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Computing VaR and AVaR in infinitely divisible distributions

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Języki publikacji
EN
Abstrakty
EN
In this paper we derive closed-form solutions for the cumulative distribution function and the average value-at-risk for five subclasses of the infinitely divisible distributions: classical tempered stable distribution, Kim–Rachev distribution, modified tempered stable distribution, normal tempered stable distribution, and rapidly decreasing tempered stable distribution. We present empirical evidence using the daily performance of the S&P 500 for the period January 2, 1997 through December 29, 2006.
Rocznik
Strony
223--245
Opis fizyczny
Bibliogr. 24 poz., wykr.
Twórcy
autor
  • Department of Econometrics, Statistics and Mathematical Finance, School of Economics and Business Engineering, University of Karlsruhe
  • KIT Kollegium am Schloss, Bau II, 20.12, R210, D-76128, Karlsruhe, Germany
autor
  • School of Economics and Business Engineering, University of Karlsruhe
  • KIT, Kollegium am Schloss, Bau II, 20.12, R210, Postfach 6980, D-76128, Karlsruhe, Germany
  • Department of Statistics and Applied Probability, University of California, Santa Barbara, USA
  • FinAnalytica Inc.
  • Department Bank of Italy, Via Nazionale, 91, 00184, Rome, Italy
  • Yale School of Management, New Haven, CT USA
Bibliografia
  • [1] L.D. Andrews, Special Functions of Mathematics for Engineers, 2nd edition, Oxford University Press, 1998.
  • [2] P. Artzner, F. Delbaen, J.-M. Eber and D. Heath, Coherent measures of risk, Math. Finance 9 (3) (1999), pp. 203-228.
  • [3] O. E. Barndorff-Nielsen and S. Levendorskii, Feller processes of normal inverse Gaussian type, Quant. Finance 1 (2001), pp. 318-331.
  • [4] M. L. Bianchi, S. T. Rachev, Y. S. Kim and F. J. Fabozzi, Tempered infinitely divisible distributions and processes (in Russian), Teor. Veroyatnost. i Primenen. 55 (1) (2010), pp. 59-86. In English: Theory Probab. Appl. 55 (1) (2011), to appear.
  • [5] S. I. Boyarchenko and S. Z. Levendorski˘i, Option pricing for truncated Lévy processes, Int. J. Theor. Appl. Finance 3 (2000), pp. 549-552.
  • [6] P. Carr, H. Geman, D. Madan and M. Yor, The fine structure of asset returns: An empirical investigation, J. Business 75 (2) (2002), pp. 305-332.
  • [7] A. S. Chernobai, S. T. Rachev and F. J. Fabozzi, Operational Risk: A Guide to Basel II Capital Requirements, Models, and Analysis, Wiley, 2007.
  • [8] G. Doetsch, Introduction to the Theory and Application of the Laplace Transformation, Springer, 1970.
  • [9] S. Dokov, S. V. Stoyanov and S. T. Rachev, Computing VaR and AVaR of skewed-t distribution, J. Appl. Funct. Anal. 3 (1) (2008), pp. 189-208.
  • [10] M. Grabchak and G. Samorodnitsky, Do financial returns have finite or infinite variance? A paradox and an explanation, Quant. Finance 10 (2010), pp. 883-893.
  • [11] Y. S. Kim, S. T. Rachev, M. L. Bianchi and F. J. Fabozzi, Financial market models with Lévy processes and time-varying volatility, J. Banking and Finance 32 (2008), pp. 1363-1378.
  • [12] Y. S. Kim, S. T. Rachev, M. L. Bianchi and F. J. Fabozzi, A new tempered stable distribution and its application to finance, in: Risk Assessment: Decisions in Banking and Finance, G. Bol, S. T. Rachev and R.Wuerth (Eds.), Physika Verlag, Springer, 2008, pp. 77-110.
  • [13] Y. S. Kim, S. T. Rachev, M. L. Bianchi and F. J. Fabozzi, Computing VaR and AVaR in infinitely divisible distributions, Technical Report, Chair of Econometrics, Statistics and Mathematical Finance, School of Economics and Business Engineering, University of Karlsruhe, 2009 (http://www.statistik.uni-karlsruhe.de/download/AVaR_ID_KRBF_03-25.pdf).
  • [14] Y. S. Kim, S. T. Rachev, M. L. Bianchi and F. J. Fabozzi, Tempered stable and tempered infinitely divisible GARCH models, J. Banking and Finance 34 (2010), pp. 2096-2109.
  • [15] Y. S. Kim, S. T. Rachev, D. M. Chung and M. L. Bianchi, A modified tempered stable distribution with volatility clustering, in: New Developments in Financial Modelling, J. O. Soares, J. P. Pina and M. Catalaõ-Lopes (Eds.), Cambridge Scholars Publishing, 2008, pp. 344-365.
  • [16] Y. S. Kim, S. T. Rachev, D. M. Chung and M. L. Bianchi, The modified tempered stable distribution, GARCH models and option pricing, Probab. Math. Statist. 29 (1) (2009), pp. 91-117.
  • [17] L. Klebanov, T. Kozubowski and S. T. Rachev, Ill-Posed Problems in Probability and Stability of Random Sums, Nova Science Publishers, New York 2006.
  • [18] I. Koponen, Analytic approach to the problem of convergence of truncated Lévy flights towards the Gaussian stochastic process, Phys. Rev. E 52 (1995), pp. 1197-1199.
  • [19] G. Pflug, Some remarks on the value-at-risk and the conditional value-at-risk, in: Probabilistic Constrained Optimization: Methodology and Applications, S. Uryasev (Ed.), Kluwer Academic Publishers, 2000, pp. 272-281.
  • [20] S. T. Rachev and S. Mittnik, Stable Paretian Models in Finance, Wiley, 2000.
  • [21] S. T. Rachev, S. Stoyanov and F. J. Fabozzi, Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization: The Ideal Risk, Uncertainty, and Performance Measures, Wiley, New Jersey, 2007.
  • [22] R. T. Rockafellar and S. Uryasev, Optimization of conditional value-at-risk, Journal of Risk 2 (3) (2000), pp. 21-41.
  • [23] R. T. Rockafellar and S. Uryasev, Conditional value-at-risk for general loss distributions, J. Banking and Finance 26 (2002), pp. 1443-1471.
  • [24] S. Stoyanov, G. Samorodnitsky, S. T. Rachev and S. Ortobelli, Computing the portfolio conditional Value-at-Risk in the α-stable case, Probab. Math. Statist. 26 (1) (2006), pp. 1-22.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f04aafaa-80e7-4a7b-92f8-04fb8d83c534
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