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Summary statistics of option-implied probability density functions and their properties

Author

Listed:
  • Damien Lynch

    (Bank of England)

  • Nikolaos Panigirtzoglou

    (Department of Economics, Queen Mary, University of London)

Abstract

The statistics that summarise probability density functions(pdfs) implied from option prices can be used to assess market expectations about future uncertainty, asymmetry and the probability of extreme movements in asset prices. A time-series analysis of these statistics for equity index and interest rate markets provides some stylised facts about the behaviour of these elements of market expectations, their historical distribution, similarity and relative stability. Relationships between them and movements in underlying asset prices are considered. Cross-asset and cross-country comparisons and the information content of the implied pdfs for future macroeconomic and financial variables are also assessed.

Suggested Citation

  • Damien Lynch & Nikolaos Panigirtzoglou, 2008. "Summary statistics of option-implied probability density functions and their properties," Bank of England working papers 345, Bank of England.
    • Handle: RePEc:boe:boeewp:0345
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    References listed on IDEAS

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    Cited by:

    1. Carol Alexander & Alexander Rubinov & Markus Kalepky & Stamatis Leontsinis, 2012. "Regime‐dependent smile‐adjusted delta hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(3), pages 203-229, March.
    2. Irma Alonso & Pedro Serrano & Antoni Vaello-Sebastià, 2021. "The impact of heterogeneous unconventional monetary policies on the expectations of market crashes," Working Papers 2127, Banco de España.
    3. Healy, J.V. & Gregoriou, A. & Hudson, R., 2018. "Test of recent advances in extracting information from option prices," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 292-302.
    4. Nessim Souissi, 2017. "The Implied Risk Neutral Density Dynamics: Evidence from the S&P TSX 60 Index," Journal of Applied Mathematics, Hindawi, vol. 2017, pages 1-10, June.
    5. Lim, Kian Guan & Chen, Ying & Yap, Nelson K.L., 2019. "Intraday information from S&P 500 Index futures options," Journal of Financial Markets, Elsevier, vol. 42(C), pages 29-55.
    6. Stephen Hansen & Michael McMahon & Carlos Velasco Rivera, 2013. "How Expoerts Decide: Preferences or Private Assessments on a Monetary Policy Committee?," CESifo Working Paper Series 4201, CESifo.
    7. Abderrahmen Aloulou & Siwar Ellouze, 2017. "Does fundamental value run asset price formation process? Evidence from option price information content," Journal of Asset Management, Palgrave Macmillan, vol. 18(4), pages 255-268, July.
    8. Hansen, Stephen & McMahon, Michael, 2011. "How experts decide: identifying preferences versus signals from policy decisions," LSE Research Online Documents on Economics 121717, London School of Economics and Political Science, LSE Library.
    9. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Asset prices and “the devil(s) you know”," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 20-35.
    10. Hansen, Stephen & McMahon, Michael & Velasco Rivera, Carlos, 2014. "Preferences or private assessments on a monetary policy committee?," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 16-32.
    11. Birru, Justin & Figlewski, Stephen, 2012. "Anatomy of a meltdown: The risk neutral density for the S&P 500 in the fall of 2008," Journal of Financial Markets, Elsevier, vol. 15(2), pages 151-180.

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    More about this item

    Keywords

    Options; implied probability density functions (pdfs); summary statistics; implied volatility; impli;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G19 - Financial Economics - - General Financial Markets - - - Other

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