End-to-End Python implementation of "Reflexivity as Prompt" (Park, 2026). Evaluates LLMs as financial forecasters during boom-bust cycles using George Soros's Reflexivity Theory as a zero-shot prompt scaffold. Implements P/E-ratio-invariant normalization, buy-and-hold calibration gates, and a structured diagnostic reproducibility audit taxonomy.
python jupyter-notebook econometrics sharpe-ratio quantitative-finance reproducibility zero-shot-learning time-series-forecasting sp500 financial-forecasting large-language-models prompt-engineering behavioral-finance rolling-window llm-evaluation boom-bust-cycles market-cycles reflexivity-theory empirical-replication soros-reflexivity
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Updated
Jun 7, 2026 - Jupyter Notebook