Probability theory forms the mathematical backbone for quantifying uncertainty and random events, providing a rigorous language with which to describe both everyday phenomena and complex scientific ...

Non-additive measure theory extends the traditional framework of measure and integration by allowing for measures that do not necessarily satisfy the additivity property. This broader perspective has ...

We discuss issues of existence and stochastic modeling in regard to sequences that exhibit combined features of independence and instability of relative frequencies of marginal events. The concept of ...

In this article, we prove that the measures ℚ T associated to the one-dimensional Edwards' model on the interval [0, T] converge to a limit measure ℚ when T goes to infinity, in the following sense: ...

This course presents the mathematical foundations of Probability Theory, including the concepts of Probability Space and random variable. Various types of convergence of sequences and measurable ...

This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option to ...

This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option to ...