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Guides to the ideas behind trading research: probability, backtesting, edge and risk. Each one shows the formulas, so you can rebuild the analysis yourself.
Foundations · 5 min read
Algorithmic trading means making trading decisions with explicit, testable rules. Here is how it works, the main strategy families, and how to start researching without writing code.
Backtesting · 6 min read
A step-by-step backtesting method, the six biases that make bad strategies look good, and the spreadsheet layout and formulas to run one honestly.
Prediction markets · 5 min read
A Kalshi contract that pays $1 trading at 62¢ implies about a 62% chance. Here is how bids, asks and multi-outcome markets turn into clean implied probabilities, with formulas.
Prediction markets · 5 min read
How to test whether prediction-market prices are well calibrated, with price bins, a reliability chart, the Brier score and the sample-size check most studies skip.
Risk and sizing · 4 min read
How to compute the expected value of a binary event contract, include fees and spreads, find your breakeven probability, and tell edge apart from variance.
Risk and sizing · 4 min read
The Kelly criterion tells you what fraction of your bankroll to risk on a bet with an edge. Here is the formula for binary event contracts, a worked example, and why fractional Kelly is the practical choice.
Using Jordan · 5 min read
A practical guide to using an AI agent that builds trading research in a spreadsheet, covering how to phrase questions, review changes, and keep the analysis auditable.
