This special issue of Applied Stochastic Models in Business and Industry presents the reader to some recent developments in the areas of insurance and finance and their interface. It contains five papers that, except for the first, were presented at the Fourth Brazilian Conference on Statistical Modelling in Insurance and Finance, which took place in Maresias, Brazil, April 4–8, 2009. The topics and the list of authors reflect the long-standing tradition of the Brazilian school of theoretical and applied statistics and its strong involvement in the international scientific community.
The first paper, by Gordon Willmot and X. Sheldon Lin, gives an overview of risk modeling with mixed Erlang distributions. The paper is discussed by David Stanford and José Garrido. The second paper, by Wilfredo Palma and Mauricio Zevallos, presents a new methodology for modeling non-Gaussian time series with long-range dependence. The third paper, by Carlo Sempi, deals with mathematical aspects of copulas, with emphasis on the construction of asymmetric and multivariate copulas. The fourth paper, by Jorge Zubelli and Max Souza, poses and analyzes the problem of strategic decisions under fast mean-reversion volatility conditions. The fifth and final paper, by Eric Cheung and co-authors, treats orders and bounds for ruin-related quantities in a generalized Sparre Andersen risk model.
We are confident that this handful of papers will be well received by a readership expecting scientific novelty and lucid exposition. They were selected among more than 60 submissions whose total contribution is considerable and many of which certainly merit publication in journals of a similar standing. The submissions are listed on the home page of the ‘Fourth Brazilian Conference’ at http://www.ime.usp.br/bcsmif/4th/.
On behalf of the Scientific Committee of the ‘Fourth Brazilian Conference’ and the Editorial Board of ASMBI we would like to thank authors, discussants and referees for their contribution to the success of the conference and of the present special issue.