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Convergence of Multi-Dimensional Quantized SDE’s

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Séminaire de Probabilités XLIII

Part of the book series: Lecture Notes in Mathematics ((SEMPROBAB,volume 2006))

Abstract

We quantize a multidimensional SDE (in the Stratonovich sense) by solving the related system of ODE’s in which the d-dimensional Brownian motion has been replaced by the components of functional stationary quantizers. We make a connection with rough path theory to show that the solutions of the quantized solutions of the ODE converge toward the solution of the SDE. On our way to this result we provide convergence rates of optimal quantizations toward the Brownian motion for \(\frac{1} {q}\)-Hölder distance, q > 2, in L p().

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References

  1. Billingsley, P.: Convergence of probability measure. Wiley Series in Probability and Mathematical Statistics. Wiley, New York, 253 p. (1968)

    Google Scholar 

  2. Coutin, L., Victoir, N.: Enhanced Gaussian processes and applications. ESAIM P&S 13, 247–269 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  3. Cuesta-Albertos, J.A., Matrán, C.: The strong law of large numbers for k-means and best possible nets of Banach valued random variables. Probab. Theory Relat. Field. 78, 523–534 (1988)

    Article  Google Scholar 

  4. Dereich, S.: The coding complexity of diffusion processes under L p[0, 1]-norm distortion, pre-print. Stoch. Process. Appl. 118(6), 938–951 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  5. Dereich S., Fehringer F., Matoussi A., Scheutzow M.: On the link between small ball probabilities and the quantization problem for Gaussian measures on Banach spaces. J. Theor. Probab. 16, 249–265 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  6. Friz, P.: Continuity of the Itô-map for Hölder rough paths with applications to the support theorem in Hölder norm. Probability and partial differential equations in modern applied mathematics, IMA Vol. Math. Appl. vol. 140, pp. 117–135. Springer, New York (2005)

    Google Scholar 

  7. Friz, P., Victoir, N.: Differential equations driven by Gaussian signals. Ann. Inst. Henri Poincar Probab. Stat. 46(2), 369–413 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Friz, P., Victoir, N.: Differential equations driven by Gaussian signals II. Available at arxiv:0711.0668 (2007)

    Google Scholar 

  9. Friz, P., Victoir, N.: Multidimensional stochastic differential equations as rough paths: theory and applications, Cambridge Studies in Advanced Mathematics, 670 p. (2010)

    Google Scholar 

  10. Graf, S., Luschgy, H.: Foundations of quantization for probability distributions. Lecture Notes in Mathematics, vol. 1730. Springer, Berlin (2000)

    Google Scholar 

  11. Graf, S., Luschgy, H., Pagès, G.: Functional quantization and small ball probabilities for Gaussian processes. J. Theor. Probab. 16(4), 1047–1062 (2003)

    Article  MATH  Google Scholar 

  12. Graf, S., Luschgy, H., Pagès, G.: Optimal quantizers for Radon random vectors in a Banach space. J. Approx. Theor. 144, 27–53 (2007)

    Article  MATH  Google Scholar 

  13. Graf, S., Luschgy, H., Pagès, G.: Distortion mismatch in the quantization of probability measures. ESAIM P&S 12, 127–153 (2008)

    Article  MATH  Google Scholar 

  14. Lejay, A.: An introduction to rough paths. Séminaire de Probabilités YXXVII. Lecture Notes in Mathematics, vol. 1832, pp. 1–59 (2003)

    Article  MathSciNet  Google Scholar 

  15. Lejay, A.: Yet another introduction to rough paths. Séminaire de Probabilités XLII. Lecture Notes in Mathematics, vol. 1979, pp. 1–101 (2009)

    Article  MathSciNet  Google Scholar 

  16. Lejay, A.: On rough differential equations. Electron. J. Probab. 14(12), 341–364 (2009)

    MathSciNet  MATH  Google Scholar 

  17. Lejay, A.: Global solutions to rough differential equations with unbounded vector fields, pre-pub. INRIA 00451193 (2010)

    Google Scholar 

  18. Luschgy, H., Pagès, G.: Functional quantization of stochastic processes. J. Funct. Anal. 196, 486–531 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  19. Luschgy, H., Pagès, G.: Sharp asymptotics of the functional quantization problem for Gaussian processes Ann. Probab. 32, 1574–1599 (2004)

    Article  MATH  Google Scholar 

  20. Luschgy, H., Pagès, G.: Functional quantization of a class of Brownian diffusions: a constructive approach. Stoch. Process. Appl. 116, 310–336 (2006)

    Article  MATH  Google Scholar 

  21. Luschgy, H., Pagès, G.: High resolution product quantization for Gaussian processes under sup-norm distortion. Bernoulli 13(3), 653–671 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  22. Luschgy, H., Pagès, G.: Functional quantization and mean pathwise regularity with an application to Lévy processes. Ann. Appl. Probab. 18(2), 427–469 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  23. Luschgy, H., Pagès, G., Wilbertz, B.: Asymptotically optimal quantization schemes for Gaussian processes. ESAIM P&S 12, 127–153 (2008)

    Article  MATH  Google Scholar 

  24. Lyons, T.: Interpretation and solutions of ODE’s driven by rough signals. Proc. Symp. Pure 1583 (1995)

    Google Scholar 

  25. Lyons, T.: Differential Equations driven by rough signals. Rev. Mat. Iberoamericana 14(2), 215–310 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  26. Lyons, T., Caruana, M.J., Lévy, T.: Differential equations driven by rough paths. Lecture Notes in Mathematics, vol. 1908, 116 p. (Notes from T. Lyons’s course at École d’été de Saint-Flour (2004).) (2007)

    Google Scholar 

  27. Pagès, G., Printems, J.: Functional quantization for numerics with an application to option pricing. Monte Carlo Methods Appl. 11(4), 407–446 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  28. Pagès, G., Printems, J.: Website devoted to vector and functional optimal quantization: http://www.quantize.maths-fi.com (2005)

  29. Revuz, D., Yor, M.: Continuous martingales and Brownian motion, 3rd edn. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences], 293, 602 p. Springer, Berlin (1999)

    Google Scholar 

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…cknowledgements

We thank A. Lejay for helpful discussions and comments about several versions of this work and F. Delarue and S. Menozzi for initiating our first “meeting” with rough path theory.

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Correspondence to Gilles Pagès .

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Pagès, G., Sellami, A. (2011). Convergence of Multi-Dimensional Quantized SDE’s. In: Donati-Martin, C., Lejay, A., Rouault, A. (eds) Séminaire de Probabilités XLIII. Lecture Notes in Mathematics(), vol 2006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15217-7_11

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