Vorträge Stochastik und Finanzmathematik

Studierende und Gäste sind herzlich eingeladen!

Auf dieser Seite finden Sie Informationen über Vorträge folgender Seminare:

Rhein-Main Kolloquium Stochastik: Gemeinsames Kolloquium der Arbeitsgruppen Stochastik TU Darmstadt / Gutenberg-Universität Mainz / Goethe-Universität Frankfurt
Stochastisches Kolloquium: Forschungsseminar des Schwerpunkts Stochastik
Oberseminar Stochastik: Forschungsseminar für Doktoranden und Masterstudenten
Oberseminar Stochastische Prozesse und Ihre Anwendungen: Das Oberseminar des FG Stochastik (Prof. Blath) findet regelmäßig statt. Es richtet sich an Bachelor- und MasterkandidatInnen und junge WissenschaftlerInnen der Arbeitsgruppe Stochastik.
Blockseminar in Riezlern im Haus Bergkranz: Infos zum Haus Bergkranz gibt es hier
Verweis auf weitere interessante Vorträge: außerhalb des Frankfurter Schwerpunkts Stochastik

Vorträge in chronologischer Reihenfolge

Oberseminar Stochastische Prozesse und ihre Anwendung; SPIELE-Seminar

Mai 18 2026

16:00

Raum 903

t.b.a.

Oberseminar Stochastische Prozesse und ihre Anwendung

Mai 11 2026

16:00

Raum 903

Leif Döring (Uni Mannheim): Reinforcement Learning: A Beautiful Playground for Probability and Beyond

Oberseminar Stochastische Prozesse und ihre Anwendung

Apr 27 2026

16:00

Raum 903

Niklas Desheimer (Uni Twente): Some aspects of biologically plausible learning

Abstract: I will present two recent results on biologically plausible learning. First, I will talk about Hebbian learning, which is a key principle underlying learning in biological neural networks. We relate a Hebbian spike-timing-dependent plasticity rule to noisy gradient descent with respect to a non-convex loss function on the probability simplex. Despite the constant injection of noise and the non-convexity of the underlying optimization problem, one can rigorously prove that the considered Hebbian learning dynamic identifies the presynaptic neuron with the highest activity and that the convergence is exponentially fast in the number of iterations. After this I will present a result on Forward Gradient Descent (FGD). FGD has been proposed as a biologically plausible alternative to classical gradient descent methods, which only requires forward passes. We show that FGD with multiple samples can achieve the same minimax optimal rate as stochastic gradient descent. In particular, we prove that FGD adapts to low dimensional structure in the input data.

Rhein-Main-Kolloquium; Oberseminar Stochastische Prozesse und ihre Anwendung

Apr 17 2026

15:15

Rhein-Main-Kolloquium Stochastik

Oberseminar Stochastik

Dez 10 2025

15:15

RM 10, Raum 711 gr.

Alexandra Levitin: Das Preferential Attachment Modell mit Anomalie

Oberseminar Stochastik

Dez 3 2025

14:15

RM10, Raum 711 gr.

Sonja Lührsen: Analyse von PageRank auf zufälligen Netzwerken

Stochastisches Kolloquium; SPIELE-Seminar

Sep 1 2025

11:00

Robert-Mayer-Straße 10, Raum 711 groß

Prof. Philipp Otto: Spatial and Spatiotemporal Volatility Models with an Application on Environmental Risks

Spatial and spatiotemporal volatility models are a class of models designed to capture spatial dependence in the volatility of spatial and spatiotemporal data. Spatial dependence in the volatility may arise due to spatial spillovers among locations; that is, in the case of positive spatial dependence, if two locations are in close proximity, they can exhibit similar volatilities. In this paper, we aim to provide a comprehensive review of the recent literature on spatial and spatiotemporal volatility models. We first briefly review time series volatility models and their multivariate extensions to motivate their spatial and spatiotemporal counterparts. We then review various spatial and spatiotemporal volatility specifications proposed in the literature, along with their underlying motivations and estimation strategies. Through this analysis, we effectively compare all models and provide practical recommendations for their appropriate usage. We highlight possible extensions and conclude by outlining directions for future research.

Oberseminar Stochastische Prozesse und ihre Anwendung

Jul 21 2025

16:00

RM 10, Raum 711 groß

Timo Dimitriadis: Ein Vortrag aus der Ökonometrie

Titel: Kullback-Leibler-Based Characterizations of Score-Driven Updates

Abstract: Score-driven models have been applied in some 400 published articles over the last decade. Much of this literature cites the optimality result in Blasques et al. (2015), which, roughly, states that sufficiently small score-driven updates are unique in locally reducing the Kullback-Leibler divergence relative to the true density for every observation. This is at odds with other well-known optimality results; the Kalman filter, for example, is optimal in a mean-squared-error sense, but occasionally moves away from the true state. We show that score-driven updates are, similarly, not guaranteed to improve the localized Kullback-Leibler divergence at every observation. The seemingly stronger result in Blasques et al. (2015) is due to their use of an improper (localized) scoring rule. Even as a guaranteed improvement for every observation is unattainable, we prove that sufficiently small score-driven updates are unique in reducing the Kullback-Leibler divergence relative to the true density in expectation. This positive, albeit weaker, result justifies the continued use of score-driven models and places their information-theoretic properties on solid footing.

Working Paper: https://arxiv.org/abs/2408.02391

Oberseminar Stochastische Prozesse und ihre Anwendung; SPIELE-Seminar

Jul 14 2025

16:00

RM 10, Raum 711 groß

Oskar Hagen (iDiv): Deep-time mechanistic biodiversity models bridging paleoenvironmental data, ecological dynamics, and evolutionary theory

Abstract: Mechanistic biodiversity simulation models, grounded in mathematical and algorithmic representations, integrate paleoenvironmental reconstructions with ecological and evolutionary dynamics across deep time. By formalizing hypotheses as explicit, process-based rules, these models enable virtual experiments to disentangle the intertwined roles of climate change, landscape evolution, biotic interactions, and trait adaptation in shaping life's diversity. Beyond historical hindcasts, they can forecast biodiversity's response to ongoing global change. This talk will show how population-based, spatially explicit eco-evolutionary models translate delicate empirical observations into tractable computational experiments, bridging Goethe's and other German Romanticists' vision of nature as a living whole with modern scientific rigor. Finally, I will highlight how mechanistic simulations can link empirical data and theory to test and generate new hypothesis, and why cross-disciplinary collaboration is vital for understanding biodiversity dynamics. From ancient climates to future ecosystems under constant change.

Oberseminar Stochastische Prozesse und ihre Anwendung

Jul 7 2025

16:00

Raum 711 groß

Imanol Nunez: The Dice Process - A Model for Partially Exchangeable Dynamics

Cimat, Mexico

Abstract: In this talk we will introduce the dice process, a probabilistic model that describes the evolution of a collection of particles moving over a graph. We will begin by presenting two motivating examples: the averaging process and a coalescent process with multiple switching. After briefly introducing the notion of partial exchangeability, a symmetry property of certain random structures, we will describe the dice process and explain how it is related to the examples introduced at the beginning. This talk is based on joint work in progress with Adrián González Casanova, Noemi Kurt, and José Luis Pérez.