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Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer by Gili Rosenberg; Poya Haghnegahdar; Phil Goddard; Peter Carr; Kesheng Wu; Marcos López de Prado is a scholarly article available to read on EtoBox.

What is Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer about?

We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and temporary market impact), and, significantly, the solution does not require the inversion of a covariance matrix. The discrete multi-period portfolio optimization problem we solve is significantly harder than the continuous variable problem. We present insight into how results may be improved using suitable software enhancements, and why current quantum annealing technology limits the size of problem that can be successfully solved today. The formulation presented is specifically designed to be scalable, with the expectation that as quantum annealing technology improves, larger problems will be solvable using the same techniques. ## Categories and Subject Descriptors [Hardware]: Emerging Technologies-quantum technologies, quantum computation, analysis and design of emerging devices and systems, emerging tools and methodologies

Author

Gili Rosenberg; Poya Haghnegahdar; Phil Goddard; Peter Carr; Kesheng Wu; Marcos López de Prado

Publisher

ACM

Published

2015

Language

EN