Die Erholunsgzone vor dem D4 Gebäude über dem Brunnen.

Abstracts

  • Aleksandar Arandjelovic - Deep Learning in Quantitative Finance: Insights from Stochastic Analysis

    This talk explores the application of deep learning in quantitative finance from the point of view of stochastic analysis. We present several universal approximation theorems tailored to quantitative finance. As a consequence of these results, we discuss deep mean-variance hedging in continuous time. Another consequence gives rise to a no free lunch with vanishing risk condition for algorithmic trading strategies. Time permitting, we will also introduce the concept of deep measure projections, exemplified through deep importance sampling.