|Title: ||Determinants of foreign exchange rate: case of Vietnamese Dong and Japanese Yen
||Author(s): ||Tran Vuong Tu
||Advisor(s): ||Dr. Nguyen Hoang Bao
||Keywords: ||VND/JPY exchange rate; Multiple regression model; Auto-regressive integrated moving average (ARIMA); Vietnamese Dong; Japanese Yen; Vietnam; Japan
||Abstract: ||Exchange rate not only plays a very important role in the economic policy of the government of Vietnam in the process of integration into the world economy, but also effects many exporters, importers, foreign investors, and commercial banks in the international transaction. Japanese economy plays as important as having mainly economic relations with Vietnamese economy in the export-import trade, foreign direct investment (FDI) capital, official development assistance (ODA), etc. However, Vietnam government applies the floating exchange rate policy between Vietnamese Dong and the Japanese Yen. Therefore, the fluctuations of Vietnamese-Japanese exchange rate might great impact on the trade and investment. The exporters and importers of two countries, Japanese investors, the commercial bankers that having international settlement with Japanese Yen, are in need of defending the exchange rate risk volatility of the exchange rate pairs. Our study enhance on analyzing and predicting the fluctuations of Vietnamese-Japanese exchange rate. The main research question identifies (1) Which Vietnamese and Japanese macroeconomics variables determine the VND/JPY exchange rate; (2) What the role of the Japanese Yen plays in the economic relationship between Vietnam and Japan and (3) Which performance of the multiple regression model and the auto-regressive integrated moving average model are in predicting the VND/JPY exchange rate. Methodology focuses on the multiple regression model to define the determinants. Moreover, our study test the reliability in the prediction between multiple regression model and auto-regressive integrated moving average model to examine the VND/JPY exchange rate data. Hence, auto-regressive integrated moving average model plays better forecasting performance.
||Issue Date: ||2013
||Publisher: ||University of Economics Ho Chi Minh City; VNP (Vietnam – The Netherlands Programme for M.A. in Development Economics)
|Appears in Collections:||MASTER'S THESES|