This study examines the statistical properties required to model the dynamics of both the returns and volatility series … adequately estimate long-memory dynamics in returns and volatility. The in-sample diagnostic tests as well as out … conditional volatility and strongly support the estimation of dynamic returns that allow for time-varying correlations. A …

This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model …

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

, with a particular emphasis on bank profitability. Methodologically, it employs two multivariate time series models, namely … comprehensive profitability outlook for the Maltese core banking sector. Key findings are summarized as follows: (i) neither of the …

We propose a methodology to include night volatility estimates in the day volatility modeling problem with high … the natural relationship between the realized measure and the conditional variance. This improves volatility modeling by … leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that …