This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point and density forecasts of macroeconomic variables. In this analysis, we consider both Bayesian autoregressive and Bayesian vector autoregressive models that incorporate some form...

This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point and density forecasts of macroeconomic variables. In this analysis, we consider both Bayesian autoregressive and Bayesian vector autoregressive models that incorporate some form...

In this paper we develop a mixed frequency dynamic factor model featuring stochastic shifts in the volatility of both the latent common factor and the idiosyncratic components. We take a Bayesian perspective and derive a Gibbs sampler to obtain the posterior density of the model parameters. This...

We study the impact of model disagreement on the dynamics of asset prices, return volatility, and trade in the market. In our continuous-time framework, two investors have homogeneous preferences and equal access to information, but disagree about the length of the business cycle. We show that...

The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. The approach for computing fractal dimension using sequence of the minimal covers with decreasing scale is used to...

We investigate the question whether macroeconomic variables contain information about future stock volatility beyond that contained in past volatility. We show that forecasts of GDP and industrial production growth from the Federal Reserve's Survey of Professional Forecasters predict volatility...