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State-dependent volatility feedback effect in the ICAPM

Author

Listed:
  • Kilic, Osman
  • Nam, Kiseok
  • O'Connor, Matthew L.

Abstract

Considering that risk-averse investors revise their expectations in response to changes in both expected and unexpected volatility, we hypothesize and demonstrate that an unexpectedly high (low) volatility shock causes an increase (decrease) in risk premium. Using a novel approach to endogeneity issues, we utilize a state dependent, ICAPM to measure volatility effects on risk-return relationships. Our empirical results show that the volatility feedback effect strengthens (attenuates) the positive risk-return relation under bad (good) news. Furthermore, the volatility feedback effect under the combined conditions of bad news and a high unexpected volatility causes an extremely heightened level of the risk-return tradeoff.

Suggested Citation

  • Kilic, Osman & Nam, Kiseok & O'Connor, Matthew L., 2024. "State-dependent volatility feedback effect in the ICAPM," Finance Research Letters, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323010723
    DOI: 10.1016/j.frl.2023.104700
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    References listed on IDEAS

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    1. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    2. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    3. Wu, Guojun, 2001. "The Determinants of Asymmetric Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 14(3), pages 837-859.
    4. Marks, Joseph M. & Nam, Kiseok, 2018. "Intertemporal risk-return tradeoff in the short-run," Economics Letters, Elsevier, vol. 172(C), pages 81-84.
    5. Carr, Peter & Wu, Liuren, 2017. "Leverage Effect, Volatility Feedback, and Self-Exciting Market Disruptions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(5), pages 2119-2156, October.
    6. Bae, Jinho & Kim, Chang-Jin & Nelson, Charles R., 2007. "Why are stock returns and volatility negatively correlated?," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 41-58, January.
    7. Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2015. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," Journal of Finance, American Finance Association, vol. 70(5), pages 1903-1948, October.
    8. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    9. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    10. Yu, Jianfeng & Yuan, Yu, 2011. "Investor sentiment and the mean-variance relation," Journal of Financial Economics, Elsevier, vol. 100(2), pages 367-381, May.
    11. Chelikani, Surya & Marks, Joseph M. & Nam, Kiseok, 2023. "Volatility feedback effect and risk-return tradeoff," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 49-65.
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    More about this item

    Keywords

    Volatility feedback effect; State-dependent ICAPM; Endogeneity issue; Investor sentiment;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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