Hybrid quantum investment optimization with minimal holding period

@article{Mugel2021HybridQI,
  title={Hybrid quantum investment optimization with minimal holding period},
  author={Samuel Mugel and Mario Abad and Miguel {\'A}ngel Bermejo and Javier S{\'a}nchez and Enrique Lizaso and Rom{\'a}n Or{\'u}s},
  journal={Scientific Reports},
  year={2021},
  volume={11}
}
In this paper we propose a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period. Our algorithm is based on sampling the near-optimal portfolios at each trading step using a quantum processor, and efficiently post-selecting to meet the minimal holding constraint. We found the optimal investment trajectory in a dataset of 50 assets spanning a 1 year trading period using the D-Wave 2000Q processor. Our method is remarkably efficient, and produces… 

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References

SHOWING 1-10 OF 35 REFERENCES

Dynamic Portfolio Optimization with Real Datasets Using Quantum Processors and Quantum-Inspired Tensor Networks

A number of quantum and quantum-inspired algorithms on different hardware platforms are implemented to solve the problem of dynamic portfolio optimization using real data from daily prices over 8 years of 52 assets, and a detailed comparison of the obtained Sharpe ratios, profits and computing times is done.

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

Benchmarking Quantum Annealing Controls with Portfolio Optimization

This work compares empirical results from the D-Wave 2000Q quantum annealer to the computational ground truth for a variety of portfolio optimization instances and identifies control variations that yield optimal performance in terms of probability of success and probability of chain breaks.

Financial Portfolio Management using D-Wave’s Quantum Optimizer: The Case of Abu Dhabi Securities Exchange

Financial portfolio selection is the problem of optimal allocation of a fixed budget to a collection of assets (commodities, bonds, securities etc.) which produces random returns over time. The word

Use Cases of Quantum Optimization for Finance

This paper discusses the prediction of financial crashes as well as dynamic portfolio optimization using quantum strategies based on quantum annealers, universal gate-based quantum processors, and quantum-inspired Tensor Networks.

The emerging commercial landscape of quantum computing

The recent growth in the commercial QC market is examined through the lens of dominant product design, and emerging strategies for developing the QC market are contrasted.

Complexity-Theoretic Foundations of Quantum Supremacy Experiments

General theoretical foundations are laid for how to use special-purpose quantum computers with 40--50 high-quality qubits to demonstrate "quantum supremacy": that is, a clear quantum speedup for some task, motivated by the goal of overturning the Extended Church-Turing Thesis as confidently as possible.

Quantum State Optimization and Computational Pathway Evaluation for Gate-Model Quantum Computers

A state determination method that finds a target system state for a quantum computer at a given target objective function value is proved and is convenient for gate-model quantum computations and the near-term quantum devices of the quantum Internet.

Demonstrating a Continuous Set of Two-Qubit Gates for Near-Term Quantum Algorithms.

This work implements two gate families: an imaginary swap-like (iSWAP-like) gate to attain an arbitrary swap angle, θ, and a controlled-phase gate that generates an arbitrary conditional phase, ϕ that can provide a threefold reduction in circuit depth as compared to a standard decomposition.