The Market Microstructure Approach to Foreign Exchange: Looking Back and Looking Forward

Abstract

Research on foreign exchange (FX) market microstructure stresses the importance of order flow, heterogeneity among agents, and private information as crucial determinants of short-run exchange rate dynamics. Microstructure researchers have produced empirically-driven models that fit the data surprisingly well. But currency markets are evolving rapidly in response to new electronic trading technologies. Transparency has risen, trading costs have tumbled, and transaction speed has accelerated as new players have entered the market and existing players have modified their behavior. These changes will have profound effects on exchange rate dynamics. Looking forward, we highlight fundamental yet unanswered questions on the nature of private information, the impact on market liquidity, and the changing process of price discovery. We also outline potential microstructure explanations for long-standing exchange rate puzzles.

A model of market making with heterogeneous speculators

“…According to the market microstructure literature, net order flows are strong predictors of exchange rate movements. Foreign exchange dealers believe that private information is crucial to operate on the exchange rate market and that trading flows collected from customers aggregate dispersed information (King et al, 2013). On the other hand, the possibility of private information in the FX market has been questioned since the fundamental value of a currency is determined by macroeconomic information (e.g.…”

“…One possible answer is that private information that is most valuable does not concern fundamentals. One source of non fundamental information, according to King et al (2013), stems from demand and supply themselves. If they have only finite elasticity, i.e.…”

Illiquidity in the Stock and Foreign Exchange Markets: An Investigation of Their Cross‐market Dynamics

“…Indeed, they are subject to the risk of not being able to offload them quickly and at a low cost, especially during crisis episodes (Melvin and Taylor 2009;Banti and Phylaktis 2015). Dealers are also prime brokers to their hedge fund clients, providing them with funding and access to interdealer trading platforms (Galati, Heath, and Mcguire 2007;King, Osler, and Rime 2013).…”

Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework

“…8. Although a TT would increase transaction costs, the spreads may be disaggregated into several components, such as the pure cost sand holding of inventory costs (King et al, 2013). In this vein, a TT may affect only the first of these components.…”