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Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

delete2016-09-01
delete127
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OA
AI
P
Peter Carr
K
Kesheng Wu
M
Marcos López de Prado
DOI:10.1109/JSTSP.2016.2574703delete
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摘要

摘要

En 中文
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.
Keyword:
Optimal trading trajectory
portfolio optimization
quantum annealing

期刊

IEEE Journal of Selected Topics in Signal Processing 封面图
IEEE Journal of Selected Topics in Signal Processing
IF:
13.7
论文数:
1.9K
被引数:
1.1W

机构

N
New York University
学者数:
4.4W
论文数: 3.9W
被引数: 5.8W
G
guggenheim partners, llc
学者数:
2
论文数: 3
被引数: 0
L
Lawrence Berkeley National Laboratory
学者数:
1.5W
论文数: 1.1W
被引数: 6.1W
U
united states department of energy (doe)
学者数:
11.3W
论文数: 9.6W
被引数: 246
U
University of British Columbia
学者数:
7.0W
论文数: 6.1W
被引数: 8.6W
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