Should Macroeconomic Forecasters Use Daily Financial Data and How?
Eric Ghysels () and
Andros Kourtellos ()
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Eric Ghysels: Department of Economics, University of North Carolina, Chapel Hill, NC, USA; Department of Finance, Kenan-Flagler Business School, University of North Carolina, Chapel Hill, NC, USA
Working Paper Series from The Rimini Centre for Economic Analysis
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 MIDAS regressions. Our analysis is designed to elucidate the value of daily information and provide real-time forecast updates of the current (nowcasting) and future quarters. Our findings show that while on average the predictive ability of all models worsens substantially following the financial crisis, the models we propose suffer relatively less losses than the traditional ones. Moreover, these predictive gains are primarily driven by the classes of government securities, equities, and especially corporate risk.
Keywords: MIDAS; macro forecasting, leads; daily financial information; daily factors (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-bec and nep-for
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Journal Article: Should Macroeconomic Forecasters Use Daily Financial Data and How? (2013)
Working Paper: Should macroeconomic forecasters use daily financial data and how? (2012)
Working Paper: Should macroeconomic forecasters use daily financial data and how? (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:42_10
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