Option pricing with realistic ARCH processes
Gilles Zumbach and
Luis Fern�ndez
Quantitative Finance, 2014, vol. 14, issue 1, 143-170
Abstract:
This paper presents a complete computation of option prices based on a realistic process for the underlying and on the construction of a risk-neutral measure as induced by a no-arbitrage replication strategy. The underlying is modelled with a long-memory ARCH process, with relative returns, fat-tailed innovations and multi-scale leverage. The process parameters are estimated on the SP500 stock index (in the physical measure). The change of measure from to the risk-neutral measure is derived rigorously along each path drawn from the process, yielding a Radon--Nikodym derivative for a given choice of a risk aversion function. A small expansion allows to compute explicitly this change of measure. Finally, a given European option's price is obtained as the expectation in of the discounted payoff with a weight given by the change of measure . This procedure is implemented in a Monte Carlo simulation, and allows to compute the option prices, without further adjustable parameters. The computed implied volatility surfaces are compared with empirical surfaces based on European put and call options on the SP500 from 1996 to 2010. Our pricing scheme is able to reproduce the level, the smile, the smirk and the term structure of the surfaces, without any calibration on the observed option prices. We discuss the respective roles of the and measures, the distribution of the terminal prices in both measures, the small impact of the risk aversion and drift premium, and finally we suggest simplifications of our pricing scheme for practical purposes.
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2013.816437 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:14:y:2014:i:1:p:143-170
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20
DOI: 10.1080/14697688.2013.816437
Access Statistics for this article
Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral
More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().