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  6. On backward Kolmogorov equation related ...

Modern Stochastics: Theory and Applications

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On backward Kolmogorov equation related to CIR process
Volume 5, Issue 1 (2018), pp. 113–127
Vigirdas Mackevičius   Gabrielė Mongirdaitė  

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https://doi.org/10.15559/18-VMSTA98
Pub. online: 6 March 2018      Type: Research Article      Open accessOpen Access

Received
20 November 2017
Revised
31 January 2018
Accepted
2 February 2018
Published
6 March 2018

Abstract

We consider the existence of a classical smooth solution to the backward Kolmogorov equation
\[ \left\{\begin{array}{l@{\hskip10.0pt}l}\partial _{t}u(t,x)=Au(t,x),\hspace{1em}& x\ge 0,\hspace{2.5pt}t\in [0,T],\\{} u(0,x)=f(x),\hspace{1em}& x\ge 0,\end{array}\right.\]
where A is the generator of the CIR process, the solution to the stochastic differential equation
\[ {X_{t}^{x}}=x+{\int _{0}^{t}}\theta \big(\kappa -{X_{s}^{x}}\big)\hspace{0.1667em}ds+\sigma {\int _{0}^{t}}\sqrt{{X_{s}^{x}}}\hspace{0.1667em}dB_{s},\hspace{1em}x\ge 0,\hspace{2.5pt}t\in [0,T],\]
that is, $Af(x)=\theta (\kappa -x){f^{\prime }}(x)+\frac{1}{2}{\sigma }^{2}x{f^{\prime\prime }}(x)$, $x\ge 0$ ($\theta ,\kappa ,\sigma >0$). Alfonsi [1] showed that the equation has a smooth solution with partial derivatives of polynomial growth, provided that the initial function f is smooth with derivatives of polynomial growth. His proof was mainly based on the analytical formula for the transition density of the CIR process in the form of a rather complicated function series. In this paper, for a CIR process satisfying the condition ${\sigma }^{2}\le 4\theta \kappa $, we present a direct proof based on the representation of a CIR process in terms of a squared Bessel process and its additivity property.

References

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A. Alfonsi. On the discretization schemes for the CIR (and Bessel squared) processes. Monte Carlo Methods Appl, pages 355–384, 2005. MR2186814
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