The objectives of this study are to find the fitting model and dependence measures of both Thailand’s exchange rate and Malaysia’s exchange rate during, between, and after the World’s recent financial crises based on linear, nonlinear and empirical copula approaches. The results of the...

This paper investigates the relationship between People’s Republic of China’s exchange rates and Thailand’s exchange rates. The selection of several mixed forecasting consisting of linear model, nonlinear models and copulas approach was experimented of People’s Republic of China’s...

Forecasting is an essential analytical tool for tourism policy and planning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q). Secondary data was used to produce forecasts of international tourists’ expenditures in Thailand for the period 2009-2010. The results...

Forecasting is an essential analytical tool for tourism policy and planning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q). Secondary data was used to produce forecasts of the number of international tourist arrivals to Thailand for the period of 2009-2010....

This study aims to accomplish three main tasks. Firstly, it seeks to determine the more appropriate choice between classical and Bayesian methods in estimating a pooled panel kink regression model under the condition of a known but bounded policy variable choice that serves as a kink point....

The dependence structure analysis of a financial time series of returns is significant when applied to contemporary financial risk management. Copula function is a flexible and effective tool to be used on modeling the financial model and risk management. This paper aims to set up the dependence...

This paper used different copula-based GARCH models (Copula-GARCH model and Copula-GJR-GARCH model) to analyze the dependence structure among gold price, stock price index of gold mining companies and Shanghai Composite Index in China. The empirical results found that the suitable margins were...