tailieunhanh - Forecasting Volatility: Evidence from the Macedonian Stock Exchange

The importance of fisheries in a country cannot only be measured by the contribution to the GDP, but one must also take into consideration that fisheries resources and products are fundamental components of human feeding and employment. Another aspect that makes fisheries resources important is the self renewable character. Unlike mineral resources, if the fishery resources or any other biological resources are well managed, their duration is pratically unlimited. An important conclusion is that the fundamental basis for the conservation and management of fisheries resources stems from the biological characteristics. (This does not mean that social, economic or. | International Research Journal of Finance and Economics ISSN 1450-2887 Issue 18 2008 EuroJournals Publishing Inc. 2008 http Forecasting Volatility Evidence from the Macedonian Stock Exchange Zlatko J. Kovacic School of Information and Social Sciences The Open Polytechnic of New Zealand Wellington New Zealand E-mail Tel 64-4-9135777 FaX 64-4-913-5727 Abstract This paper investigates the behavior of stock returns in an emerging stock market namely the Macedonian Stock Exchange focusing on the relationship between returns and conditional volatility. The conditional mean follows a GARCH-M model while for the conditional variance one symmetric GARCH and four asymmetric GARCH types of models EGARCH GJR TARCH and PGARCH were tested. We examine how accurately these GARCH models forecast volatility under various error distributions. Three distributions were assumed . Gaussian Student -t and Generalized Error Distribution. The empirical results show the following i the Macedonian stock returns time series display stylized facts such as volatility clustering high kurtosis and low starting and slow-decaying autocorrelation function of squared returns ii the asymmetric models show a little evidence on the existence of leverage effect iii the estimated mean equation provide only a weak evidence on the existence of risk premium iv the results are quite robust across different error distributions and v GARCH models with non-Gaussian error distributions are superior to their counterparts estimated under normality in terms of their in-sample and out-of-sample forecasting accuracy. Keywords Stock market forecasting volatility South-Eastern Europe GARCH models non-Gaussian error distribution Macedonia JEL Classification Codes G12 C22 C52. 1. Introduction Financial market volatility is a central issue to the theory and practice of asset pricing asset allocation and risk management. Though earlier financial models

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