Strategy Engine
Turning nuanced, natural-language trading observations into structured decision logic.
Matched 5 of 6 conditions in Rule #47.
The engine evaluates a structured set of market conditions against an evolving rule library rather than relying entirely on memory.
Expert observations are useful — until there are too many to remember.
Trading rules often start as nuanced observations involving multiple indicators, session behavior, candlestick features, recent momentum, and exceptions.
Turn observations into structured conditions.
The application models those observations as rules and checks current inputs against the rule library.
Market conditions
Price + sessions + indicators + candle characteristics + recent behavior
Rule match
Result + confidence + explanation
The same problem exists in many industries.
Expertise is often stored as unwritten conditional logic. If your team says “it depends” a lot, there may be a decision framework worth structuring.
Candidate evaluation
Experience + skills + salary + interview score → next-step recommendation.
Vendor selection
Weighted criteria + constraints → consistent comparison.
Readiness assessment
Competencies + evidence + thresholds → structured decision support.
This case study demonstrates software design and decision-logic structuring. It is not trading advice or a representation of investment performance.