TY - GEN
T1 - Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer
AU - Rosenberg, Gili
AU - Haghnegahdar, Poya
AU - Goddard, Phil
AU - Carr, Peter
AU - Wu, Kesheng
AU - De Prado, Marcos López
PY - 2015/11/15
Y1 - 2015/11/15
N2 - We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a for- mulation of the problem, discuss several possible integer en- coding 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 port- folio 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 technol- ogy 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.
AB - We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a for- mulation of the problem, discuss several possible integer en- coding 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 port- folio 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 technol- ogy 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.
KW - Optimal trading trajectory
KW - Portfolio optimization
KW - Quantum annealing
UR - http://www.scopus.com/inward/record.url?scp=84959320086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959320086&partnerID=8YFLogxK
U2 - 10.1145/2830556.2830563
DO - 10.1145/2830556.2830563
M3 - Conference contribution
AN - SCOPUS:84959320086
T3 - Proceedings of WHPCF 2015: 8th Workshop on High Performance Computational Finance - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis
BT - Proceedings of WHPCF 2015
PB - Association for Computing Machinery, Inc
T2 - 8th Workshop on High Performance Computational Finance, WHPCF 2015
Y2 - 15 November 2015 through 20 November 2015
ER -