Optimal search for parameters in Monte Carlo simulation for derivative pricing

Chuan Ju Wang; Ming-Yang Kao

doi:10.1016/j.ejor.2015.08.060

Optimal search for parameters in Monte Carlo simulation for derivative pricing

Chuan Ju Wang^*, Ming-Yang Kao

^*Corresponding author for this work

Computer Science

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

This paper provides a novel and general framework for the problem of searching parameter space in Monte Carlo simulations. We propose a deterministic online algorithm and a randomized online algorithm to search for suitable parameter values for derivative pricing which are needed to achieve desired precisions. We also give the competitive ratios of the two algorithms and prove the optimality of the algorithms. Experimental results on the performance of the algorithms are presented and analyzed as well.

Original language	English (US)
Pages (from-to)	683-690
Number of pages	8
Journal	European Journal of Operational Research
Volume	249
Issue number	2
DOIs	https://doi.org/10.1016/j.ejor.2015.08.060
State	Published - Mar 1 2016

Keywords

Competitive ratio
Deterministic online algorithm
Finance
Monte Carlo simulation
Randomized online algorithm

ASJC Scopus subject areas

General Computer Science
Modeling and Simulation
Management Science and Operations Research
Information Systems and Management

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10.1016/j.ejor.2015.08.060

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title = "Optimal search for parameters in Monte Carlo simulation for derivative pricing",

abstract = "This paper provides a novel and general framework for the problem of searching parameter space in Monte Carlo simulations. We propose a deterministic online algorithm and a randomized online algorithm to search for suitable parameter values for derivative pricing which are needed to achieve desired precisions. We also give the competitive ratios of the two algorithms and prove the optimality of the algorithms. Experimental results on the performance of the algorithms are presented and analyzed as well.",

keywords = "Competitive ratio, Deterministic online algorithm, Finance, Monte Carlo simulation, Randomized online algorithm",

author = "Wang, {Chuan Ju} and Ming-Yang Kao",

note = "Publisher Copyright: {\textcopyright} 2015 Elsevier B.V.",

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AU - Kao, Ming-Yang

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AB - This paper provides a novel and general framework for the problem of searching parameter space in Monte Carlo simulations. We propose a deterministic online algorithm and a randomized online algorithm to search for suitable parameter values for derivative pricing which are needed to achieve desired precisions. We also give the competitive ratios of the two algorithms and prove the optimality of the algorithms. Experimental results on the performance of the algorithms are presented and analyzed as well.

KW - Competitive ratio

KW - Deterministic online algorithm

KW - Finance

KW - Monte Carlo simulation

KW - Randomized online algorithm

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EP - 690

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 2

ER -

Optimal search for parameters in Monte Carlo simulation for derivative pricing

Abstract

Keywords

ASJC Scopus subject areas

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