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This paper introduces TradeLens, a trace-grounded diagnostic toolkit for evaluating whether LLM-based agentic trading systems convert their reasoning and tool-use costs into measurable incremental profit, analyzing failure patterns across models like DeepSeek-V3.2 and GLM-4.7.
A comprehensive guide explaining the Kalman filter and its application in building smarter trading systems, including mathematical foundations and production-grade examples.