Abstract
Understanding the behavior of market volatility is crucial for asset pricing, portfolio selection, risk management, and trading strategies. The standard Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model assumes that there is no shift in variance, hence its inability to produce a good estimate of volatility persistence. Thus, this research paper re-examines volatility persistence as well as the sudden changes in variance for some major European capital markets-French CAC 40, German DAX 30, and Britain's FTSE 100 stock. The study captures the simultaneous shifts in variance, detected by the iterated cumulative sums of squares (ICSS) algorithm, incorporated into the multivariate BEKKGARCH model. Information obtained shows that the detected changes correspond to both global and domestic events. Results also showed that volatility persistence is reduced in a controlled volatility change model compared to a model ignoring volatility changes. The implication of these results indicates that previous studies on European volatility persistence may have reported overestimated results.
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