In this paper, linear and non-linear Granger causality tests are used to examine the dynamic relationship between daily Korean stock returns and trading volume. We find evidence of significant bidirectional linear and non-linear causality between these two series. ARCH-type models are used to...

This paper develops a time domaine score statistic for testing fractional integration at zero and seasonal frequencies in quarterly time series models.

This paper investigates whether the systematic asymmetric behaviour of the US unemployment rate can be explained by the stock market. We consider threshold models to capture the asymmetric relationship between quarterly US unemployment rate and Dow Jones Industrial Average (DJ) stock returns. We...

It has been argued that research on market efficiency should be evaluated in terms of whether it improves our ability to predict the time series of security returns. Much recent work has addressed the issue of the presence of long memory components in stock prices because of the controversial...

There as been on-going debate and empirical investigation in the literature as to whether or not the term structure contains information about future inflation. In this paper, the authors present new evidence about the information in the term structure of interest rates about future inflation in...

Recently, it has been shown that seasonal and business cycles are related and a similar economic mechanism is at work in producing both types of cycles. Thus, an analysis of seasonal fluctuations shed light on the nature of the business cycle. This paper uses the LM-type tests proposed by Canova...

This paper investigates whether or not the LM techniques proposed to test the null hypothesis of linearity against GARCH, bilinear (BL) and Joint GARCH-BL alternatives separately, have desirable finite sample properties. The result of a Monte carlo simulation study show that their sizes are...

An issue that arises in applications involving the ARCH-in-Mean (ARCH-M) model is whether or not the error variance is constant over time. A proper statistical formulation of this as a test of hypothesis presents two difficulties. First, the model does not satisfy the standard regularity...