With investing, even a small edge that can be identified and pursued can result in huge returns. That’s why, as experienced investor Daniel Calugar explains, hedge funds are already experimenting with quantum computing to help them solve complex financial modeling and risk analysis.
Quantum computing is still a relatively new technology, at least from the standpoint that it isn’t yet widely adopted. There are many reasons for this, of course, not the least of which is the fact that the emerging technology is still expensive and not readily available.
Still, major hedge funds are diving headfirst into at least the exploration phase of quantum computing, trying to figure out how they can best use it to their advantage.
Quantum computing has transformative potential for many industries, and particularly for financial institutions. Thanks to the completely new way of processing and analyzing data — using something called qubits instead of the classic bits that traditional computers use — the technology is able to deliver things that weren’t even imaginable until now.
It’s also not a surprise that major hedge funds are some of the early adopters of quantum computing, as they’re often among the earliest adopters of any emerging technology. Those leading hedge funds are always looking for new ways to gain an edge in financial markets, and quantum computing is the next great thing promising to overdeliver on expectations.
Below, Dan Calugar will dive deeper into quantum computing from the aspect of how hedge funds utilize the new technology, discussing some of the potential advantages and obstacles that early adopters face in the era of quantum finance.
What is Quantum Computing?
Much of the recent focus on emerging technologies has been placed on artificial intelligence and machine learning, and for good reason. Both of these technologies have already delivered on their promise of changing how computing is done, adding tons of value to multiple aspects of people’s lives.
In the financial sector, AI and machine learning have brought new value to investors and investment firms through more efficient and effective data analysis, all done at impressive speeds and with the need for little to no human intervention once the initial setup is complete.
Despite these technologies’ very impressive features, there are still significant limitations. The main reason for this is that they run on classical computer systems, which use bits that either have values of 0 or 1.
These bits can only be used for individual processes, relying on inputs and parameters that are set by humans to produce individual answers to problems. These bits don’t communicate with each other outside of individual applications, which means that they can only go so far in solving big problems.
Quantum computing, meanwhile, uses qubits instead of bits. There are many complicated aspects to what qubits are and how they work. But, at a basic level, qubits can have multiple values simultaneously and communicate with each other back and forth, even outside of individual “questions.”
There are many significant benefits with qubits. For one, they have the ability to process and analyze data at exponentially faster rates than bits can. They are also much more accurate and can “think outside the box.”
Because they are able to communicate with each other, they can produce multiple answers to a single query, which can help financial firms see all the possible outcomes of a particular problem.
This is a massive benefit of quantum computing because finances typically aren’t as simple as one question and one answer. Any given financial challenge has multiple potential outcomes, making quantum computing a great fit for the industry.
A New Application of an Old Concept
While quantum computing might sound futuristic, the fact is that the technology isn’t new. The original concept of quantum computing dates back to the 1940s when computer scientists first outlined the rules of quantum mechanics to define how atomic scales operate.
About 40 years ago, MIT academics started to apply the principles of quantum mechanics to computing. They believed that if these concepts could be applied to computing, it would have the ability to perform calculations in mere seconds that, before then, seemed utterly impossible.
Again, instead of only producing a single response to a question in a short amount of time, quantum computing has the ability to produce a range of potential outcomes simultaneously and almost instantaneously.
Because of the sheer power of quantum computing, major service providers around the world are doing their best to understand, develop and roll out these offerings to their customers. Daniel Calugar says IBM is considered one of the leaders in this realm, though many other companies are right on their tail.
They are doing this because multiple research and advisory firms such as McKinsey & Company, Strategic Intelligence Advisory, and Boston Consulting Group — have all suggested that the market could be valued at as much as $120 billion by the end of this decade and at least $450 billion halfway through this century.
How Financial Services Are Using Quantum Computing
Companies in the financial services sector were some of the earliest adopters of quantum computing, which is no surprise. The fact that quantum computing can potentially handle virtually any problem it’s given at exponentially accelerated speeds provides immense benefits for huge returns.
Even the slightest of advantages or edges that can be identified in financial services can result in significantly better outcomes for firms and their clients. Hedge funds, in particular, are always investigating new ways that they can gain an edge in the market. Quantum computing is the latest emerging technology that these funds are investigating to see how they can benefit from it.
Today, the Bank of International Settlements reports that more than $10 trillion worth of derivatives and options are exchanged globally. According to the firm, much of that is priced using a technique known as Monte Carlo — where random samples are fed into complex functions using probability distributions.
The problem is that this pricing approach is time-consuming, inefficient, and can lack accuracy. None of those things are good in the world of finance.
Quantum computing, by contrast, has the ability to model outcomes in an extremely efficient and effective way. Not only can the technology operate at significantly faster speeds and with higher accuracy, but it can also produce variable potential outcomes — allowing those who use it the ability to make more informed decisions, all in the blink of an eye.
Benefits Hedge Funds Are Realizing with Quantum Computing
Major hedge funds such as WorldQuant, DE Shaw, Renaissance and Two Sigma have already begun to experiment with quantum systems. These financial entities are searching for new ways to capitalize on the market and are already seeing significant benefits from doing so.
A November note from Goldman Sachs outlined the significant differences in returns that hedge funds were able to gain using quantum computing systems versus those that used humans to pick stocks.
The strategy, known as systematic long/short hedge funds, resulted in gains of 4.97 percent in October 2023. According to Goldman Sachs, hedge funds using traditional means of trading experienced a loss of 0.66 percent in that same month.
One of the big reasons for this is the immense speed at which quantum computers can operate compared to their traditional counterparts. For instance, many simulations of Montel Carlo-based pricing could experience what’s known as a “quadratic speedup.” This refers to the speed at which the algorithm can operate on a quantum computer compared to a traditional computer.
An algorithm that takes 100 seconds to run would only take 10 seconds if it had a quadratic speedup. An algorithm that takes 1 million seconds would now only take 1,000 seconds. This extreme speed difference gives hedge funds a significant edge when assessing risk and accurately pricing assets.
According to a Deloitte Insights report, it’s a big reason why spending on quantum computing by the financial services industry is expected to increase at a CAGR of 72% by 2032.
Below, Dan Calugar highlights some of the main ways that hedge funds are realizing benefits with quantum computing.
Portfolio Management
Efficient and effective portfolio management is a major key to success for hedge funds. Since things develop and change so quickly in the world of finance, it’s essential for firms to constantly monitor what’s happening.
For years, hedge funds have used classical computer models to do so. And while they’ve certainly benefited from other emerging technologies such as AI, machine learning and algorithmic trading, all of those have limitations.
For hedge funds that are constantly seeking to maximize their returns and minimize their risks, quantum computing presents immense potential. The technology helps via the ability to analyze multiple combinations of investments en route to discovering an optimal mix of assets in the portfolio.
Algorithms that run on classical systems are great, but they require a lot of time, especially when taking into account multiple assets. Meanwhile, algorithms that are powered by quantum computers can find the best solutions at significantly faster speeds.
This can lead to portfolio adjustments being made in real-time, allowing hedge funds to respond to changes in the market instantly. This is potentially a substantial edge for these financial firms, as even slight changes in the market can mean significant money gained or lost due to the fact that such large amounts of money are being traded.
Hedge funds are harnessing the power of quantum computing systems to constantly consider multiple factors and outcomes, all of which can be used to maximize their expected returns while also minimizing their financial risk.
Pricing
Every financial entity is sensitive to pricing, but maybe none more so than hedge funds. Since they trade at such huge volumes and lightning speed — even compared to large investment firms — even the slightest difference in price can make or break a hedge fund’s investments.
Quantum computing has the ability to produce optimal prices for assets more accurately so that hedge funds can time their trades more effectively.
Hedge funds can use quantum versions of classic pricing techniques such as Monte Carlo to arrive at better outcomes for derivatives and options, as well as market simulation and portfolio evaluation.
Quantum Machine Learning
Quantum machine learning is the next step in a technology that’s being widely adopted across industries. It’s a hybrid method combining the processing powers of both classical and quantum computing.
This new way of modeling and learning uses artificial intelligence to better predict outcomes and thereby optimize returns. The quantum aspects of machine learning are able to produce multiple potential outcomes, which is a considerable benefit to hedge funds.
Instead of basing their decision-making process on singular responses, they can weigh the multiple results that quantum computing can produce to make more informed trading decisions.
Challenges to Quantum Computing Adoption
Despite the many potential benefits that quantum computing can provide to hedge funds, there are challenges to its adoption. Fortunately, many of these challenges are currently being addressed and hopefully will be ironed out in the near future.
Daniel Calugar outlines some of the main challenges below.
Integration with Current Systems
One of the most basic challenges to quantum computing adoption is that the new systems must be integrated with the current ones. Even the most forward-thinking hedge funds have large-scale systems already in place that, in no small terms, power everything they do.
Any time a new system is developed, it has to be integrated in some ways with existing legacy systems. When the new systems are based on similar classical computing models, it’s simpler to figure out the best way of rolling them out.
Quantum computing, though, provides a new integration challenge since its basics (qubits) are so different from those of classical computing systems (bits).
In essence, full-scale integration could require current systems to be completely redeveloped. That’s just not feasible for most financial entities at this point, especially as quantum computing systems aren’t readily available, affordable, or even applicable to legacy systems.
As a result, hedge funds are having to operate some of their quantum computing systems in a silo separate from their legacy systems. They are, however, working to bridge the gap between the two types of systems.
Even if hedge funds would love to do so, it’s very unlikely that quantum computers will replace classical computers any time soon. It’s much more likely that they will need to work hand-in-hand with these legacy systems for some time yet.
The good news is that new use cases should become available incrementally as the emerging technology continues to mature. However, that’s not likely to occur in either a linear or steady manner.
Limitations with Qubits
Another major challenge is the limitations of the qubits themselves.
The machines that run these systems today are referred to as Noisy Intermediate Scale Quantum systems. The downfall of these systems is that the total number of qubits that can be used is limited.
In addition, the qubits can’t hold onto their quantum states for much longer than microseconds. As a result, “noise” — or errors — are often introduced into calculations.
Creating a quantum computer system that is fully functional and operational is extremely difficult, as qubits have to be completely isolated from their environment for the information to be stored optimally.
What’s more, quantum chips require temperatures that are much lower than those seen in outer space — only a 100th of a degree above absolute zero — and consume energy at much higher rates than traditional computing systems.
This means that quantum computing systems are not perfect yet, and there aren’t many available. For hedge funds, this creates challenges in not only finding a system that works for them — and makes sense financially — but in finding one that is also stable and likely to be around for a while.
Lofty Promises
A final challenge, or potential concern, of hedge funds adopting quantum computing is whether the technology is promising more than it can feasibly deliver. Many pundits are saying that emerging technology is currently at the same stage as AI was about a decade ago.
In other words, Daniel Calugar says that it’s possible that it will take some time for quantum computing to reach its full potential.
That may be a warning sign to some in the financial services industry who are looking for more of a sure thing instead of something that promises lofty returns but is currently unproven.
That being said, there have already been enough use cases to show that there is immense potential in quantum computing for the financial services industry.
Plus, as mentioned before, hedge fund managers are typically more willing to at least test out emerging technologies than some of their counterparts in the wider financial sector.
Still, reporting on failures or shortcomings of quantum computing — specifically if the technology isn’t meeting the lofty expectations many are setting for it — could cause hedge funds to shy away from its application, depending on what those reports reveal.
About Daniel Calugar
Daniel Calugar is a versatile and experienced investor with a background in computer science, business, and law. While working as a pension lawyer, he developed a passion for investing and leveraged his technical capabilities to write computer programs that helped him identify more profitable investment strategies. When Dan Calugar is not working, he enjoys working out, being with friends and family, and volunteering with Angel Flight.
