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Should macroeconomic forecasters use daily financial data and how?

  • Elena Andreou
  • Eric Ghysels
  • Andros Kourtellos

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.

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File URL: http://papers.econ.ucy.ac.cy/RePEc/papers/09-10.pdf
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Paper provided by University of Cyprus Department of Economics in its series University of Cyprus Working Papers in Economics with number 09-2010.

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Length: 67 pages
Date of creation: Nov 2010
Date of revision:
Handle: RePEc:ucy:cypeua:09-2010
Contact details of provider: Web page: http://www.econ.ucy.ac.cy

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  1. Anthony Tay, 2007. "Financial Variables as Predictors of Real Output Growth," Working Papers 14-2007, Singapore Management University, School of Economics.
  2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  3. Libero Monteforte & Gianluca Moretti, 2010. "Real time forecasts of inflation: the role of financial variables," Temi di discussione (Economic working papers) 767, Bank of Italy, Economic Research and International Relations Area.
  4. Sydney Ludvigson & Serena Ng, 2006. "The Empirical Risk-Return Relation: a factor analysis approach," 2006 Meeting Papers 236, Society for Economic Dynamics.
  5. Christopher A. Sims, 1980. "Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered," NBER Working Papers 0430, National Bureau of Economic Research, Inc.
  6. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  7. D'Agostino, Antonello & Domenico, Giannone & Surico, Paolo, 2006. "(Un)Predictability and Macroeconomic Stability," Research Technical Papers 5/RT/06, Central Bank of Ireland.
  8. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
  9. Barro, Robert J, 1990. "The Stock Market and Investment," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 115-31.
  10. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
  11. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
  12. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank, Research Centre.
  13. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2007. "Regression Models with Mixed Sampling Frequencies," University of Cyprus Working Papers in Economics 8-2007, University of Cyprus Department of Economics.
  14. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
  15. Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.
  16. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
  17. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
  18. Bernanke, Ben S. & Gertler, Mark & Waston, Mark, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Working Papers 97-25, C.V. Starr Center for Applied Economics, New York University.
  19. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-60, May.
  20. Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 21(2), pages 201-218.
  21. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  22. Charles Engel & Kenneth D. West, 2004. "Exchange Rates and Fundamentals," NBER Working Papers 10723, National Bureau of Economic Research, Inc.
  23. Peter A. Zadrozny, 1990. "Forecasting U.S. GNP at monthly intervals with an estimated bivariate time series model," Economic Review, Federal Reserve Bank of Atlanta, issue Nov, pages 2-15.
  24. Avramov, Doron, 2002. "Stock return predictability and model uncertainty," Journal of Financial Economics, Elsevier, vol. 64(3), pages 423-458, June.
  25. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
  26. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
  27. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  28. Arturo Estrella & Gikas A. Hardouvelis, 1989. "The term structure as a predictor of real economic activity," Research Paper 8907, Federal Reserve Bank of New York.
  29. Marianne Sensier & Dick van Dijk, 2004. "Testing for Volatility Changes in U.S. Macroeconomic Time Series," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 833-839, August.
  30. Gambetti, Luca & D’Agostino, Antonello & Giannone, Domenico, 2010. "Macroeconomic forecasting and structural change," Working Paper Series 1167, European Central Bank.
  31. Ben S. Bernanke & Alan S. Blinder, 1989. "The federal funds rate and the channels of monetary transmission," Working Papers 89-10, Federal Reserve Bank of Philadelphia.
  32. Andrew Ang & Monika Piazzesi & Min Wei, 2003. "What does the yield curve tell us about GDP growth?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  33. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
  34. David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
  35. Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.
  36. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  37. Domenico Giannone & Lucrezia Reichlin & David Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
  38. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
  39. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
  40. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Money, Income, Prices, and Interest Rates," American Economic Review, American Economic Association, vol. 82(3), pages 472-92, June.
  41. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
  42. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
  43. Emanuel Moench & Serena Ng & Simon Potter, 2013. "Dynamic Hierarchical Factor Model," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1811-1817, December.
  44. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
  45. Robert D. Laurent, 1988. "An interest rate-based indicator of monetary policy," Economic Perspectives, Federal Reserve Bank of Chicago, issue Jan, pages 3-14.
  46. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  47. Vladimir Yankov & Egon Zakrajsek & Simon Gilchrist, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," 2009 Meeting Papers 514, Society for Economic Dynamics.
  48. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  49. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
  50. Refet S. Gürkaynak & Brian Sack & Jonathan H. Wright, 2008. "The TIPS yield curve and inflation compensation," Finance and Economics Discussion Series 2008-05, Board of Governors of the Federal Reserve System (U.S.).
  51. Wasserfallen, Walter, 1989. "Macroeconomics news and the stock market: Evidence from Europe," Journal of Banking & Finance, Elsevier, vol. 13(4-5), pages 613-626, September.
  52. Alper, C. Emre & Fendoglu, Salih & Saltoglu, Burak, 2008. "Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets," MPRA Paper 7460, University Library of Munich, Germany.
  53. Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.).
  54. Leon, Angel & Nave, Juan M. & Rubio, Gonzalo, 2007. "The relationship between risk and expected return in Europe," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 495-512, February.
  55. Michelle T. Armesto & Rubén Hernández-Murillo & Michael T. Owyang & Jeremy Piger, 2009. "Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(1), pages 35-55, 02.
  56. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
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