نقش اطلاعات خصوصی در نوسان پذیری بازده، اسپرد قیمت خرید و فروش و سطح قیمت در بازار ارز

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.

Private information is a common theme across various theories in the context of the widely documented patterns that exist in intraday trading data. These patterns emerge in volume, volatility and bid–ask spread data from a wide variety of financial markets. There is a distinct literature within market microstructure that aims to explain why these intraday patterns occur (see ap Gwilym and Sutcliffe, 1999). Our research uses that literature to explore how private information influences the formation of price changes and bid–ask spreads. We also introduce order flow as an additional variable for intraday pattern analysis. Our data are sourced from the world's largest financial market, the inter-dealer spot foreign exchange market. This market is particularly important because, as McGroarty et al. (2006) explain, the inter-dealer market effectively sets the spot exchange rates for the entire FX market.1 In spite of its size and importance, the spot FX market has been underrepresented in the literature on intraday empirical regularities, due to difficulties in obtaining data. Our analysis addresses this imbalance. Intraday trading data exhibit M- and U-shaped patterns, as markets go through the daily ritual of opening, trading normally and closing. Patterns in bid–ask spreads, trading volume and return volatility have been observed in all major financial markets. We believe that we are the first to reveal the intraday pattern for order flow, for any market.2 Evans and Lyons (2002) established a strong relationship between cumulative order flow and exchange rates. They define order flow as “the net of buyer-initiated and seller-initiated orders” and interpret it as “a measure of net buying pressure”. They argue that order flow is driven by (private) information and they provide strong evidence that order flow is the proximate driver of price in the spot FX market. Specifically, they show that cumulative order flow is highly correlated with cumulative price change. From market microstructure theory, Easley and O’Hara (1992) suggest that another variable is closely linked to private information, namely, unanticipated deviations from normal intraday trading volume levels. We explore both ideas. There is an abundance of theory which models bilateral relationships between the variables that we observe in intraday data, e.g. linking volatility and volume, or volume and bid–ask spreads. As ap Gwilym and Sutcliffe (1999) observe, the most common theme across these bilateral relationship models is private information. We use a correlation matrix to test multiple contemporaneous hypotheses, and to examine how the relationships under investigation changed following the introduction of the euro. We reveal the role of private information in explaining bid–ask spreads and in determining exchange rate volatility, whose determinants Flood and Rose (1995) tell us “are not macroeconomic”. Finally, we explore how private information contributes to incremental returns which compound to determine the overall price level. We take account of structures and practices in the inter-dealer spot FX market that are different from the assumed market structure underlying most of the existing market microstructure theory. The market we study is electronic, order-driven and conspicuously lacks market makers at its core. Rather, any eligible agent who wishes to trade in this market has two choices. He can submit a market order or a limit order. A market order executes immediately by selecting a trader on the other side of the market who has previously advertised on the system that he is willing to trade. A limit order is where a potential trader submits an advertisement that he is willing to trade. This limit order will sit alongside orders already in the system, awaiting execution. Limit orders can be either ask-side or bid-side. The same is true for market orders. There is no pressure on any market participant to submit two-way limit orders and no evidence that anyone routinely submits such orders. The remainder of the paper is organized as follows. Section 2 reviews the empirical literature documenting patterns in intraday trading variables and explores the theory relating these data variables to each other in order to deduce a comprehensive set of mutually consistent bilateral hypothesized relationships. Section 3 describes the data and methodologies we use. Section 4 presents the empirical results. Section 5 concludes.

This paper presents compelling evidence that our theoretical understanding of how this market works is generally correct. Strong support is shown for 15 theory-based bilateral relationships between 6 trading variables: bid–ask spread, return volatility, expected volume, unexpected volume, expected order flow and unexpected order flow. These results are robust across 10 data samples, made up of 5 exchange rates which were sampled from 2 separate time periods. McGroarty et al.'s (2006) characterization of the bid–ask spreads as being very different from that normally assumed in the market microstructure literature is strongly vindicated by the evidence. Our analysis documents the M-shaped intraday pattern of order flow and identifies that this closely tracks the intraday pattern for trading volume. This scenario also accords with Garman's (1976) assertion that order flow arises from random temporal imbalances between supply and demand, rather than being a strict proxy for private information, as might be inferred from Evans and Lyons (2002). This uninformed order flow disturbs price, contributing to return volatility, as is consistent with Clark's (1973) MDH model. This contrasts with financial markets which have market makers at their core, who suppress this particular source of return volatility by ‘shading’ quote prices in order to buy back or sell on any acquired inventory, as Amihud and Mendelson (1980) describe. While it may indeed be less volatile, trading with market makers will be more expensive than trading on electronic market maker-less venues because market makers must be compensated via wider bid–ask spreads. This study shows that, while electronic inter-dealer spot FX bid–ask spreads are always of a low-general level, they widen and narrow with the normal ebb and flow of trading activity over the day, i.e. they are narrowest when expected volume is high and widen when expected volume falls. McGroarty et al. (2006) show that this is not due to changes in adverse selection risk facing market makers, but is attributable to volume-driven variations in the frequency at which the drift component of the underlying price is sampled. Utilizing Easley and O’Hara's (1992) notion that price signals are associated with deviations from normal trading levels, we use unexpected order flow and unexpected volume as proxies for private information. Both proxies show that private information has no discernable effect on the bid–ask spread in this market, as predicted. This is consistent with McGroarty et al.'s (2007) assertion that bid–ask spreads in this type of market have no adverse selection risk component and that, instead, informed trading passes straight through to return volatility. Furthermore, we show that this private information based return volatility is a separate, additional, source of volatility and is larger than the other (uninformed) return volatility which arises from normal trading activity alone. According to McGroarty et al. (2006), both these sources of return volatility radiate outwards from the inter-dealer market to permeate the entire foreign exchange market. This sheds some light on the excess exchange rate volatility puzzle identified by Flood and Rose (1995), by suggesting that some of this non-macroeconomic volatility is due to market microstructure effects and that a portion results directly from the way the market is structured, i.e. this source of volatility would not arise under alternative market structures. However, this does not necessarily imply that market structure contributes to exchange rate volatility measured at lower frequencies because much of this high-frequency volatility may dissipate when returns are aggregated.