What is the future of quantitative finance?

Jun 19, 2021 by

Like many industries today, quantitative finance won’t be immune to developments in automation. Why do you need a human when a computer can sort through massive amounts of data 24/7? While some analyst roles may eventually become redundant, other roles will evolve and skills will become more diversified. The actual decision making is still very much human driven too, with automated technology like machine learning used to tackle the large quantities of data around today in a role that ultimately helps inform decision making.

Yet despite the march of automation, quant finance is far from dying, it is just changing. Human quants will still be required, but they will have to constantly adapt to ensure that their skills remain relevant to an ever-changing industry. Whether it is quant finance or Tokyo, every area will be impacted by automation. 

Quants who are highly experienced in areas such as computer science, statistics, modeling, and even programming will be highly sought after. They need to be capable of selecting the best machine learning techniques from amidst some of the lesser, snake-oil like techniques floating around today in order to generate true value. Machine learning may be automated, but it’s people who will have the job of ensuring that the firm they work for is using the right and most efficient techniques for the results they want to achieve. To do this, quants will also need to be well versed in all areas of the business they work for and how each department works, in order to be confident in the business need for the solutions they develop.

But a trained quant will no longer have a job for life in whichever firm they land in. Instead, they need to be seen to adapt their skills and be more attuned to the bigger picture, or they’re in danger of having better talent take their job from underneath them. They will need to continue to build new tool-sets to solve brand new problems and be flexible when it comes to rapidly changing technology and markets. There will still be new ways of trading and new financial products, but a quant will need to have a good overview of the entire system and continue to evolve their skillset.

With the overwhelming amount of data available today, as well as cheap, cloud storage and always increasing computer processing capacities, quant investments will be driven more by the data than ever before. However, you still need a large degree of resources to tackle this amount of data and deploy systems that use machine learning, so the smaller firms may lose out as they’re swamped by the big players. This may lead to smaller companies merging, or even going out of business altogether.

Finally, there are still many markets that quants aren’t really involved in, so the future will see them moving more into these markets to open up other sources of revenue. With big data and its increasing complexity becoming the norm, areas like optimised trading strategies will always require a lot of talent and a combination of both a quants methods and machine learning. 

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