forecasting ability of four other important variables: the US economic policy uncertainty, the equity market uncertainty, the …

benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1859 …

Forecasting the density of returns is useful for many purposes in finance, such as risk manage- ment activities …

In this paper, we first provide empirical evidence of the existence of intraday jumps in the crude oil price series. We … then show that these jumps, in conjunction with realized volatility measures, are important in modeling the convenience …

ability is evaluated and we compare the forecasting performance of various specifications across as well as within models. It …

’s financial stress index appear to be strong at almost all horizons and sub-periods. However, the forecasting prowess of the …

interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting … Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed …-of-sample forecasting. Finally, we argue that this new methodology can be used as an early warning system for forecasting sudden house …