The growth of artificial intelligence and automation is expected to revolutionise the asset management industry, with experts predicting a wide-scale loss of jobs as a result.
Many commentators believe that developments in technology will lead to robo-advisers replacing humans and algorithms suggesting funds to investors.
While it is not a new phenomenon, the use of data science to plan an investment strategy is growing in popularity with asset managers after the reputation of quantitative strategies dipped in the aftermath of the financial crisis.
Over the past 10 years the cost reduction in processing power and the availability of data and information has led to a boom in quant investment strategies.
While robo-advice typically provides financial advice online with minimal human input, quant strategies can be employed by more traditional fund managers who use algorithms to help select investments.
Traditional quant strategies analyse historical stock market and economic data to help identify the most attractive investment opportunities. But with constantly fluctuating markets and an increasingly crowded tech space, is it really possible to capture profits from formula-driven strategies?
Last year, BlackRock announced it was shifting a number of its active funds to quant and passive strategies.
David Wright, head of product strategy at BlackRock’s EMEA quantitative investment arm, Systematic Active Equity, says that while it has switched some funds to quant investment strategies, it still believes in using a traditional fund management approach.
He says: “The move to quants has been driven by client demand for lower tracking error, better alpha and more consistency. They deliver lower risk so are available at very attractive prices.”
Wright says that one of the main advantages of quants is that they give the company market breadth.
He says: “We can analyse almost every listed company out there. This allows us to build diversified portfolios so investors are never reliant on individual names for driving active return, which gives us a strong ability to hedge risk.”
BMO Global Asset Management head of factor investments Erik Rubingh says: “There is a trend in the industry for more traditional managers to incorporate quant-based techniques into their portfolios.
“Whereas individuals are subject to behavioural bias, quants take emotion out of the investment process. The advantage of this is that it leads to better decision-making as you have a framework that gives you guidance on how to run your process in a more consistent way.”
Beating the downturns
A major criticism of quants is that they rely on historical data for success, whereas a portfolio manager is more forward-looking and able to make strategic decisions about the future.
AJ Bell head of fund selection Ryan Hughes warns that investors should be careful of quant-based strategies if they think there is going to be a downturn in the market. He says: “A human can spot trouble ahead and de-risk a portfolio to navigate a change in the market whereas a quant-based model is not geared to do that.
“What you often find is that when you get a serious turning point in the market, a quant model performs quite badly through that period. It can take a while for the data to catch up with the market once it picks up again.”
This is what happened after the 2008 financial crisis, when quant trading came in for heavy criticism after it was found that computer methods were not accurate enough, leading to a huge sell-off in the market. Hughes says: “It is very difficult to build a portfolio made up entirely of quants, and while we are very happy to use them where appropriate, for me they should only be used as part of an overall strategy.”
Dipping a toe back into the water
Most of the big investment houses now have quant teams. As they are becoming a larger part of the investment process, they are beginning to displace fund managers and their teams.
Top fund managers are more artist than scientist; they paint a picture for a portfolio rather than fill in a spreadsheet
Axa Investment Management announced last week it is cutting 210 jobs as part of a broader shake up and said it would be reinvesting some of the €100m (£87.5m) it plans to save on quant and data science skills.
It follows a growing number of asset managers that are moving back towards a quant-based model as they look to make cost savings.
Since quant strategies are purely mathematical they can be fully automated, so they are cheaper as they do not need as many analysts or portfolio managers to run them.
Fund managers are also coming under increasing pressure to prove the value of their charges from the FCA and one way of doing this is by reducing costs through the introduction of quants.
Aberdeen Standard head of quantitative investments Sean Phayre says that while there has been growth in more competitively-priced strategies in recent years, he is unsure whether this trend will continue at the same pace.
He says: “There is always going to be room for expansion in the quant investment landscape but whether companies do this will largely depend on the desire of their clients to change strategy.
Fiveways Financial Planning director Chris Gilchrist says that the use
of quants will largely depend on the objectives of the fund.
He says: “If you are running a fund with the aim of outperforming the FTSE by 1 to 2 per cent, a quant-based approach makes sense to reduce the risk of underperformance.
“However, quants will never replace the judgement of the best stock pickers.
“The best fund managers are more artist than scientist; they paint a picture when creating a portfolio rather than just filling in a spreadsheet. That is way beyond the capabilities of any quant process.”
Havelock chief executive Matthew Beddall says: “The poor performance of active has led many to the conclusion that it doesn’t work, rather than it being too expensive.
“We believe the use of technology will drive efficiencies, such that there is a resurgence of active managers who pass these savings back to customers.
“Quants won’t replace active managers – the winners will be those
who use an intelligent mixture of man and machine.”