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Robust global mood influences in equity pricing

  • Dowling, Michael
  • Lucey, Brian M.

This paper investigates the relationship between seven mood-proxy variables and a global equity dataset using a variety of group tests. The mood-proxy variables are constructed from weather data (precipitation, temperature, wind, geomagnetic storms) and biorhythm data (seasonal affective disorder, daylight savings time changes, lunar phases). This study contributes a greater understanding of the relationship between mood and equity pricing through testing the strength of the relationship between groups of mood-proxy variables and both returns and variance. Using a large and globally diverse equity dataset, robust econometric testing approaches, and testing deseasonalised and regular weather variables, we conclude that seasonal affective disorder and low temperatures show the greatest relationship with equity pricing.

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Article provided by Elsevier in its journal Journal of Multinational Financial Management.

Volume (Year): 18 (2008)
Issue (Month): 2 (April)
Pages: 145-164

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Handle: RePEc:eee:mulfin:v:18:y:2008:i:2:p:145-164
Contact details of provider: Web page: http://www.elsevier.com/locate/mulfin

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  1. Anna Krivelyova & Cesare Robotti, 2003. "Playing the field: Geomagnetic storms and international stock markets," Working Paper 2003-5, Federal Reserve Bank of Atlanta.
  2. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
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  4. Kamstra, M.J. & Kramer, L.A. & Levi, M.D., 1998. "Losing Sleep at the Market: The Daylight-Savings Anomaly," Discussion Papers dp98-04, Department of Economics, Simon Fraser University.
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  6. David Hirshleifer & TYLER G. SHUMWAY, 2004. "Good Day Sunshine: Stock Returns and the Weather," Finance 0412004, EconWPA.
  7. Yuan, Kathy & Zheng, Lu & Zhu, Qiaoqiao, 2006. "Are investors moonstruck? Lunar phases and stock returns," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 1-23, January.
  8. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  9. Loughran, Tim & Schultz, Paul, 2004. "Weather, Stock Returns, and the Impact of Localized Trading Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 343-364, June.
  10. J. Michael Pinegar, 2002. "Losing Sleep at the Market: Comment," American Economic Review, American Economic Association, vol. 92(4), pages 1251-1256, September.
  11. Saunders, Edward M, Jr, 1993. "Stock Prices and Wall Street Weather," American Economic Review, American Economic Association, vol. 83(5), pages 1337-45, December.
  12. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
  13. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2002. "Losing Sleep at the Market: The Daylight Saving Anomaly: Reply," American Economic Review, American Economic Association, vol. 92(4), pages 1257-1263, September.
  14. Jacobsen, B. & Marquering, W.A., 2004. "Is it the weather?," ERIM Report Series Research in Management ERS-2004-100-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  15. Cao, Melanie & Wei, Jason, 2005. "Stock market returns: A note on temperature anomaly," Journal of Banking & Finance, Elsevier, vol. 29(6), pages 1559-1573, June.
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