In this installment of our webinar series we'll explore how techniques in Reinforcement Learning and AI can be applied to Algorithmic Trading.

We'll begin with an overview of Reinforcement Learning, covering value based and policy based methods. This will be followed by a demonstration of how this technique can be applied to market making.

Next up we'll have a presentation of Causal AI and how it can be used to find explicit cause-and-effect links and hidden signals in large amounts of data. These techniques can be applied to gain real-time predictive analytics.

Finally there will be a presentation on how PyTorch can be used to train a Deep Neural Network using technical indicators. Backtesting results from these methods will also be discussed.