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Reduced order models in PIDE constrained optimization

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EN
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Mathematical models for option pricing often result in partial differential equations originally starting with the Black-Scholes model. In this context, recent enhancements are models driven by Levy processes, which lead to a partial differential equation with an additional integral term. If one solves the problems mentioned last numerically, this yields large linear systems of equations with dense matrices. However, by using the special structure and an iterative solver the problem can be handled efficiently. To further reduce the computational cost in the calibration phase we implement a reduced order model, like proper orthogonal decomposition (POD), which proves to be very efficient. In this paper we use a special multi-level trust region POD algorithm to calibrate the option pricing model and give numerical results supporting the gain in efficiency.
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661--675
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Bibliogr. 23 poz., wykr.
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Bibliografia
  • ALMENDRAL, A. and OOSTERLEE, C.W. (2005) Numerical valuation of options with jumps in the underlying. Appl. Numer. Math. 53, 1-18.
  • ANDERSEN, L. and ANDREASEN, J. (2000) Jump-Diffusion Processes: Volatility Smile Fitting and Numerical Methods for Option Pricing. Review of Derivatives Research 4, 231-262.
  • ARIAN, E., FAHL, M. and SACHS, E.W. (2000) Trust-Region Proper Orthogonal Decomposition for Optimal Flow Control. NASA/CR-2000-210124, ICASE Report.
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  • BRIANI, M., NATALINI, R. and RUSSO, G. (2005) Implicit-Explicit Numerical Schemes for Jump-Diffusion Processes. Calcolo.
  • CONT, R. and TANKOV, P. (2004) Financial Modelling with Jump Processes. Chapman and Hall.
  • CONT, R. and VOLTCHKOVA, E. (2005) A finite difference scheme for option pricing in jump diffusion and exponential Levy models. SIAM J. Numer. Anal. 43 (4), 1596-1626
  • DAUTRAY, R. and LIONS, J.-L. (1992) Mathematical Analysis and Numerical Methods for Science and Technology, Vol. 5: Evolution Problems I. Springer, Berlin.
  • DUPIRE, B. (1994) Pricing with a smile. Risk 7 (1), 18-20.
  • GRATTON, S., SARTENAER, A. and TOINT, P.L. (2008) Recursive Trust-Region Methods for Multiscale Nonlinear Optimization. SIAM J. on Optimization 19 (1), 414-444.
  • HULL, J.C. (2006) Options, Futures, and Other Derivatives. Sixth ed., Prentice Hall, Upper Saddle River, N.J.
  • IKONEN, S. and TOIVANEN, J. (2006) Numerical valuation of European and American options with Kou’s jump-diffusion model. Amamef Conference on Numerical Methods in Finance, INRIA-Rocquencourt, France.
  • KOU, S.G. (2002) A Jump-Diffusion Model for Option Pricing. Mgmt. Sci. 48 (8), 1086-1101.
  • KRAGEL, B. (2005) Streamline Diffusion POD Models in Optimization. PhD thesis, Universität Trier.
  • KUNISCH, K. and VOLKWEIN, S. (2001) Galerkin proper orthogonal decomposition methods for parabolic problems. Numerische Mathematik 90, 117-148.
  • MATACHE, A.-M., VON PETERSDORFF, T. and SCHWAB, C. (2004) Fast deterministic pricing of options on Levy driven assets. Math. Modelling Numer. Anal, 38 (1), 37-71.
  • MERTON, R.C. (1973) Theory of rational option pricing. Bell Journal of Economics and Management Science 4, 141-183.
  • MERTON, R.C. (1976) Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics 3 (1-2), 125-144.
  • SACHS, E.W. and SCHU, M. (2009) A priori error estimates for reduced order models in finance. In preparation.
  • SACHS, E.W. and SCHU, M. (2007) Reduced order models (POD) for calibration problems in finance. ENUMATH Proceedings 2007, Springer, Heidelberg, 735-742.
  • SACHS, E.W. and STRAUSS, A. (2008) Efficient solution of a partial integro-differential equation in finance. Appl. Numer. Math. 58(11), 1687-1703.
  • SCHOUTENS, W. (2003) Levy-Processes in Finance: Pricing Financial Derivatives. Wiley.
  • VOLKWEIN, S. (2001) Optimal control of a phase-field model using proper orthogonal decomposition. Zeitschrift fur angewandte Mathematik und Mechanik 81, 83-97.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0055-0023
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