the heterogeneous markets hypothesis (HMH), this study first examines the dynamic behaviour of global stock markets using daily and high frequency information. The identified predictable components of stock market dynamics are then captured using econometric models available in the literature with the aim to produce accurate risk forecasts. One of the main applications in conditional volatility modelling and forecasting of financial assets is the value-at-risk (VaR) estimation, which is used by financial institutions to report on the daily capital in risk. It remains as a question, whether realized volatility (RV) models that incorporate intraday data produce better VaR forecasts compared to methodologies which solely based on daily returns. Thus, this study provides extensive comparison of the out-of-sample volatility and the VaR forecast performance on global equity market indices: S&P500, FTSE100, and DAX30 by using 21 risk models which consist of 5 conventional GARCH specifications and 16 RV (ARFIMA and HAR) specifications.
format	Thesis
qualification_level	Master's degree
author	Wong, Zhen Yao
author_facet	Wong, Zhen Yao
author_sort	Wong, Zhen Yao
title	Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
title_short	Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
title_full	Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
title_fullStr	Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
title_full_unstemmed	Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information
title_sort	heterogeneous stock market modelling and market risk evaluation using high frequency information
granting_institution	Multimedia University
granting_department	Faculty of Management
publishDate	2016
_version_	1747829637978783744

Heterogeneous Stock Market Modelling and Market Risk Evaluation using High Frequency Information

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