This paper develops a two-step inference procedure to test for a local one-for-one relation of contemporaneous jumps in high-frequency financial data corrupted by market microstructure noise. The first step develops a new bivariate Lee-Mykland jump test for pre-averaged, intra-day returns. If a...

This paper studies high-frequency econometric methods to test for a jump in the spread of bond yields. We propose a coherent inference procedure that detects a jump in the yield spread only if at least one of the two underlying bonds displays a jump. Ignoring this inherent connection by basing...

Using high-frequency data, we decompose the time-varying beta for stocks into beta for continuous systematic risk and beta for discontinuous systematic risk. Estimated discontinuous betas for S&P500 constituents between 2003 and 2011 generally exceed the corresponding continuous betas. We...

This paper develops a methodology for detecting and measuring contagion using high frequency data which disentangles continuous and discontinuous price movements. We demonstrate its finite sample properties using Monte-Carlo simulation, focusing on the empirically plausible parameter space....

We evaluate the impact of extreme market shifts on equity portfolios and study the difference in negative and positive reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of the S&P500 index over the period 2 January 2003...