Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation

@article{Steinhauer2020SolvingTO,
  title={Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation},
  author={Kyle Steinhauer and Takahisa Fukadai and Shotaro Yoshida},
  journal={Bioengineering eJournal},
  year={2020}
}
We use an optimization procedure based on simulated bifurcation (SB) to solve the integer portfolio and trading trajectory problem with an unprecedented computational speed. The underlying algorithm is based on a classical description of quantum adiabatic evolutions of a network of non-linearly interacting oscillators. This formulation has already proven to beat state of the art computation times for other NP-hard problems and is expected to show similar performance for certain portfolio… 
1 Citations
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References

SHOWING 1-10 OF 44 REFERENCES
Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer
TLDR
A multi-period portfolio optimization problem using D-Wave Systems' quantum annealer is solved, and the formulation presented is specifically designed to be scalable, with the expectation that as quantumAnnealing technology improves, larger problems will be solvable using the same techniques.
An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints
TLDR
Extensions of the classical Markowitz mean-variance portfolio optimization model are studied, which considers that the expected asset returns are stochastic by introducing a probabilistic constraint, and proposes an exact solution approach, which permits to solve to optimality problems with up to 200 assets in a reasonable amount of time.
Portfolio Optimization of 40 Stocks Using the DWave Quantum Annealer
We investigate the use of quantum computers for building a portfolio out of a universe of U.S. listed, liquid equities that contains an optimal set of stocks. Starting from historical market data, we
Heuristic algorithms for the portfolio selection problem with minimum transaction lots
Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems
TLDR
Implementing SB with a field-programmable gate array, it is demonstrated that the SB machine can obtain good approximate solutions of an all-to-all connected 2000-node MAX-CUT problem in 0.5 ms, which is about 10 times faster than a state-of-the-art laser-based machine called a coherent Ising machine.
Lagrangian relaxation procedure for cardinality-constrained portfolio optimization
TLDR
The problem is formulated as a cardinality-constrained quadratic programming problem, and a dedicated Lagrangian relaxation method is developed that has been applied to track the major market indices, using real data and computational results are promising.
Computational aspects of alternative portfolio selection models in the presence of discrete asset choice constraints
TLDR
This work considers the mean-variance model of Markowitz and the construction of the risk-return efficient frontier and proposes alternative approaches for computing this frontier and provides insight into its discontinuous structure.
Selecting Portfolios with Fixed Costs and Minimum Transaction Lots
TLDR
Different mixed-integer linear programming models dealing with fixed costs and possibly minimum lots, and heuristic procedures, based on the construction and optimal solution of mixed integer subproblems, are proposed.
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
TLDR
The results show that the Digital Annealer currently exhibits a time-to-solution speedup of roughly two orders of magnitude for fully connected spin-glass problems with bimodal or Gaussian couplings, over the single-core implementations of simulated annealing and parallel tempering Monte Carlo used in this study.
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