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Risk-neutral systemic risk indicators

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  • Allan M. Malz
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    Abstract

    This paper describes a set of indicators of systemic risk computed from current market prices of equity and equity index options. It displays results from a prototype version, computed daily from January 2006 to January 2013. The indicators represent a systemic risk event as the realization of an extreme loss on a portfolio of large-intermediary equities. The technique for computing them combines risk-neutral return distributions with implied return correlations drawn from option prices, tying together the single-firm return distributions via a copula to simulate the joint distribution and thus the financial-sector portfolio return distribution. The indicators can be computed daily using only current market prices; no historical data are involved. They are therefore forward-looking and can exploit all the information impounded in current prices. However, the indicators blend both market expectations and the market's desire to protect itself against volatility and tail risk, so they cannot be readily decomposed into these two elements. The paper presents evidence that the indicators have some predictive power for systemic risk events and that they can serve as a meaningful market-adjusted point of comparison for fundamentals-based systemic risk indicators.

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    Bibliographic Info

    Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 607.

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    Date of creation: 2013
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    Handle: RePEc:fip:fednsr:607

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    Keywords: Systemic risk ; Options (Finance);

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    References

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    1. Acharya, Viral V & Pedersen, Lasse H & Philippon, Thomas & Richardson, Matthew P, 2012. "Measuring Systemic Risk," CEPR Discussion Papers, C.E.P.R. Discussion Papers 8824, C.E.P.R. Discussion Papers.
    2. 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.
    3. Campa, J.M. & Chang, P.H.K., 1995. "The Forecasting Ability of Correlations Implied in Foreign Exchange Options," Papers 95-26, Columbia - Graduate School of Business.
    4. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, American Economic Association, vol. 102(3), pages 59-64, May.
    5. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
    6. Banz, Rolf W & Miller, Merton H, 1978. "Prices for State-contingent Claims: Some Estimates and Applications," The Journal of Business, University of Chicago Press, vol. 51(4), pages 653-72, October.
    7. 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 621-51, October.
    8. Bakshi, Gurdip & Panayotov, George & Skoulakis, Georgios, 2011. "Improving the predictability of real economic activity and asset returns with forward variances inferred from option portfolios," Journal of Financial Economics, Elsevier, Elsevier, vol. 100(3), pages 475-495, June.
    9. Joost Driessen & Pascal J. Maenhout & Grigory Vilkov, 2009. "The Price of Correlation Risk: Evidence from Equity Options," Journal of Finance, American Finance Association, American Finance Association, vol. 64(3), pages 1377-1406, 06.
    10. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(3), pages 339-50, July.
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    Cited by:
    1. Tobias Adrian & Daniel Covitz & Nellie J. Liang, 2013. "Financial stability monitoring," Staff Reports, Federal Reserve Bank of New York 601, Federal Reserve Bank of New York.

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