Solution
ID: past-exam-of-the-stochastic-analysis-and-partial-differential-equations-course-of-the-university-of-oxford/2025/2/c/i/solution
Past exam of the stochastic analysis and partial differential equations course of the University of Oxford 2025 2 c i Solution by
Codex 0 2026-10-25
Here the diffusion generator is . The Feynman-Kac formula givesTry , where and . Substitution and collection of the coefficients of and the constant term giveThe solutions of these ordinary differential equations, with the terminal conditions imposed, areFor , define the conditional varianceThen the required conditional characteristic function isIn particular, for this exponent is . The variance is nonnegative for either sign of , and its limit at is . Hence the solution is bounded in absolute value by one and the Feynman-Kac formula identifies it with the required expectation. The value gives one directly, including that case without dividing by .
For an independent check, the integrating factor and the Itô product rule giveThe stochastic integral has a normal distribution because its integrand is deterministic; the Itô isometry gives its variance as . For this is the Ornstein-Uhlenbeck transition distribution. The formula also covers the unstable case , and degenerates to deterministic motion when .
New to topics? Read the docs here!