GARCH CLASS MODELS PERFORMANCE IN CONTEXT OF HIGH MARKET VOLATILITY

Abstract

In the presented paper GARCH class models were considered for describing and forecasting market volatility in context of the economic crisis. The sample composition was designed to emphasize models performance in two groups of markets: well-developed and transition. As a preview to our results, we presented the procedure of model selection form the GARCH family. We distinguished three subperiods in the time series in a way that the dependencies between forecast outcomes and a scale of market volatility were emphasized. The comparison of the forecast errors revealed a serious problem of volatility prediction in times of high market instability. The crisis impact was particularly apparent in transition markets. Our findings showed that GARCH models allowed risk control, with risk understood as a relation of forecast error to the level of predicted volatility.