Dear colleagues,

We are pleased to announce that, in conjunction with the 12th General AMaMeF Conference that will take place at the Department of Economics of the University of Verona, on the 23-27 of June, we will host a series of special seminars led by some of the distinguished plenary speakers. These seminars, taking place during the weeks immediately preceding and following the Conference, are specifically designed for PhD students and offer an exceptional opportunity to engage with advanced topics in mathematical finance and to interact closely with leading experts in the field.

All the seminars will take place in aula Vaona (Polo Santa Marta, Via Cantarane 24, 1st floor).

Here the program:

- *XUNYU ZHOU (Columbia University)* "Continuous Time Reinforcement Learning"

Tuesday 17 June, h. 9.30-11.30 Wednesday 18 June, h. 9.30-11.30 Thursday 19 June, h. 9.30-11.30

- *SAMUEL COHEN (University of Oxford)* "Deep Galerkin method for PDEs":

Monday 30 June, h. 10.00-12.00 Tuesday 1 July, h. 10.00-12.00 Wednesday 2 July, h. 10.00-12.00

- *AGOSTINO CAPPONI (Columbia University)* "Advances in Mathematics and Machine Learning for Finance" :

Monday 30 June, h. 14.00-16.00: Microstructure of automated market makers. Introduction of the main properties and conceptual innovation of AMMs, and draw parallel with limit order books (CLOB). It will be shown how the convexity of the AMM pricing curve and depth of liquidity pools relates to price impact. It will be highlighted how mathematical control techniques can be used to decide on the best execution venues (AMMs vs CLOBs), and show what data can be used to validate model predictions

Tuesday 1 July, h. 14.00-16.00: Machine Learning in Finance. State-of-art ML techniques, and how they can be used to solve financial mathematics problems. Introduction of diffusion maps, graph machine learning methods, and causal investing.

Wednesday 2 July, h. 14.00-16.00: Goal-Based Wealth Management. A new framework to solve dynamic portfolio optimization problems in finance will be discussed. Rather than postulating risk-averse utility functions, the investor will specify deadlines and amounts of liabilities to be matched by an investment strategy. The basic framework, as well as future extensions and avenues of research, including the inclusion of insurance funds, stochastic deadlines, and connections to multiple optimal stopping will be presented.

Best wishes, Athena Picarelli