Identifying extreme values of exchange market pressure

This paper contributes to the existing literature of currency crisis dating in a number of areas. Firstly, we combine the Monte Carlo simulation with a modified version of the Hill’s estimator to obtain robust results and deal with the bias–variance tradeoff in identifying extreme values. Secondly, to avoid sample- specific thresholds, we construct our results upon stationary series with the help of the Hill’s estimator. We also report the whole identified crisis episodes while disregarding the exclusion window technique, which may induce identification problems. To select the reference country when building the exchange market pressure, a statistical search between two exogenously given options is employed. Thirdly, different data frequencies are applied and the results are evaluated. Our findings suggest that higher frequency data are more appropriate when applying extreme value theory (EVT). Our results recommend researchers to be more cautious when applying EVT and interpreting tail incidences that are obtained from lower frequency data. Copyright Springer-Verlag Berlin Heidelberg 2015