MARC Record from Library of Congress

LEADER: 02339nam a22002897a 4500
001 2008610988
003 DLC
005 20080813102316.0
007 cr |||||||||||
008 080723s2008 mau sb 000 0 eng
010 $a 2008610988
040 $aDLC$cDLC
050 00 $aHB1
100 1 $aFaust, Jon.
245 10 $aEfficient prediction of excess returns$h[electronic resource] /$cJon Faust, Jonathan H. Wright.
260 $aCambridge, MA :$bNational Bureau of Economic Research,$cc2008.
490 1 $aNBER working paper series ;$vworking paper 14169
538 $aSystem requirements: Adobe Acrobat Reader.
538 $aMode of access: World Wide Web.
500 $aTitle from PDF file as viewed on 7/23/2008.
530 $aAlso available in print.
504 $aIncludes bibliographical references.
520 3 $a"It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns, valid augmenting variables exist and are likely to yield substantial gains in estimation efficiency and, hence, predictive accuracy. The proposed augmenting variables are ex post measures of an unforecastable component of excess returns: ex post errors from macroeconomic survey forecasts and the surprise components of asset price movements around macroeconomic news announcements. These "surprises" cannot be used directly in forecasting--they are not observed at the time that the forecast is made--but can nonetheless improve forecasting accuracy by reducing parameter estimation uncertainty. We derive formal results about the benefits and limits of this approach and apply it to standard examples of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for standard excess bond return regressions; gains for forecasting excess stock returns are much smaller"--National Bureau of Economic Research web site.
700 1 $aWright, Jonathan H.
710 2 $aNational Bureau of Economic Research.
830 0 $aWorking paper series (National Bureau of Economic Research : Online) ;$vworking paper no. 14169.
856 40 $uhttp://papers.nber.org/papers/w14169