Essays on the Impact of Brexit-related Shocks on High-Frequency Trading in the Foreign Exchange Market

This chapter contributes to the study of high-frequency trading and the impact of Brexit on the foreign exchange (FX) market. It uses high-frequency data to analyze market microstructure and Brexit’s effects on currency dynamics. Chapter 1 examines the impact of the Brexit referendum on 1-minute currency returns using the ARMA-FIGARCH (Autoregressive Moving Average- Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity) model. It also explores the role of order flows in price discovery. Key findings include: (1) Order flows significantly influence currency returns; (2) Brexit news has asymmetric effects on currency movements; (3) Brexit can reduce the explanatory power of order flows, as seen in their interaction; and (4) Long memory in volatility is observed, though order flows and Brexit news do not significantly affect conditional variance of returns. Chapter 2 studies the spillovers across currency returns, volatilities, order flows, and percentage effective spreads using the VAR (Vector Autoregression) model and Diebold-Yilmaz spillover index. It compares patterns before, during, and after Brexit. Results show: (1) GBPUSD (current exchange rate British Pound to US Dollar) and EURUSD (current exchange rate Euro to US Dollar) were net transmitters of returns before and during the vote, with GBPUSD intensifying its role post-vote, while EURUSD became a net receiver; (2) For return volatilities, GBPUSD’s role as a transmitter strengthened post-vote, while EURUSD shifted to a net receiver; (3) The spillover index for both returns and volatilities peaked during the Brexit vote, with volatility spillovers showing greater interconnectedness; (4) For percentage effective spread spillovers, GBPUSD showed a lower negative net spillover index post-Brexit, while EURUSD became a net transmitter of illiquidity. Chapter 3 employs a multivariate ARMA-DCC-GARCH (Autoregressive Moving Average - Dynamic Conditional Correlation - Generalized Autoregressive Conditional Heteroskedasticity) model to analyze Brexit’s impact on FX liquidity for six currency pairs. It also explores how Brexit influenced order flows and currency returns. Findings reveal: (1) Brexit increased illiquidity in most currency pairs; (2) Brexit heightened order flow volatility for EURUSD; (3) Brexit news elevated return volatility for GBPUSD, with ,EURUSD also experiencing increased return volatility post-Brexit.