I built a 9-stage ML pipeline that turns Reddit into timestamped options signals (github.com)

Matthew Charles Busel has introduced a groundbreaking real-time financial intelligence platform called ROT (Reddit Options Trader), which leverages social media discourse from Reddit and over 15 other sources to generate timestamped options trade signals. This system employs a sophisticated 9-stage machine learning pipeline that includes a custom-built natural language processing (NLP) engine and a dual-layer credibility scoring architecture. It provides users with structured trade ideas, complete with confidence scores and risk annotations, making it a significant tool for quantitative analysts and ML engineers seeking actionable insights from social media sentiment. What's particularly noteworthy about ROT is its comprehensive approach to processing unstructured data, where each stage of the pipeline is interdependent and conditioned on the data integrity of previous stages. The NLP section executes ten passes to analyze sentiments, while advanced features are extracted for credibility scoring through a GradientBoosting model trained on historical outcomes to minimize bias. Additionally, the platform mitigates common pitfalls in trading algorithms, such as false signals from sarcastic comments and the volatility environment of options strategies, ensuring that the trades suggested align well with current market conditions. This innovative combination of AI techniques represents a significant advancement in the use of social media sentiment for financial trading, potentially transforming how options traders leverage real-time data.