Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data

By David Berger, A. Chaboud, Sergey Chernenko, E. Howorka, Rajkamal Iyer, David Liu, Jonathan H. Wright. 2005

287 citations recorded by the source corpus.

We study the association between order flow and exchange rate returns in five years of high-frequency intraday data from the leading interdealer electronic broking system, EBS. While the association between order flow and exchange rate returns has been studied in several previous papers, these have mostly used relatively short spans of daily data from older bilateral dealing systems and, usually, transaction counts instead of actual trading volume. Using a substantially longer span of recent high-frequency data and measuring order flow as actual signed trading volume, we find a strong positive association between order flow and exchange rate returns at frequencies ranging from one minute to one day, and a more modest but still sizeable association at the monthly frequency. We find, however, no evidence that order flow has predictive power for future exchange rate movements beyond, possibly, the next minute. Focusing on the behavior of order flow and exchange rates at the time of scheduled U.S. economic data releases, we find that the surprise components of these announcements are associated with order flow at high frequency immediately after the data releases. This finding seems inconsistent with a simple efficient markets view of how a public news announcement is incorporated into prices.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/c8a19d72e99b7bf2e15aa7c7ce647596a1a8af39

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In Economics and Econometrics

Citations in the corpus

Understanding the Forward Premium Puzzle: A Microstructure Approach (2009, unknown): “Berger et al. (2008) provide evidence that microstructure frictions in exchange rate markets are relevant at horizons as long as three months.”
The Price Impact of Order Book Events (2010, unknown): “Alternatively, empirical studies on public data [16, 18, 20, 28, 29, 43, 38, 39] have investigated the relation between the direction and sizes of trades and price changes and typically conclude that the price impact of trades is an increasing, concave (“square root”) function of their size.”
Understanding FX Liquidity (2015, unknown): “4 Following the seminal work of Evans and Lyons (2002) on FX order flow, several papers investigate the role of FX order flow, including those by Breedon and Vitale (2010), Breedon and Ranaldo (2013), Berger et al. (2008) and Banti, Phylaktis, and Sarno (2012). 5 See Bessembinder (1994), Bollerslev ”
The Scapegoat Theory of Exchange Rates: The First Tests (2014, background): “explanatory and forecasting power of order ow has been mainly linked to macroeconomic news (e.g. Dominguez and Panthaki, 2006; Berger et al., 2008; Love and Payne, 2008; Evans and Lyons, 2010), changes in expectations about the macroeconomy (Rime, Sarno and Sojli, 2010), and signals on the current ”
The Returns to Currency Speculation (2006, unknown): “Berger et al. (2006) provide estimates of under di erent assumptions about the length of the time period, ranging from one minute to three months. Their estimates of for daily frequencies are roughly equal to 0 0040, with a corresponding 2 of about 0 50. Using monthly data Berger et al. (2006) estim”
Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market: Rise of the Machines (2009, unknown): “[10] Berger, D.”