اطلاعات محلی در بازار ارز خارجی

This study shows that order flow in a foreign exchange market appears to have permanent price impact only if it comes from certain regions. These regions are – as predicted by the local information hypothesis – centers of political and financial decision making. It is revealing that orders from other regions only show a very short-lived but no permanent price impact. Local information is so important that it carries over from the usually considered market orders to aggressively priced limit orders too. The finding is robust to common news shocks, to the consideration of feedback trading and to further controls.

In light of the failure of the traditional macro approach in exchange rate modeling the microstructure analysis of currency markets seems to provide new insights (see e.g. Frankel and Rose, 1995, Lyons, 2001 and Sarno and Taylor, 2002). In a sense, it reverses the conventional top down macro perspective by analyzing trader behavior bottom up. Assuming that market participants are asymmetrically informed, it seems worthwhile to analyze behavior at the microstructure level in order to better understand who has information and in which way this information gets into prices. One plausible source of information advantage could be local proximity to centers of decision making. Goodhart and Figliuoli (1992) “regard it as inevitable that some aspects of news [in foreign exchange] will differ between geographical locations”. Obviously, an analysis testing the potential price impact of local information requires transaction data where currency orders can be linked to locations. This paper is the first, due to a new data set, that is able to examine this question exactly. We find clear evidence supporting the notion of local information advantage in foreign exchange markets. The possible existence of local information advantages in financial markets does not seem to be self-evident in times of the Internet and other modern instruments of communication. These instruments may nourish some skepticism and, indeed, enough studies demonstrate that investments in local assets are often based on home bias instead of an information advantage (e.g. Huberman, 2001). Nevertheless, the careful analysis of locally rooted information asymmetries has brought about overwhelming evidence during the last years that local information still exists, even in modern globalized markets. Coval and Moskowitz (2001) identify performance advantages of fund managers that invest in local firms, Hau (2001) shows that trading profits are higher for local equity traders, Ivković and Weisbenner (2005) find that local equity investments of individual investors earn higher risk-adjusted returns and Malloy (2005) demonstrates superior forecasting performance of analysts for firms within the analysts' region (see also Bae et al., 2005). So, local proximity to centers of decision making, such as firm headquarters, can provide an information advantage. Recently, Berger et al. (2006) have extended this line of research to monetary policy forecasting and find that Frankfurt-based analysts predict interest rate changes of the European Central Bank significantly better than others. Obviously, local information advantages do not only appear in stock markets but also in the domain of macroeconomic fundamentals which is of particular importance for foreign exchange. In contrast to this strong evidence for equity and money markets, there is hardly any outright test of the local information hypothesis in foreign exchange. Goodhart and Figliuoli (1992) are the first to examine local information asymmetries in foreign exchange. They find some evidence that indeed price movements between centers, such as London and New York, show negative correlation in returns, indicating different information sets, whereas price movements within locations do not. Peiers (1997) compares the quotes of single banks analyzing potential price leadership in the mark/dollar market around interventions of the Deutsche Bundesbank. She shows that at least one German bank seems to be better informed than others (but there is no such effect for US interventions according to Dominguez, 2003). De Jong et al. (2001) extend this work, among other things by considering more banks, and find a slight tendency but no unanimous proof of a local information hypothesis. Sapp (2002) identifies different price-leading banks in the European and the US market, again without a clear relation to the location of these banks' headquarters. Whereas these studies are actually interested in potential price leadership of single banks, Covrig and Melvin (2002) disaggregate the yen/dollar market into Japanese and other quotes and find that Japanese traders lead the market under certain circumstances. So there is some first evidence in favor of the local information hypothesis, but all these analyses are limited by the fact that they have to rely on indicative quotes which differ from prices (Daníelsson and Payne, 2002). Therefore, it seems highly warranted to examine the hypothesis of a local information advantage in foreign exchange markets with better data. For this purpose, we can rely on the full record of orders in a modern electronic foreign exchange market, i.e. the Russian interbank Russian rouble/US dollar market. Fortunately, all orders can be linked unanimously to one of eight different regions in Russia. This allows a straightforward test of the local information hypothesis by applying the standard concept of price impact analysis (Hasbrouck, 1991 and Hasbrouck, 2006). Accordingly, all kinds of microstructural effects, such as liquidity-induced price impacts, compensate each other and disappear over time – the only price impact that will be of permanent nature is due to information. As this concept is very well established in the literature it can be used as a reliable method to test the local information hypothesis1: if there are regions which are better informed, trades from these regions should have a high permanent price impact whereas order flow from regions without any systematic information advantage should have a smaller permanent price impact or only temporary impacts on exchange rates due to liquidity effects. Following the local information literature, regions are better informed when they host centers of decision making. In foreign exchange, this applies to two kinds of institutions: first, institutions which generate or inform about public information, such as the central bank or ministries, and second, institutions which interpret public information better than others or which have access to private information from financial institutions by receiving their order flow (Lyons, 1997).2 In Russia, the political, financial and economic center is all in one place, i.e. Moscow. The only other region that can be considered as possibly better informed than the average is the country's second largest city, St. Petersburg. As orders reflect the location of the trading bank and its customer base, the local information hypothesis predicts that order flow from Moscow – possibly from St. Petersburg too – has more price impact than orders from Russia's periphery. Of course, there will be noise in the data as not every bank or its customers in Moscow will be better informed than others in the large country. However, this only heightens the stakes when testing the local information hypothesis. At the core of our research, we find that only trades from the regions Moscow and St. Petersburg have permanent price impact in the Russian rouble/US dollar market, i.e. provide information. Trades from the other six Russian regions also show some short-lived price impact, which disappears, however, within a few minutes. This result provides strong evidence in favor of the local information hypothesis in foreign exchange markets. In fact, it is new evidence for foreign exchange markets based on trading data. We further substantiate the importance of local information by considering limit orders, i.e. orders that are not executed immediately, for the first time in foreign exchange. Results show that not only the usually considered market orders (see e.g. Evans and Lyons, 2002a and Payne, 2003) but also aggressively priced limit orders from both center regions provide information whereas those from other regions do not. Moreover, we show that findings are robust. They hold when we consider the possibility of common news shocks, i.e. a joint influence on order flow and prices, they hold when we allow for feedback trading, i.e. influences from ongoing price changes on order flow, and they hold when we control for sample splits, market conditions and trader size. Due to the new and detailed data being used here, this paper also provides evidence on related lines of recent research. First, it increases credence of the local information hypothesis in general because there has been no other study testing the local information hypothesis by the price impact approach, according to the best of our knowledge. Second, the new evidence highlights the importance of limit orders for information processing. It supports recent findings of an experimental study by Bloomfield et al. (2005), findings for the US equity market studied by Kaniel and Liu (2006) and it motivates to disaggregate limit orders according to their economic purpose (see Hasbrouck and Saar, 2004). Third, the evidence on local information in foreign exchange markets supports the view that order flow indeed conveys information.3 This paper continues with a description of the market structure under consideration, data and descriptive statistics in Section 2. Section 3 analyzes price impacts of different regions and extends the analysis to different order types, common news shocks and feedback trading. Section 4 provides further robustness tests and Section 5 concludes.

This paper supports the hypothesis that information is asymmetrically distributed between locations in foreign exchange markets. As our standard method to infer about information, we use price impact analyses to determine whether orders have transitory or permanent impact (Hasbrouck, 2006). If prices change temporarily, this is interpreted as indicating market frictions, such as short-term liquidity shocks. If prices, however, do not reverse after a trade to the former level, information is conveyed. The local information hypothesis states that information may be asymmetrically distributed between different regions. Those locations which are close to centers of decision making are potentially better informed, whereas peripheral locations are expected to be rather less informed. In the Russian rouble/dollar market under review, locations being close to decision makers should be in the region of Moscow and possibly the region of St. Petersburg, the center regions. Orders from the six other regions, being quite different from the two centers according to the Russian economic statistics, should be less informed on average. Fortunately, the data set of 9 days country-wide interbank RUR/USD trading allows allocating orders to eight regions each. Accordingly, the local information hypothesis can be tested with exact trading data for the first time in foreign exchange. We do, indeed, find that regions make a difference in the price impact of orders. Orders from the center regions tend to move prices permanently, i.e. they provide information. Orders from other regions, however, move prices for a few minutes only before they reverse to their former level. Local information is so important, according to our analysis, that it even dominates conventional wisdom regarding preferred order type. Earlier studies have argued forcefully that informed traders prefer market orders and the uninformed tend to rely on limit orders (see the excellent discussion in Bloomfield et al., 2005). Consequently, the former have price impact and the latter have not. In a novel analysis we break down this simplified distinction of two cases – market versus limit orders – into six cases, i.e. three types of orders times two types of traders, either from center regions or others. Due to this disaggregation we find that location “beats” order type. Market orders and aggressively priced limit orders of center traders are informative whereas orders from other regions are on average never informative, whatever order type they choose. This evidence cannot be easily explained by different order size as we measure the price impact per dollar. Moreover, we control for possible effects of common news shocks and feedback trading which might both drive results, as has been argued recently. The findings are robust to and also hold for different aggregation of trading data, for splits of the overall sample, for various market conditions and when we control for trader size. Finally, concerns might refer to the Russian RUR/USD market, which is small compared to world's leading markets. This lower transaction volume, however, basically seems to reflect the smaller size of the Russian economy and does not lead to different market statistics. Moreover, the Russian foreign exchange market uses a very similar trading technology to other leading electronic currency markets. Nevertheless, we have conducted standard tests on market behavior to see whether this market might be different; results confirm market characteristics of leading markets as examined, for example, by Payne (2003). Therefore, findings may be seen as an extension of earlier price impact analyses: we split aggregate order flow according to regions and in a further step even consider aggressively priced limit orders. Whatever analysis is performed, order flows from the center regions tend to be informed and order flows originating from other regions are not – providing strong evidence in favor of local information in foreign exchange markets.