| dc.contributor.author | Andreou, Elena | en |
| dc.contributor.author | Ghysels, Eric | en |
| dc.contributor.author | Kourtellos, Andros | en |
| dc.creator | Andreou, Elena | en |
| dc.creator | Ghysels, Eric | en |
| dc.creator | Kourtellos, Andros | en |
| dc.date.accessioned | 2019-05-03T05:21:46Z | |
| dc.date.available | 2019-05-03T05:21:46Z | |
| dc.date.issued | 2013 | |
| dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/47087 | |
| dc.description.abstract | 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. © 2013 Copyright Taylor and Francis Group, LLC. | en |
| dc.language.iso | eng | en |
| dc.source | Journal of Business and Economic Statistics | en |
| dc.subject | Daily financial factors | en |
| dc.subject | Financial markets and the macroeconomy | en |
| dc.subject | MIDAS regressions | en |
| dc.title | Should Macroeconomic Forecasters Use Daily Financial Data and How? | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.identifier.doi | 10.1080/07350015.2013.767199 | |
| dc.description.volume | 31 | |
| dc.description.startingpage | 240 | |
| dc.description.endingpage | 251 | |
| dc.author.faculty | Σχολή Οικονομικών Επιστημών και Διοίκησης / Faculty of Economics and Management | |
| dc.author.department | Τμήμα Οικονομικών / Department of Economics | |
| dc.type.uhtype | Article | en |
| dc.contributor.orcid | Kourtellos, Andros [0000-0001-9662-0420] | |
| dc.description.totalnumpages | 240-251 | |
| dc.gnosis.orcid | 0000-0001-9662-0420 | |
