A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Three lectures in Machine Learning in Finance
Lecture 1: Deep Learning and Equity Portfolio Modeling
This lab session shall demonstrate how deep learning can be used to model equity factors, commonly used in asset management. The emphasis shall be on interpretability, the ability of deep learning to capture non-linearities, and understanding the differences between linear models.
Lecture 2: Stochastic filtering and MCMC in finance
Description: While the focus in machine learning is on neural networks, we shall demonstrate that other algorithms can be considered in this paradigm. In particular, we shall introduce stochastic filtering and MCMC with applications to finance.
Lecture 3: Reinforcement Learning and Inverse Reinforcement Learning: simple examples and applications in Finance
Brief description: This talk will introduce Reinforcement Learning (RL) and its Inverse (IRL) and illustrate how they work on very simple simulated experiments. I will then give a short overview of applications of RL and IRL for quantitative finance.