Taming volatile high frequency data with long lag structure: An optimal filtering approach for forecasting
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References listed on IDEAS
- Rodriguez, Abel & Puggioni, Gavino, 2010. "Mixed frequency models: Bayesian approaches to estimation and prediction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 293-311, April.
- Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, pages 3-11.
- Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
- Oliver W. Lerbs, 2014.
"House prices, housing development costs, and the supply of new single-family housing in German counties and cities,"
Journal of Property Research,
Taylor & Francis Journals, vol. 31(3), pages 183-210, September.
- Oliver Lerbs, 2012. "House Prices, Housing Development Costs, and the Supply of New Single-Family Housing in German Counties and Cities," ERSA conference papers ersa12p258, European Regional Science Association.
- Oliver Wolfgang Lerbs, 2012. "House prices, housing development costs, and the supply of new single-family housing in German counties and cities," ERES eres2012_261, European Real Estate Society (ERES).
- C. Tsuriel Somerville, 2001. "Permits, Starts, and Completions: Structural Relationships Versus Real Options," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 29(1), pages 161-190.
- Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011.
"U-MIDAS: MIDAS regressions with unrestricted lag polynomials,"
Discussion Paper Series 1: Economic Studies
2011,35, Deutsche Bundesbank.
- Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2012. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," CEPR Discussion Papers 8828, C.E.P.R. Discussion Papers.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006.
"Predicting volatility: getting the most out of return data sampled at different frequencies,"
Journal of Econometrics,
Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- 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.
- Clements, Michael P & GalvÃ£o, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
- Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- Michael P. Clements & Ana Beatriz Galvao, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206.
- Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
- McDonald, John F. & McMillen, Daniel P., 2000. "Residential Building Permits in Urban Counties: 1990-1997," Journal of Housing Economics, Elsevier, vol. 9(3), pages 175-186, September.
More about this item
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2016-06-25 (All new papers)
- NEP-ECM-2016-06-25 (Econometrics)
- NEP-ETS-2016-06-25 (Econometric Time Series)
- NEP-FOR-2016-06-25 (Forecasting)
- NEP-NET-2016-06-25 (Network Economics)
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