Order Flow and Exchange Rate Dynamics

Evans, Martin D.D.; Lyons, Richard K.

doi:10.3386/w7317

Cited by 317 publications

(268 citation statements)

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“…7 The relationship between the spot rates and the cumulated order flow is shown in Figure 1. 8 Both series are highly persistent and we confirmed that unit-root tests are unable to reject the null hypothesis that any of the spot exchange rate or cumulated order flow series are I(1). The question at issue is whether there is a stable long-run relationship within each pair of series.…”

Section: Methodssupporting

confidence: 55%

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Exchange rates and order flow in the long run

Boyer

Norden

2006

Finance Research Letters

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Section: Methodssupporting

confidence: 55%

“…As mentioned above, this is the same measure of order flow used by Bjonnes and Rime (2005). 8 All figures and tables are in the paper's appendix. 9 Specifically, we include a constant but no deterministic trends in the VECM representation of our system; this corresponds to case 1 in the notation of MacKinnon, Haug and Michelis (1999).…”

Section: Methodsmentioning

confidence: 99%

Exchange rates and order flow in the long run

Boyer

Norden

2006

Finance Research Letters

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“…Order flow is interpreted as an empirical proxy for dispersed information flows and can indeed explain exchange rate changes over medium-term horizons (Evans and Lyons, 2002). Also the relation of order flow to macroeconomic information has been demonstrated recently (e.g., Evans, 2010).…”

Section: Literaturementioning

confidence: 95%

Individual Exchange Rate Forecasts and Expected Fundamentals

2011

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Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.Download this ZEW Discussion Paper from our ftp server:http://ftp.zew.de/pub/zew-docs/dp/dp11062.pdf Non-technical SummaryExchange rates are one of the most important prices in open economies. Despite their great importance for many enterprises, surprisingly little is known about the economic factors influencing the ups and downs of exchange rates at intermediate horizons. Although several theoretical macroeconomic models do identify potential determinants of exchange rates, empirical studies since the mid-1980s have found that these models do not make more accurate medium-term forecasts than random forecasts. This empirical finding has led to the conclusion that exchange rates and fundamentals are unrelated in the medium term. However, the complexity of currency markets (with heterogeneous market participants or time-variant influencing factors) could conceal a potential relation between economic fundamentals and exchange rates.The present study takes an indirect approach to investigating whether exchange rates are formed based on fundamentals. The defining idea behind our study is to analyze individual forecasts without making assumptions regarding the forecaster's macroeconomic models. Instead, we judge individual forecasts by their forecast ability only. We assume that good exchange rate forecasts are generally based on better information, and analyze whether this information is macroeconomic. To this end, we take a look at the forecast ability of individual forecasts for the USD/EUR exchange rate in conjunction with the forecast ability of associated short-term interest rate forecasts.We view the significant, positive relationship between good exchange rate forecasts (on a one-month horizon) and good interest rate forecast as evidence that exchange rate forecasts benefit from a better interpretation of the macroeconomic reality. This requires a fundamental linkage between exchange rates and macroeconomic variables.If this linkage exists, it should vary in its importance across different market phases. Our further analyses indeed indicate that a correlation between exchange rates and interest rates is especially important when there is an obvious fundamental misalignment between the respective countries. This is the case when there is a great difference between exchange rates and their fundamental values (based on purchasing power parity), when interest rate differences between the two currencies are large, and when exchange rates do not exhibit a strong tren...

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“…The discussion surrounding the information content gained momentum with the seminal paper by Evans and Lyons (2002a). Regressing exchange rate returns on interdealer order flow and the change in interest differentials, the authors find that 64% of daily mark-dollar returns and 45% of daily yen-dollar returns can be primarily explained by (interdealer) order flow.…”

Section: The Information Content Of End-user Order Flowmentioning

confidence: 99%

“…Thus, FX dealers are not uninformed market makers as in Kyle (1985), and may exploit this private information for future trades in the interdealer market. Evans and Lyons (2002a) develop a model that specifies how interdealer order flow maps information to exchange rates and find a strong positive correlation between the two variables. Alternatively, the trader may consider order flow information when quoting future spreads in the customer market, which is intensively 1 We thank Joachim Grammig, Axel Jochem and Carol Osler for very helpful comments on an earlier draft of this paper.…”

Section: End-user Order Flow and Exchange Rate Dynamics 1 1 Introductionmentioning

confidence: 99%

End-User Order Flow and Exchange Rate Dynamics

2008

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Abstract:In this paper we provide evidence for Evans and Lyons' (2005b) model of an information aggregation process in FX markets using a German bank's end-user order flow from 2002 to 2003. Though customer order flow is unambiguously the vehicle incorporating non-public information into exchange rates over time, our empirical analysis does not support the widespread optimism in the market microstructure literature that customer order flow is the high-powered source of information easily exploitable for short-run speculation. Moreover, commercial customers' order flow produces negative coefficients in contemporaneous return regressions, stressing their role as liquidity providers. Keywords:Foreign exchange; market microstructure; end-user order flow JEL-Classification: F31 Non-technical summaryIn spite of many years of extensive research short-run exchange rate fluctuations still remain difficult to explain. The microstructure approach attempts to make progress in this respect by stressing the role of asymmetric information on foreign exchange markets.At the core of standard microstructure models a market maker is assumed to anonymously collect orders from informed and uninformed traders (Kyle, 1985). The market maker infers private information from informed traders by analyzing the incoming order flow and sets prices accordingly. As a result the microstructure approach suggests order flow as a major driving force of exchange rates dynamics. This paper empirically investigates FX dealer behavior in the Euro-US dollar market using the transaction data of a German bank in a one-year period from October 2002 to September 2003. In a first step, we estimate standard market microstructure models finding that order size and currency spreads are negatively correlated and commercial customers are faced with higher spreads than financial customers. This contrasts with standard adverse selection theory, which suggests that dealers increase spreads with a rising likelihood of private information indicated by customer type or order size (Glosten and Milgrom, 1985;Easley and O'Hara, 1987). Moreover, our dealer refrains from quote shading, i.e. he does not quote currency prices in order to manage inventory. Instead, undesired inventory is unloaded in the interdealer market.The empirical results in this section are in line with other studies such as and Osler et al. (2006), implying that the end-user order flow investigated here is similar to that of other dealing banks. This lends support to the view that the data set at hand is a representative fraction of market wide order flow. Thus, our second step is to use cointegration techniques to assess the information content of end-user order flow.In line with the price discovery process suggested by Evans and Lyons (2005b), we find that exchange rates are cointegrated with customer order flow. Within the cointegration relationship, exchange rates are positively related to financial customer orders and negatively related to commercial customer orders. In the short run, however, ne...

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Order Flow and Exchange Rate Dynamics

Cited by 317 publications

References 64 publications

Exchange rates and order flow in the long run

Exchange rates and order flow in the long run

Individual Exchange Rate Forecasts and Expected Fundamentals

End-User Order Flow and Exchange Rate Dynamics

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