IDEAS home Printed from https://ideas.repec.org/a/sae/iimkoz/v6y2017i1p90-97.html
   My bibliography  Save this article

Estimating Option-implied Risk Aversion for Indian Markets

Author

Listed:
  • Sonalika Sinha
  • Bandi Kamaiah

Abstract

What do nearly 1.5 lakh observations of options data say about risk preferences of Indian investors? This paper explores a nonparametric technique to compute probability density functions (PDFs) directly from NIFTY 50 option prices in India, based on the utility preferences of the representative investor. Use of probability density functions to estimate investor expectations of the distribution of future levels of the underlying assets has gained tremendous popularity over the last decade. Studying option prices provides information about the market participants’ probability assessment of the future outcome of the underlying asset. We compare the forecast ability of the risk-neutral PDF and risk-adjusted density functions to arrive at a unique index of relative risk aversion for Indian markets. Results indicate that risk-adjusted PDFs are reasonably better forecasts of investor expectations of future levels of the underlying assets. We find that Indian investors are not neutral to risk, contrary to the theoretical assumption of risk-neutrality among investors. The computed time-series of relative risk aversion overcomes the limitations of the VIX (implied volatility index) to yield a more reliable index, particularly useful for the Indian markets. Validity of the computed index is established by comparing with existing measures of risk and the relationships are found to be consistent with market expectations.

Suggested Citation

  • Sonalika Sinha & Bandi Kamaiah, 2017. "Estimating Option-implied Risk Aversion for Indian Markets," IIM Kozhikode Society & Management Review, , vol. 6(1), pages 90-97, January.
  • Handle: RePEc:sae:iimkoz:v:6:y:2017:i:1:p:90-97
    DOI: 10.1177/2277975216677600
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2277975216677600
    Download Restriction: no

    File URL: https://libkey.io/10.1177/2277975216677600?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mr. Kevin C Cheng, 2010. "A New Framework to Estimate the Risk-Neutral Probability Density Functions Embedded in Options Prices," IMF Working Papers 2010/181, International Monetary Fund.
    2. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    3. de Vincent-Humphreys, Rupert & Noss, Joseph, 2012. "Estimating probability distributions of future asset prices: empirical transformations from option-implied risk-neutral to real-world density functions," Bank of England working papers 455, Bank of England.
    4. repec:bla:jfinan:v:59:y:2004:i:1:p:407-446 is not listed on IDEAS
    5. Allan M. Malz, 2014. "Simple and reliable way to compute option-based risk-neutral distributions," Staff Reports 677, Federal Reserve Bank of New York.
    6. Cox, John C. & Ross, Stephen A., 1976. "The valuation of options for alternative stochastic processes," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 145-166.
    7. Bliss, Robert R. & Panigirtzoglou, Nikolaos, 2002. "Testing the stability of implied probability density functions," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 381-422, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jukka Sihvonen & Sami Vähämaa, 2014. "Forward‐Looking Monetary Policy Rules and Option‐Implied Interest Rate Expectations," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(4), pages 346-373, April.
    2. Monteiro, Ana Margarida & Tutuncu, Reha H. & Vicente, Luis N., 2008. "Recovering risk-neutral probability density functions from options prices using cubic splines and ensuring nonnegativity," European Journal of Operational Research, Elsevier, vol. 187(2), pages 525-542, June.
    3. Fabien Floc’h & Cornelis W. Oosterlee, 2019. "Model-free stochastic collocation for an arbitrage-free implied volatility: Part I," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 679-714, December.
    4. Hardeep Singh Mundi, 2023. "Risk neutral variances to compute expected returns using data from S&P BSE 100 firms—a replication study," Management Review Quarterly, Springer, vol. 73(1), pages 215-230, February.
    5. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.
    6. Ruijun Bu & Kaddour Hadri, 2005. "Estimating the Risk Neutral Probability Density Functions Natural Spline versus Hypergeometric Approach Using European Style Options," Working Papers 200510, University of Liverpool, Department of Economics.
    7. Gabriele Galati & Patrick Higgins & Owen Humpage & William Melick, 2007. "Option prices, exchange market intervention, and the higher moment expectations channel: a user's guide," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 225-247.
    8. Datta, Deepa Dhume & Londono, Juan M. & Ross, Landon J., 2017. "Generating options-implied probability densities to understand oil market events," Energy Economics, Elsevier, vol. 64(C), pages 440-457.
    9. Josep Puigvert-Gutiérrez & Rupert Vincent-Humphreys, 2012. "A Quantitative Mirror on the Euribor Market Using Implied Probability Density Functions," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 2(1), pages 1-31, June.
    10. Wilkens, Sascha & Roder, Klaus, 2006. "The informational content of option-implied distributions: Evidence from the Eurex index and interest rate futures options market," Global Finance Journal, Elsevier, vol. 17(1), pages 50-74, September.
    11. Nick Gebbia, 2016. "Option-Implied Libor Rate Expectations across Currencies," International Finance Discussion Papers 1182, Board of Governors of the Federal Reserve System (U.S.).
    12. Taboga, Marco, 2016. "Option-implied probability distributions: How reliable? How jagged?," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 453-469.
    13. Ivanova, Vesela & Puigvert Gutiérrez, Josep Maria, 2014. "Interest rate forecasts, state price densities and risk premium from Euribor options," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 210-223.
    14. Abderrahmen Aloulou & Younes Boujelbene, 2019. "Dynamic analysis of implied risk neutral density," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 12(1), pages 39-58.
    15. Äijö, Janne, 2008. "Impact of US and UK macroeconomic news announcements on the return distribution implied by FTSE-100 index options," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 242-258.
    16. Vergote, Olivier & Puigvert Gutiérrez, Josep Maria, 2012. "Interest rate expectations and uncertainty during ECB Governing Council days: Evidence from intraday implied densities of 3-month EURIBOR," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2804-2823.
    17. Seung Hwan Lee, 2014. "Estimation of risk-neutral measures using quartic B-spline cumulative distribution functions with power tails," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1857-1879, October.
    18. Arindam Kundu & Sumit Kumar & Nutan Kumar Tomar, 2019. "Option Implied Risk-Neutral Density Estimation: A Robust and Flexible Method," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 705-728, August.
    19. 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.
    20. Bondarenko, Oleg, 2003. "Estimation of risk-neutral densities using positive convolution approximation," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 85-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:iimkoz:v:6:y:2017:i:1:p:90-97. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.