تجارت آگاهانه در بازار ارز خارجی: بررسی تجربی

This paper presents new evidence on information asymmetries in inter-dealer FX markets. We employ a new USD/DEM data set covering the activities of multiple dealers over one trading week. We utilise and extend the VAR structure introduced in Hasbrouck [J. Finance 46(1) (1991) 179] to quantify the permanent effects of trades on quotes and show that asymmetric information accounts for around 60% of average bid-ask spreads. Further, 40% of all permanent price variation is shown to be due to transaction-related information. Finally, we uncover strong time-of-day effects in the information carried by trades that are related to the supply of liquidity to D2000-2; at times when liquidity supply is high, individual trades have small permanent effects on quotes but the proportion of permanent quote variation explained by overall trading activity is relatively high. In periods of low liquidity supply the converse is true—individual trades have large permanent price effects but aggregate trading activity contributes little to permanent quote evolution.

Prior to the 1990s, analysis of the causes of exchange rate movements was a field that was firmly in the hands of macroeconomists. Exchange rate models, based on the goods and asset market approaches were set out and tested using low frequency (e.g. monthly or quarterly) data on exchange rates and macroeconomic fundamentals. However, these tests most often revealed that the fundamentals were less important for exchange rate determination than models predicted. The explanatory power of macroeconomic data for exchange rates was poor and the forecasting power of regressions based on fundamentals was less good than that of a simple random walk. A classic reference along these lines is Meese and Rogoff (1983). This failure has led, in the last decade or so, to increasing attention being paid to models of FX market activity and exchange rate determination based on market microstructure analysis. This large and growing literature places the process by which currencies are actually exchanged in centre stage and focusses on the impact of heterogeneities in the trading population for prices and traded quantities. A key source of heterogeneity in standard microstructure finance is informational—some agents are assumed to be better informed about future asset prices than others (Glosten and Milgrom, 1985). On an empirical level, such informational asymmetries have several important implications. First, faced with the possibility of trading with a better-informed individual, uninformed liquidity suppliers widen the bid-ask spreads that they charge. This allows them to recoup the losses inflicted upon them by insiders from uninformed individuals. Second, and more importantly in the current context, transaction activity carries information and thus trades permanently alter prices. Episodes in which aggressive traders tend to be buying a given currency will lead to its price rising while the converse is true during episodes of aggressive sales. This second prediction is vital—it opens a channel through which transaction activity in FX markets might play a role in exchange rate determination, a feature that is entirely absent from standard macroeconomic exchange rate models. The current study seeks to assess the importance of this channel. Recent empirical papers that also focus on the explanatory power of currency trading activity for exchange rate changes include Lyons (1995) and Yao (1998). Both of these studies use data from single FX dealers to demonstrate that spreads contain an asymmetric information component. Lyons (1996) extends his prior work by examining the role of time in the relationship between trades and quotes. He finds that trades occurring in periods when the market is active convey less information than those consummated when the market is quiet. This is interpreted as consistent with his ‘hot potato hypothesis’ by which high interdealer volumes are generated more by inventory rebalancing than exploitation of private information. Most recently, studies by Evans and Lyons (2001) and Evans (2001) provide strong evidence for an information content to inter-dealer FX order flow using 4 months of data on direct (i.e. non-brokered) FX trading activity. Theoretical models that focus on the information contained in inter-dealer spot FX trading activity can be found in Lyons (1995) and Perraudin and Vitale (1996). In these models dealers receive private signals of future exchange rate evolution from their customer (i.e. non-dealer) order flow. and On an institutional level, this is possible as customer–dealer trade is entirely opaque (i.e. dealer B cannot observe the customer order flow arriving at dealer A and vice versa). The customer order flow arriving at dealers may be informative for a number of reasons. First, and most blatantly, a given dealer might have an intervening central bank as a customer and thus may learn about future interest rates from the central bank’s order. However, such occurrences are likely to be rare and hence this channel is not ideal for arguing that customer orders contain information in general.3 A second rationale for the information content of customer order flow comes from arguing that information regarding future exchange rate fundamentals, for example trade balances, is dispersed among individual customers. A given dealer observes the trading behaviour of a group of individual customers and, thus, from their aggregate trading activity receives a signal regarding future fundamentals which can be exploited in inter-dealer trade. Note that in both of the prior examples, customer order flow is informative about exchange rate fundamentals—i.e. interest rates or trade balances. Another class of models, see Evans and Lyons (2001), generates customer trading activity that forecasts future prices because it is informative about risk premia. These ‘portfolio shifts’ or portfolio balance models generate permanent price shifts due to risk-aversion. Assume that the non-dealer segment of the market experiences a portfolio shift that requires currency trade. Further assume that there is no expectation that this trade will be reversed such that the aggregate inventory imbalance (and risk) foisted upon the market is permanent and undiversifiable. Assuming risk averse agents operating in the FX markets then delivers a permanent change in prices due to a permanent change in risk premia. Dealers are informed in this setting as they see a signal of the aggregate portfolio shift through their customer order flow, before the size of the shift becomes public. Again, dealers can exploit their signals in trade in the inter-dealer market. As stated above, for the current paper the key empirical implication of the preceding models is that trading activity in the inter-dealer market will have a permanent affect on interdealer quotes. This permanent effect is generated by the information carried by inter-dealer trades (regardless of whether this information is about future fundamentals or future risk premia). We test for this permanent price effect using the bivariate VAR model for quote revisions and signed trades introduced in Hasbrouck (1991a). Further, whilst earlier studies have demonstrated that at least some FX trades carry information, none has computed the aggregate impact of such information. Use of the variance decomposition presented in Hasbrouck (1991b) allows us to calculate the proportion of all information entering the quotation process via order flow and hence address this issue. Finally, we examine variations in the information content of trades with the pace of the market. Theoretical contributions such as Admati and Pfleiderer (1988) and Foster and Viswanathan (1993) predict correlations in the intra-day variation of transactions costs, volume and the intensity of informed trade which we evaluate via a time-of-day subsample analysis of the D2000-2 data. We refine the time-of-day analysis by modifying the basic VAR structure to allow for dependence of the parameters on D2000-2 liquidity measures. One of the main innovations of this work is the use of a new data set on inter-dealer USD/DEM trades, drawn from an electronic brokerage called D2000-2. Whilst earlier work in this area has employed data based on the operations of single dealers, the D2000-2 data reflect the interactions of multiple traders. As such, these data provide broader coverage of inter-dealer activity. Further, the D2000-2 data can be used to construct proxies for the liquidity of the FX market as a whole. D2000-2 operates as a closed, electronic order book and every limit and market order entered onto the system are available from the data. Liquidity and depth measures can be constructed from the limit order data and used as conditioning variables in the analysis of the effects of private information. Our main results are as follows. First, our estimates imply that over 60% of the D2000-2 spread can be thought of as compensation for informed trade. An unexpected market buy, for example, leads to an upwards equilibrium quote revision of 1 pip (i.e. DM 0.0001) on average. The 60% figure derives from comparing this 1 pip permanent price impact to one half of the average bid-ask spread on D2000-2. Further, we estimate that around 40% of all information entering the quotation process does so through order flow, a figure which is comparable in magnitude to equivalent measures from equity market studies. The 40% number quoted above is important in that it quantifies the relative impact of trade-related versus non-trade-related information on exchange rate evolution. However, given that the data we study here cover only one of several venues for inter-dealer FX trade we should clarify its interpretation. Our result does not imply that 40% of the information relevant to long-run USD/DEM determination is revealed on D2000-2. The number is derived from the correlation between D2000-2 order flow and permanent USD/DEM movements. If we were to assume, quite reasonably, that all inter-dealer FX venues shared the same permanent price component, and further that all order flows were perfectly correlated, then we would get the same value for the size of the trade correlated component from each venue. Thus in this case 40% would be a market-wide figure. We would suggest that, in the current context, the size of the trade correlated component should be interpreted along similar lines. However, there is the possibility that informed FX trade is more prevalent on other (less transparent) trading venues. In this case, our 40% number might be interpreted as a lower bound on the impact of private information in FX markets. Finally, impact of informed trade on D2000-2 quotes is shown to depend strongly on the level of market activity. When the D2000-2 order book is relatively thin and volume low (i.e. from the late GMT afternoon to the early GMT morning,) an unexpected trade has a much larger permanent effect on quotes than in peak trading periods. This result is consistent with the empirical analysis of Lyons (1996) and the theoretical predictions of Admati and Pfleiderer (1988). A more direct examination of the relationship between informed trade and market conditions is obtained from some extended VAR results. These demonstrate that the permanent impact of informed trade on quotes and the supply of limit orders to D2000-2 are negatively and non-linearly related. However, it should be noted that while we show that individual trades have larger permanent price effects in periods of lower trading activity or liquidity supply, the variance decompositions tell us that the aggregate contribution of transaction activity to permanent exchange rate determination is low at these times. Thus these periods should not be considered those in which price discovery is particularly intensive. The rest of the paper is set out as follows. Section 2 introduces the basic features of the D2000-2 data set and Section 3 details the empirical methodology employed in the current study. Section 4 presents the empirical findings from the VAR estimations. Finally, Section 5 concludes and presents ideas for further work.

This paper analyses trades and quotes from the electronically brokered segment of the spot USD/DEM market. Specifically, we examine whether this market can be characterised as subject to information asymmetries. Using the technology introduced by Hasbrouck (1991a) and Hasbrouck (1991b) we find that trades do carry information. Roughly 60% of the bid-offer spread in our data can be related to the asymmetric information problem. Further, around 40% of the variation in the fundamental price is shown to be order flow driven, a proportion which is comparable to those found in studies of equity markets. We uncover clear intra-day variation in the information content of a trade and the total information content of order flow. In line with the theoretical predictions, in high volume/liquidity intervals the information content of a single trade is low while the share of information entering the midquote through order flow is high. A more refined analysis of the relationship between the price impact of trades and market activity is also presented. Similar to the time-of-day analysis, results from an arranged VAR estimation indicate that the asymmetric information coefficients vary systematically with market liquidity. There are several possible extensions to the current study. First, a more careful analysis of the non-linearities in the VAR structure may prove to be fruitful. Parameterising the nonlinearities would likely yield insights into the determination of price impacts from trade. Another interesting area of research would be to examine how transaction activity affects subsequent liquidity supply through analysis of the excess demand and supply schedules for currency. Furthermore, econometric analysis of individual limit order entry and execution would provide stronger evidence on the order placement strategy of dealers and how it reacts to trading activity and quote volatility. Such issues are currently under investigation. Finally, as we have mentioned above, D2000-2 is one of several venues for inter-dealer foreign exchange trade. It would be interesting to evaluate how these venues interact (in terms of trading activity and quoting behaviour). This would give a clearer picture of when and where informed trade was trading price.