奥恩斯坦-乌伦贝克过程

在数学中，奥恩斯坦-乌伦贝克过程（Ornstein-Uhlenbeck process，简称OU过程）是一个随机过程，在金融数学和物理学中有很多的引用。OU过程描述一个经历摩擦的布朗粒子（damped random walk）。^[1]

这个过程以奥恩斯坦（Leonard Ornstein）和乔治·乌伦贝克的名字命名。

这是一个自迴歸模型AR(1)。

θ =1.0，σ =3和μ =(0,0) 粒子在(10,10)开始

定义

 

θ =1.0，σ =3, μ =(0,0,0) 粒子在(10,10,10)开始

OU过程有下面的随机微分方程

${\displaystyle dx_{t}=-\theta \,x_{t}\,dt+\sigma \,dW_{t}}$ 

其中的 ${\displaystyle \theta >0}$  ， ${\displaystyle \sigma >0}$  是参数，并且 ${\displaystyle W_{t}}$  是维纳过程。^[2][3][4]

${\displaystyle dx_{t}=\theta (\mu -x_{t})\,dt+\sigma \,dW_{t}}$ 

${\displaystyle \mu }$  是常值。上面的方程是Vasicek模型。^[5]

福克–普朗克方程

OU过程的福克–普朗克方程是^[6]

${\displaystyle {\frac {\partial P}{\partial t}}=\theta {\frac {\partial }{\partial x}}(xP)+D{\frac {\partial ^{2}P}{\partial x^{2}}}}$ 

${\displaystyle D=\sigma ^{2}/2}$ 。这是一个抛物偏微分方程。方程的解是

${\displaystyle P(x,t\mid x',t')={\sqrt {\frac {\theta }{2\pi D(1-e^{-2\theta (t-t')})}}}\exp \left[-{\frac {\theta }{2D}}{\frac {(x-x'e^{-\theta (t-t')})^{2}}{1-e^{-2\theta (t-t')}}}\right]}$ 

 

三个OU进程，θ = 1, μ = 1.2, σ = 0.3:
蓝：在a = 0 开始（几乎必然）
绿：在a=2开始
红：初始值呈正态分布

相关

• CKLS过程^[7]（Chan–Karolyi–Longstaff–Sanders process）
• 陈模型
• 缩放极限

参考文献

1. MacLeod, C. L.; Ivezić, Ž; Kochanek, C. S.; Kozłowski, S.; Kelly, B.; Bullock, E.; Kimball, A.; Sesar, B.; Westman, D. Modeling the Time Variability of SDSS Stripe 82 Quasars as a Damped Random Walk. The Astrophysical Journal. October 2010, 721: 1014. doi:10.1088/0004-637X/721/2/1014 （英语）. ^{[永久失效連結]}
2. Karatzas, Ioannis; Shreve, Steven E., Brownian Motion and Stochastic Calculus 2nd, Springer-Verlag: 358, 1991, ISBN 978-0-387-97655-6 
3. Gard, Thomas C., Introduction to Stochastic Differential Equations, Marcel Dekker: 115, 1988, ISBN 978-0-8247-7776-0 
4. Gardiner, C.W., Handbook of Stochastic Methods 2nd, Springer-Verlag: 106, 1985, ISBN 978-0-387-15607-1 
5. Björk, Tomas. Arbitrage Theory in Continuous Time 3rd. Oxford University Press. 2009: 375, 381. ISBN 978-0-19-957474-2. 
6. Risken, H., The Fokker-Planck Equation: Methods of Solution and Application, Springer-Verlag: 99–100, 1984, ISBN 978-0-387-13098-9 
7. Chan et al. (1992)

阅读

• Bibbona, E.; Panfilo, G.; Tavella, P. The Ornstein-Uhlenbeck process as a model of a low pass filtered white noise. Metrologia. 2008, 45 (6): S117–S126. Bibcode:2008Metro..45S.117B. doi:10.1088/0026-1394/45/6/S17. 
• Chan, K. C.; Karolyi, G. A.; Longstaff, F. A.; Sanders, A. B. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance. 1992, 47 (3): 1209–1227. doi:10.1111/j.1540-6261.1992.tb04011.x. 
• Doob, J.L. The Brownian Movement and Stochastic Equations. Annals of Mathematics. April 1942, 43 (2): 351–369. JSTOR 1968873. doi:10.2307/1968873. 
• Gillespie, D. T. (PDF). Phys. Rev. E. 1996, 54 (2): 2084–2091 [2020-02-11]. Bibcode:1996PhRvE..54.2084G. PMID 9965289. doi:10.1103/PhysRevE.54.2084. （原始内容 (PDF)存档于2022-03-01）. 
• Leung, Tim; Li, Xin. Optimal Mean Reversion Trading with Transaction Costs and Stop-Loss Exit. International Journal of Theoretical & Applied Finance. 2015, 18 (3): 1550020. arXiv:1411.5062  . doi:10.1142/S021902491550020X. 
• Risken, H. The Fokker–Planck Equation: Method of Solution and Applications. New York: Springer-Verlag. 1989. ISBN 978-0387504988. 
• Uhlenbeck, G. E.; Ornstein, L. S. On the theory of Brownian Motion. Phys. Rev. 1930, 36 (5): 823–841. Bibcode:1930PhRv...36..823U. doi:10.1103/PhysRev.36.823. 
• Martins, E.P. Estimating the Rate of Phenotypic Evolution from Comparative Data. Amer. Nat. 1994, 144 (2): 193–209. 

外部链接

• Review of Statistical Arbitrage, Cointegration, and Multivariate Ornstein–Uhlenbeck （页面存档备份，存于互联网档案馆）, Attilio Meucci
• A Stochastic Processes Toolkit for Risk Management, Damiano Brigo, Antonio Dalessandro, Matthias Neugebauer and Fares Triki
• , M. A. van den Berg
• Maximum likelihood estimation of mean reverting processes （页面存档备份，存于互联网档案馆）, Jose Carlos Garcia Franco
• . [2015-07-03]. （原始内容存档于2015-09-20）.