We propose a new clustering approach for comparing financial time series and employ it to study how the COVID-19 pandemic affected the U.S. stock market. Essentially, we compute the forecast accuracy of asymmetric GARCH models applied to S&P500 industries and use the model forecast errors for...

This paper explores the structural driving sources of oil market volatility and correlation dynamics. Our results highlight a steadily declining oil production volatility and concurrent increasing real oil price volatility since the mid-1980s. We find that a decrease in the persistence of the...

Did Covid19 indiced market turmoil impact the intraday volatility spillovers between energy and other ETFs?. To examine this , we first estimate the realized volatility of ETFs using the 5-minute high-frequency data. Next, we employ time-varying parameter vector autoregressions (TVP-VAR)....

Modeling futures market risk simultaneously influenced by macro low-frequency information and daily risk factors is a valuable challenge. We propose a new general framework for it based on the flexible GARCH-MIDAS model. It uses a skewed t distribution to describe the asymmetry of long and short...