A Comparison of Reinforcement Learning and Deep Trajectory Based Stochastic Control Agents for Stepwise Mean-Variance Hedging

no code implementations • 16 Feb 2023 • Ali Fathi, Bernhard Hientzsch

We consider two data-driven approaches to hedging, Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective.

Adversarial Attacks on Deep Algorithmic Trading Policies

no code implementations • 22 Oct 2020 • Yaser Faghan, Nancirose Piazza, Vahid Behzadan, Ali Fathi

Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies.

Algorithmic Trading reinforcement-learning +1

PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards

1 code implementation • 24 Aug 2020 • Masoud Hashemi, Ali Fathi

We propose a model criticism and explanation framework based on adversarially generated counterfactual examples for tabular data.

Adversarial Attack BIG-bench Machine Learning +2

Machine Learning for Yield Curve Feature Extraction: Application to Illiquid Corporate Bonds (Preliminary Draft)

no code implementations • 5 Jun 2018 • Greg Kirczenow, Ali Fathi, Matt Davison

This paper studies the application of machine learning in extracting the market implied features from historical risk neutral corporate bond yields.

BIG-bench Machine Learning Denoising