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
--
*Athena Picarelli*
Professor
Coordinator of the PhD program in Economics and Finance
Dipartimento di Scienze Economiche
Università di Verona
Polo Santa Marta, Verona.