OUT-OF-SAMPLE FORECASTING PERFORMANCE OF A ROBUST NEURAL EXCHANGE RATE MODEL OF RON/USD

Corina Saman

Journal for Economic Forecasting, 2015, issue 1, 93-106

Abstract: This paper aims to explore the forecasting accuracy of RON/USD exchange rate structural models with monetary fundamentals. I used robust regression approach for constructing robust neural models less sensitive to contamination with outliers and I studied its predictability on 1 to 6-month horizon against nonrobust linear and nonlinear regressions and, especially, random walk. The results show that robust model with low breakdown point improve the forecast accuracy of RW and AR models on 1- and 4-month horizon and performs better than RW at all time horizons.

Keywords: exchange rate; forecasting; neural networks; outliers (search for similar items in EconPapers)
JEL-codes: C22 C45 C53 E22 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.ipe.ro/rjef/rjef1_15/rjef1_2015p93-106.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:rjr:romjef:v::y:2015:i:1:p:93-106

Access Statistics for this article

Journal for Economic Forecasting is currently edited by Lucian Liviu Albu and Corina Saman

More articles in Journal for Economic Forecasting from Institute for Economic Forecasting Contact information at EDIRC.
Bibliographic data for series maintained by Corina Saman ( this e-mail address is bad, please contact ).