Technical paper/Deep learning
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
The market generator
A generative neural network is proposed to create synthetic datasets that mantain the statistical properties of the original dataset
Interpretability of neural networks: a credit card default model example
Recently developed techniques aimed at answering interpretability issues in neural networks are tested and applied to a retail banking case
Optimal posting of collateral with recurrent neural networks
Pierre Henry-Labordère applies neural networks to a control problem approach for managing collateral