How quantum can provide the pot of gold in an ever-growing maze


Posted on: May 2, 2019 by Ruben Van der Ploeg

It was always one of the greatest challenges as a little kid: finding your way out of a maze. Every time an attempt took me longer than I wanted, I wished for a simulator of some kind that could help me find the exit sooner. Now, imagine yourself being in a maze with a simulator that could walk the different paths of the maze for you. However, instead of a child’s maze, the maze offers an enormous number of alternative routes, with several exits that will give you small rewards, but with only one perfect outcome that will give you the pot of gold. It would take years for the simulator to find the pot of gold, so either you can improve the simulator, or you can decide to be satisfied with the smaller rewards.

This is a problem that current bankers face every day. The maze is a simulation of estimated risks, so-called Monte Carlo simulations. By using different components and weights, these simulations give an estimate of the prospective returns and its associated risk. However, the computational power that the Monte Carlo simulations need is large and grows exponentially due to ever-growing globalization and digitalization. In the financial world, where time is money, in the most literal sense of the phrase, the problem around this computational complexity is being tackled by many stakeholders as well as researchers.

The revolutionizing field of quantum finance

The latest field that is being investigated in search of the solution to computational complexity, is quantum computing. Quantum computing has started to enjoy the interest of financial institutions initially because of its potential cybersecurity threat. However, the interest is broadening as research has shown that, quantum computers - due to their probabilistic nature - can enhance Monte Carlo simulations, which are widely used in financial operations like NPV calculations, option valuation, bond price calculations, risk management, portfolio optimization, and capital investment planning.

Bridging the gap with the quantum learning machine

The downside to this huge quantum prospect, is that research is still only focused on proving quantum superiority in these fields. This leads to an ever-expanding maze, without bullet-proof cases of worthwhile investments in quantum operations. Industry experts should not be looking to expand the maze, nor be satisfied with minor improvements in these challenges. Instead, already developed algorithms should be put into practice, to explore the costs and advantages of quantum computing. One example is optimization around Quantum Risk Analysis! Not only to find quantum speed-ups or quantum superiority, but to show an end-to-end case where a quantum computing service can give both faster and, more importantly, achieve further optimal results. This can be done by:

1/ Designing circuits that not only enhance the predesigned Monte Carlo simulations, but enhance the whole risk management process;

2/ Testing the quantum models against real data on quantum emulators.

To elaborate, Monte Carlo simulations are part of a portfolio risk evaluation estimation and thus far, it is the only part that is investigated for quantum speedups. However, the components that influence the portfolio, like interest, subsidy, exchange rates etc., as well as the optimal portfolio composition, are still classically estimated by for example MLE. By shifting the attention from finding quantum speedups, to developing a quantum program which optimizes business processes like risk valuation, we could not only show quantum superiority but also quantum applicability.

By bridging the gap between quantum hardware and software, as the vision in the Atos Thought Leadership paper Journey 2022 “Resolving Digital Dilemmas”  sets out, it is possible to architect a product for a variety of quantum financial operations. The possibility to develop end-to-end use cases with Quantum emulators can be leveraged, to make this a practical reality.

The possibilities which can be offered through Quantum emulators are seemingly endless. The only question remains, do you keep wandering the maze satisfied with the small rewards, or do you dare reach for that pot of gold?

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About Ruben Van der Ploeg

Intern Quantum Finance at Atos Global Financial Services
Ruben is a MSc student at the University of Amsterdam who is currently performing an investigation on the usefulness of quantum computers for financial services. As a Finance student specializing in Quantitative Finance, he is one of the first people to shine a light on the quantum revolution from a non-physics point of view. As a graduation project, he is trying to bridge the gap between Quantum Physics and Finance models. Apart from his graduation project, Ruben can be found behind the piano as well as on the race bike.

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