Forecasting the equity risk premium: The role of technical indicators
Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that...
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sg-smu-ink.lkcsb_research-40622020-04-02T06:27:17Z Forecasting the equity risk premium: The role of technical indicators Neely, Christopher J. Rapach, David E. TU, Jun Zhou, Guofu Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample predictive power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, whereas macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial counter cyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables. 2014-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/3063 info:doi/10.1287/mnsc.2013.1838 https://ink.library.smu.edu.sg/context/lkcsb_research/article/4062/viewcontent/NeelyRapachTuZhou_2013_ForecastingEquityRiskPremiumTechInd_PP.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University equity risk premium predictability macroeconomic variables moving-average rules momentum volume sentiment out-of-sample forecasts asset allocation business cycle Finance and Financial Management Portfolio and Security Analysis |
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equity risk premium predictability macroeconomic variables moving-average rules momentum volume sentiment out-of-sample forecasts asset allocation business cycle Finance and Financial Management Portfolio and Security Analysis Neely, Christopher J. Rapach, David E. TU, Jun Zhou, Guofu Forecasting the equity risk premium: The role of technical indicators |
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Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample predictive power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, whereas macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial counter cyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables. |
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text |
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Neely, Christopher J. Rapach, David E. TU, Jun Zhou, Guofu |
author_facet |
Neely, Christopher J. Rapach, David E. TU, Jun Zhou, Guofu |
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Neely, Christopher J. |
title |
Forecasting the equity risk premium: The role of technical indicators |
title_short |
Forecasting the equity risk premium: The role of technical indicators |
title_full |
Forecasting the equity risk premium: The role of technical indicators |
title_fullStr |
Forecasting the equity risk premium: The role of technical indicators |
title_full_unstemmed |
Forecasting the equity risk premium: The role of technical indicators |
title_sort |
forecasting the equity risk premium: the role of technical indicators |
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Institutional Knowledge at Singapore Management University |
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2014 |
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https://ink.library.smu.edu.sg/lkcsb_research/3063 https://ink.library.smu.edu.sg/context/lkcsb_research/article/4062/viewcontent/NeelyRapachTuZhou_2013_ForecastingEquityRiskPremiumTechInd_PP.pdf |
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