AIFinTechPythonLLMsAPIs

AI Stock Trading Assistant

AI-driven research tool for long-term stock/ETF analysis focused on explainability.

Problem

Traditional stock research tools overwhelm users with raw data without context. Investors need clear, explainable insights to make informed long-term decisions, especially when evaluating ETFs and individual stocks for portfolio construction.

Approach

Built an AI-powered research assistant that aggregates data from multiple financial APIs (Polygon, Tiingo, QuiverQuant) and uses LLMs to generate explainable analysis. The system creates feature vectors from financial indicators, sentiment analysis, and fundamental data, then presents findings in a structured, easy-to-understand format.

Key Features

Multi-source data aggregation, explainable AI analysis with reasoning, long-term trend identification, ETF comparison tools, sentiment analysis from news and social sources, customizable research parameters, and exportable reports.

Tech Stack

PythonReactTypeScriptTailwindFastAPIPolygonTiingoOpenAIFeature vectorsIndicatorsSentiment

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