In this paper we suggest an approach to comparison of models' forecasting performance in unstable environments. Our … tracking how the relative forecasting performance of competing models evolves over time. We illustrate the suggested approach …

We propose a new methodology to identify the sources of models’ forecasting performance. The methodology decomposes the … models’ forecasting performance into asymptotically uncorrelated components that measure instabilities in the forecasting … understanding the causes of the poor forecasting ability of economic models for exchange rate determination. …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by … characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the … forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA …

regression used in Bai and Ng (2008), called the elastic net (Zou and Hastie, 2005). We illustrate our approach by forecasting …

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …