A Decision Trace Must Distinguish False From Missing
A dashboard says WAIT. Was the spread check false, or did the engine never receive a spread observation? Those are different failures to investigate. A trace that turns both into an empty cell loses the distinction before debugging starts. A current discussion about trading-engine decision traces asks which evidence belongs beside a score and decision. My answer starts with a small requirement:…
The article discusses the importance of distinguishing between false observations and missing data in decision traces for trading engines. It emphasizes the need to preserve inputs that actually existed at decision time, including explicit false values, rather than treating missing data as if it were a false result. The author suggests that a system should give explicit status and reason to unavailable observations, rather than validating a boolean with if (!value).
The article also provides a code example demonstrating how to preserve and validate the necessary information for decision traces, using Node's built-in test runner.
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