Abundant Intelligence, Scarce Judgment
As intelligence becomes abundant, judgment becomes more scarce.
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What I Wish I’d Known About Scaling Before Building with AI
Slow backtests, blown memory, and the coding habits I wish I’d caught sooner.
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This Model Beat FanDuel AND DraftKings on NFL Totals. Then the “Best” Bets Lost Money.
A LightGBM model made money on NFL totals at both FanDuel and DraftKings. The same-side agreement filter looked stronger, but its historical edge is a lead for one locked 2026 test, not a betting strategy.
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Two MLB Betting Models Made Money. That Was Not Enough.
Two MLB models were profitable in a corrected 2022–2025 backtest. That is a lead worth following, not proof of an edge. Their plausible profit ranges still included losses, so the right next move is one locked-down test on new games, not another model sweep, and not capital.
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Deconstructing a Failed Strategy: Was Anything Worth Saving?
A strategy redesign looked dramatically better in sample. A 2022 out-of-sample test exposed the hidden leverage, and the strategy was rejected before the final holdout.
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Why the Best Backtest Metric Might Be the Wrong Optimizer Target
A walkforward optimizer objective test using geometric Martin as the out-of-sample path-quality judge.
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Before alpha, there must be trust
The first job of a serious research system is not to find alpha. It is to create the infrastructure where alpha can be trusted.
READ MORE →I haven't been absent. I've been building.
Three systems, one thesis: reliable judgment requires infrastructure.
READ MORE →Retail quant finance is a never-ending cycle of tutorials and Jupyter notebooks.
The notebook taught you theory, but not how to deploy.
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AWSCloud
AWS Trading Part 2 - The Strategy
The code and diagrams for the strategy can be found on github. AWS Trading Part 2 Youtube video is here. Introduction In part 1 youtube video link we covered the data pipeline portion of the AWS trading bot architecture. I demonstrated how to set up your AWS environment, including creating a simple dynamoDB database to hold our price and strategy data. Then we walked through the data pipeline code in detail including how to grab the data and populate our db with it. In this post we’ll cover t
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AutomationCloud
New YouTube Series Launched: Building Your AWS Trading Data Pipeline!
I just published Part 1 of my new YouTube series, and I'm excited to share it with you all! After my recent post about automating trading strategies with AWS Cloud, many of you asked for a deeper dive into the technical implementation. Well, here it is! What's in Part 1? In this first video, we're tackling the foundation: configuring your AWS data pipeline and writing the Python code to make it all work. I walk through the exact steps I use in my own automated trading system, showing you how
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