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Tradologics is proud to be hosting the first AlgoTrading Summit - a day packed full to discover and rediscover what is happening in algo-trading now.
If you like trading and want to get better at it, come and join like-minded traders at the event.
You will hear from some of the brightest minds in algo-trading that will bring you the latest trends on topics ranging from strategy to crypto, quant-trading, how to source data and alternative data, how to automatically act on that data, the latest in short squeeze and how to automate your entire trading workflow.
“The Algorithmic trading market size is expected to grow from $11.1 bn in 2019 to $18.8 bn by 2024”
World's famous speakers
Hours of talks and Q&A
Quant platform walkthroughs
Conference to rule them all
Introduction to the first annual Algo Trading Summit hosted by Tradologics
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.
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.
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.
The session will cover the various important aspects of building & running a HFT setup, and the potential sources of alpha for such strategies.
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.
A walkthrough of the Tradologics cloud platform, overview of features and workflow automation
Overview of the importance of working with real data... and real data is not clean
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.
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
Is the drawdown a useful statistic for risk scaling?
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.
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In this talk, Illya will review some of the roadblocks to finding rewarding pairs, introduce the Machine0Learning approach to pairs selection, and compare it to other approaches.
A walkthrough of the Tradologics cloud platform, overview of features and workflow automation
Our speakers and partners are coming from leading companies in the field!
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