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Forecasting Volatility: Evidence from the Bucharest Stock Exchange
Erginbay UĞURLU

Last modified: 2016-01-06


Financial series tend to be characterized by volatility and this characteristic affects both financial series of developed markets and emerging markets.  Because of the emerging markets have provided major investment opportunities in last decades their volatility have been widely investigated in the literature. The most popular volatility models are the Autoregressive Conditional Heteroscedastic (ARCH) or Generalized Autoregressive Conditional Heteroscedastic (GARCH) models. This paper aims to investigate the volatility of Bucharest Stock Exchange, BET index as an emerging capital market and compare forecasting power for volatility of this index, during 2000-2014. To do this, this paper use several GARCH type models against Normal distribution, Student-t distribution and Generalized Error distribution. Then we provide the testing of the predictive power of these GARCH type models and compare their performances on an in sample test. After comparing the forecasting performance of all models, best model will be found by means of forecasting performance.


stock returns; volatility; GARCH model; emerging markets.

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