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Bayesian Model Averaging in Exchange Rate of Malaysia Ringgit to China Yuan Renminbi
Humaida Banu Samsudin1, Tan Li Ping2

1Humaida Banu Samsudin*, Actuarial Science Programme, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
2Tan Li Ping, Actuarial Science Programme, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia. 

Manuscript received on November 18, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 2506-2510 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7079129219/2019©BEIESP | DOI: 10.35940/ijitee.B7079.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The depreciation of Malaysia Ringgit (MYR) value since 2013 until 2016 have brought many negative impacts on Malaysia’s economy such as the depreciation of export value and the appreciation of import value. Such impacts are getting more severe when the exchange rate of MYR to the currency of Malaysia’s biggest trading partner, China Yuan Renminbi (CNY) is increasing. The study is conducted to explain the movement in the exchange rate of Malaysia Ringgit to China Yuan Renminbi (MYR/CNY). The four macroeconomic factors used to build the estimation models for the exchange rate of MYR/CNY in this study are relative current account balance, relative trade openness, relative sovereign debt, crude oil price. The estimation models are built using two different methods, Bayesian Model Averaging (BMA) and Multiple Linear Regression (MLR). The comparison of the results from the two models in the context of model accuracy shows that BMA model has better performance capability than MLR model in estimating the exchange rate of MYR/CNY. 
Keywords: Exchange Rate, Estimation, MYR/CNY, BMA, MLR.
Scope of the Article: Bio-Science and Bio-Technology