PORTFOLIO RISK MEASUREMENT VIA STOCHASTIC MESH

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publication2017 Winter Simulation Conference (WSC)
PublisherIEEE
Pages1796-1807
ISBN (Electronic)9781538634288
StatePublished - Jan 2018

Publication series

NameSimulation Winter Conference
PublisherIEEE
ISSN (Print)0891-7736
ISSN (Electronic)1558-4305

Conference

Title2017 Winter Simulation Conference, WSC 2017
PlaceUnited States
CityLas Vegas
Period3 - 6 December 2017

Abstract

We propose a stochastic mesh approach to portfolio risk measurement under the nested setting in which revaluation of the portfolio value requires simulations. While stochastic mesh was originally proposed as a tool for American option pricing, we are interested in estimating via simulation the risk of the portfolio. We establish asymptotic properties of the stochastic mesh estimator for portfolio risk. In particular, we show that the estimator is asymptotically unbiased and consistent, and its mean squared error (MSE) converges to zero in a rate of Γ−1 , where Γ is the effort required to simulate the sample paths. This rate of convergence is the same as that under the non-nested setting. The proposed method allows for path dependence of financial instruments in the portfolio. Preliminary numerical experiments show that the proposed method works reasonably well.

Citation Format(s)

PORTFOLIO RISK MEASUREMENT VIA STOCHASTIC MESH. / Zhang, Kun; Liu, Guangwu; Wang, Shiyu.

2017 Winter Simulation Conference (WSC). IEEE, 2018. p. 1796-1807 8247917 (Simulation Winter Conference).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review