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Markovian projections for Itô semimartingales with jumps

Martin Larsson, Shukun Long

Abstract

Given a general Itô semimartingale, its Markovian projection is an Itô process, with Markovian differential characteristics, that matches the one-dimensional marginal laws of the original process. We construct Markovian projections for Itô semimartingales with jumps, whose flows of one-dimensional marginal laws are solutions to non-local Fokker--Planck--Kolmogorov equations (FPKEs). As an application, we show how Markovian projections appear in building calibrated diffusion/jump models with both local and stochastic features.

Markovian projections for Itô semimartingales with jumps

Abstract

Given a general Itô semimartingale, its Markovian projection is an Itô process, with Markovian differential characteristics, that matches the one-dimensional marginal laws of the original process. We construct Markovian projections for Itô semimartingales with jumps, whose flows of one-dimensional marginal laws are solutions to non-local Fokker--Planck--Kolmogorov equations (FPKEs). As an application, we show how Markovian projections appear in building calibrated diffusion/jump models with both local and stochastic features.
Paper Structure (10 sections, 4 theorems, 56 equations)

This paper contains 10 sections, 4 theorems, 56 equations.

Key Result

Lemma 2.3

Let $X$ be an $\mathbb{R}^d$-valued measurable process, and $\alpha$ be a $C$-valued measurable process, where $C \subseteq \mathbb{R}^n$ is a closed convex set, satisfying Then, there exists a measurable function $a: \mathbb{R}_+ \times \mathbb{R}^d \to C$ such that for Lebesgue-a.e. $t \geq 0$,

Theorems & Definitions (19)

  • Definition 2.1: Transition kernel
  • Definition 2.2
  • Lemma 2.3: cf. MR3098443, Proposition 5.1
  • Remark 2.4
  • Lemma 2.5
  • proof
  • Remark 2.6
  • Definition 2.7
  • Definition 2.8
  • Remark 2.9
  • ...and 9 more