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Smile Asymptotics II: Models with Known Moment Generating Functions

Published online by Cambridge University Press:  14 July 2016

Shalom Benaim*
Affiliation:
University of Cambridge
Peter Friz*
Affiliation:
University of Cambridge
*
Postal address: Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WB, UK.
Postal address: Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WB, UK.
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Abstract

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The tail of risk neutral returns can be related explicitly with the wing behaviour of the Black-Scholes implied volatility smile. In situations where precise tail asymptotics are unknown but a moment generating function is available we establish, under easy-to-check Tauberian conditions, tail asymptotics on logarithmic scales. Such asymptotics are enough to make the tail-wing formula (see Benaim and Friz (2008)) work and so we obtain, under generic conditions, a limiting slope when plotting the square of the implied volatility against the log strike, improving a lim sup statement obtained earlier by Lee (2004). We apply these results to time-changed exponential Lévy models and examine several popular models in more detail, both analytically and numerically.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2008 

References

[1] Albin, J. M. P. and Bengtsson, M. (2008). On the asymptotic behaviour of Lévy processes. Part I: Subexponential and exponential processes. To appear in Stoch. Process. Appl. Google Scholar
[2] Andersen, L. B. G. and Piterbarg, V. V. (2005). Moment explosions in stochastic volatility models. Preprint. Available at http://ssrn.com/abstract=559481.Google Scholar
[3] Barndorff-Nielsen, O., Kent, J. and Sørensen, M. (1982). Normal variance-mean mixtures and z distributions. Internat. Statist. Rev. 50, 145159.CrossRefGoogle Scholar
[4] Benaim, S. and Friz, P. K. (2008). Regular variation and smile asymptotics. To appear in Math. Finance.Google Scholar
[5] Bingham, N. H., Goldie, C. M. and Teugels, J. L. (1987). Regular Variation. Cambridge University Press.CrossRefGoogle Scholar
[6] Cont, R. and Tankov, P. (2004). Financial Modelling with Jump Processes. CRC Press, Boca Raton, FL.Google Scholar
[7] Gatheral, J. (2006). The Volatility Surface, A Practitioner's Guide. John Wiley, New York.Google Scholar
[8] Lee, R. (2004). The moment formula for implied volatility at extreme strikes. Math. Finance 14, 469480.CrossRefGoogle Scholar
[9] Nakagawa, K. (2006). Application of Tauberian theorem to the exponential decay of the tail probability of a random variable. Available at http//:arxiv.org/abs/math/0602569.Google Scholar
[10] Revuz, D. and Yor, M. (1989). Continuous Martingales and Brownian Motion. Springer, Berlin.Google Scholar
[11] Schoutens, W. (2003). Lévy Processes in Finance. John Wiley, New York.CrossRefGoogle Scholar
[12] Schoutens, W., Simons, E. and Tistaert, J. (2004). A perfect calibration! Now what? Wilmott Magazine, March 2004.CrossRefGoogle Scholar