This paper introduces a new information density indicator to provide a more comprehensive understanding of price reactions to news and, more specifically, to the sources of jumps in financial markets. Our information density indicator, which measures the abnormal amount of noisy “ticker”...

This study examines short selling in stocks of firms that reveal partial earnings-related information prior to their eventual earnings announcements (EA). By decomposing short selling into two components where the first corresponds to the final partial earnings disclosure and the second captures...

We develop a measure of how information events impact investors' perceptions of risk that is broadly applicable and simple to implement. We derive this measure from an option-pricing model where investors anticipate an announcement that simultaneously conveys information on the announcer's...

This study employs macroeconomic news announcements as proxy for new information arrivals and examines their impact on price discovery of Canadian cross-listed stocks. We compare the price discovery of 38 Canadian companies listed on the Toronto Stock Exchange (TSX) and the New York Stock...

We empirically explore the role of investor disagreement and news for various types of stock jumps, where the dynamic of stock returns is captured by a contagion model. Our disagreement measure is derived from more than 173 million tweets from a social media investing platform, StockTwits, for...

This paper aims to examine the reactions among institutional and individual investors when facing those listed firms' public announcements, and the effects of their trading on stock returns on the Taiwan Stock Exchange (TSE). By employing a trivariate vector autoregressive (VAR) model, we find...

Dynamic average correlations of stock returns are predicted by the volatility of the market excess return and moving average returns of value, size and momentum portfolios. While the influence of market volatility on average correlation is well-known, the role of value, size and momentum appears...

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with exogenous predictors. Unlike existing Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms, our approach is not based on a structural form representation of the...

The COVID-19 pandemic has caused severe disruption to economic activity worldwide. This note analyzes what happened to the aggregate U.S. stock market during this period, including implications for both short and long-horizon investors. We identify bull and bear market regimes including their...

This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics, the interlinkages, and the conditional correlations...