Asymmetric Conditional Volatility Modeling: Evidence from Central European Stock Markets

This paper investigates the asymmetric response of equity volatility to return shocks. The effects of good and bad news on volatility in the Czech and Polish stock markets using asymmetric ARCH models before and during the global fmancial crisis of 2008-09 are examined. Moreover we generalize the news impact function to study asymmetric volatility under the ARCH-type models. The PX and WIG20 stock indexes were used as a proxy to the Czech and Polish stock markets to study the asymmetric volatility over 7 year's period. Commonly used asymmetric volatility models i.e. EGARCH and TGARCH models were applied. The PX and WIG20 returns series found to react to the good and bad news asymmetrically. The presence of the leverage effect would imply that the negative news has a greater impact on volatility than a positive innovation. We found that GARCH-class models with normal errors are not capable to capture fully the leptokurtosis in empirical time series, while GED and Student's t errors provide a better description for the conditional volatility.