Template-Type: ReDIF-Article 1.0
Author-Name: Chan Tze-Haw 
Author-Workplace-Name: Graduate School of Business, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia
Author-Email: thchan@usm.my
Author-Name: Lye Chun Teck
Author-Workplace-Name: Faculty of Business, Multimedia University, Jalan Ayer Keroh Lama, 75450 Ayer Keroh, Melaka, Malaysia
Author-Name: Hooy Chee Wooi
Author-Workplace-Name: School of Management, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia
Title: Forecasting Malaysian Ringgit: Before and After The Global Crisis 
Abstract: The forecasting of exchange rates remains a difficult task due to global crises and authority interventions. This study employs the monetary-portfolio balance exchange rate model and its unrestricted version in the analysis of Malaysian Ringgit during the post-Bretton Wood era (1991M1–2012M12), before and after the subprime crisis. We compare two Artificial Neural Network (ANN) estimation procedures (MLFN and GRNN) with the random walks (RW) and the Vector Autoregressive (VAR) methods. The out-of sample forecasting assessment reveals the following. First, the unrestricted model has
superior forecasting performance compared to the original model during the 24-month forecasting horizon. Second, the ANNs have outperformed both the RW and VAR forecasts in all cases. Third, the MLFNs consistently outperform the GRNNs in both exchange rate models in all evaluation criteria. Fourth, forecasting performance is
weakened when the post-subprime crisis period was included. In brief, economic fundamentals are still vital in forecasting the Malaysian Ringgit, but the monetary mechanism may not sufficiently work through foreign exchange adjustments in the short run due to global uncertainties. These findings are beneficial for policy making,
investment modelling, and corporate planning. 
Classification-JEL:
Keywords: Artificial Neural Networks, forecasting, modified monetary-portfolio balance model, Malaysian Ringgit, global crisis 
Pages: 157-175
Volume: 9
Issue: 2
Year: 2013
File-URL: http://web.usm.my/journal/aamjaf/vol 9-2-2013/AAMJAF 9-2-art 7 (155-175).pdf
File-Format: Application/pdf
Handle: RePEc:usm:journl:aamjaf00902_157-175