Option-Implied Risk-Neutral Distributions and Risk Aversion

Jackwerth, Jens Carsten

doi:10.2470/rf.v2004.n1.3925

Cited by 48 publications

(2 citation statements)

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“…The pros and cons of the choices involved are reviewed in Bliss and Panigirtzoglou (2002), Jackwerth (2004), andMandler (2003). In the first step, as I've implemented it for this paper, the Bloomberg implied volatilities are used to estimate a smooth interpolating function, specifically, a cubic spline with endpoints clamped so that the slope of the interpolating function is zero beyond the lowest-and highest-strike options, i.e.…”

Section: Risk-neutral Probability Distributionsmentioning

confidence: 99%

“…MES is defined as the loss a firm would suffer in the event of a 2 percent decline in the broader equity market. 24 We run the regression using results for the 18-firm SCAP/CCAR portfolio. The independent variable in the regression is, again, the conditional systemic expected shortfall, averaged for each firm over the daily results for April 2012.…”

Section: Option-based Indicators and Other Systemic Risk Measuresmentioning

confidence: 99%

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Risk-Neutral Systemic Risk Indicators

Malz

2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis 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 fundamentalsbased systemic risk indicators.

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Section: Risk-neutral Probability Distributionsmentioning

confidence: 99%

Section: Option-based Indicators and Other Systemic Risk Measuresmentioning

confidence: 99%

Risk-Neutral Systemic Risk Indicators

Malz

2013

SSRN Journal

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Test of recent advances in extracting information from option prices

Healy

Gregoriou

Hudson

2018

International Review of Financial Analysis

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A large literature exists on techniques for extracting probability distributions for future asset prices from option prices. No definitive method has been developed however. The parametric ‘mixture of normals’, and nonparametric ‘smoothed implied volatility’ methods remain the most widespread approaches. These though are subject to estimation errors due to discretization, truncation, and noise. Recently, several authors have derived ‘model free’ formulae for computing the moments of the risk neutral density (RND) directly from option prices, without first estimating the full density. The accuracy of these formulae is studied here for the first time. The Black-Scholes formula is used to generate option prices, and error curves for the first 4 moments of the RND are computed using the ‘model-free’ formulae. It is found that, in practice, the formulae are prone to large and economically significant errors, because they contain definite integrals that can only be solved numerically. We show that without mathematically equivalent expressions with analytical solutions the formulae are difficult to deploy effectively in practice

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Incorporating views on marginal distributions in the calibration of risk models

Dey

Juneja

Murthy

2015

Operations Research Letters

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Entropy based ideas find wide-ranging applications in finance for calibrating models of portfolio risk as well as options pricing. The abstracted problem, extensively studied in the literature, corresponds to finding a probability measure that minimizes relative entropy with respect to a specified measure while satisfying constraints on moments of associated random variables. These moments may correspond to views held by experts in the portfolio risk setting and to market prices of liquid options for options pricing models. However, it is reasonable that in the former settings, the experts may have views on tails of risks of some securities. Similarly, in options pricing, significant literature focuses on arriving at the implied risk neutral density of benchmark instruments through observed market prices. With the intent of calibrating models to these more general stipulations, we develop a unified entropy based methodology to allow constraints on both moments as well as marginal distributions of functions of underlying securities. This is applied to Markowitz portfolio framework, where a view that a particular portfolio incurs heavy tailed losses is shown to lead to fatter and more reasonable tails for losses of component securities. We also use this methodology to price non-traded options using market information such as observed option prices and implied risk neutral densities of benchmark instruments.

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Option-Implied Risk-Neutral Distributions and Risk Aversion

Cited by 48 publications

References 172 publications

Risk-Neutral Systemic Risk Indicators

Risk-Neutral Systemic Risk Indicators

Test of recent advances in extracting information from option prices

Incorporating views on marginal distributions in the calibration of risk models

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