Quantum Computing in Asset Allocation

Quantum Computing in Asset Allocation

Author Name : Suresh Chandra Thakur

ABSTRACT The integration of quantum computing in asset allocation represents a transformative leap in financial modeling and decision-making. Quantum computing, with its ability to process vast amounts of data simultaneously through quantum bits (qubits), offers the potential to solve complex optimization problems that classical computing struggles to handle efficiently. In asset allocation, where decision-making involves balancing risk and return across a variety of assets, quantum algorithms can accelerate the search for optimal portfolios, enhance risk management, and provide more precise predictions in highly volatile markets. This paper explores the theoretical foundations of quantum computing, its application to asset allocation strategies, and the potential impact on modern finance. We examine the advantages of quantum computing in portfolio optimization, pricing derivatives, and improving the accuracy of financial forecasts, alongside the challenges in implementing quantum solutions in real-world financial markets. By investigating the future possibilities and limitations, this paper aims to contribute to the growing body of research in quantum finance and its practical application in asset allocation.