It’s an exciting time to be a quant! There are numerous projects – from machine learning to quantum computing – that you could get your teeth into and become part of an innovative team that changes the game for quant finance. At QuantMinds International 2019, we asked leading quants what will disrupt the industry the most. The answers vary, but there’s a theme: technology and human consciousness.
Machine learning, artificial intelligence, and technology to change the game in quant finance
If there’s one thing that captures the imagination of all quants, it would be machine learning. When we asked John Hull, Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto, what will disrupt quant finance the most, he stated that machine learning may not be disrupting this industry, but it is certainly sweeping quants off their feet!
“I started off working in derivatives, so it was pricing derivatives in the front office that was really important in the early days. Then risk management became progressively more important and this was particularly true after the last crisis”, Hull explained. “And now, machine learning is becoming progressively more important, and we can see that with the number of topics at this conference that are concerned with machine learning.”
The expectations are high, and the opportunities range wide with machine learning. One key research published this year was on deep learning volatility, focusing on “a powerful neural network-based calibration method for a number of volatility models, including the rough volatility family, that perform the calibration task within a few milliseconds for the full implied volatility surface”, Blanka Horvath, Lecturer in Financial Mathematics, King’s College London, summarised.
So what’s the one thing that will disrupt quant finance the most, according to Horvath?
“Technology, definitely, but also more sophisticated and more realistic models, artificial intelligence, and data-driven technologies in our research and in our pricing models”, Horvath told us.
But these comments and quants’ obvious interest in machine learning should raise our concerns – maybe ML is over-hyped in this industry.
Applications of common sense
According to Damiano Brigo, Chair and Co-Head Of Group, Mathematical Finance, Imperial College London, “excessive reliance on technology and artificial intelligence” would be the most disruptive.
“We have to be very careful with these methods because they’re not interpretable”, Brigo told us.
“In a certain way, you apply machine learning without understanding exactly the limitations, in which conditions you can apply it, and whether you’re just recovering biases in the past data”, Marcos Costa Santos Carreira, PhD Candidate, École Polytechnique, said. “If you just leave engineers to do their thing – they’ll just build something, they’ll put it in production, and they’ll think they solved the problem.”
Lorenzo Bergomi, Head of Quantitative Research, Société Générale, proposes that quants themselves can be the disruptors of this industry, if only they focussed on the right things.
“I guess I’m supposed to answer artificial intelligence or machine learning. No”, Bergomi stated. “I think what will disrupt quantitative finance is us using our brains, making a judgement. We have more tools at our disposal, for example machine learning, which is just another word for optimisation... I think we should focus our brains on the relevance of the questions we tackle, and that will disrupt everything.”
More data needed
So critical thinking should still be championed. Over-reliance on existing models of the past might ignore current real-world common sense.
“There has been a tendency, particularly in financial modelling, to become attached to models and concepts when the real world declined to obey those rules and predictions”, Jessica James, Managing Director, Senior Quantitative Researcher, Commerzbank AG, noted. “Over the last decade the shortcomings in models which weren’t very in tune with what the market was really doing became very apparent. If there’s a word or a single concept that will disrupt, I think data would be the one.”
“Many quantitative investment models have been built on long horizons of data of a universe that doesn’t really exist anymore”, Michael Steliaros, Global Head of Quantitative Execution Services, Goldman Sachs, commented.
Indeed, data is what feeds analytical technologies and to incite true innovative insights, we need more of it. According to Iuliia Shpak, Quant Strategies Specialist, Sarasin & Partners, the thing that disrupts quant finance the most today is alternative data.
“Today’s quant managers still face the challenge of relatively short samples, even though there are more alternative data providers. They are growing though”, Shpak noted.
Infinite computing power – qubits to the rescue
Quant finance has its limitations, some of which can be traced to our current computational capacity. That can change, however. Recent breakthroughs in quantum computing brought us one step closer to infinite computing power.
“Quantum computing today is still a few more years away”, Shpak said, “but it will help us significantly in portfolio optimisation. It will enhance the computing power and managers will be able to tackle multi-period rebalancing and construct better portfolios which you can’t put together today.”
Julien Guyon, Senior Quant, Bloomberg, is cautiously optimistic about the prospects of quantum computing in quant finance.
“I’m not 100% confident in this answer, but it could be that quantum computing might allow many people in the world, including quants in finance, to do computations very quickly that would usually take a very long time or forever! In terms of option pricing, the possibilities that are open are actually extremely large. But it’s still not so clear how that would be. I’m not an expert in the field but I can just sense that it might be very disruptive. But again, maybe not. We’ll see – the future will tell us.”
Quants – disrupted or disrupting?
With one eye on the present and one eye on the future, quants have a lot to think about. As quants actively explore new technologies to pave new avenues for success, it can be argued that quants are the disruptors of this industry.
“I actually think that we hold a lot of the solutions to a lot of the problems that banks and financial institutions have right now and in the future”, Jesper Andreasen, Kwant Daddy, SaxoBank, told us.
Decade after decade, quant finance has been changing from derivatives trading to risk management, and now it’s tapping into more complicated machine learning.
“I don’t know if you might call this disruptive, but the traditional material that might have been taught in quantitative finance courses 10 years ago is not as relevant now”, Hull said. “I think that’s probably going to be true in the next five or ten years as well – what we teach now might not be as relevant. What I always tell my students is that you’ve just got to keep up to date, you just have to keep learning. You can’t think ‘I’ve taken a course in quantitative finance, I now know everything that I need to know’. It’s a very fast-changing field.”