Dealer Behavior and Trading Systems in Foreign Exchange Markets

We study dealer behavior in the foreign exchange spot market using a detailed data set on the complete transactions of four dealers. There is strong support for an information effect in incoming trades. Although there is evidence that the information effect increases with trade size in direct bilateral trades, the direction of a trade seems to be more important. The large share of electronically brokered trades is probably responsible for this finding. In direct trades it is the initiating dealer that determines trade size, while in broker trades it is the dealer submitting the limit order that determines the maximum trade size. We also find strong evidence of inventory control for all the four dealers. Inventory control is not, however, manifested through a dealer's own prices as suggested in inventory models. This is different from the strong price effect from inventory control found in previous work by Lyons [J. Fin. Econ 39(1995) 321]. A possible explanation for this finding is that the introduction of electronic brokers allowed more trading options. Furthermore, we document differences in trading styles among the four dealers, especially how they actually control their inventories.Foreign Exchange; Trading; Microstructure

Dealer Behavior and Trading Systems in Foreign Exchange Markets

We study dealer behavior in the foreign exchange spot market using a detailed data set on the complete transactions of four dealers. There is strong support for an information effect in incoming trades. Although there is evidence that the information effect increases with trade size in direct bilateral trades, the direction of a trade seems to be more important. The large share of electronically brokered trades is probably responsible for this finding. In direct trades it is the initiating dealer that determines trade size, while in broker trades it is the dealer submitting the limit order that determines the maximum trade size. We also find strong evidence of inventory control for all the four dealers. Inventory control is not, however, manifested through a dealer's own prices as suggested in inventory models. This is different from the strong price effect from inventory control found in previous work by Lyons [J. Fin. Econ 39(1995) 321]. A possible explanation for this finding is that the introduction of electronic brokers allowed more trading options. Furthermore, we document differences in trading styles among the four dealers, especially how they actually control their inventories.Foreign Exchange; Trading; Microstructure

Volume and Volatility in the FX Market: Does it matter who you are?

The relationship between volume and volatility has received much attention in the literature on financial markets. However, due to the lack of data, few results have been presented for the foreign exchange (FX) market. Furthermore, most studies contain only aggregate series, and cannot distinguish between the impact of different participants or instruments. We study the impact of volume on volatility in the FX market using a unique data set of daily trading in the Swedish krona (SEK) market. The data set covers 95 percent of worldwide SEK trading, and is disaggregated on a number of reporting banks' buying and selling in five different instruments on a daily basis from 1995 until 2002. We find that volume in general show a positive correlation with volatility. However, the strength of the relationship depends on the instrument traded and the identity of the reporting bank. In particular, we find that trading tends to concentrate around the largest banks during periods of high volatility. These banks are probably also best informed. This is especially the case when volatility is high. We interpret this as evidence that heterogeneous expectations are important to an understanding of the volume- volatility relationship.Volume-volatility relation; microstructure; exchange rates

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants