Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

Gili Rosenberg, Poya Haghnegahdar, Phil Goddard, Peter Carr, Kesheng Wu and Marcos L\'opez de Prado

Papers from arXiv.org

Abstract: 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.

Date: 2015-08, Revised 2016-08
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Published in IEEE Journal of Selected Topics in Signal Processing (JSTSP), Volume 10, Issue 6, 2016, and Proc. of the 8th Workshop on High Performance Computational Finance (WHPCF), p. 7, ACM, 2015

Downloads: (external link)
http://arxiv.org/pdf/1508.06182 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1508.06182

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().