City Research Online

Abstract

Using two unique datasets, one at a daily frequency including six currency pairs, and another tick-by-tick dataset in €/US$, we investigate some of the unanswered questions in the field of foreign exchange market microstructure. We confirm the contemporaneous relationship between flows and exchange rates found in the literature in the daily data, but in the forecasting experiments we find no forecasting power, regardless of model, history used forecast horizon or currency pair. The forecasting performance is not improved by considering a system of exchange rates, or by evaluating based on directional ability instead of the more usual RMSE ratio. Subsequently we estimate two standard market microstructure models - Madhavan- Smidt and Huang-Stoll – using the high-frequency dataset in order to gain an insight into the information content of customer order flow. While we are unable to find any evidence of information content from financial customer trades, we find strong evidence that large corporate customer trades are perceived to have statistically and economically significant information content. Lastly we turn our attention to the issue of causality. Using a distributed lag model to investigate the impact of flows on exchange rates and vice versa, corporate orders are found to have a small long-term impact, but more significantly we find evidence of positive feedback trading in both corporate and financial customers. We explore the long-run dynamics of the system using a VECM, and find that all counterparty types have a positive equilibrium relationship with the exchange rate. Crucially, the adjustment dynamics show that all of the weight of adjustment to restore equilibrium after a shock falls to flows. Lastly, we conduct a high frequency forecasting experiment, but again find no evidence of forecasting power. Two important themes emerge from the high-frequency investigation. The first is the apparent importance of corporate customers, and the second is that the direction of causality runs not from flows to exchange rates, but from exchange rates to flows. We conclude that the weight of the evidence suggests that feedback rather than information content is what drives the strong contemporaneous relationship between exchange rates and flows.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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