We propose using a permutation test to detect discontinuities in an underlying economic model at a known cutoff point. Relative to the existing literature, we show that this test is well suited for event studies based on time‐series data. The test statistic measures the distance between the...

This paper introduces new econometric tests to identify stochastic intensity jumps in high-frequency data. Our approach exploits the behavior of a time-varying stochastic intensity and allows us to assess how intensely stock market reacts to news. We describe the asymptotic properties of our...

This work quantifies the financial and macroeconomic effects of the most significant Brexit events from 23 June 2016 up to 31 December 2019 for fifteen economies. The study uses high-frequency data and shows that following the referendum outcome, overall the 10-year government bond yield of the...

We study the impact of news embedded in scheduled macroeconomic announcements on the government bond market in Poland and the Czech Republic. We conduct an event study on intraday data and time-series regressions using daily data over an eight-year period, distinguishing between effects under...

This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in...

This paper examines reactions in the Ukrainian stock market to force majeure events, which are divided into four groups: economic force majeure, social force majeure and terrorist acts, natural and technological disasters. More specifically, using daily data for the main Ukrainian stock market...

This paper examines the hypothesis that both stock returns and volatility are asymmetric functions of past information derived from domestic and U.S. stock-market news. The results show the presence of negative autocorrelation, which is consistent with the dominance of positive-feedback trading...

We find that investor attention proxies proposed in the literature collectively have a common component that has significant power in predicting stock market risk premium, both in-sample and out-of-sample. This common component is well extracted by using partial least squares, scaled principal...