Title: Reinforcement learning in algorithm trading using python

Speaker: Dr. Atousa Assadi Senior Quantitative Manager, CIBC

Abstract: “Deep Reinforcement Learning (RL)”, is the extension of deep learning where the objective is not only learning through examples but also learning via try and error in a wise and autonomous way. It is based on a learning process in which an agent interacts with its environment to reach a pre-defined goal in such a way that the agent can maximize the number of rewards, and minimize the penalties given by the environment for each step made by the agent. RL in finance is now considered a key aspect of several financial services and applications, including trading bot, chat bot, risk optimization in lending, portfolio management, pricing strategy, recommendation system and more. In this presentation, I talk about the concept of reinforcement learning along with some demos. The first demo is about a bot for trading application. The second demo is about sentiment analysis to take the emotional angle out of the stock market by creating a trading indicator. I demonstrate how we can define customized environment and policy from the available libraries in python.

(For further information please contact Dr. Kai Liu at kailiu@upei.ca)

Date: Monday, November 29, 3:30 pm (Atlantic Time)

Zoom Meeting Link: https://zoom.us/j/97342598765?pwd=SzNxOU0za1I4RmdSRFh0STlKN0 NtUT09

Meeting ID: 97342598765; Passcode: 316255