IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2208.06930.html
   My bibliography  Save this paper

Do Investors Hedge Against Green Swans? Option-Implied Risk Aversion to Wildfires

Author

Abstract

Measuring beliefs about natural disasters is challenging. Deep out-of-the-money options allow investors to hedge at a range of strikes and time horizons, thus the 3-dimensional surface of firm-level option prices provides information on (i) skewed and fat-tailed beliefs about the impact of natural disaster risk across space and time dimensions at daily frequency; and (ii) information on the covariance of wildfire-exposed stocks with investors' marginal utility of wealth. Each publicly-traded company's daily surface of option prices is matched with its network of establishments and wildfire perimeters over two decades. First, wildfires affect investors' risk neutral probabilities at short and long maturities; investors price asymmetric downward tail risk and a probability of upward jumps. The volatility smile is more pronounced. Second, comparing risk-neutral and physical distributions reveals the option-implied risk aversion with respect to wildfire-exposed stock prices. Investors' marginal utility of wealth is correlated with wildfire shocks. Option-implied risk aversion identifies the wildfire-exposed share of portfolios. For risk aversions consistent with Barro (2012), equity options suggest (i) investors hold larger shares of wildfire-exposed stocks than the market portfolio; or (ii) investors may have more pessimistic beliefs about wildfires' impacts than what observed returns suggest, such as pricing low-probability unrealized downward tail risk. We calibrate options with models featuring both upward and downward risk. Results are consistent a significant pricing of downward jumps.

Suggested Citation

  • Amine Ouazad, 2022. "Do Investors Hedge Against Green Swans? Option-Implied Risk Aversion to Wildfires," Papers 2208.06930, arXiv.org.
  • Handle: RePEc:arx:papers:2208.06930
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2208.06930
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Benzoni, Luca & Collin-Dufresne, Pierre & Goldstein, Robert S., 2011. "Explaining asset pricing puzzles associated with the 1987 market crash," Journal of Financial Economics, Elsevier, vol. 101(3), pages 552-573, September.
    2. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    3. Beber, Alessandro & Brandt, Michael W., 2006. "The effect of macroeconomic news on beliefs and preferences: Evidence from the options market," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1997-2039, November.
    4. 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.
    5. Chernov, Mikhail & Ghysels, Eric, 2000. "A study towards a unified approach to the joint estimation of objective and risk neutral measures for the purpose of options valuation," Journal of Financial Economics, Elsevier, vol. 56(3), pages 407-458, June.
    6. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
    7. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    8. Keith Barnatchez & Leland D. Crane & Ryan A. Decker, 2017. "An Assessment of the National Establishment Time Series (NETS) Database," Finance and Economics Discussion Series 2017-110, Board of Governors of the Federal Reserve System (U.S.).
    9. Laura A. Bakkensen & Lint Barrage, 2017. "Flood Risk Belief Heterogeneity and Coastal Home Price Dynamics: Going Under Water?," NBER Working Papers 23854, National Bureau of Economic Research, Inc.
    10. Dessaint, Olivier & Matray, Adrien, 2017. "Do managers overreact to salient risks? Evidence from hurricane strikes," Journal of Financial Economics, Elsevier, vol. 126(1), pages 97-121.
    11. Mark L. Egan & Alexander MacKay & Hanbin Yang, 2021. "What Drives Variation in Investor Portfolios? Estimating the Roles of Beliefs and Risk Preferences," NBER Working Papers 29604, National Bureau of Economic Research, Inc.
    12. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    13. Carr, Peter & Madan, Dilip B., 2005. "A note on sufficient conditions for no arbitrage," Finance Research Letters, Elsevier, vol. 2(3), pages 125-130, September.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Laura Bakkensen & Toan Phan & Russell Wong, 2023. "Leveraging the Disagreement on Climate Change: Theory and Evidence," Working Paper 23-01, Federal Reserve Bank of Richmond.

    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. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    2. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
    3. Chen, Ren-Raw & Hsieh, Pei-lin & Huang, Jeffrey, 2018. "Crash risk and risk neutral densities," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 162-189.
    4. Elyasiani, Elyas & Gambarelli, Luca & Muzzioli, Silvia, 2020. "Moment risk premia and the cross-section of stock returns in the European stock market," Journal of Banking & Finance, Elsevier, vol. 111(C).
    5. Joshua Aurand & Yu-Jui Huang, 2019. "Epstein-Zin Utility Maximization on a Random Horizon," Papers 1903.08782, arXiv.org, revised May 2023.
    6. Geert Bekaert & Eric Engstrom, 2009. "Asset Return Dynamics under Bad Environment Good Environment Fundamentals," NBER Working Papers 15222, National Bureau of Economic Research, Inc.
    7. 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.
    8. Benzoni, Luca & Collin-Dufresne, Pierre & Goldstein, Robert S., 2011. "Explaining asset pricing puzzles associated with the 1987 market crash," Journal of Financial Economics, Elsevier, vol. 101(3), pages 552-573, September.
    9. Lu, Junwen & Qu, Zhongjun, 2021. "Sieve estimation of option-implied state price density," Journal of Econometrics, Elsevier, vol. 224(1), pages 88-112.
    10. Manuel Ammann & Alexander Feser, 2019. "Robust Estimation of Risk-Neutral Moments," Working Papers on Finance 1902, University of St. Gallen, School of Finance.
    11. Mykola Babiak, 2017. "Generalized Disappointment Aversion, Learning, and Asset Prices," CERGE-EI Working Papers wp606, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    12. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2005. "Can Standard Preferences Explain the Prices of out of the Money S&P 500 Put Options," NBER Working Papers 11861, National Bureau of Economic Research, Inc.
    13. Leiss, Matthias & Nax, Heinrich H., 2018. "Option-implied objective measures of market risk," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 241-249.
    14. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
    15. Bjørn Eraker & Aoxiang Yang, 2022. "The Price of Higher Order Catastrophe Insurance: The Case of VIX Options," Journal of Finance, American Finance Association, vol. 77(6), pages 3289-3337, December.
    16. Garcia, Rene & Luger, Richard & Renault, Eric, 2003. "Empirical assessment of an intertemporal option pricing model with latent variables," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 49-83.
    17. Bryan Kelly & Ľuboš Pástor & Pietro Veronesi, 2016. "The Price of Political Uncertainty: Theory and Evidence from the Option Market," Journal of Finance, American Finance Association, vol. 71(5), pages 2417-2480, October.
    18. Song, Zhaogang & Xiu, Dacheng, 2016. "A tale of two option markets: Pricing kernels and volatility risk," Journal of Econometrics, Elsevier, vol. 190(1), pages 176-196.
    19. René Garcia & Richard Luger & Eric Renault, 2001. "Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables (Note : Nouvelle version Février 2002)," CIRANO Working Papers 2001s-02, CIRANO.
    20. Steven Heston & Kris Jacobs & Hyung Joo Kim, 2023. "The Pricing Kernel in Options," Finance and Economics Discussion Series 2023-053, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2208.06930. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.