Should Macroeconomic Forecasters Use Daily Financial Data and How?
提出基于回归的简易方法，利用每日金融数据通过混合数据抽样回归的预测组合来预测季度实际经济活动，并提取每日金融因子，评估其对实际GDP增长预测的价值。
We introduce easy-to-implement, regression-based methods for predicting quarterly real economic activity that use daily financial data and rely on forecast combinations of mixed data sampling (MIDAS) regressions. We also extract a novel small set of daily financial factors from a large panel of about 1000 daily financial assets. Our analysis is designed to elucidate the value of daily financial information and provide real-time forecast updates of the current (nowcasting) and future quarters of real GDP growth.