Genest, C., Ghoudi, K., Rivest, L.P. (1995) proposed a two-stage semi-parametric estimation procedure for a broad class of copulas satisfying minimal regularity conditions. A three-stage semi-parametric estimation method based on Kendall's tau has been recently proposed in the financial...

Evidence that the distribution of daily changes of exchange rates has fatter tails than the normal has led researchers to consider different alternative distributions to estimate quantile-based risk measures. In this paper we investigate the ability of SU-curves to capture fat tail risk of...

This paper compares a number of different approaches for determining the Value at Risk (VaR) and Expected Shortfall (ES) of hedge fund investment strategies. We compute VaR and ES through completely model-free methods, as well as through mean/variance and distribution model-based methods. Among...

The current research examines the capacity of the Edgeworth-Sargan density on forecasting market crashes. Focusing on the 1987 stock market crash the performance of this distribution is compared to the Student's t concluding that the latter overestimates the risk. In contrast, and due to its...

In financial groups, enterprise risk management is becoming increasingly important in controlling and managing the different independent legal entities in the group. The aim of this paper is to assess and relate risk concentration and joint default probabilities of the group's legal entities in...

In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well defined for all values in the parameter space, as well as it integrates up to...

In this note we propose a simple method of measuring directional predictability and testing for the hypothesis that a given time series has no directional predictability. The test is based on the correlogram of quantile hits. We provide the distribution theory needed to conduct inference,...

This paper derives the asymptotic distribution of the nonparametric neural network estimator of the Lyapunov exponent in a noisy system. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for testing the chaotic hypothesis based on the...

We investigate a class of semiparametric ARCH(amp;#8734;) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form with regard to the 'news impact' function. We propose an...