Over the last decade, the microstructure approach to exchange rates has become very popular. The underlying idea of this approach is that the order flows at different levels of aggregation contain valuable information to explain exchange rate movements. The bulk of empirical literature has focused on evaluating this hypothesis in a linear framework. This paper analyzes nonlinearities in the relation between exchange rates and customer order flows. We show that the relationship evolves over time and that it is different under different market conditions defined by exchange rate volatility. Further, we found that the nonlinearity can be captured successfully by the Threshold regression and Markov Switching models, which provide substantial explanatory power beyond the constant coefficients approach.
customer order flows nonlinear models microstructure exchange rate