We test the soccer myth suggesting that a particularly good moment to score a goal is just before half time. To this end, rich data on 1,179 games played in the UEFA Champions League and UEFA Europa League are analysed. In contrast to the myth, we find that, conditional on the goal difference...

This paper proposes a model for optimizing the duration of transition under the assumption that the government main goal is to minimize the social cost of reforms. At the beginning of transition there are two main sectors in the economy: an old technology sector - mainly the public one - where...

This paper develops the idea of renewal time sampling, a novel sampling scheme constructed from stopping times of semimartingales. Based on this new sampling scheme we propose a class of volatility estimators named renewal based volatility estimators. In this paper we show that: (1) The spot...

We propose a semiparametric method to estimate the average treatment effect under the assumption of unconfoundedness given observational data. Our estimation method alleviates misspecification issues of the propensity score function by estimating the single-index link function involved through...

We introduce two neural network models designed for application in statistical learning. The mean-variance neural network regression model allows us to simultaneously model the mean and the variance of a response variable. In case of a two-dimensional response vector, the...

In this paper we implement the method of Feynman path integral for the analysis of option pricing for certain L'evy process driven financial markets. For such markets, we find closed form solutions of transition probability density functions of option pricing in terms of various special...

One of the main issues in the statistical literature of extremes concerns the tail index estimation, closely linked to the determination of a threshold above which a Generalized Pareto Distribution (GPD) can be fi tted. Approaches to this estimation may be classifi ed into two classes, one using...

Generalized single-index models are natural extensions of linear models and circumvent the so-called curse of dimensionality. They are becoming increasingly popular in many scientific fields including biostatistics, medicine, economics and financial econometrics. Estimating and testing the model...

We show how spectral filtering techniques can improve the convergence of numerical schemes which use discrete Hilbert transforms based on a sinc function expansion, and thus ultimately on the fast Fourier transform. This is relevant, for example, for the computation of fluctuation identities,...