Five metrics that matter

Quant Science’s checklist was published as a multi‑tweet unroll (9 tweets) and archived on ThreadReader on Feb. 16, presenting a compact operational checklist for converting backtests into live systems. (threadreaderapp.com) The account behind the thread runs an algorithmic‑trading education product and a “Hedge Fund in a Box” toolkit, framing the metric guidance toward retail quants and course participants. (quantscience.io) The Calmar (MAR) ratio referenced in the thread was created by Terry W. Young in 1991 and is computed as annualized return divided by maximum drawdown, making it a direct return‑per‑downside‑risk measure. (en.wikipedia.org) Broker and platform research groups likewise emphasise drawdown‑centric metrics over volatility‑only measures; Interactive Brokers’ IBKR Quant guides and recent platform articles promote Calmar/MAR and drawdown diagnostics for risk‑aware strategy selection. (interactivebrokers.com) Trading terminals and community guides now surface recovery and drawdown diagnostics in standard reports — MetaTrader’s updated reporting adds max‑drawdown and recovery‑factor checks, and advanced metric guides routinely include Calmar, SQN, and Sortino alongside Sharpe. (mql5.com (algostrategyanalyzer.com) Market practitioners and prop‑firm trackers document that account kills are overwhelmingly triggered by drawdown breaches, with multiple sources estimating 80–90% fail rates on initial prop challenges and daily/trailing drawdown caps (e.g., 4–5% daily limits) being common. (damnpropfirms.com (investetica.net) Common practitioner thresholds cited across industry writeups include targeting max drawdowns below ~20%, profit factors >1.75, and Calmar/MAR above 1 as sanity checks, while robustness workstreams emphasise walk‑forward validation and Monte‑Carlo drawdown simulations implemented in backtesting suites. (luxalgo.com (quantifiedstrategies.com)