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Our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions. We use real\u2010time data to forecast the density of US inflation. The results indicate that the proposed method materially improves the real\u2010time accuracy of density forecasts <jats:italic>vis\u2010\u00e0\u2010vis<\/jats:italic> those from the (unknown) individual econometric models. Copyright \u00a9 2013 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.2352","type":"journal-article","created":{"date-parts":[[2013,10,12]],"date-time":"2013-10-12T00:42:19Z","timestamp":1381538539000},"page":"736-757","source":"Crossref","is-referenced-by-count":17,"title":["CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS"],"prefix":"10.1002","volume":"29","author":[{"given":"Wagner Piazza","family":"Gaglianone","sequence":"first","affiliation":[{"name":"Research Department Banco Central do Brasil  Rio de Janeiro Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luiz Renato","family":"Lima","sequence":"additional","affiliation":[{"name":"Department of Economics University of Tennessee at Knoxville  TN USA"},{"name":"Federal University of Paraiba  Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2013,9,25]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"AdolfsonM LindeJ VillaniM.2005.Forecasting performance of an open economy dynamic stochastic general equilibrium model. 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