The empirical risk-return relation: a factor analysis approach
"A key criticism of the existing empirical literature on the risk-return relation relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants hav...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass.
National Bureau of Economic Research
2005
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| Schriftenreihe: | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series
11477 |
| Schlagworte: | |
| Online-Zugang: | kostenfrei |
| Zusammenfassung: | "A key criticism of the existing empirical literature on the risk-return relation relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that three new factors, a "volatility," "risk premium," and "real" factor, contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically insignificant"--National Bureau of Economic Research web site. |
| Beschreibung: | 26, [30] S. graph. Darst. |
Internformat
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| 490 | 1 | |a National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |v 11477 | |
| 520 | 3 | |a "A key criticism of the existing empirical literature on the risk-return relation relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that three new factors, a "volatility," "risk premium," and "real" factor, contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically insignificant"--National Bureau of Economic Research web site. | |
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| id | DE-604.BV023591580 |
| illustrated | Illustrated |
| index_date | 2024-07-02T22:41:28Z |
| indexdate | 2024-07-09T21:25:11Z |
| institution | BVB |
| language | English |
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| physical | 26, [30] S. graph. Darst. |
| publishDate | 2005 |
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| publisher | National Bureau of Economic Research |
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| series | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |
| series2 | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |
| spelling | Ludvigson, Sydney C. 1964- Verfasser (DE-588)124925510 aut The empirical risk-return relation a factor analysis approach Sydney C. Ludvigson ; Serena Ng Cambridge, Mass. National Bureau of Economic Research 2005 26, [30] S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series 11477 "A key criticism of the existing empirical literature on the risk-return relation relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that three new factors, a "volatility," "risk premium," and "real" factor, contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically insignificant"--National Bureau of Economic Research web site. Ökonometrisches Modell Rate of return Econometric models Ng, Serena 1959- Verfasser (DE-588)12865080X aut Erscheint auch als Online-Ausgabe National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series 11477 (DE-604)BV002801238 11477 http://papers.nber.org/papers/w11477.pdf kostenfrei Volltext |
| spellingShingle | Ludvigson, Sydney C. 1964- Ng, Serena 1959- The empirical risk-return relation a factor analysis approach National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series Ökonometrisches Modell Rate of return Econometric models |
| title | The empirical risk-return relation a factor analysis approach |
| title_auth | The empirical risk-return relation a factor analysis approach |
| title_exact_search | The empirical risk-return relation a factor analysis approach |
| title_exact_search_txtP | The empirical risk-return relation a factor analysis approach |
| title_full | The empirical risk-return relation a factor analysis approach Sydney C. Ludvigson ; Serena Ng |
| title_fullStr | The empirical risk-return relation a factor analysis approach Sydney C. Ludvigson ; Serena Ng |
| title_full_unstemmed | The empirical risk-return relation a factor analysis approach Sydney C. Ludvigson ; Serena Ng |
| title_short | The empirical risk-return relation |
| title_sort | the empirical risk return relation a factor analysis approach |
| title_sub | a factor analysis approach |
| topic | Ökonometrisches Modell Rate of return Econometric models |
| topic_facet | Ökonometrisches Modell Rate of return Econometric models |
| url | http://papers.nber.org/papers/w11477.pdf |
| volume_link | (DE-604)BV002801238 |
| work_keys_str_mv | AT ludvigsonsydneyc theempiricalriskreturnrelationafactoranalysisapproach AT ngserena theempiricalriskreturnrelationafactoranalysisapproach |