Essays on price discovery and volatility dynamics in the foreign exchange market

Su, Fei

Essays on price discovery and volatility dynamics in the foreign exchange market

Su, Fei

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Publication Type:: Thesis
Issue Date:: 2018

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Field	Value	Language
dc.contributor.author	Su, Fei
dc.date.accessioned	2018-10-08T02:14:20Z
dc.date.available	2018-10-08T02:14:20Z
dc.date.issued	2018
dc.identifier.uri	http://hdl.handle.net/10453/127972
dc.description	University of Technology Sydney. Faculty of Business.	en_AU
dc.description.abstract	This dissertation consists of three independent essays that explore different aspects of price discovery and volatility dynamics in the FX market. In the first essay, I estimate daily information shares of different trading sessions (namely, Asia, Europe, and U.S.) in the global foreign exchange market, and more importantly, I examine their determinants, i.e. when and how a market contributes more to the price discovery of the exchange rates. Specifically, I study the short- and long-run price discovery in the FX market on a global basis and their determinants by taking the AUD as an example. Interestingly, I find that more favourable market states contribute to price discovery in the short-run, while the capital market openness and financial liberalization, as measured by the Chinn-Ito Index, have a strong impact on the long-run variations in price discovery. The empirical results presented in this essay provide a better understanding of the global information distribution in the FX market and contribute to the literature on the determinants of price discovery. Furthermore, I provide important policy implications regarding international financial competitiveness and market development. In the second essay, I revisit the meteor showers and heat waves effects (namely, the inter- and intra-regional volatility spillovers) in the FX market, which have been extensively recorded and examined in the previous studies. The main methodological tools used in this essay are the heterogeneous autoregressive model (HAR) and the Shapley-Owen R² decomposition techniques. By examining the dynamic patterns of volatility spillover for exchange rates of AUD/USD, GBP/USD, EUR/USD, and USD/JPY spanning the period of January 1999 (January 2000 for EUR/USD) to December 2013, I confirm the presence of both meteor showers and heat waves effects, however, the meteor showers effect has been increasing steadily and predominated over heat waves effects with the trend toward global trading and correlated common shocks of the financial markets. Furthermore, I explicitly examine the role of changing market states in determining volatility spillover in the foreign exchange market. Unlike the conventional information-based models, such as the mixture of distribution hypothesis (MDH) theory, the empirical results suggest that the volatility spillover is attributed to not only exogenous information shocks, but also endogenous information arrivals and price discovery process, which resolves uncertainty and therefore mitigates information propagation. In sum, this essay presents new evidence on the patterns and economic mechanisms of volatility spillover and contributes to the relevant literature on volatility modelling in the FX market by proposing the time-varying volatility spillovers in different regions and suggesting the segment-wise properties of FX volatility modelling. The last essay focuses on the statistical significance and economic value of the Conditional Volatility Persistence (CVP) model as proposed in Wang and Yang (2017). Namely, the CVP model calibrates future volatility persistence base on the observed market states as captured by return and volatility. Then, I compare the economic gains of a variety of RV-based HAR models by developing a volatility-timing strategy based on the signal of predicted volatility. By applying the CVP model to the spot exchange rates of AUD/USD, GBP/USD, EUR/USD, and USD/JPY, I confirm both the statistical and economic significance of the CVP model in the FX market. Namely, the CVP model can improve the forecasting performance and generate moderate economic gains. For example, under empirically reasonable assumptions, the CVP model I use in this thesis can gain an estimated 1.26% of total wealth on an annual basis, or 0.51% of total wealth relative to a static model. Furthermore, it achieves higher Sharpe ratios, especially during the turmoil period. The gains in using CVP model remain positive and significant after controlling for the transaction costs and market microstructure noise.	en_AU
dc.format	Thesis (PhD)
dc.language.iso	en_AU	en_AU
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/127972/2/02whole.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	au.edu.uts.lib/ppc
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.subject	Price Discovery.	en_AU
dc.subject	Foreign exchange.	en_AU
dc.subject	Volatility dynamics in the Forex market.	en_AU
dc.subject	Distribution hypothesis theory.	en_AU
dc.title	Essays on price discovery and volatility dynamics in the foreign exchange market	en_AU
dc.type	Thesis	en_AU
utslib.copyright.status	open_access

Abstract:

This dissertation consists of three independent essays that explore different aspects of price discovery and volatility dynamics in the FX market. In the first essay, I estimate daily information shares of different trading sessions (namely, Asia, Europe, and U.S.) in the global foreign exchange market, and more importantly, I examine their determinants, i.e. when and how a market contributes more to the price discovery of the exchange rates. Specifically, I study the short- and long-run price discovery in the FX market on a global basis and their determinants by taking the AUD as an example. Interestingly, I find that more favourable market states contribute to price discovery in the short-run, while the capital market openness and financial liberalization, as measured by the Chinn-Ito Index, have a strong impact on the long-run variations in price discovery. The empirical results presented in this essay provide a better understanding of the global information distribution in the FX market and contribute to the literature on the determinants of price discovery. Furthermore, I provide important policy implications regarding international financial competitiveness and market development. In the second essay, I revisit the meteor showers and heat waves effects (namely, the inter- and intra-regional volatility spillovers) in the FX market, which have been extensively recorded and examined in the previous studies. The main methodological tools used in this essay are the heterogeneous autoregressive model (HAR) and the Shapley-Owen R² decomposition techniques. By examining the dynamic patterns of volatility spillover for exchange rates of AUD/USD, GBP/USD, EUR/USD, and USD/JPY spanning the period of January 1999 (January 2000 for EUR/USD) to December 2013, I confirm the presence of both meteor showers and heat waves effects, however, the meteor showers effect has been increasing steadily and predominated over heat waves effects with the trend toward global trading and correlated common shocks of the financial markets. Furthermore, I explicitly examine the role of changing market states in determining volatility spillover in the foreign exchange market. Unlike the conventional information-based models, such as the mixture of distribution hypothesis (MDH) theory, the empirical results suggest that the volatility spillover is attributed to not only exogenous information shocks, but also endogenous information arrivals and price discovery process, which resolves uncertainty and therefore mitigates information propagation. In sum, this essay presents new evidence on the patterns and economic mechanisms of volatility spillover and contributes to the relevant literature on volatility modelling in the FX market by proposing the time-varying volatility spillovers in different regions and suggesting the segment-wise properties of FX volatility modelling. The last essay focuses on the statistical significance and economic value of the Conditional Volatility Persistence (CVP) model as proposed in Wang and Yang (2017). Namely, the CVP model calibrates future volatility persistence base on the observed market states as captured by return and volatility. Then, I compare the economic gains of a variety of RV-based HAR models by developing a volatility-timing strategy based on the signal of predicted volatility. By applying the CVP model to the spot exchange rates of AUD/USD, GBP/USD, EUR/USD, and USD/JPY, I confirm both the statistical and economic significance of the CVP model in the FX market. Namely, the CVP model can improve the forecasting performance and generate moderate economic gains. For example, under empirically reasonable assumptions, the CVP model I use in this thesis can gain an estimated 1.26% of total wealth on an annual basis, or 0.51% of total wealth relative to a static model. Furthermore, it achieves higher Sharpe ratios, especially during the turmoil period. The gains in using CVP model remain positive and significant after controlling for the transaction costs and market microstructure noise.

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