A procedure for clustering and classifying images determined by three classification variables is presented. A measure of global variability based on the singular value decomposition of the image matrices, and two average measures of local variability based on spatial correlation and spatial...

Ruin probabilities in a controlled discrete-time risk process with a Markov chain interest are studied. To reduce the risk there is a possibility to reinsure a part or the whole reserve. Recursive and integral equations for ruin probabilities are given. Generalized Lundberg inequalities for the...

We propose to estimate non-linear small area population quantities by using Empirical Best (EB) estimators based on a nested error model. EB estimators are obtained by Monte Carlo approximation. We focus on poverty indicators as particular non-linear quantities of interest, but the proposed...

The explosion of algorithmic trading has been one of the most prominent recent trends in the financial industry. Algorithmic trading consists of automated trading strategies that attempt to minimize transaction costs by optimally placing orders. The key ingredient of many of these strategies are...

We consider the quality of the maximum likelihood estimators for the parameters of the two-parameter gamma distribution in small samples. We show that the methodology suggested by Cox and Snell (1968) can be used very easily to bias-adjust these estimators. A simulation study shows that this...

We examine the small-sample behaviour of the maximum likelihood estimator for the Poisson regression model with random covariates. Analytic expressions for the first-order bias and second-order mean squared error for this estimator are derived, and we undertake some numerical evaluations to...

This paper provides an introduction to the problem of modeling randomly spaced longitudinal data. Although Point Process theory was developed mostly in the sixties and early seventies, only in the nineties did this field of Probability theory attract the attention of researchers working in...

This paper analyzes the exposure of the oil and gas industry of 34 countries to oil prices. Using a multifactor panel model to estimate the oil and gas excess stock returns, our results strongly support the view that oil price is a globally priced factor for the oil industry. In particular, the...

Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poor volatility forecasts. Therefore, their detection and correction should be taken seriously when modeling financial data. This paper focuses on these issues and proposes a general detection and...

In this paper, we compare the statistical properties of some of the most popular GARCH models with leverage effect when their parameters satisfy the positivity, stationarity and nite fourth order moment restrictions. We show that the EGARCH specication is the most exible while the GJR model may...