Abstract
This study investigates volatility clustering and leverage effects in the Canadian banking industry. Estimates from first-differenced highly-frequency data reveal a systematic over-performance of the exponential calibration of the generalised ARCH model against the standard GARCH specification for volatility-modelling purposes, which further supports reviewed lessons from behavioural finance predicting those leverage effects in share markets. The asymmetric impact shows a greater magnitude for negative news than that for good news. Moreover, this study identifies a higher reward for shareholders of the Canadian banking industry when an increased volatility is faced by the market. Robustness of directions and magnitudes is achieved across banks and somehow across different econometric specifications used.
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