I build the systems, not just design them.

A full-stack quantum finance app that prices European call options and calculates Value at Risk two ways: Iterative Quantum Amplitude Estimation against classical Monte Carlo.

IQAE encodes a log-normal price distribution into quantum amplitudes and extracts expected payoff with O(1/N) convergence, a quadratic speedup over Monte Carlo's O(1/√N).

• Prices options via a 3-qubit IQAE circuit with log-normal amplitude encoding and a payoff oracle, shown side by side with a 10,000-path Monte Carlo baseline.
• Calculates portfolio VaR at 95% confidence using both methods, with live market data and volatility pulled from Yahoo Finance.
• Documents hardware constraints honestly: statevector simulation, 8 price bins, quantum advantage theoretical but the algorithm hardware-ready.

A hybrid quantum-classical optimizer that solves asset allocation as a QUBO problem: QAOA selects which stocks to hold, classical mean-variance optimization sets the weights.

QAOA builds a superposition of all 2^n possible portfolios, amplifies strong selections through cost and mixer layers tuned by COBYLA, and collapses to the optimal subset on measurement.

• Returns optimal allocation percentages with expected return, volatility, Sharpe ratio and QAOA energy, plus a view of the actual quantum circuit used.
• Offers Conservative, Balanced and Aggressive risk profiles with a GBP per-stock breakdown, backed by live Yahoo Finance data.
• Handles up to 9 assets (9 qubits) under statevector memory limits, with a glassmorphism React UI.