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Extreme Value theory and Poisson statistics for discrete time samplings of stochastic differential equations

F. Flandoli, S. Galatolo, P. Giulietti, S. Vaienti

Abstract

We investigate the distribution and multiple occurrences of extreme events stochastic processes constructed by sampling the solution of a Stochastic Differential Equation on $\mathbb{R}^n$. We do so by studying the action of an annealead transfer operators on ad-hoc spaces of probability densities. The spectral properties of such operators are obtained by employing a mixture of techniques coming from SDE theory and a functional analytic approach to dynamical systems.

Extreme Value theory and Poisson statistics for discrete time samplings of stochastic differential equations

Abstract

We investigate the distribution and multiple occurrences of extreme events stochastic processes constructed by sampling the solution of a Stochastic Differential Equation on . We do so by studying the action of an annealead transfer operators on ad-hoc spaces of probability densities. The spectral properties of such operators are obtained by employing a mixture of techniques coming from SDE theory and a functional analytic approach to dynamical systems.
Paper Structure (18 sections, 23 theorems, 156 equations)

This paper contains 18 sections, 23 theorems, 156 equations.

Key Result

Theorem 2

Let $h,\tau>0$ and let $X_t$ be the solution of eq:system1 at time $t$. Let $u_n$ be a real sequence such that where $B_{n}$ is the ball $B\left( x_{0},e^{ -u_{n}} \right)$. Let $t_{k}:=kh$. Then

Theorems & Definitions (51)

  • Remark 1
  • Theorem 2
  • Remark 3
  • Remark 4
  • Definition 5
  • Theorem 6
  • Theorem 7: MPZ, Theorem 1.2 and Remark 1.3.
  • Definition 8
  • Definition 9: transfer operator
  • Lemma 10
  • ...and 41 more