This paper evaluates the profitability of applying four different volatility forecasting models to the trading of … applied in this paper are: historical volatility, two ARCH models, and an autoregressive model for the volatility index. VDAX …. The ARCH models perform best in generating profits for market makers. Forecasts based on historical volatility also …

framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our … countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other … results show that by considering time-varying return and volatility spillovers when calculating the risk-minimising portfolio …

The uncertainty of U.S. core inflation, measured by the stochastic volatility of forecast errors, has soared to a level …

Among a variety of small area estimation methods, one popular approach for the estimation of linear and non …-linear indicators is the empirical best predictor. However, parameter estimation using standard maximum likelihood methods is not … is often the case for income variables. Therefore, this work proposes an estimation method, which enables the estimation …

This paper proposes a Skewed Stochastic Volatility (SSV) model to model time varying, asymmetric forecast distributions … volatility and asymmetric measurement densities. Estimating the model based on US data yields conditional forecast densities that …

Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed … divergent when volatility clusters idiosyncratically.It is illustrated that this property is important for empirical …