Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are …

shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail … stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the …

inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an …

volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically … forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility …

While international election interference is not new, Russia is credited with "industrializing" trolling on English … written by trolls from Russia's Internet Research Agency. Most active 2015-2017, these Russian trolls generally supported the …

achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian …

common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent … method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the …

premium. We use this simple observation to forecast the equity-premium time series with the cross-sectional price of risk. We …