Аннотация:
The problem of particular importance in financial risk management is
forecasting the magnitude of a market crash. We address this problem using statistical inference on heavy tailed distributions. Our
approach involves accurate estimates of the tail index, extreme quantiles, and the mean excess function. We apply our approach to
real financial data, and argue that the September 2001 crash had
two components: one (systematic) could be predicted, while another
(non systematic) was due to the shock of the event. We present empirical evidence that the degree of tail heaviness can change considerably as one switches to less frequent data. This fact has important
implications to the problem of estimating financial risks.