Kris from Robot Wealth writes about building and running systematic trading strategies, drawing on live trading experience and research. Issues cover mechanism-first strategy design, statistical arbitrage details, and lessons on judgment and trading operations.

Engineering notes from building a live algorithmic trading system in Elixir, covering production failures and design decisions such as token stores, rate limiting, account state and portfolio risk. Each post explains what was chosen, why it was enough, and what it cost.

A daily pre-market brief that picks five verified signals, mostly recent quant finance and machine learning preprints plus market data, and labels each as fact, inference or uncertainty. It also draws out implications for volatility, execution, factors and MATLAB implementation.

Technical newsletter on quantitative trading research, covering event-driven strategies, macroeconomic signal construction, and hypothesis testing frameworks, often with code. Readers get structured, methodology-focused lessons on avoiding look-ahead bias, defining signals, and validating trading ideas.