The monetary model of exchange rates is better than the random walk in out-of-sample forecasting

Imad Moosa and Kelly Burns

Applied Economics Letters, 2013, vol. 20, issue 14, 1293-1297

Abstract: It is demonstrated that the monetary model of exchange rates is better than the random walk in out-of-sample forecasting if forecasting accuracy is measured by metrics that take into account the magnitude of the forecasting errors and the ability of the model to predict the direction of change. It is suggested that such a metric is the numerical value of the Wald test statistic for the joint coefficient restriction implied by the line of perfect forecast. The results reveal that the monetary model outperforms the random walk in out-of-sample forecasting for four different exchange rates.

Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2013.799753 (text/html)
Access to full text is restricted to subscribers.

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:taf:apeclt:v:20:y:2013:i:14:p:1293-1297

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504851.2013.799753

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().