FORECASTING VOLATILITY IN TEHRAN STOCK EXCHANGE (TSE)
Abstract. Within two past two decades, volatility has become a focal point to academics and decision makers. Since volatility was criterion for assessing the risk, it was firstly used by many investors and capital markets traders. Throughout the time as volatility affected the economy and stability of capital markets and as a result of that bonds and foreign exchange markets became important. In this article 9 modeled for forecasting volatility of TEPIX index using Tehran Stock Exchange daily data. Models employed in this article include both simple models such as historical average and complicated models such as ARCH and GARCH groups. 4 measuring tools are used to assess the accuracy of forecasting results of these models. Based on the results of this study, forecasts of GARCH (2,3) presented the most accurate results and GARCH (1,1) and regression models showed less accuracy respectively, while Exponential smoothing and random walk had the worst performance.
Keywords : Forecasting, volatility, tepix, arch, garch
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