Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-23T23:44:41.613Z Has data issue: false hasContentIssue false

Joint law of an Ornstein–Uhlenbeck process and its supremum

Published online by Cambridge University Press:  16 July 2020

Christophette Blanchet-Scalliet*
Affiliation:
University of Lyon
Diana Dorobantu*
Affiliation:
University of Lyon
Laura Gay*
Affiliation:
University of Lyon
*
**Postal Address: University Lyon 1, ISFA, LSAF (EA 2429), France
**Postal Address: University Lyon 1, ISFA, LSAF (EA 2429), France
*Postal address: CNRS UMR 5208, Ecole Centrale de Lyon, Institut Camille Jordan, France. Email address: [email protected]

Abstract

Let X be an Ornstein–Uhlenbeck process driven by a Brownian motion. We propose an expression for the joint density / distribution function of the process and its running supremum. This law is expressed as an expansion involving parabolic cylinder functions. Numerically, we obtain this law faster with our expression than with a Monte Carlo method. Numerical applications illustrate the interest of this result.

MSC classification

Type
Research Papers
Copyright
© Applied Probability Trust 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alili, L., Patie, P. and Pedersen, J-L. (2005). Representations of first hitting time density of an Ornstein–Uhlenbeck process. Stoch. Models 21 (4), 967980.CrossRefGoogle Scholar
Borodin, A. N. and Salminen, P. (2015). Handbook of Brownian Motion: Facts and Formulae, 2nd edn (Probability and its Applications). Birkhäuser.Google Scholar
Boyce, W. and DiPrima, R.C. (2008). Elementary Differential Equations and Boundary Value Problems. Wiley.Google Scholar
Brézis, H. (1983). Analyse Fonctionelle, Collection Mathématiques appliquées pour la maîtrise. Masson.Google Scholar
Coutin, L. and Pontier, M. (2019). Existence and regularity of law density of a pair (diffusion, first component running maximum). Statist. Prob. Lett. 153, 130138.10.1016/j.spl.2019.05.013CrossRefGoogle Scholar
Coutin, L., Pontier, M. and Ngom, W. (2018). Joint distribution of a Lévy process and its running supremum. J. Appl. Prob. 55 (2), 488512.CrossRefGoogle Scholar
Delarue, F., Inglis, J., Rubenthaler, S. and Tanré, E. (2013). First hitting times for general non-homogeneous 1d diffusion processes: density estimates in small time. Working paper hal-00870991.Google Scholar
Doney, R. and Kyprianou, A. (2006). Overshoots and undershoots of Lévy processes. Ann. Appl. Prob. 16 (1), 91106.10.1214/105051605000000647CrossRefGoogle Scholar
Escobar, M. and Hernandez, J. (2014). A note on the distribution of multivariate Brownian extrema. Int. J. Stoch. Anal. 2014, 575270, 16.10.1155/2014/575270CrossRefGoogle Scholar
Gardiner, C. W. (2004). Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences, 3rd edn (Springer Series in Synergetics 13). Springer.CrossRefGoogle Scholar
He, H., Keirstead, W. and Rebholz, J. (1998). Double lookbacks. Math. Finance 8 (3), 201228.10.1111/1467-9965.00053CrossRefGoogle Scholar
Jeanblanc, M., Yor, M. and Chesney, M. (2009). Mathematical Methods for Financial Markets (Springer Finance). Springer, London.CrossRefGoogle Scholar
Karatzas, I. and Shreve, S. (1991). Brownian Motion and Stochastic Calculus (Graduate Texts in Mathematics). Springer, New York.Google Scholar
Lebedev, N. N. and Silverman, R. A. (1972). Special Functions and Their Applications (Dover Books on Mathematics). Dover.Google Scholar
Linetsky, V. (2004). Computing hitting time densities for CIR and OU diffusions: applications to mean-reverting models. J. Comput. Finance 7, 122.CrossRefGoogle Scholar
Lipton, A. and Kaushansky, V. (2018). On the first hitting time density of an Ornstein–Uhlenbeck process. Available from arXiv:1810.02390.Google Scholar
Ngom, W. (2016). Contributions to the study of default time of a Lévy process in complete observation and in incomplete Observation. Doctoral thesis, Université Paul Sabatier – Toulouse III.Google Scholar
Risken, H. and Haken, H. (1989). The Fokker–Planck Equation: Methods of Solution and Applications, 2nd edn. Springer.10.1007/978-3-642-61544-3CrossRefGoogle Scholar
Sleeman, B. D. (1968). On parabolic cylinder functions. IMA J. Appl. Math. 4 (1), 106112.CrossRefGoogle Scholar
Sommerfeld, A. (1894). Sur la théorie analytique de la conduction thermique. Ann. Math. 45 (2), 263277.CrossRefGoogle Scholar