In this paper, we will discuss a parametric approach to risk-neutral density extraction from option prices based on the knowledge of the estimated historical density. A flexible distribution is needed in order to find an equivalent change of measure and, at the same time, take into account the historical estimates. To this end, we introduce a new tempered stable distribution that we refer to as the KR distribution.
Some properties of this distribution will be discussed in this paper, along with the advantages in applying it to financial modeling. Since the KR distribution is infinitely divisible, a Lélvy process can be induced from it. Furthermore, we can develop an exponential Lévy model, called the exponential KR model, and prove that it is an extension of the Carr, Geman, Madan, and Yor (CGMY) model.
The risk-neutral process is fitted by matching model prices to market prices of options using nonlinear least squares. The easy form of the characteristic function of the KR distribution allows one to obtain a suitable solution to the calibration problem. To demonstrate the advantages of the exponential KR model, we present the results of the parameter estimation for the S&P 500 Index and option prices.
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References
Anderson, T. W. and Darling, D. A. (1952). Asympotic Theory of Certain ‘Goodness of fit’ Criteria Based on Stochastic Processes, Annals of Mathematical Statistics, 23, 2, 193–212
Anderson, T. W. and Darling, D. A. (1954). A Test of Goodness of Fit, Journal of the American Statistical Association, 49, 268, 765–769
Andrews, L. D. (1998). Special Functions of Mathematics for Engineers, 2nd Edn, Oxford University Press, Oxford
Breton, J. C., Houdré, C. and Privault, N. (2007). Dimension Free and Infinite Variance Tail Estimates on Poisson Space, in Acta Applicandae Mathematicae, 95, 151–203
Black, F. and Scholes M. (1973). The Pricing of Options and Corporate Liabilities, Journal of Political Economy, 81, 3, 637–654
Boyarchenko, S. I. and Levendorskiĭ, S. Z. (2000). Option Pricing for Tuncated Lévy Processes, International Journal of Theoretical and Applied Finance, 3, 3, 549–552
Carr, P., Geman, H., Madan, D. and Yor M. (2002). The Fine Structure of Asset Returns: An Empirical Investigation, Journal of Business, 75, 2, 305–332
Carr, P. and Madan, D. B. (1999). Option Valuation Using the Fast Fourier Transform, Journal of Computational Finance, 2, 4, 61–73
Cont, R. and Tankov P. (2004). Financial Modelling with Jump Processes, Chapman & Hall/CRC, London
D'Agostino, R. B. and Stephens, M. A. (1986). Goodness of Fit Techniques, Dekker, New York
Kawai, R. (2004). Contributions to Infinite Divisibility for Financial modeling, Ph.D. thesis, http://hdl.handle.net/1853/4888
Kim, Y. S., Rachev, S. T., Chung, D. M., and Bianchi. M. L. The Modified Tempered Stable Distribution, GARCH-Models and Option Pricing, Probability and Mathematical Statistics, to appear
Kim, Y. S. and Lee, J. H. (2007). The Relative Entropy in CGMY Processes and Its Applications to Finance, to appear in Mathematical Methods of Operations Research
Koponen, I. (1995). Analytic Approach to the Problem of Convergence of Truncated Lévy Flights towards the Gaussian Stochastic Process, Physical Review E, 52, 1197–1199
Lewis, A. L. (2001). A Simple Option Formula for General Jump-Diffusion and Other Exponential Levy Processes, avaible from http:// www.optioncity.net.
Lukacs, E. (1970). Characteristic Functions, 2nd Ed, Griffin, London
Mandelbrot, B. B. (1963). New Methods in Statistical Economics, Journal of Political Economy, 71, 421–440
Marsaglia, G., Tsang, W. W. and Wang, G. (2003). Evaluating Kolmogorov's Distribution, Journal of Statistical Software, 8, 18
Marsaglia, G. and Marsaglia, J. (2004). Evaluating the Anderson-Darling Distribution, Journal of Statistical Software, 9, 2
Fujiwara, T. and Miyahara, Y. (2003). The Minimal Entropy Martingale Measures for Geometric Lévy Processes, Finance & Stochastics 7, 509–531
Rachev, S. and Mitnik S. (2000). Stable Paretian Models in Finance, Wiley, New York
Rachev, S., Menn C., and Fabozzi F. J. (2005). Fat-Tailed and Skewed Asset Return Distributions: Implications for Risk Management, Portfolio selection, and Option Pricing, Wiley, New York
Rosiński, J. (2006). Tempering Stable Processes, Working Paper, http://www.math.utk.edu/̃rosinski/Manuscripts/tstableF.pdf.
Sato, K. (1999). Lévy Processes and Infinitely Divisible Distributions, Cambridge University Press, Cambridge
Schoutens, W. (2003). Lévy Processes in Finance: Pricing Financial Derivatives, Wiley
Shao, J. (2003). Mathematical Statistics, 2nd Ed, Springer, Berlin Heidelberg New York
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Kim, Y.S., Rachev, S.T., Bianchi, M.L., Fabozzi, F.J. (2009). A New Tempered Stable Distribution and Its Application to Finance. In: Bol, G., Rachev, S.T., Würth, R. (eds) Risk Assessment. Contributions to Economics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2050-8_5
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