This paper examines the integration of stock markets in Germany, France, Netherlands, Ireland and UK over January 1973-August 2008 at the aggregate market and industry level considering the following industries: basic materials, consumer goods, industrials, consumer services, health care and...

This paper examines the dynamics of stock prices in Ukraine by estimating the degree of persistence of the PFTS stock market index. Using long memory techniques we show that the log prices series is I(d) with d slightly above 1, implying that returns are characterised by a small degree of long...

This paper examines the long-run dynamics and the cyclical structure of the US stock market using fractional integration techniques, specifically a version of the tests of Robinson (1994a) which allows for unit (or fractional) roots both at the zero (long-run) and at the cyclical frequencies. We...

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory counterparts. Since long memory models should have a...

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory counterparts. Since long memory models should have a...

The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield which can be derived from the cost-of-carry relationship. In a recursive...

This paper studies a nonlinear one-factor term structure model in discrete time. The single factor is the short-term interest rate, which is modeled as a self-exciting threshold autoregressive (SETAR) process. Our specification allows for shifts in the intercept and the variance. The process is...

This paper presents and compares several time-series models for returns of broadbased stock indices. These models nest a nonlinear asymmetric GARCH (NGARCH) model as a special case. Some of these models are empirically motivated ad-hoc specifications others are derived from a representative...

This paper presents and compares several time-series models for returns of broadbased stock indices. These models nest a nonlinear asymmetric GARCH (NGARCH) model as a special case. Some of these models are empirically motivated ad-hoc specifications others are derived from a representative...

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...