Asymptotic distribution of the EPMS estimator for financial derivatives pricing

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/105728

Title:	Asymptotic distribution of the EPMS estimator for financial derivatives pricing
Authors:	黃士峰;Huang, Shih-Feng;Tu, Ya-Ting
Contributors:	理學院統計研究所
Keywords:	Asymptotic properties;Empirical [formula omitted]-martingale simulation;Monte Carlo simulation;Option pricing;prices;variance
Date:	2014-01-01
Issue Date:	2026-04-23 12:50:58 (UTC+8)
Publisher:	Elsevier;Elsevier B.V
Abstract:	摘要： The empirical P-martingale simulation (EPMS) is a new simulation technique to improve the simulation efficiency for derivatives pricing when a risk-neutral model is not conveniently obtained. However, since the EPMS estimator creates dependence among sample paths to reduce its estimation variance, the corresponding standard error is not available from using only one simulation path. The asymptotic normality of the EPMS estimator is derived for piecewise smooth payoffs, which could be either continuous or discontinuous. Simulation results indicate that the asymptotic distribution serves as a persuasive approximation for samples consisting of as few as 500 simulation paths, which helps to reduce the computational costs. 出版者： Elsevier B.V 出版日期： 2014-05-01 出處： Computational statistics & data analysis, 2014-05, Vol.73, p.129-145 資源來源： Elsevier ScienceDirect Freedom Collection 版權： 2013 Elsevier B.V. 識別號： ISSN: 0167-9473 識別號： EISSN: 1872-7352 識別號： DOI: 10.1016/j.csda.2013.12.001
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

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