Markov cubature rules for polynomial processes

被引：3

作者：

Filipovic, Damir ^{[1
,2
]}

Larsson, Martin ^{[3
]}

Pulido, Sergio ^{[4
,5
]}

机构：

[1] Ecole Polytech Fed Lausanne, CH-1015 Lausanne, Switzerland

[2] Swiss Finance Inst, CH-1015 Lausanne, Switzerland

[3] Swiss Fed Inst Technol, Dept Math, Ramistr 101, CH-8092 Zurich, Switzerland

[4] Univ Evry Val Essonne, Lab Math & Modelisat Evry LaMME, UMR CNRS 8071, IBGBI 23 Blvd France, F-91037 Evry, France

[5] Univ Paris Saclay, ENSILE, St Aubin, France

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2020年 / 130卷 / 04期

基金：

欧洲研究理事会; 瑞士国家科学基金会;

关键词：

Polynomial process; Cubature rule; Asymptotic moments; Transition rate matrix; Transition probabilities; American options; DIFFERENTIAL-EQUATIONS; DIFFUSION-MODELS; EXCHANGE-RATES; APPROXIMATIONS; SIMULATION;

D O I：

10.1016/j.spa.2019.06.010

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We study discretizations of polynomial processes using finite state Markov processes satisfying suitable moment matching conditions. The states of these Markov processes together with their transition probabilities can be interpreted as Markov cubature rules. The polynomial property allows us to study such rules using algebraic techniques. Markov cubature rules aid the tractability of path-dependent tasks such as American option pricing in models where the underlying factors are polynomial processes. (C) 2019 Elsevier B.V. All rights reserved.

引用

页码：1947 / 1971

页数：25

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