Outperforming the naïve Random Walk forecast of foreign exchange daily closing prices using Variance Gamma and normal inverse Gaussian Levy processes

Dean Teneng

MPRA Paper from University Library of Munich, Germany

Abstract: This work demonstrates that forecast of foreign exchange (FX) daily closing prices using the normal inverse Gaussian (NIG) and Variance Gamma (VG) Levy processes outperform the naïve Random Walk model. We use the open software R to estimate NIG and VG distribution parameters and perform several classical goodness–of -fits test to select best models. Seven currency pairs can be forecasted by both Levy processes: TND/GBP, EGP/EUR, EUR/GBP, EUR/JPY, JOD/JPY, USD/GBP, and XAU/USD, while USD/JPY and QAR/JPY can be forecasted with the VG process only. RMSE values show that NIG and VG forecast are comparable, and both outperform the naïve Random Walk out of sample. Appended R-codes are original.

Keywords: Levy process; NIG; VG; forecasting; goodness of fits; foreign exchange; Random Walk model (search for similar items in EconPapers)
JEL-codes: C44 C52 C53 (search for similar items in EconPapers)
Date: 2013-06-26
New Economics Papers: this item is included in nep-for and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/47851/1/MPRA_paper_47851.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:47851

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter (winter@lmu.de).