Hybrid Quantum investment optimization with minimal holding period

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Spain has become surprisingly the European center of quantum research in finance, thanks to its universities, startups and smart innovation teams in local banks.

A team at Multiverse Computing and Bankia, a Spanish financial organization currently in merge with CaixaBank, has just released a paper about a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period.

Their 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.

They found the optimal investment trajectory in a dataset of 50 assets spanning a one year trading period using the D-Wave 2000Q processor. Their method is remarkably efficient, and produces results much closer to the efficient frontier than typical portfolios.

Moreover, they have also showed how this approach can easily produce trajectories adapted to different risk profiles, as typically offered in financial products. Their results are a clear example of how the combination of quantum and classical techniques can offer novel valuable tools to deal with real-life problems, beyond simple toy models, in current NISQ quantum processors.

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