DealTech: Rollout of quantum computing to impact deal pricing models - experts

06 May 2021 - 01:24 pm UTC

by Rupert Cocke and Boris Maleshkov

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The rollout of quantum computing in the years ahead is likely to have an impact on pricing deals as it facilitates views across multiple scenarios, experts said.


Finding the right price for an M&A deal involves considering multiple variables and then combining them in an optimized way, Magdalena Hauser, co-founder and CEO of ParityQC, said. This task is intrinsically hard for classical computers, she said, adding that quantum computers will be able to tackle optimization problems much more easily.


Quantum computers are becoming very good at complex model building, Katie Pizzolato, Director of IBM’s QStart and IBM Quantum, said. They will come to eclipse classical computers in pricing portfolios, she said, adding that projecting cashflows in multiple scenarios is an example of a field where a new approach can make a difference.


Now is a good time to start thinking about the implications of quantum computing, Pizzolato said, adding that there will be significant advantages for early movers. Some financial services firms are already looking at portfolio optimization and pricing derivatives, she added.


Pricing deals would be an interesting application, Roger McKinlay, Challenge Director Quantum Technologies for UK Research and Innovation (UKRI), said. The first quantum deal priced using a quantum computer will be a milestone to watch, he added. UKRI is a non-departmental public body in the UK that champions research and innovation in cutting-edge areas like quantum computing.


As a general rule, quantum computers will be faster than classical computers but also different, McKinlay said. They are probabilistic rather than deterministic, which makes them better for simulations, he said, adding that their optimization capabilities will make them good at analyzing risks and portfolios.


ParityQC, which is based in Austria, develops blueprints for quantum computers to solve optimization problems. Its use cases span areas including traffic and logistics, chemistry simulations and car sharing, as well as finance.


Meanwhile, IBM has already deployed 28 quantum computers as part of its road map to scale systems to 1,000 qubits and beyond. It is developing a network of blue-chip companies, startups, and research institutions, according to its website.


In 2019, scientists at Google – part of Alphabet  – published an article in Nature saying that they had developed a quantum computer that runs a circuit of 53 qubits. It would take the best classical computer 10,000 years to solve the same problem, they said at the time.


A quantum computer with 100 qubits is possible within the next five years, McKinlay said. This is a “very useable” level, he said, adding that a computer with 300 qubits would be able to handle more states than there are particles in the universe.


Quantum computing will be as transformative in the 2020s as the internet was in the 1990s and beyond, IBM’s Pizzolato said. There is still a lot that experts do not know, she said, adding that financial applications will include settlement transactions, statistical analysis, derivative pricing and fraud detection.


Obvious applications within finance include portfolio optimization, fraud detection, asset pricing/hedging and developing trading strategies upon real time optimization, ParityQC’s Hauser said.


The sheer power of quantum computers has implications for cybersecurity, McKinlay of UKRI said. Quantum computers will be able to use brute force to hack existing systems, while quantum keys will offer new levels of security, he said. Quantum computing will be “a gamechanger” in cybersecurity, Pizzolato agreed.