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Brad was good enough to join us on the Quant Cartel a couple of weeks back, and the value he imparted on the group was invaluable.
As background, Brad transitioned from a 25-year career in IT to trading in 2020, leveraging his analytical skills and understanding of complex systems to spot trading opportunities. His strategy centers on identifying news catalysts that move individual stocks, using a proprietary platform for order flow analysis and execution. Over the past two years, Brad has broadened his approach by developing algorithmic trading systems for indexes like the ASX200, UK100, and SP500. He operates three main strategies: two based on momentum and catalysts, and one on mean reversion. This automation has significantly increased his trading efficiency and diversified his opportunities without increasing his workload.
Brad has also been good enough to provide some resources which he believes, will significantly turbocharge the learning curve of an aspiring algorithmic trader. I hope you find these helpful.
Here are the Slides Brad put together to help us with the basics of Algorithmic Trading:
Here is Brad’s curated list of links which he believes are most helpful for Beginners:
Comprehensive online training course - https://www.coursera.org/learn/algorithms-part1
I have always liked “Brilliant” for online learning, lees comprehensive than the Princeton course but could be a great starting point for beginners -
https://brilliant.org/courses/thinking-in-code/?from_llp=computer-science
https://brilliant.org/courses/programming-python/?from_llp=computer-science
Here are the best books I have read that give both the fundamental makeup of markets and the coding aspects, both of which are required to write profitable algos -
Algorithmic Trading and DMA: An Introduction to Direct Access Trading Strategies - https://amzn.asia/d/csEOYwv
Trading and Exchanges: Market Microstructure for Practitioners - https://amzn.asia/d/bfAu6cR
Kaufman Constructs Trading Systems - https://amzn.asia/d/2kr5IPw
Algorithms Illuminated - https://amzn.asia/d/7scOzGW (Author has some good videos available here - https://algorithmsilluminated.org/)
So you're not re-inventing the wheel, this article has some great links to some Python libraries that will assist with sourcing data, code for indicators and backtesting engines, the author has also provided a brief review of each resource - https://www.qmr.ai/best-python-libraries-for-trading/
On the same theme of not doing everything from scratch, the Quantconnect platform is a great turnkey type platform that can be used to develop, backtest and forward trade strategies. It is a paid service however should be considered as it lowers the barrier to entry - https://www.quantconnect.com/
Finally, here are some youtube channels that I feel offer value -
Kevin Davey (generalised algo trading) - https://www.youtube.com/@AlgoTradingWithKevinDavey
sentdex (Python programming) - https://www.youtube.com/@sentdex
Part Time Larry (algo trading with an AI flavour) - https://www.youtube.com/@parttimelarry/videos
SMB Capital (Prop firm that delivers great content for idea generation) - https://www.youtube.com/@smbcapital
Related Reads:
If you’re a Sophisticated Investor, I recommend checking out Trade Nation, who have been massive supporters of what I’m trying to do with improving the financial outcomes and risk management strategies of CFD traders through using Data and Statistics.
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