Tradologics is proud to have hosted the AlgoTrading Summit 💜
This repository contains link to videos of the 2021 AlgoTrading Summit talks, along with slides and code made available by the speakers.
📺 Watch all the videos (YouTube playlist)
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NOTE: We've made available the slides and code that were given to us by the speakers. If there's no link to download the slides and/or code for a talk - it was not provided to us (yet) by the speaker.
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If investment is a process, then automation is the only logical conclusion. In this session Laurent will explain why short-selling is the key to raising AUM, and how to generate more Long/Short ideas than you will ever have capital to allocate.
Laurent Bernut, 20+ Years Long/Short, Short-Seller expert, and Algorithmic Trader
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In this presentation, based on The Book of Alternative Data, we will introduce the topic of alternative data and how it can be used by investors. We show specific use cases where it can be used by traders in markets including FX.
Saeed Amen, Founder at Cuemacro, Author, Visiting Lecturer at QMUL
Video | Twitter | LinkedIn | Website
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Traditional factor model is based on linear regression, with all its attendant shortcomings. The machine learning technique of feature selection can take into account nonlinearity, collinearity, and interdependence of such factors in returns prediction or attribution.
Ernest Chan, CEO at PredictNow.ai, Managing Member of QTS Capital Management
Video | Slides | Twitter | LinkedIn | Website
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The session will cover the various important aspects of building & running a HFT setup, and the potential sources of alpha for such strategies.
Nitesh Khandelwal, CEO & Co-Founder at QuantInsti, Partner & Co-founder at iRage
Video | Slides | Twitter | LinkedIn | Website
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In this talk, we'll be building a simple machine learning model to trade the "buy low sell high" daily strategy, and use tools like Jupyter Lab to backtest our strategy using Python.
Dr. Hui Liu, Creator of IBridgePy & CEO of Running River Investment LLC. BS, MS, Phd and MBA
Video | Slides | Code | LinkedIn | Website
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Overview of the importance of working with real data... and real data is not clean
Chris Bartlett, CEO @ AlgoSeek
Video | Slides | Twitter | LinkedIn | Website
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In this session we'll talk about how to build better-factor, smart-beta portfolios using Hierarchical Risk Parity Algorithm. We'll also take a look at how fundamental data is used to filter-out the stock universe to replicate specific factors, and how to mix various factors inside of one portfolio using ML allocation techniques.
Alexandr Proskurin, CIO at Principia Invest, Head of Consulting at Hudson and Thames
Video | Slides | Twitter | LinkedIn | Website
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Discussion of the elements of price action, including direction, volatility/range, and trend, as well as go over the metrics/ways to measure and categorize these factors - and their practical implications on trading strategies
Brian Blandin, Co-Founder at Markets Science, Writer @ Quantfiction
Video | Slides | Code | Twitter | LinkedIn | Website
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Is the drawdown a useful statistic for risk scaling?
Robert Carver, Independent futures trader and Best-selling author
Video | Slides | Code | Twitter | LinkedIn | Website
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Christina started Domeyard, a hedge fund focused on HFT, almost 10 years ago. In this rapid-fire talk, Christina will open up about her biggest mistakes and lessons learned from fundraising, to hiring, to building strategies, to launching the fund.
Christina Qi, CEO of Databento, Founding Partner of Domeyard LP, Forbes 30 Under 30
Video | Twitter | LinkedIn | Website
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In this presentation, based on The Book of Alternative Data, we will introduce the topic of alternative data and how it can be used by investors. We show specific use cases where it can be used by traders in markets including FX.
Illya Barziy, Quantitatve Research Lead @ Hudson & Thames
Video | Slides | Twitter | LinkedIn | Website
Get the books written by the speakers on Amazon (not an affiliate link).