Term Explainers — The vocabulary of algorithmic trading is precise — and the details matter. These explainers go beyond surface definitions to cover the mechanics, edge cases, and implementation implications of the terms, concepts, and market structures that serious systematic traders work with every day.
How-To Guides — Step-by-step technical guides for building, testing, and deploying algorithmic trading systems. Each piece goes from concept to working implementation — covering code, infrastructure, execution, and the failure modes you'll hit before you go live.
Market Events & News — Real-time and in-depth coverage of macro events, market-structure shifts, and regulatory developments — filtered through one lens: what it means for systematic and algorithmic traders. No noise, no narrative filler. Just the signal that affects your models, your execution, and your edge.
New Investing Vehicles — Markets keep minting new instruments — ETFs, tokenized assets, volatility products, structured notes, and derivatives with genuinely novel payoff profiles. This category covers what they are, how they're built, and — critically — whether and how they can be traded algorithmically. No hype cycles, no surface-level overviews: just mechanics, liquidity realities, and implementation edge.
AI & Machine Learning in Trading — Machine learning and AI aren't magic — but applied correctly, they're a genuine edge. This category covers how to integrate AI into systematic trading workflows: from model selection and feature engineering to live deployment, overfitting traps, and knowing when a neural net is worse than a linear regression. Practical, code-grounded, and built for traders who want results, not research paper summaries.
Position Sizing Explainers — Position sizing is where strategy theory meets capital survival. This category breaks down the mechanics of how to size trades, allocate risk, and scale positions across instruments and regimes — from Kelly-based frameworks and volatility targeting to portfolio-level allocation logic. Built for systematic traders who want the math, the edge cases, and the implementation detail, not a rulebook.
Trade Recaps — Post-mortem analysis of real algorithmic trades and strategy runs — what the setup was, what happened, and what the data actually says about it. No cherry-picking, no hindsight heroics: just honest breakdowns of execution, slippage, signal behaviour, and P&L attribution that help you build better systems.