We plot aggregated daily stock returns with absolute value less than x against x and show empirically that this produces a typical spoon-shaped pattern which indicates a special type of asymmetry which has not been discussed before. This pattern disappears when individual returns are averaged; it...

Today we live in a post-truth and highly digitalized era characterized by a flow of (mis-) information around the world. Identifying the impact of this information on stock markets and forecasting stock returns and volatilities has become a much more difficult task, perhaps almost impossible....

This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...

This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...

This paper estimates a bivariate HEAVY system including daily and intra-daily volatility equations and its macro-augmented asymmetric power extension. It focuses on economic factors that exacerbate stock market volatility and represent major threats to financial stability. In particular, it...

This study investigates the short- and long-term effects of various sources of uncertainty on the share prices of key exchanges in emerging nations. The sample comprises monthly time series data from January 2017 to December 2021 for China, India, Russia, and Brazil. The study contains a version...

Estimating the covariance between assets using high frequency data is challenging due to market microstructure effects and asynchronous trading. In this paper we develop a multivariate realised quasi maximum likelihood (QML) approach, carrying out inference as if the observations arise from an...

Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using...

We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors. We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and...

Investigating linkages between credit and equity markets, we consider daily aggregate U.S. CDS spreads as well as well-chosen equity market and implied volatility indexes over ten years. We describe such robust (to spurious correlation) relationship with the quantile cointegrating regression...