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Geometric fractional Brownian motion model for commodity market simulation

The geometric Brownian motion (GBM) model is a mathematical model that has been used to model asset price paths. By incorporating Hurst parameter to GBM to characterize long-memory phenomenon, the geometric fractional Brownian motion (GFBM) model was introduced, which allows its disjoint increments...

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Autores Principales: Ibrahim, Siti Nur Iqmal, Misiran, Masnita, Laham, Mohamed Faris
Formato: Artículo
Lenguaje:English
Publicado: Elsevier 2021
Acceso en línea:http://psasir.upm.edu.my/id/eprint/97441/1/ABSTRACT.pdf
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spelling oai:psasir.upm.edu.my:97441 http://psasir.upm.edu.my/id/eprint/97441/ Geometric fractional Brownian motion model for commodity market simulation Ibrahim, Siti Nur Iqmal Misiran, Masnita Laham, Mohamed Faris The geometric Brownian motion (GBM) model is a mathematical model that has been used to model asset price paths. By incorporating Hurst parameter to GBM to characterize long-memory phenomenon, the geometric fractional Brownian motion (GFBM) model was introduced, which allows its disjoint increments to be correlated. This paper investigates the accuracy of GBM and GFBM in modelling Malaysia’s crude palm oil price simulation, and to see display of persistent or anti-persistent behaviour across different periods. Results show that the GFBM model is more accurate than the GBM model in simulating future price path for the given data set. Elsevier 2021 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/97441/1/ABSTRACT.pdf Ibrahim, Siti Nur Iqmal and Misiran, Masnita and Laham, Mohamed Faris (2021) Geometric fractional Brownian motion model for commodity market simulation. Alexandria Engineering Journal, 60 (1). 955 - 962. ISSN 2090-2670 https://www.sciencedirect.com/science/article/pii/S111001682030541X 10.1016/j.aej.2020.10.023
institution UPM IR
collection UPM IR
language English
description The geometric Brownian motion (GBM) model is a mathematical model that has been used to model asset price paths. By incorporating Hurst parameter to GBM to characterize long-memory phenomenon, the geometric fractional Brownian motion (GFBM) model was introduced, which allows its disjoint increments to be correlated. This paper investigates the accuracy of GBM and GFBM in modelling Malaysia’s crude palm oil price simulation, and to see display of persistent or anti-persistent behaviour across different periods. Results show that the GFBM model is more accurate than the GBM model in simulating future price path for the given data set.
format Article
author Ibrahim, Siti Nur Iqmal
Misiran, Masnita
Laham, Mohamed Faris
spellingShingle Ibrahim, Siti Nur Iqmal
Misiran, Masnita
Laham, Mohamed Faris
Geometric fractional Brownian motion model for commodity market simulation
author_facet Ibrahim, Siti Nur Iqmal
Misiran, Masnita
Laham, Mohamed Faris
author_sort Ibrahim, Siti Nur Iqmal
title Geometric fractional Brownian motion model for commodity market simulation
title_short Geometric fractional Brownian motion model for commodity market simulation
title_full Geometric fractional Brownian motion model for commodity market simulation
title_fullStr Geometric fractional Brownian motion model for commodity market simulation
title_full_unstemmed Geometric fractional Brownian motion model for commodity market simulation
title_sort geometric fractional brownian motion model for commodity market simulation
publisher Elsevier
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/97441/1/ABSTRACT.pdf
_version_ 1819300933621776384
score 13.4562235

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