This paper highlights the previously neglected role of the futures markets in US Treasury price discovery. The estimates of 5-and 10-year GovPX spot market information shares typically fail to reach 50% from 1999 on. The GovPX information shares for the 2-year contract are higher than those of the 5-and 10-year maturities but also decline after 1998. Relative bid-ask spreads, number of trades, and realized volatility are statistically significant and explain up to 21% of daily information shares. In roughly 1/4 of cases when public information is released, the futures market gains information share, but macroeconomic announcements rarely explain information shares independently of liquidity.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper assesses the microstructure of the U.S. Treasury securities market, using newly available tick data from the BrokerTec electronic trading platform. Examining trading activity, bid-ask spreads, and depth for on-the-run two-, three-, five-, ten-, and thirty-year Treasury securities, we find that market liquidity is greater than that found in earlier studies that use data only from voice-assisted brokers. We find that the price effect of trades on BrokerTec is quite small and is even smaller once order-book information is considered. Moreover, order-book information itself is shown to affect prices. We also explore a novel feature of BrokerTec-the ability to enter hidden ("iceberg") orders-and find that, as predicted by theory, such orders are more common when price volatility is higher.

Exchange rate modelling has been a persistent puzzle for international economists. Forecasts from popular models for the exchange rate generally fail to improve upon the random walk out‐of‐sample. While a multivariate nonparametric approach provides useful information about exchange rates, the model produces forecasts superior to the random walk for only one of the three EMS currencies examined. Using a statistic developed in Mizrach (1991), I find that the forecast improvement, a 4.5 percent reduction in mean squared error for the Lira in daily returns, is not statistically significant. A cross‐validation exercise suggests that the improvement is also not robust.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper assesses the microstructure of the U.S. Treasury securities market, using newly available tick data from the BrokerTec electronic trading platform. Examining trading activity, bid-ask spreads, and depth for on-the-run two-, three-, five-, ten-, and thirty-year Treasury securities, we find that market liquidity is greater than that found in earlier studies that use data only from voice-assisted brokers. We find that the price effect of trades on BrokerTec is quite small and is even smaller once order-book information is considered. Moreover, order-book information itself is shown to affect prices. We also explore a novel feature of BrokerTec-the ability to enter hidden ("iceberg") orders-and find that, as predicted by theory, such orders are more common when price volatility is higher.

No abstract