World economies, and especially European ones, have become strongly interconnected in the last decades and a joint modelling is required. We propose here the use of Copulas to build flexible multivariate distributions, since they allow for a rich dependence structure and more flexible marginal...

Many empirical studies showed the strong degree of persistence of shocks to the conditional variance process. In this case, the distinction between stationary and unit root processes may be too restrictive, since the propagation of shocks occurs at an exponential rate of decay in a stationary...

The financial crisis of 2007-2009 has begun in July 2007 when a loss of confidence by investors in the value of securitized mortgages in the United States resulted in a liquidity crisis. World stock markets peaked in October 2007 and then entered a period of high volatility which culminated with...

The ex-ante forecast of the SP500 index discussed in Fantazzini (2010a), covering the time sample 14/04/2009-09/10/2010, and originally submitted to the Economics Bulletin on the 15/05/2009 is analyzed. It is found that the realized values of the SP500 index trailed the forecasted values quite...

This work proposes to forecast the Realized Volatility (RV) and the Value-at-Risk (VaR) of the most liquid Russian stocks using GARCH, ARFIMA and HAR models, including both the implied volatility computed from options prices and Google Trends data. The in-sample analysis showed that only the...

The ability of Google Trends data to forecast the number of new daily cases and deaths of COVID-19 is examined using a dataset of 158 countries. The analysis includes the computations of lag correlations between confirmed cases and Google data, Granger causality tests, and an out-of-sample...

While there is an increasing interest in crypto-assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we consider a unique data set on 144 exchanges active from the first quarter of 2018 to the first quarter of 2021. We analyze the determinants of the...

This paper focuses on the forecasting of market risk measures for the Russian RTS index future, and examines whether augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the estimated risk measures. We considered a time sample of...

This paper examined a set of over two thousand crypto-coins observed between 2015 and 2020 to estimate their credit risk by computing their probability of death. We employed different definitions of dead coins, ranging from academic literature to professional practice, alternative forecasting...

In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the daily range incorporates all the information...