framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our … results lend support to the existence of a substantial time-variation in the dynamic linkages between these financial assets … countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other …

no leverage. Yet using unique granular data on the bond holdings of institutional funds, we show that their trading …

stochastic volatility of asset prices and to give theoretical arguments for empirically well documented facts. We show that … stochastic volatility. …

volatility. Hence, they are viable alternatives to the geometric Brownian motion. …

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

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 …

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 …