|
On 18 and 19 April 2018, RMI co-hosted the 6th NUS-USPC Workshop on Machine Learning and Fintech with Laboratoire de Probabilités, et Modèles Aléatoires at University Paris Diderot/Sorbonne Paris Cité and the Centre for Quantitative Finance (CQF) at NUS. The conference was held in Singapore this time at the Institute of Mathematical Sciences (IMS) at NUS. The Workshop was attended by over 80 participants from industry and academia. This workshop featured an overview of recent advances in machine learning and innovations in financial technology by experts, academics, and practitioners in fields such as finance, numerics, statistics and engineering/computer science. The speakers of this workshop came from various institutions in Europe, Singapore, as well as Australia. Some of the speakers included, Jean-François Chassagneux, Huyên Pham, and Claudio Fontana of University Paris Diderot, France; Min Dai, Steven Kou, Ilija Ilievski, Hao Lei, and Simon Trimborn of NUS, Singapore; Christa Cuchiero of University of Vienna, Austria; Ivan Guo and Gregoire Loeper of Monash University, Australia, Nicolas Langrene of CSIRO, Australia, and Michael Kupper of University of Konstanz, Germany. The organizing committee included professors from both NUS and University Paris Diderot. The Workshop contained a total of 13 talks and the topics included; a probabilistic numerical methods for mean field game (MFG), designing stable coins, the value of informational arbitrage, interpretable forecasting of financial time series with deep learning, sparse-group network autoregressive model for the bitcoin blockchain, unsupervised probabilistic topic modelling, robo-advising: a dynamic mean-variance approach, deep learning algorithms for stochastic control problems, computation of optimal transport and related hedging problems via penalization and neural networks, calibration of financial models with neural networks, and machine learning in stochastic optimal transport and volatility calibration.
|
|