Efficient prediction of excess returns:
"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,...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass.
National Bureau of Economic Research
2008
|
| Schriftenreihe: | Working paper series / National Bureau of Economic Research
14169 |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "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 |
| Beschreibung: | 32, [16] S. graph. Darst. 22 cm |
Internformat
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| 245 | 1 | 0 | |a Efficient prediction of excess returns |c Jon Faust ; Jonathan H. Wright |
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| 490 | 1 | |a Working paper series / National Bureau of Economic Research |v 14169 | |
| 520 | 8 | |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 | |a Wright, Jonathan H. |e Verfasser |0 (DE-588)134265815 |4 aut | |
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Datensatz im Suchindex
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| author | Faust, Jon Wright, Jonathan H. |
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| id | DE-604.BV023594046 |
| illustrated | Illustrated |
| index_date | 2024-07-02T22:41:33Z |
| indexdate | 2024-07-09T21:25:16Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016909376 |
| oclc_num | 255136141 |
| open_access_boolean | 1 |
| owner | DE-521 |
| owner_facet | DE-521 |
| physical | 32, [16] S. graph. Darst. 22 cm |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | National Bureau of Economic Research |
| record_format | marc |
| series2 | Working paper series / National Bureau of Economic Research |
| spelling | Faust, Jon Verfasser (DE-588)124507395 aut Efficient prediction of excess returns Jon Faust ; Jonathan H. Wright Cambridge, Mass. National Bureau of Economic Research 2008 32, [16] S. graph. Darst. 22 cm txt rdacontent n rdamedia nc rdacarrier Working paper series / National Bureau of Economic Research 14169 "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 Wright, Jonathan H. Verfasser (DE-588)134265815 aut Erscheint auch als Online-Ausgabe National Bureau of Economic Research <Cambridge, Mass.> NBER working paper series 14169 (DE-604)BV002801238 14169 http://papers.nber.org/papers/w14169.pdf kostenfrei Volltext |
| spellingShingle | Faust, Jon Wright, Jonathan H. Efficient prediction of excess returns |
| title | Efficient prediction of excess returns |
| title_auth | Efficient prediction of excess returns |
| title_exact_search | Efficient prediction of excess returns |
| title_exact_search_txtP | Efficient prediction of excess returns |
| title_full | Efficient prediction of excess returns Jon Faust ; Jonathan H. Wright |
| title_fullStr | Efficient prediction of excess returns Jon Faust ; Jonathan H. Wright |
| title_full_unstemmed | Efficient prediction of excess returns Jon Faust ; Jonathan H. Wright |
| title_short | Efficient prediction of excess returns |
| title_sort | efficient prediction of excess returns |
| url | http://papers.nber.org/papers/w14169.pdf |
| volume_link | (DE-604)BV002801238 |
| work_keys_str_mv | AT faustjon efficientpredictionofexcessreturns AT wrightjonathanh efficientpredictionofexcessreturns |