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Should stock market return forecasts be conditioned on politics?

John G Powell, Meifen Qian, Jing Shi and Qiaoqiao Zhu
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John G Powell: Research School of Finance, Actuarial Studies and Applied Statistics, The Australian National University, Australia
Meifen Qian: International Institute for Financial Studies, Jiangxi University of Finance and Economics, China
Jing Shi: International Institute for Financial Studies, Jiangxi University of Finance and Economics, China; School of Economics, Finance and Marketing, RMIT University, Australia
Qiaoqiao Zhu: Research School of Finance, Actuarial Studies and Applied Statistics, The Australian National University, Australia

Australian Journal of Management, 2015, vol. 40, issue 4, 672-700

Abstract: This paper examines whether stock market returns forecasts should take account of the political party in power by re-examining the prior literature to demonstrate that US stock market political regime differences are neither significant nor long-lasting. We demonstrate that the presidential regime dummy variable used in prior studies is highly auto-correlated, thus potentially violating the ordinary least squares assumption of independently distributed regression errors. Simulation and bootstrap analyses are used to demonstrate that prior findings of higher returns and lower risk under Democratic presidencies are less than would be expected by chance, once account is taken of the persistence properties of the presidential regime dummy variable used in prior studies. Theoretical considerations are also used to explain why presidential regime differences are unlikely to persist, thus further reconciling the paper’s findings with prior studies.

Keywords: Auto-correlated explanatory variables; presidential regimes; spurious regression; stock market return differences (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:ausman:v:40:y:2015:i:4:p:672-700

DOI: 10.1177/0312896214526213

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