We derive autocorrelation-robust asymptotic variances of the Brier score and Brier skill score, which are generally applicable in circumstances with weak serial correlation. A simulation experiment and an empirical application from macroeconomics underscore the importance of taking care of...

This paper contributes to the GMM literature by introducing the idea of self-instrumenting target variables instead of searching for instruments that are uncorrelated with the errors, in cases where the correlation between the target variables and the errors can be derived. The advantage of the...

This paper proposes the transformed maximum likelihood estimator for short dynamic panel data models with interactive fixed effects, and provides an extension of Hsiao et al. (2002) that allows for a multifactor error structure. This is an important extension since it retains the advantages of...

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility, and study its properties. Based on an...

The renewed momentum in the German housing market has led to concerns that Germany is vulnerable to asset price shocks. In this paper, we apply recently developed recursive unit root tests to detect the beginning and the end of potential speculative bubbles in Germany over the sample period...

In this paper, we contribute to the literature on international stock market comovement. The novelty of our approach lies in usage of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock market returns in a different way. Major part...

Assessing the extreme events is crucial in financial risk management. All risk managers and financial institutions want to know the risk of their portfolio under rare events scenarios. We illustrate a multivariate market risk estimating method which employs Monte Carlo simulations to estimate...

This paper focuses on the extraction of volatility of financial returns. The volatility process is modeled as a superposition of two autoregressive processes which represent the more persistent factor and the quickly mean-reverting factor. As the volatility is not observable, the logarithm of...

In the paper we test for the different reactions of stock markets to the current financial crisis. We focus on Central European stock markets, namely the Czech, Polish and Hungarian ones, and compare them to the German and U.S. benchmark stock markets. Using wavelet analysis, we decompose a time...