[NOVA Math] Statistics and Risk Management Seminar

The Center of Mathematics and Applications (NOVA Math), promote the Seminar of Statistics and Risk Management with the title: “Directional Statistics in modelling high volatility”.  Ashis SenGupta (CSIR Emeritus Scientist, Govt of India; Augusta University, Georgia, USA; METU, Turkey) is the speaker.

Abstract: Modern data in many areas of applied science are characterized by high volatility, e.g. long tails as well as high kurtosis or peakedness. They also exhibit asymmetry and multimodality. Classical families of distributions with well-defined probability density functions are inadequate to model such data. On the other hand, families that may be good contenders for modelling high volatility do not in general admit probability density functions on the Euclidean manifold. But these families often can be mapped onto non-Euclidean manifolds, through deep results involving characteristic functions, for which the densities can have elegant Fourier series representations. This connection also immensely helps in statistical inference for the associated parameters. Also, on their own these families provide ample flexibilities in modelling data on non-Euclidean manifolds. We first develop the related theories for deriving these highly flexible families. Next, optimal inference procedures are outlined. Finally, emerging real-life examples from both Euclidean and non-Euclidean manifolds are presented to illustrate the results.

18th September 2025, 14:30