Identifying Extreme Values of Exchange Market Pressure

This paper contributes to the existing literature on dating currency crisis in three ways. First, we combine the Monte Carlo simulation with a modified Hill’s estimator method to obtain more robust results and efficiently deal with bias variance tradeoff in identifying extreme values. Second, we propose a systematic way to choose the reference country in building the Exchange Market Pressure index rather than arbitrary or descriptive reasoning. Third, different data frequencies are applied and the results are evaluated. Our finding suggests that higher frequency data are more appropriate while applying Extreme Value Theory. It urges researchers to be more cautious in applying EVT and interpreting tail incidences that are obtained from lower frequency data.