Articles & Interviews
18 February 2019
The great quant talent grab: the inside line on one firm’s renewed focus
Traditional asset managers are going to find themselves in an increasingly competitive battle to hire quant and machine-learning specialists as a direct result of research coverage diminishing.
That is according to Thomas de Saint-Seine (pictured), chief executive officer of Swiss group RAM Active Investments.
Speaking to Citywire Selector in the wake of adding two new quant specialists to his own company, de Saint-Seine said MiFID II’s impact on research budgets means that asset managers will need to be savvier in their data collection approaches.
For some, this will mean centralising research among a few providers, and de Saint-Seine said it could also prompt capital to be redeployed to other areas, notably in improving the systematic and quant investment coverage.
‘There is reallocation of budgets but there were also some firms – particularly the banks – that had to restructure for other measures. It was projected that the top 10 banks will cut their budgets by another 30% in the mid-term, which is purely linked to new regulation.
‘The secondary impact is the fact you have more and more passive approaches into the market. The growing importance of ETFs will imply less fundamental research for a number of asset management firms, which will could also influence restructuring or redeploying of capital.’
De Saint-Seine pointed to how technological advances can be harnessed to plug this gap. ‘We are in a phase where the machine is becoming much more an intelligence extension of humans. The research budget will therefore be allocated a bit differently than before, so you will have a different fundamental approach and a bit more technology in the research side.
‘The profile of the people doing the research will move more towards quants. That is the reason why we have announced we are increasing the number of people on the research side, as we are adding people with very technical backgrounds.’
De Saint-Seine warned, however, that a blind grab to add quantitative specialists would not work, as you would need to uncover those who also have financial acumen. ‘When you do this kind of exercise, the experience of people is important.
‘If you have a machine-learning expert with no financial knowledge, he won’t be as useful as someone who can see the link between what we are looking for and the finance. The experience is also important for me.’RAM AI boasts nine quantitative research specialists, who cross over with the firm’s investment teams. ‘For us the challenge and the opportunity is very linked to a different area of research.
‘Machine learning is, typically, a very powerful tool for analysing and combining more information, to try to find some non-linear explanations in the market. We definitely see a lot of potential areas to create new strategies to improve our existing strategies.’