forecasting volatility. We outline the genesis of this approach from similar models of turbulent flows in statistical physics and …

-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models …

for realized volatility (RV). We estimate the RV-MSM model via Generalized Method of Moments and perform forecasting by …

that estimated parameters can be used for forecasting the evolution of the turbulent flow. We compare forecasting results … by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and …

This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with … rolling window and recursive forecasting schemes. The capabilities of single predictors and of adaptive techniques for … measures. The forward premium and a predictor based on a Taylor rule yield the most promising forecasting results out of the …

The main goal of the article is to investigate forecasting quality of two approaches to modelling main macroeconomic … accuracy not inferior to that of structural models. Additional advantage of their approach is that the forecasting procedure … can be mostly automated and the influence of subjective decisions made in the forecasting process can be significantly …

business-cycle state in the target year with quarterly information about its state in the forecasting period, we find that …

the implications of these scenarios in projecting the future path of fiscal aggregates. We argue that our forecasting …

. Using an out-of-sample forecasting exercise and a stability analysis, it is shown that core money growth carries important … information not contained in the inflation history, that its inclusion in a forecasting model can increase the forecasting … forecasting model at all horizons is the one proposed by Gerlach (2004) that includes the inflation gap, the difference between …