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We present evidence that non-financial customers are the main liquidity providers in the overnight foreign exchange market using a unique daily data set covering almost all transactions in the SEK/EUR market over almost 10 years. Two main findings support this: (i) the net position of non-financial customers is negatively correlated with the exchange rate, opposed to the positive correlation found for financial customers and (ii) changes in net position of non-financial customers are forecasted by changes in net position of financial customers, indicating that non-financial customers take a passive role consistent with liquidity provision.

The provision of liquidity is important for well-functioning asset markets. Liquid markets match counterparties well (immediacy), have low transaction costs (tight spreads), and are less volatile (O'Hara, 1995). In this paper, we study liquidity provision in the foreign exchange market. A central question raised is the following: who is providing liquidity? The conventional wisdom is that market making banks are the main liquidity providers in floating exchange rate regimes. However, from the studies by Lyons (1995) and Bjønnes and Rime (in press) we know that dealers of market making banks have only limited overnight positions and cannot be expected to take lasting open positions. Hence, market making banks provide liquidity intraday, but are less likely to provide liquidity on longer horizons. In this paper, we empirically investigate whether there is a particular group of market participants that act as liquidity providers overnight. To address this question, we use a unique data set from the Swedish krona (SEK) market that contains observations of 90–95% of all transactions in five different instruments on a day-to-day basis from the beginning of 1993 up to the summer of 2002. The study of liquidity in the foreign exchange market is particularly interesting for at least two reasons. First, our understanding of the movements of floating exchange rates is rather poor, and better knowledge of how the market works may improve our understanding. Second, as a largely unregulated market, patterns of liquidity provision have evolved endogenously. This is in contrast to several equity markets where, e.g., market makers have obligations to provide liquidity. Daníelsson and Payne (2002) study intraday liquidity in an electronic FX order book. The present paper is to the best of our knowledge the first to study liquidity in a longer perspective for the foreign exchange market. Our data allow us to distinguish between four distinct groups of market participants: (i) Market making banks; (ii) Financial customers; (iii) Non-Financial customers; and (iv) the Central Bank (Sveriges Riksbank). Currently there is no other data set on the foreign exchange market that gives such broad overview of the trading of a single currency. A notable feature of our data is that the flows of different customers (Financial, Non-Financial, and the Central Bank) will equal the flow of Market making banks.1 If flows of one group of participants are positively correlated with changes in the foreign exchange rate, we will see a negative correlation for another group, or groups, of participants. How can we identify the liquidity provider? The theory of market making predicts that a positive demand shock (i.e., a purchase by the aggressive part in the trade) will lead the market maker to revise prices upwards, hence a positive contemporaneous correlation between the trading decision of the aggressive part and the change of the exchange rate.2 The supplier of the asset, e.g., a market maker, will fill the role of liquidity provider. There are in particular two characteristics of liquidity providers: (a) the net flow of liquidity providers will be negatively correlated with the change in the value of the currency and (b) liquidity providers match others' demand and supply passively. These two predictions are borne out in the data. Our findings suggest that Non-Financial customers are the main liquidity providers overnight. First, we find a negative correlation between the net purchases of foreign currency made by Non-Financial customers and changes in the exchange rate. This negative correlation is matched by a positive correlation between net purchases of Financial customers and changes in the exchange rate. The coefficients of the two groups are not only similar in absolute value, but are also very stable. These findings lead us to conclude that the Non-Financial customers we observe fulfill requirement (a) above, while Financial customers do not. The fact that the foreign exchange rate and positions held by Financial and Non-Financial customers are cointegrated suggest that the price effect is permanent. Second, requirement (b), that the presumed liquidity providers passively match changes in the demand and supply of others, is tested using Granger causality. We find that the trading of Financial customers tends to forecast the trading of Non-Financial customers. This suggests that the Non-Financial customer group is not in the active end of trading. These results are not obvious. Four important issues might come to mind. First, if these are liquidity effects, how can they be permanent? It is important to remember that it is not liquidity effects that cause the change in the exchange rate. The exchange rate change is due to a portfolio shock by the Financial customers. We identify the supply of liquidity that meets this portfolio shock (more on the economic intuition for the permanent effect below). Second, it might seem counter-intuitive that Non-Financial customers should provide liquidity. However, one should note that Non-Financial customers in our data behave like profit-takers; they react to a change in the exchange rate. A liquidity provider, as used here, is one who enters the market as a reaction to the action of others. It is not necessary for the Non-Financial to perceive themselves as liquidity providers. Third, it is clear that the group of Financial customers must be very diversified. It should contain a spectrum of customers from hedge funds to portfolio managers. Especially hedge funds might use a range of trading strategies. If anything, this could weaken our findings relative to a data set were we could identify hedge funds specifically. Last, if Non-Financial behave like profit-takers, are they then “Friedman speculators”? The positions of a Friedman speculator will be negatively correlated with the exchange rate when the level is moving away from equilibrium, while the positions will be positively correlated with the exchange when the rate is moving towards the equilibrium level. Hence, the liquidity providers do not necessarily act as “Friedman speculators”. Closest in spirit to this paper are those by Froot and Ramadorai (2002) and Fan and Lyons (2003). Froot and Ramadorai (2002) have data from the global custodian State Street Corporation, covering transactions over a period of 7 years in 111 currencies. Given the source of the data, it is reasonable to believe that the transactions are those of financial customers. Fan and Lyons (2003) use data on customer trading from Citibank. Both studies find results similar to ours for financial customers. While the data employed by Froot and Ramadorai (2002) and Fan and Lyons (2003) only represent a small market share of total currency transactions in a currency, our data reflect entire market activity. Also in contrast to these studies, our data allow us to directly test how flows of different groups of customers are related to changes in the foreign exchange rate. To give a brief theoretical interpretation of our results, we may consider the model by Evans and Lyons (2002). A trading day is split into three trading rounds. In the first round, market making banks provide liquidity to customers. To offload their inventories after trading with non-bank customers in round 1, dealers trade among themselves in round 2. However, if there is excess demand for one currency after the round of interdealer trading, the market making banks must induce the customers to hold this. The customers in round 3 then need a risk premium to be willing to change their portfolio holdings. Hence, one expects to see a positive correlation between round 1 excess demand for a currency and the value of this currency. Using data from the interdealer market, Evans and Lyons (2002) find strong empirical support for such a positive correlation. In the Evans and Lyons (2002) model, market making banks provide liquidity intraday to round 1 customers, while round 3 customers are compensated for providing overnight liquidity. In this model, net purchases of all customers sum to zero after the third round of trading. However, this does not mean that net purchases of a particular group of customers must sum to zero. In light of the Evans and Lyons (2002) model, it is possible to interpret our results such that the typical aggressive round 1 customer is financial, while the typical liquidity providing round 3 customer is non-financial. Our results also have implications for the exchange rate determination puzzle (see e.g., Meese and Rogoff, 1983 and Frankel and Rose, 1995). A better understanding of the role played by different market participants may be necessary to understand the movements of exchange rates. We document cointegration between the exchange rate and net currency positions held by Financial and Non-Financial customers, which suggests that price effects are permanent. We also show that net flows are able to explain changes in the foreign exchange rate at frequencies commonly used in tests of macroeconomic models. The explanatory power is very good. Flows by Financial or Non-Financial customers combined with interest rate differentials explain roughly 70% of changes in the foreign exchange rate at the 90-day horizon. As mentioned, the coefficient for the net flow of Financial or Non-Financial customers is also remarkably stable over the sample. The paper is organized as follows. Section 2 discusses liquidity provision in FX markets. Our data are presented in Section 3. Section 4 reports the results on our attempts to identify the liquidity provider. Section 5 provides a discussion of our results, while Section 6 concludes.

The provision of liquidity is important for well-functioning asset markets. Still, the liquidity of the foreign exchange market, perhaps the most important financial market, is a black box. We know that market makers provide liquidity in the intraday market when exchange rates are floating. This paper addresses the issue of who provides liquidity overnight in the foreign exchange market. To this end we use a unique data set from the Swedish foreign exchange market which covers the trading of several distinct groups over a long time span, from the beginning of 1993 to the summer of 2002. The distinct groups we analyze are: (i) Market making banks; (ii) Financial customers; (iii) Non-Financial customers; and (iv) the Central Bank. We use the theory of market making to characterize what to expect of a liquidity providing group of market participants, if one exists. There are two characteristics of a liquidity provider: (a) The net currency position of the liquidity provider will be negatively correlated with the value of the currency; and (b) The trading of the liquidity provider will be result of passively matching others’ demand and supply. We have presented several findings supporting the proposition that Non- Financial customers are the main liquidity providers in the Swedish market. First, we confirm that there is a positive correlation between the net purchases of currency made by Financial customers and changes in the exchange rate. Thus, when Financial investors buy SEK, the SEK tends to appreciate. The correlation becomes stronger as we lower the frequency. These findings are consistent with the results of Froot and Ramadorai (2002) and Fan and Lyons (2003) . Furthermore, we find that the positive correlation between net purchases of currency of Financial customers and the exchange rate is matched by a negativecorrelation between the net purchases of Non-Financial customers and changes in the exchange rate. The coefficient is not only similar to the one of Financial customers in absolute value, but is also very stable. These findings lead us to conclude that Non- Financial customers fulfill requirement (a) above, while Financial customers do not. Second, we also find that requirement (b), that the liquidity providers passively match changes in the demand and supply of others, is supported for the Non-Financial customers. We find that the trading of Financial customers and Market making banks can forecast the trading of Non-Financial customers, but not the other way. We interpret this as evidence that the Non-Financial customer group is not the active part in trading. Third, in our cointegration analysis we find the two previous points supported for the steady state long run. The permanent effect of Non-Financial customers’ trading is negative, while the permanent effect of Financial customers’ trading is positive. More important, we find that there is a close, but opposite, relation between the two flows in the long run. It appears that identifying a liquidity provider has been an important issue. Several authors, e.g., Hau and Rey (2002) and several papers by Carlson and Osler, utilize the idea of a liquidity provider comparable to the one identified here. In Carlson and Osler (2000) ‘‘current account’’ traders fill the role of liquidity providers. They assume that these ‘‘current account’’ traders’ ‘‘demands for currency are [ . ] determined predominantly by the level of the exchange rate and by factors unconnected to the exchange rate which appear random to the rest of the market.’’ This paper is a first attempt to address the question of overnight liquidity provision in the foreign exchange market. To what extent can we expect these findings to be generalized to other currencies? The SEK is the eight most traded currency according to the latest BIS survey of the foreign exchange market. The Swedish currency market is similar to other currency markets in many respects. The trading facilities are similar for most currency markets. Trading in e.g. USD/EUR, SEK/EUR and other currency crosses take place at the same systems. Also, the market shares of Financial and Non-Financial customers found for the Swedish currency market, are very similar to those found for other currency markets. Our results have implications for the exchange rate determination puzzle. We document that changes in net positions held by Financial or Non-Financial cus- tomers are capable of explaining changes in the foreign exchange rate at frequencies commonly used in tests of macro economic models. Hence, it is important to acquire more knowledge about which factors determine different FX flows. This will be the focus of our future research in this area.