Should Macroeconomic Forecasters Use Daily Financial Data and How?

被引：200

作者：

Andreou, Elena ^{[1
]}

Ghysels, Eric ^{[2
,3
]}

Kourtellos, Andros ^{[1
]}

机构：

[1] Univ Cyprus, Dept Econ, CY-1678 Nicosia, Cyprus

[2] Univ N Carolina, Dept Econ, Chapel Hill, NC 27599 USA

[3] Kenan Flagler Business Sch, Dept Finance, Chapel Hill, NC 27599 USA

来源：

JOURNAL OF BUSINESS & ECONOMIC STATISTICS | 2013年 / 31卷 / 02期

基金：

欧洲研究理事会;

关键词：

Daily financial factors; Financial markets and the macroeconomy; MIDAS regressions; DYNAMIC-FACTOR MODEL; OUTPUT GROWTH; INFLATION; GDP; COINCIDENT; NUMBER;

D O I：

10.1080/07350015.2013.767199

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：240 / 251

页数：12

共 47 条

[1] Persistence in forecasting performance and conditional combination strategies [J].