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The Risk and Return Conundrum Explained: International Evidence

Author

Listed:
  • Christos S Savva
  • Panayiotis Theodossiou

Abstract

The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so far have been inconclusive. Using a generalization of the analytical framework developed by Theodossiou and Savva (2016) along with time-varying asymmetry, linked to the upside and downside uncertainty, the risk–return puzzle is investigated across international stock markets. The investigation reveals that the contradictory findings are the result of ignoring the impact of skewness on the total price of risk. That is, in the absence of skewness the relationship between risk and return is positive as depicted by finance theory. However, negative skewness results in lowering the total price of risk and in some cases reverting its sign from positive to negative.

Suggested Citation

  • Christos S Savva & Panayiotis Theodossiou, 2018. "The Risk and Return Conundrum Explained: International Evidence," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 486-521.
    • Handle: RePEc:oup:jfinec:v:16:y:2018:i:3:p:486-521.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nby014
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    Citations

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    Cited by:

    1. Delis, Manthos & Savva, Christos & Theodossiou, Panayiotis, 2020. "A Coronavirus Asset Pricing Model: The Role of Skewness," MPRA Paper 100877, University Library of Munich, Germany.
    2. Delis, Manthos D. & Savva, Christos S. & Theodossiou, Panayiotis, 2021. "The impact of the coronavirus crisis on the market price of risk," Journal of Financial Stability, Elsevier, vol. 53(C).
    3. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    4. Nektarios Aslanidis & Charlotte Christiansen & Christos S. Savva, 2021. "Quantile Risk–Return Trade-Off," JRFM, MDPI, vol. 14(6), pages 1-14, June.
    5. Panayiotis Theodossiou & Polina Ellina & Christos S. Savva, 2022. "Stochastic properties and pricing of bitcoin using a GJR-GARCH model with conditional skewness and kurtosis components," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 695-716, August.
    6. Zaremba, Adam, 2019. "Price range and the cross-section of expected country and industry returns," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 174-189.
    7. Panayiotis Theodossiou & Dimitris Tsouknidis & Christos Savva, 2020. "Freight rates in downside and upside markets: pricing of own and spillover risks from other shipping segments," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1097-1119, June.

    More about this item

    Keywords

    national stock markets; risk premium; skewness premium; skewed generalized t; downside risk; upside uncertainty;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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