Forecasting Volatility: Evidence from the Bucharest Stock Exchange

Erginbay Ugurlu ()

International Conference on Economic Sciences and Business Administration, 2014, vol. 1, issue 1, 302-310

Abstract: 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 has 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 GARCH, TARCH, EGARCH and PARCH models against Generalized Error distribution. We estimate these models then we compare the forecasting power of these GARCH type models in sample period. The results show that the EGARCH is the best model by means of forecasting performance.

Keywords: stock returns; volatility; GARCH models; emerging markets. (search for similar items in EconPapers)
JEL-codes: C13 C32 C51 C52 G17 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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