Machine learning is increasingly applied to time series data, as it constitutes an attractive alternative to forecasts based on traditional time series models. For independent and identically distributed observations, cross-validation is the prevalent scheme for estimating out-of-sample...

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast...

The real estate market in China has been growing rapidly during the past decade, with different property price patterns across various regions. Among different types of properties, prices of retail properties have not been sufficiently analyzed. This study focuses on forecasting problems of...