Estimating Option-Implied Distributions in Illiquid Markets and Implementing the Ross Recovery Theorem

27 Pages Posted: 4 Aug 2016

See all articles by Emlyn James Flint

Emlyn James Flint

Legae Peresec; Department of Actuarial Science, University of Cape Town

Eben Mare

Independent

Date Written: August 4, 2016

Abstract

We describe how forward-looking information on the statistical properties of an asset can be extracted directly from options market data and how this can be used practically in portfolio management. Although the extraction of a forward-looking risk-neutral distribution is well-established in the literature, the issue of estimation in an illiquid market is not. We use the deterministic SVI volatility model to estimate weekly risk-neutral distribution surfaces. The issue of calibration with sparse and noisy data is considered at length and a simple but robust fitting algorithm is proposed. Furthermore, we attempt to extract real-world implied information by implementing the recovery theorem introduced by Ross (2015). Recovery is an ill-posed problem that requires careful consideration. We describe a regularization methodology for extracting real-world implied distributions and implement this method on a history of SVI volatility surfaces. We analyse the first four moments from the implied risk-neutral and real-world implied distributions and use them as signals within a simple tactical asset allocation framework, finding promising results.

Keywords: option-implied distributions, SVI volatility model, Ross Recovery, Tikhonov regularization, Illiquid markets, tactical asset allocation

JEL Classification: C15, C4, C5, C61, G13

Suggested Citation

Flint, Emlyn James and Mare, Eben, Estimating Option-Implied Distributions in Illiquid Markets and Implementing the Ross Recovery Theorem (August 4, 2016). Available at SSRN: https://ssrn.com/abstract=2817080 or http://dx.doi.org/10.2139/ssrn.2817080

Emlyn James Flint (Contact Author)

Legae Peresec ( email )

15 Cavendish Street
Claremont
Cape Town, Western Cape 7700
South Africa
27117227556 (Phone)

HOME PAGE: http://www.legaeperesec.co.za

Department of Actuarial Science, University of Cape Town ( email )

Actuarial Science Section, University of Cape Town
Private Bag X3, Rondebosch
Cape Town, Western Cape 7701
South Africa
+27 21 650 2475 (Phone)

Eben Mare

Independent ( email )

No Address Available
United States

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