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The relationships between unsystematic risk, skewness and stock returns during up and down markets

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  • Tang, Gordon Y. N.
  • Shum, Wai Cheong

Abstract

A recent article published in International Business Review (12 (2003) 109) argues for the usefulness of beta as a measure of risk in international stock markets. The beta-return relationship is significantly positive (negative) when the market excess returns are positive (negative). This paper extends their study further by examining other statistical risk measures. It is well known that stock returns are non-normally distributed with significant skewness and kurtosis. Under the same conditional framework, investors are found not only compensated for bearing beta risk, but also for bearing unsystematic risk, providing evidence that international investors do not hold well-diversified portfolios. Skewness, but not kurtosis, plays a significant role in pricing international stock returns. Investors accept less positive returns for positively skewed portfolios. Total risk is significantly and positively (negatively) related to realized weekly returns during up (down) markets. Our results support previous findings and add that other statistical risk measures are also useful in explaining the cross-sectional variations in international stock returns, and hence, are relevant to portfolio managers.

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  • Tang, Gordon Y. N. & Shum, Wai Cheong, 2003. "The relationships between unsystematic risk, skewness and stock returns during up and down markets," International Business Review, Elsevier, vol. 12(5), pages 523-541, October.
    • Handle: RePEc:eee:iburev:v:12:y:2003:i:5:p:523-541
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    3. Basher, Syed A. & Sadorsky, Perry, 2006. "Oil price risk and emerging stock markets," Global Finance Journal, Elsevier, vol. 17(2), pages 224-251, December.
    4. Algia Hammami & Ameni Ghenimi & Abdelfattah Bouri, 2015. "Relation Between Risk And Return In Tunisian’S Stock Market After The Revolution (During Political Instability)," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 6(1), December.
    5. Durand, Robert B. & Lan, Yihui & Ng, Andrew, 2011. "Conditional beta: Evidence from Asian emerging markets," Global Finance Journal, Elsevier, vol. 22(2), pages 130-153.
    6. Yu, Jing-Rung & Lee, Wen-Yi, 2011. "Portfolio rebalancing model using multiple criteria," European Journal of Operational Research, Elsevier, vol. 209(2), pages 166-175, March.
    7. Nandha, Mohan & Hammoudeh, Shawkat, 2007. "Systematic risk, and oil price and exchange rate sensitivities in Asia-Pacific stock markets," Research in International Business and Finance, Elsevier, vol. 21(2), pages 326-341, June.
    8. Hammoudeh, Shawkat & Li, Huimin, 2005. "Oil sensitivity and systematic risk in oil-sensitive stock indices," Journal of Economics and Business, Elsevier, vol. 57(1), pages 1-21.
    9. Paweł Wnuk Lipinski, 2013. "Portfolio selection models based on characteristics of return distributions," Working Papers 2013-14, Faculty of Economic Sciences, University of Warsaw.
    10. Valadkhani, Abbas, 2022. "Do large-cap exchange-traded funds perform better than their small-cap counterparts in extreme market conditions?☆," Global Finance Journal, Elsevier, vol. 53(C).
    11. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.
    12. Ali Matar, 2016. "Does Portfolio’s Beta in Financial Market Affected by Diversification? Evidence from Amman Stock Exchange," International Journal of Business and Management, Canadian Center of Science and Education, vol. 11(11), pages 101-101, October.
    13. Jayanta K. Pokharel & Erasmus Tetteh-Bator & Chris P. Tsokos, 2022. "A Real Data-Driven Analytical Model to Predict Information Technology Sector Index Price of S&P 500," Papers 2209.10720, arXiv.org.

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