Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation

Kyle Steinhauer; Sho Yoshida; Takahisa Fukadai

Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation

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arxiv 2009.08412 v1 pith:3U3N6BHZ submitted 2020-09-17 q-fin.CP q-fin.PMq-fin.RMquant-ph

Kyle Steinhauer , Takahisa Fukadai , Sho Yoshida This is my paper

classification q-fin.CPq-fin.PMq-fin.RMquant-ph

keywords portfoliotradingoptimizationproblemtrajectoryalgorithmalreadybifurcation

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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 optimization problems. Inspired by such we apply the SB approach to the portfolio integer optimization problem with quantity constraints and trading activities. We show first numerical results for portfolios of up to 1000 assets, which already confirm the power of the SB algorithm for its novel use-case as a portfolio and trading trajectory optimizer.

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Large-scale portfolio optimization with variational neural annealing
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VNA produces Sharpe-ratio-competitive portfolios on indices up to 2,008 assets, but the claimed speed advantage and universal finite-size scaling are not robustly supported.

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