This paper proposes a new test for simultaneous intraday jumps (cojumps) in a panel of high frequency financial data. We utilize intraday first-high-low-last values of asset prices to construct estimates for the cross-variation of returns in a large panel of high frequency financial data, which we then use to form a test statistic that can detect cojumps. Simulations show that a bias corrected version of the test performs well when microstructure noise is present. Applied to a panel of high frequency Chinese equity data, our test identifies cojumps that coincide with announcements relating to monetary policy and stock market regulations.

This paper examines how firm specific and macroeconomic announcements affect transaction rates in U.S. airline stocks. Using a version of the autoregressive conditional hazard framework of Hamilton and Jordà (2002) that incorporates market microstructure variables, we show that on average, trading intensity spikes prior and consequent to macroeconomic announcements, but decreases around firm-specific releases. Further, when we use intraday crude oil futures returns as a proxy for industry relevant and globally important news we find that their effects are statistically significant, with higher oil futures returns increasing the probability of trade.

This paper shows that yields to maturity of U.S. Treasury bills are cointegrated, and that during periods when the Federal Reserve specifically targeted short-term interest rates, the spreads between yields of different maturity define the cointegrating vectors.This cointegrating relationship implies that a single non-stationary common factor underlies the time series behavior of each yield to maturity and that risk premia are stationary.An error correction model which uses spreads as Ihe error correction terms is unstable over the Federal Reserve's policy regime changes, but a model using post 1982 data is stable and is shown to be useful for forecasting changes in yields.