Provides a comprehensive and updated study of GARCH models and their applications in
finance, covering new developments in the discipline This book provides a comprehensive …

This paper aims to select the best model or set of models for modelling volatility of the four
most popular cryptocurrencies, ie Bitcoin, Ethereum, Ripple and Litecoin. More than 1000 …

We perform a large-scale empirical study in order to compare the forecasting performances
of single-regime and Markov-switching GARCH (MSGARCH) models from a risk …

Since the pioneering work by Tong (1978, 1983), threshold time series modelling and its
applications have become increasingly important for research in economics and finance. A …

Since Bitcoin price is highly volatile, forecasting its volatility is crucial for many applications,
such as risk management or hedging. We study which model is the most suitable for …

We investigate the role of geopolitical risks in forecasting stock market volatility at monthly
horizons within a robust autoregressive Markov-switching GARCH mixed-data-sampling (AR …

Over the past years, cryptocurrencies have drawn substantial attention from the media while
attracting many investors. Since then, cryptocurrency prices have experienced high …

We use high-frequency intra-day realized volatility data to evaluate the relative forecasting
performances of various models that are used commonly for forecasting the volatility of …

The experience from the global financial crisis has raised serious concerns about the
accuracy of standard risk measures as tools for the quantification of extreme downward …

GARCH volatility models with fixed parameters are too restrictive for long time series due to
breaks in the volatility process. Flexible alternatives are Markov-switching GARCH and …