Relationship between Thai Baht and Oil Price: A Neural Network Model
The research aims to investigate the relationship between the exchange rate of Thai Baht against USD and oil price using daily data from January 1999 to March 2019. To test whether three is the long-run relationship between selected variables, the Johansen cointegration method is employed. The results indicate the evidence of long-run relationship between oil price and the Thai Baht. Then, Artiï¬cial neural networks (ANN) technique is employed for estimation. For ANN estimation, the results suggest that the most influential variables for the Thai Baht is gold price and oil price is third influential variable for Thai Baht. The research used the Mean Squared Error (MSE), Root Mean Square Error (MSE) and the Mean Absolute Percentage Error (MAPE) to measure the error. The results suggest that ANN estimation is more efficient than linear model in term of error.
Keywords: Thai Baht, ANN, Cointegration
JEL Classification: A1