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Does Aggregate Riskiness Predict Future Economic Downturns?

Author

Listed:
  • Bali, Turan G.

    (Georgetown University)

  • Cakici, Nusret

    (Fordham University)

  • Chabi-Yo, Fousseni

    (OH State University)

Abstract

Aumann and Serrano (2008) and Foster and Hart (2009) introduce riskiness measures based on the physical return distribution of gambles. This paper proposes model-free options' implied measures of riskiness based on the risk-neutral distribution of financial securities. In addition to introducing the forward-looking measures of riskiness, the paper investigates the significance of aggregate riskiness in predicting future economic downturns. The results indicate strong predictive power of aggregate riskiness even after controlling for the realized volatility of the U.S. equity market, the implied volatility of S&P 500 index options (VIX) proxying for financial market uncertainty, as well as the TED spread proxying for interbank credit risk and the perceived health of the banking system.

Suggested Citation

  • Bali, Turan G. & Cakici, Nusret & Chabi-Yo, Fousseni, 2012. "Does Aggregate Riskiness Predict Future Economic Downturns?," Working Paper Series 2012-09, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2012-09
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    References listed on IDEAS

    as
    1. Turan G. Bali & Nusret Cakici & Fousseni Chabi-Yo, 2011. "A Generalized Measure of Riskiness," Management Science, INFORMS, vol. 57(8), pages 1406-1423, August.
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    Cited by:

    1. Sylvia Sarantopoulou-Chiourea & George Skiadopoulos, 2015. "A New Predictor of Real Economic Activity: The S&P 500 Option Implied Risk Aversion," Working Papers 741, Queen Mary University of London, School of Economics and Finance.
    2. Sylvia Sarantopoulou-Chiourea & George Skiadopoulos, 2015. "A New Predictor of Real Economic Activity: The S&P 500 Option Implied Risk Aversion," Working Papers 741, Queen Mary University of London, School of Economics and Finance.
    3. Leiss, Matthias & Nax, Heinrich H., 2015. "Option-implied objective measures of market risk," LSE Research Online Documents on Economics 65446, London School of Economics and Political Science, LSE Library.
    4. Bhatt, Vipul & Kishor, N Kundan & Ma, Jun, 2017. "The impact of EMU on bond yield convergence: Evidence from a time-varying dynamic factor model," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 206-222.
    5. Nartea, Gilbert V. & Bai, Hengyu & Wu, Ji, 2020. "Investor sentiment and the economic policy uncertainty premium," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    6. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    7. Leiss, Matthias & Nax, Heinrich H., 2018. "Option-implied objective measures of market risk," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 241-249.
    8. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.

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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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