Machine Learning for Finance Reading Group Series

This series of reading groups will go over material covering different aspects of machine learning and AI in algorithmic trading and quantitative finance. The reading group is organised by Matthias Qian and Jan Calliess. Please mail Matthias to join the mail-list. The reading group is from 11 to 12 am on Friday during term time, at the lecture theatre of the Oxford Man Institute of Quantitative Finance, Eagle House.

MICHAELMAS 2019

We will continue to read research papers.

• 18 October: G. Ban, N. El-Karoui and A. Lim: "Machine learning and portfolio optimization"
• 25 October '19 Elmachtoub et. al. "Smart predict then optimize", 2019
• 1 Nov. '19 No reading required (presentation). Richard Spady and Sami Stouli "Gaussian Transformations, Recursive Learning, and the Maximum Likelihood Estimation of Conditional Distribution Functions", 2019
• 8 Nov. '19 Ke et. al. "Predicting Returns with Text Data", 2019

HILARY 2019

We will be reading research papers now. The papers for each week, along with the dates of the reading group, will always be available here in advance.

• 13 February: S. Gu, B. Kelly and D. Xiu "Empirical Asset Pricing via Machine Learning", 2018
• 20 February: Feng et. al., "Deep Learning Asset Pricing", 2019
• 27 February: Xing Yan et. al., "Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning", NIPS 2018
• 6 March: Introduction to DMD and Koopman Operators. No reading required. Tutorial (optional reading).
• 13 March: J. Mann and J. N. Kutz, "Dynamic Mode Decomposition for Financial Trading Strategies", arXiv:1508.04487v1, 2015.

MICHAELMAS 2018

We kick off the series covering the material presented in the following book: Algorithmic Trading: Winning Strategies and their Rationale by Ernest P. Chan, Wiley. We will cover one chapter per session. The discussion of each chapter will be let by a course member each week. Furthermore, code examples and application of the methods to data will be presented.

The book can be read online via the Bodleian. Slides and codes examples for past sessions (created by the group members) can be found here:

• Chapter 1 (Introduction and Basics): Slides
• Chapter 2 (Basics of Mean Reversion): Slides;
• code archive.
• Chapter 4 (Mean Reversion of ETFs): Slides;
• Chapter 5 : Slides.