The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

This paper assesses the performance of a number of long-term interest rate forecast approaches, namely time series … is compared using out of sample forecast errors, where a random walk forecast acts as benchmark. It is found that for … approaches do not outperform the random walk, or a somewhat more sophisticated time series model, on a 3 month forecast horizon …

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the … conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the … conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain …

dynamic factor and a vector autoregressive model and includes stochastic volatility, denoted by FAVAR-SV. Next, a Bayesian … momentum strategy. The estimation of this modeling and strategy approach can be done using an extended and modified version of … the forecast combination methodology of Casarin, Grassi, Ravazzolo and Van Dijk(2016). Given the complexity of the non …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures …

estimation of static factor models and factor augmented autoregressions using a set of 190 quarterly observations of 144 US …

allows for a more flexible weighting of financial squared-returns for the filtering of volatility. The parameter for the …-return replaced by the product of the volatility innovation and its lagged value. This local estimate of the first order … autocorrelation of volatility innovations acts as an indicator of the importance of the squared-return for volatility updating. When …