Portfolio Optimization with Python and Quantum Computing Techniques

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How to optimize portfolios using quantum computing and Python, featuring QUBO conversion and QAOA solving algorithm.

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Quantum computing can be used to solve the problem of finding the optimal allocation of assets in a portfolio more efficiently and accurately than traditional methods. We will use the Qiskit library, a Python-based open-source framework for quantum computing. To illustrate, we will create a simple portfolio of four assets and use the Quantum Approximate Optimization Algorithm (QAOA)