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University of Waterloo / Borealis AI Machine Learning and Finance Reading Group

Organizer: Peter Forsyth Jr.

Mailing List

Winter 2024

The reading group is on hiatus this term.

Presentations (Fall 2023)

Co-organizer: Martin

Modified format: 20 minute talk. 10 minutes of discussion.

Book: Advances in Financial Machine Learning

Date Presenter Topic Slides (Optional)
3 October 2023 Martin Chapters 1-2: Financial ML as a distinct subject. Financial data structures. Slides
10 October 2023 Martin Chapters 3,4: Labelling. Sample weights. Slides
24 Octover 2023 Tristan Chapters 6, 8: Ensemble methods. Feature importance. Slides
31 October 2023 Alex Chapters 7, 9: Cross-validation in finance. Hyper-parameter tuning with cross-validation. Slides
7 November 2023 Serena Chapters 11, 14: Backtesting 1/3. The dangers of backtesting. Backtest statistics. Slides
21 November 2023 Eric Chapters 10, 12, 13. Slides
28 November 2023 Alexey Chapters 15, 16 Slides
5 December 2023 Cynthia Chapters 17, 18, 19: Useful features: Structural breaks. Entropy features. Microstructural features. Slides
12 December 2023 Kry Chapter 5: Fractionaly Differentiated Features Slides

Presentations (Summer 2023)

Theme: Large Language Models

Date Presenter Topic Location (May change) Slides (Optional)
4 July 2023 Organization Webex
18 July 2023 Wenjie Zi Introduction to LLMs Webex Slides
15 August 2023 Peter Forsyth Generative AI at Work Webex Slides
29 August 2023 Hanieh, Jacey, Lorne Taming the Jargon: How LLMs transform financial conversations into insights Webex
12 September 2023 Eric Jiawei He Paper 1, Paper 2 Webex Slides

Presentations (Winter 2023)

Date Presenter Topic Location (May change) Slides (Optional)
7 February 2023 Organization Webex
21 February 2023 Raquel Aoki Intro to Causality for ML Finance Webex Slides
7 March 2023 Tristan Sylvain Scaleformer Iterative Multi-scale Refining Transformers for Time Series Forecasting Webex Slides
21 March 2023 Andrew Na GANS for Volatility Surfaces Webex Slides
4 April 2023 Francis Duplessis Next Generation Language Models and an open discussion of their uses in finance Webex Slides
18 April 2023 Marc Andre Chen and Mohammed Shirazi Determining an Optimal Dynamic Allocation/ Decumulation Strategy Using NNs Webex Slides

Presentations (Fall 2022)

Topic: Open

Date Presenter Topic Location (May change) Slides (Optional)
27 September 2022 Organization Webex
11 October 2022 Yuying Li Optimal dynamic allocation without dynamic programming Webex Slides
25 October 2022 Mohamed Ahmed Monotone neural networks Webex Slides
8 November 2022 Chendi Investment under high inflation Webex Slides
22 November 2022 Frédéric Godin Bridging the gap between reinforcement learning and extreme value theory (Abstract) Webex Slides
13 December 2022 Peter ML for credit Webex Slides

Presentations (Summer 2022)

Topic: Deep Hedging

Date Presenter Topic Location (May change) Slides (Optional)
7 June 2022 Organization Webex
21 June 2022 Finhub Deep theta and gamma hedging Webex Slides
5 July 2022 Frédéric Godin Equal risk option pricing with deep reinforcement learning Webex Slides
19 July 2022 Peter Transaction costs in deep hedging Webex Slides Video
2 August 2022 Alexey Robust deep hedging Webex Slides
16 August 2022 Martin Do differentiable simulators give better policy gradients? Webex Slides

Presentations (Winter 2022)

Topic: The Retail investor

Date Presenter Topic Location (May change) Slides (Optional)
25 January 2022 Organization Webex
8 February 2022 Peter Defined Contribution Pension Plans Webex Slides Video
22 February 2022 Francis Neural Portfolio Optimization Webex Slides
8 March 2022 Muhammed Tontines Webex Slides
22 March 2022 Alexey Annuties Webex Slides
5 April 2022 Dan Goal-based Wealth Management Webex Slides
19 April 2022 Graham The retail landscape: asset managers, taxes & the investor life cycle Webex Slides

Possible Papers:

Finance

ML Finance

ML

Presentations (Fall 2021)

Topic: Generation of Synthetic Financial Data

Date Presenter Topic Location (May change) Slides (Optional)
14 September 2021 Organization Webex
28 September 2021 Chendi Bootstrap Methods in Quantiative Finance Webex Slides
12 October 2021 Dan Quant GANS Webex Slides
26 October 2021 Talk by John Hull See link
2 November 2021 Ben Evaluation of Deep Generative Models Webex Slides
9 November 2021 Anderson VAE for Volatility Surfaces Webex Slides
23 November 2021 Marc Clustering Market Regimes Using the Wasserstein Distance Webex Slides
7 December 2021 Qinglan Generating Realistic Stock Market Order Streams Webex Slides

Presentations (Summer 2021)

Text: Griewank, Andreas, and Andrea Walther. Evaluating derivatives: principles and techniques of algorithmic differentiation. Society for Industrial and Applied Mathematics, 2008.

Date Presenter Topic Location (May change) Slides (Optional)
25 May 2021 Organization Zoom
1 June 2021 Peter Chapter 1-2 Zoom Slides Video
15 June 2021 Francis Chapter 3 Zoom Slides
29 June 2021 Dan Chapter 4 Zoom Slides
13 July 2021 Shenghao Chapter 5 Zoom Slides
27 July 2021 Chendi Luca Capriotti, "Fast Greeks by algorithmic differentiation" Journal of Computational Finance Vol 14 (2011) 3-35 Zoom Slides

Presentations (Winter 2021)

Date Presenter Topic Location (May change) Slides (Optional)
26 January 2021 Organization
9 February 2021 Dan Autoregressive Convolutional Neural Networks for Asynchronous Time Series Zoom Slides
23 February 2021 Michael A neural network-based framework for financial model calibration Zoom Slides
23 March 2021 Chendi The Market Generator Zoom Slides
6 April 2021 Francis The Deep Parametric PDE Method: Application to Option Pricing Zoom Slides
13 April 2021 Ashish TF Quant Finance Zoom

Presentations (Fall 2020)

Date Presenter Topic Location (May change) Slides (Optional)
6 October 2020 Andrew A summary of Machine learning in Option Pricing on arxiv Zoom Slides Table
20 October 2020 Chendi A summary of Machine learning in Wealth Management on arxiv Zoom Slides
3 November 2020 Pablo AlphaPorfolio for Investment and economically Interpretable AI Zoom Slides
17 November 2020 Peter Neural Importance Sampling Zoom Slides
1 December 2020 Pieter Factor Investing: a Short Overview of the Research Over the Last 10 Years Zoom Slides

Presentations (Summer 2020)

Date Presenter Topic Location (May change) Slides (Optional)
9 June 2020 Giuseppe Smooth Market Games Zoom Slides
23 June 2020 Francis Empirical Asset Pricing via Machine Learning Zoom Slides
7 July 2020 Irene Deep Learning for Portfolio Optimisation Zoom Slides
21 July 2020 Andrew A mean-field analysis of two-player zero-sum games Zoom Slides
4 August 2020 Chendi Data-driven approach to asset allocation with tax Zoom Slides
18 August 2020 Pieter Factor Investing Zoom Slides

Presentations (Winter 2020)

Date Topic Presenter Location (May change) Slides (Optional)
13 January 2020 Organization N/A University of Waterloo (DC2102)
27 January 2020 Option Data Augmentation Using the SABR model and LVF Nick Unveristy of Waterloo (DC2310) Slides
10 February 2020 Stochastic Portfolio Theory: A Machine Learning Perspective Chendi University of Waterloo (DC2310) Slides
24 February 2020 Meta-learning for Optimization Pascal Borealis AI Slides
9 March 2020 The Distribution of Terminal Wealth Under Dynamic Mean-Variance Optimal Investment Strategies Pieter University of Waterloo (DC2310) Slides
23 March 2020 A deep learning approach for computations of exposure profiles for high-dimensional Bermudan options Peter Zoom Slides
6 April 2020 Option pricing with residual networks (paper) Andrew Zoom Slides

Presentations (Fall 2019)

Date Topic Presenter Location (May change) Slides (Optional)
10 September 2019 Organization N/A University of Waterloo (DC2102)
24 September 2019 Deep Hedging Ad Tayal Borealis AI Slides
8 October 2019 Data-Driven Model for Hedging (Paper1, Paper2, Paper3) Ke Nian University of Waterloo (DC1304) Slides
22 October 2019 Option Pricing with Machine Learning (Paper1, Paper2) Peter Borealis AI Slides
5 November 2019 A Neural Network Approach to Optimal Asset Allocation With Stochastic Benchmark Targets Chendi University of Waterloo (DC1304) Slides
12 November 2019 Universal features of price formation in financial markets: perspectives from Deep Learning Dan University of Waterloo (DC3317) Slides
19 November 2019 Neural Network Optimal Asset Allocation: Put Writing and Trend Following Strategy Bo University of Waterloo (DC3317) Slides
26 November 2019 Stock Movement Prediction from Tweets and Historical Prices Kshitij Borealis AI Slides
3 December 2019 Generative Adversarial Nets for Financial Trading Strategies (Paper) Andrew University of Waterloo (DC3317) (Special time: 11:00am) Slides
10 December 2019 Machine Learning for XVA (Paper) Jakub University of Waterloo (DC3317)
17 December 2019 Enhancing Time Series Momentum Strategies Using Deep Neural Networks and Optimal Trend Following Trading Rules Irene Borealis AI Slides

Time

12:00 Noon.

Format

  • Select an interesting paper applying machine learning techniques to finance. Email Peter the name of your paper one week in advance.

  • Present a summary of the paper.

  • Be sure to include necessary background. It is preferable to spend time explaining things you think are obvious than to risk the audience not understanding your presentation

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