Extremes, return level and identification of currency crises

Recent literature has attempted to apply Extreme Value Theory (EVT) in the identification of currency crises. However, these approaches seem to have confused the thresholds in extreme modeling with the cutoffs of currency crises. Our paper proposes a Return Level Identification Approach, also based on EVT but overcoming this pitfall. Besides, it includes the conventional identification approach in the most literature as a special case, but relaxes the embedded normality assumption. A detailed procedure is outlined to demonstrate the implementation of the new approach, further illustrated by an empirical study on identifying the currency crises of China. Results are compared and evaluated by different approaches, and reveal remarkable improvement of our approach. We further combine our method with Early Warning Systems and the second-generation crisis models. Results demonstrate better performance of models with crises identified by our approach than those by conventional approach and also the necessity to include market-expectation variables in the prediction.