Recovering the Real-World Density and Liquidity Premia From Option Data

Mathias Barkhagen, Jörgen Blomvall and Eckhard Platen ()

No 363, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney

Abstract: In this paper we develop a methodology for simultaneous recovery of the real-world probability density and liquidity premia from observed S&P 500 index option prices. Assuming the existence of a num´eraire portfolio for the US equity market, fair prices of derivatives under the benchmark approach can be obtained directly under the real-world measure. Under this modeling framework there exists a direct link between observed call option prices on the index and the real-world density for the underlying index. We use a novel method for estimation of option implied volatility surfaces of high quality, which enables the subsequent analysis. We show that the real-world density that we recover is consistent with the observed realized dynamics of the underlying index. This admits the identification of liquidity premia embedded in option price data. We identify and estimate two separate liquidity premia embedded in S&P 500 index options that are consistent with previous findings in the literature.

Keywords: Real-world density; Liquidity premia; Local volatility model; Non-parametric estimation; Simulated Maximum Likelihood (search for similar items in EconPapers)
JEL-codes: C61 C63 G12 G13 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2015-09-01
References: View references in EconPapers View complete reference list from CitEc
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Published as: Barkhagen, M., Blomvall, J. and Platen, E., 2016, "Recovering the Real-World Density and Liquidity Premia From Option Data", Quantitative Finance, 16(7), 1147-1164.

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https://www.uts.edu.au/sites/default/files/qfr-archive-03/QFR-rp363.pdf (application/pdf)

Related works:
Journal Article: Recovering the real-world density and liquidity premia from option data (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:uts:rpaper:363

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