Performance of GARCH models in forecasting stock market volatility

This paper studies the performance of GARCH model and its modifications, using the rate of returns from the daily stock market indices of the Kuala Lumpur Stock Exchange (KLSE) including Composite Index, Tins Index, Plantations Index, Properties Index, and Finance Index. The models are stationary GARCH, unconstrained GARCH, non‐negative GARCH, GARCH‐M, exponential GARCH and integrated GARCH. The parameters of these models and variance processes are estimated jointly using the maximum likelihood method. The performance of the within‐sample estimation is diagnosed using several goodness‐of‐fit statistics. We observed that, among the models, even though exponential GARCH is not the best model in the goodness‐of‐fit statistics, it performs best in describing the often‐observed skewness in stock market indices and in out‐of‐sample (one‐step‐ahead) forecasting. The integrated GARCH, on the other hand, is the poorest model in both respects. Copyright © 1999 John Wiley & Sons, Ltd.     

Structure, sequence and expression of the hepatitis delta (delta) viral genome

Biochemical and electron microscopic data indicate that the human hepatitis delta viral agent contains a covalently closed circular and single-stranded RNA genome that has certain similarities with viroid-like agents from plants. The sequence of the viral genome (1,678 nucleotides) has been determined and an open reading frame within the complementary strand has been shown to encode an antigen that binds specifically to antisera from patients with chronic hepatitis delta viral infections.     

半定量RT-PCR法检测Weel基因在水稻胚乳发育过程中的表达模式

通过半定量RT-PCR研究Weel基因在水稻胚乳中的表达模式.结果发现Weel基因的表达伴随水稻种子胚乳的整个发育过程.在所检测的几个时期中,授粉后第4 d(4 days after pollination,4 DAP)的胚乳中Weel基因表达量最大;以后随着发育的进行,其表达量逐渐降低,直至15 DAP的胚乳中仍有微弱表达.     

Noradrenaline and cyclic AMP--independent growth stimulation in newt limb blastemata

Adult newts regenerate functional limbs after amputation. This process normally depends on the trophic influence of nerves on the regenerating limbs, particularly in the early stages before differentiation of the regeneration blastema, when it stimulates growth by maintaining high rates of macromolecular synthesis. The sequence of biochemical events involved is unknown, but it has been suggested that intracellular cyclic AMP may be a second messenger within the blastema. Many studies have indicated that the neural agent(s) involved might be protein. The recent finding that blastemata contain high levels of catecholamines, however, has implicated noradrenaline (NA) as the neurotrophic agent, and suggested that it works via stimulation of beta-adrenergic receptors on the blastemal cells, thereby raising the intracellular concentrations of cyclic AMP. To test this hypothesis we studied the ability of NA alone and in combination with alpha-and beta-adrenergic antagonists to increase cyclic AMP levels and to mimic the effects of nerves by maintaining high rates of protein synthesis and high mitotic indices (MI) in denervated blastemata in organ culture. We find that although NA raises cyclic AMP levels through a beta-adrenergic effect, it does not maintain high rates of protein synthesis or high MI in cultured blastemata. It is unlikely therefore, that this hypothesis applies.     

Trading volume and realized volatility forecasting: Evidence from the China stock market

The existing contradictory findings on the contribution of trading volume to volatility forecasting prompt us to seek new solutions to test the sequential information arrival hypothesis (SIAH). Departing from other empirical analyses that mainly focus on sophisticated testing methods, this research offers new insights into the volume-volatility nexus by decomposing and reconstructing the trading activity into short-run components that typically represent irregular information flow and long-run components that denote extreme information flow in the stock market. We are the first to attempt at incorporating an improved empirical mode decomposition (EMD) method to investigate the volatility forecasting ability of trading volume along with the Heterogeneous Autoregressive (HAR) model. Previous trading volume is used to obtain the decompositions to forecast the future volatility to ensure an ex ante forecast, and both the decomposition and forecasting processes are carried out by the rolling window scheme. Rather than trading volume by itself, the results show that the reconstructed components are also able to significantly improve out-of-sample realized volatility (RV) forecasts. This finding is robust both in one-step ahead and multiple-step ahead forecasting horizons under different estimation windows. We thus fill the gap in studies by (1) extending the literature on the volume-volatility linkage to EMD-HAR analysis and (2) providing a clear view on how trading volume helps improve RV forecasting accuracy.