Desire To Trade (Etienne Crete)

Why I Trade 25 Strategies After 17 Years of Trading (Dave Mabe)

Dave Mabe, a veteran day trader with roughly two decades of experience, explains why he now operates 25 fully automated strategies every market day. After an early career of swing and discretionary trading, he transitioned to systematic approaches, recognizing that intuition often masks underlying, codifiable rules. By gradually automating components—position sizing, entry signals, and exit orders—he eliminated the human tendency to make costly split‑second decisions. Mabe emphasizes that discretionary traders are a fertile source of systematic ideas, provided they can discern which tactics are modelable. A pivotal moment came when his first backtest outperformed his manual process, proving that simple code could capture the same edge more consistently. He also highlights the importance of rigorous back‑testing, data reconciliation, and incremental live deployment, warning against over‑optimistic equity curves and premature scaling. Illustrative anecdotes include a mentor’s rule to skip low‑volume trades—an intuitive filter that became a quantifiable parameter—and the modern advantage of large language models like ChatGPT, which lower the coding barrier for aspiring systematic traders. Yet Mabe cautions that while LLMs accelerate development, disciplined paper‑trading, small‑size live trials, and continuous variance monitoring are indispensable. For the broader trading community, Mabe’s journey underscores a hybrid model: retain discretionary insight while systematically extracting repeatable patterns. The accessibility of AI‑driven coding tools democratizes algorithmic trading, but success still hinges on methodical testing, realistic expectations, and a patient, iterative rollout strategy.