← Laboratory Experiment

Alpha Signals

FlaskReactLLM Integration

Objective

To augment traditional technical analysis with semantic intelligence. This project integrates real-time market data with LLM-driven sentiment analysis to provide a multidimensional view of portfolio health.

Architecture

The system operates on a lightweight, decoupled stack:

  1. Backend (Flask):
    • Handles secure API connections to brokerage accounts.
    • Aggregates price action and news feeds.
    • Pre-processes textual data for context optimization.
  2. Intelligence Layer:
    • Feeds sanitized market news into an LLM context window.
    • Generates concise “Bull/Bear” sentiment scores and risk summaries.
  3. Frontend (React):
    • renders a clean, component-based dashboard.
    • Visualizes P&L velocity and exposure in real-time.

Utility

Unlike standard trading terminals which flood the user with raw data, Alpha Signals focuses on synthesis—reducing information overload by highlighting only significant deviations and narrative shifts affecting held assets.