limited to short-term predictions, the value of Google data for forecasting purposes is episodic, and the improvements in … forecasting accuracy are only modest. The results, obtained by (pseudo) out-of-sample forecast comparison, are robust to a state …

In this report we document the ETLAnow project. ETLAnow is a model for forecasting with big data. At the moment, it …

A forecasting exercise is presented to assess the predictive potential of a daily price index based on online prices …

agreed. In short, forecasting inflation is of foremost importance to households, businesses, and policymakers. In 2016, the …

have been shown to improve forecasting models for various economic and financial series. In the aftermath of the global … financial crisis, modeling and forecasting mortgage demand and subsequent approvals have become a central issue in the banking … number of new mortgage approvals and markedly improve their nowcasting and forecasting performance. …

We present a comprehensive disaggregate approach for short-term forecasting economic activity in Germany by explicitly …

variables by aggregation. To investigate the potential gain in using such a large information set, we compare the forecasting …

on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new …