The cryptocurrency market has experienced stunning growth, with market value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, and stablecoins. Our results demonstrate that...

We apply a functional data approach for mixture model-based multivariate innovation clustering to identify different regional innovation portfolios in Europe. Innovation concentration is considered as pattern of specialization among innovation types. We examine patent registration data and...

The way of working is evolving constantly, and in the last year, the changes have been major under the influence of the COVID-19 pandemic. Even before the pandemic, the work flexibility was encouraged and stimulated in Romania by the promotion of the telework law, becoming an important factor...

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC...

This paper introduces a multivariate long-memory model with structural breaks. In the proposed framework, time series exhibit possibly fractional orders of integration which are allowed to be different in each subsample. The break date is endogenously determined using a procedure which minimises...

Decisions under risk are often multidimensional, where the preferences of the decision maker depend on several attributes. For example, an individual might be concerned about both her level of wealth and the condition of her health. Many times the signs of successive cross derivatives of a...