We study the impact of algorithmic trading in the foreign exchange market using a long time series of high-frequency data that specifically identifies computer-generated trading activity. Using both a reduced-form and a structural estimation, we find clear evidence that algorithmic trading...

As the economic disruptions associated with the COVID-19 pandemic increased in March 2020, there was a global dash-for-cash by investors. This selling pressure occurred across advanced sovereign bond markets and caused a deterioration in market functioning, leading to central bank interventions....

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using volatility signature...

This paper examines the available data that may shed light on the carry trade in Japanese yen. We define an individual or a sector to be engaged in the carry trade if it has a short position in yen and a long position in other currencies. The tendency of large yen movements to be skewed toward...

We analyze the factors driving the widely-noted persistence in asset return volatility using a unique dataset on global euro-dollar exchange rate trading. We propose a new simple empirical specification of volatility, based on the Kyle-model, which links volatility to the information flow,...