To challenge the appropriateness of the theory of the weak-form market efficiency, this study examines the day-of-the-week effect and the twist-of-the-Monday effect for the ASEAN – 5 stock markets for the period June 10, 2002 through August 21, 2009. Our Kruskal-Wallis statistic test...

Exponential Smooth Transition Autoregressive (ESTAR) model is widely adopted in the exchange rate study as its symmetrical distribution matches that of the symmetrical exchange rate adjustment behaviour. In contrast, another specification of STAR model, namely the LSTAR (logistic STAR) model is...

This study is undertaken with the objective of investigating the performance of Akaike’s Information Corrected Criterion (AICC) as an order determination criterion for the selection of Autoregressive Moving-average or ARMA (p, q) time series models. A simulation investigation was carried out...

In an attempt to determine the predictability of ASEAN exchange rates, five currencies including Malaysian ringgit, Thailand baht, Singapore dollar, Indonesian rupiah and the Philippines peso, denominated in US dollar as well as Japanese yen, were modeled using advanced time series analysis....

This study proposes an alternative procedure for modelling exchange rates behaviour, which is a linear combination of a long-run function and a short-run function. Our procedure involves modelling of the long- run relationship and this is followed by the short-run function. Among all the...

This study compares the forecasting performance between Smooth Transition Autoregressive (STAR) non-linear model and the conventional linear Autoregressive (AR) time series model using the simple random walk (SRW) model as the standard reference model. To accomplish this objective, quarterly...

Smooth Transition Autoregressive (STAR) model has been employed in a number of current studies dealing with non-linearities. The usefulness of this model has been documented in these studies. However, the population statistical properties of the parameters in this model remain unknown. This...