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A project making use of the Variational Quantum Eigensolver ( VQE ) and Quantum Approximate Optimization Algorithms ( QAOA ) in qiskit to optimize an endowment portfolio, with weights defined by risk-parity analysis..

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anishrverma/Hybrid-Quantum-Endowment-Portfolio-Optimization

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Hybrid Quantum Portfolio Optimization

Endowment Portfolio Analysis

This repository utilizes gate model quantum computing, making use of the qiskit framework, to analyze an endowment portfolio.

The problem is cast as a Quadratic Unconstrained Binary Optimization (QUBO) problem, which takes into account the yield of the portfolio and the risk / relationship between asset returns, with a budget constraint.

This qubo is solved by the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA), to select the best $B$ assets from a total of $n$ assets.

From here, risk-parity analysis is used to weight the assets in the portfolio. An extension of this work could explore developing the QUBO to include transaction costs, a more sophisticated measure of risk, etc.

For a thorough explanation, please see the contents of the 'presentations' directory.

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A project making use of the Variational Quantum Eigensolver ( VQE ) and Quantum Approximate Optimization Algorithms ( QAOA ) in qiskit to optimize an endowment portfolio, with weights defined by risk-parity analysis..

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