Future Improvements

• Complete the quantum computing modules. quantum_portfolio_optimize (in quant/portfolio_optimization.py) and quantum_amplitude_estimation_call (in quant/option_pricing.py) are scaffolded with the correct QUBO and circuit framing, but still need to run against real IBM Quantum hardware access through Qiskit.
• True live stock data. Currently near real-time through yfinance polling; a future version could add a genuine streaming feed via a paid provider such as Polygon.io, IEX Cloud, or Finnhub, enabling sub-second updates.
• Deploy the standalone AI backend. ai_assistant/server/app.py is a structurally complete Flask server built for a future deployment outside Streamlit, for example a custom chat widget on this site talking to its own hosted backend. The Streamlit dashboard's built-in AI tab remains the primary, fully working version for now.
• Expand automated testing. The calculation layer is manually regression-tested against known values; a proper test suite built with pytest would formalize that process.
• More novel visualizations, in the same spirit as the Sankey money-flow diagram and the diagnostic radar chart already built.