Hill estimation (Hill, 1975), the most widespread method for estimating tail thickness of heavy-tailed financial data, suffers from two drawbacks. One is that the optimal number of tail observations to use in the estimation is a function of the unknown tail index being estimated, which...

This paper illustrates the usefulness of resampling-based methods in the context of multiple (simultaneous) tests, with emphasis on econometric applications. Economic theory often suggests joint (or simultaneous) hypotheses on econometric models; consequently, the problem of evaluating joint...

Using Monte Carlo simulations, we compare the forecasting performance of the single equation error correction model (SEECM) with that of the (misspecified) difference autoregressive model with exogenous variables (ARX). The main result of the article is that the SEECM produces superior forecasts...

In this article, we apply the Log Periodic Power Law (LPPL), introduced by Johansen <italic>et al.</italic> (2000), for capturing the recent stock market crash in the German stock index (Deutscher Aktien Index, DAX). The contribution of this article consists not only in describing the historical crash by the...

We examine the asymptotic properties of the coefficient of determination, R2, in models with α-stable   random variables. If the regressor and error term share the same index of stability α2, we show that the R2  statistic does not converge to a constant but has a nondegenerate distribution...

In this paper, we construct a single composite financial stress indicator (FSI) which aims to predict developments in the real economy in the euro area. Our FSI was shown to perform better than the Euro STOXX 50 volatility index for the recent banking crisis and the euro-area sovereign debt...

Since Mandelbrot's seminal work (1963), alpha-stable distributions with infinite variance have been regarded as a more realistic distributional assumption than the normal distribution for some economic variables, especially financial data. After providing a brief survey of theoretical results on...

In this paper, we consider a combined forecast using an optimal combination weight in a generalized autoregression framework. The generalized autoregression provides not only a combined forecast but also an optimal combination weight for combining forecasts. By simulation, we find that short-...