Portfolio Optimization: Applications in Quantum Computing
Michael Marzec · 2016
This chapter demonstrates how the framework can be used to solve financial problems. It discusses the limitations of the environment with respect to financial modeling considerations. This will be accomplished by presenting the formulation of financial portfolio optimization in the context of the hardware paradigm. The chapter presents and discusses quantum computing paradigm. The research question covers three areas that are reflected in the literature: classical mean-variance portfolio theory; general operations research theory with specific consideration given to combinatorial optimization topics; and the hardware realization of adiabatic quantum computation. The chapter reviews a survey of background literature, the models used and experimental methodology. It relates the portfolio optimization representation to the graph theoretic domain and into the underlying Ising problem domain of the target hardware. Finally, it provides results to the underlying domain, along with limitations and future areas for investigation.