We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log-returns using Markov-switching GARCH (MSGARCH) models. We also compare MSGARCH to traditional single-regime GARCH specifications in predicting one-day ahead Value-at-Risk (VaR). The Bayesian approach is used...

We empirically test the prediction of Pastor, Stambaugh, and Taylor 2020 that green firms can outperform brown firms when climate change concerns strengthen unexpectedly for S&P 500 companies over the period January 2010 - June 2018. To capture unexpected increases in climate change concerns, we...

This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH models. These models are widespread and essential tools in financial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique....

Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indices worldwide. The value-at-risk forecast performance is investigated for different markets and industries, considering the test for correct conditional coverage using the false discovery rate...