Chapter 1 Stock Return and Inflation: An Analysis Based on the State-Space Framework -- Chapter 2 Diffusion Index Model Specification and Estimation: Using Mixed Frequency Datasets -- Chapter 3 Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks -- Chapter 4 On the...

This study tests whether the behaviour of daily stock returns for the sample of three banks and the composite index in the Malaysian market are nonlinear dependence. Using three nonlinear testing procedures, the study suggests nonlinearity in the return series for all cases. The cause for the...

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved components model with an asymmetric cyclical component. The asymmetric cycle is defined as a sine-cosine wave where the frequency of the cycle depends on past oil price...

Fractional dependent variables and models with state dependence arise in many economic applications. However, estimating models with fractional dependent variables is complicated by the presence of two corner solution outcomes. When coupled with a dynamic panel data setting, estimating...

In this paper, we propose a fully Bayesian approach to the special class of nonlinear time-series models called the logistic smooth transition autoregressive (LSTAR) model. Initially, a Gibbs sampler is proposed for the LSTAR where the lag length, k, is kept fixed. Then, uncertainty about k is...

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved components model with an asymmetric cyclical component. The asymmetric cycle is defined as a sine-cosine wave where the frequency of the cycle depends on past oil price...