Human intelligence vs. AI
Most analysts would be interested in any system that can help update models, compile documents, and do Internet research. However, machine learning, a subfield of artificial intelligence, is not being implemented by research analysts yet. For that matter, few analysts are pulling numbers directly into their spreadsheets using XBRL (extensible business reporting language). The job still involves a significant amount of manual number crunching, which is being done either by interns and junior analysts or offshore.
However, it is likely that machine learning will be used for simple tasks in the future. Some are concerned that it could pose a threat to the industry in the longer term, because junior analysts will no longer be able to train for more complex work by doing mundane tasks. A counterargument is that machine learning can be used to check junior analysts’ work and enhance their training.
Senior analyst jobs probably are not at immediate risk from machine learning because making judgment calls on companies is so specialised. To a large extent, the screening systems used by the asset management industry currently are based on mathematical formulas. Psychometric questionnaires score an investor’s risk tolerance, and then the system chooses the building blocks for their portfolio. Other systems can assess whether a stock looks underrated or the accounting looks fishy, but these are based on algorithms; it is much harder to teach a computer to figure out whether or not a company’s products are going to be successful or to interpret and predict human behaviour and emotional responses.
“Marrying machines and behavioural finance is the next frontier,” says Concannon. “There’s a huge question mark over when those two will converge. Considering how important behavioural finance is to this business, that’s a major headwind.”
“Deep into the numbers”
Analysts are measured by the quality and relevance of their research, so an expert is someone who knows their sector inside and out — the industry, companies, and value drivers. Every sector has a different analytical approach. In the pharmaceutical sector, for example, having an understanding of the technologies and drugs companies produce is imperative. Understanding financial statement analysis and accounting is also critical, because business structures and arrangements are becoming more complex.
“You really need to dive quite deep into the numbers,” says Miemietz. “Ten to 15 years ago, if pharma analysts were good in science and had a very basic understanding of how a P&L and balance sheet were constructed, they could somehow scrape by. Those days are over.”
Experts are adept at interfacing with clients and understanding what investors are trying to achieve in the context of their specific portfolios. They recognise that the buy side will likely use research more selectively in the future, so they will seek to provide more comprehensive answers to meet their clients’ individual needs.
In Younus’s opinion, the top analysts have certain traits. They are curious about the industry sector that they cover, can understand and interpret how changes in the macroeconomic and political environment will affect their sector, and can communicate ideas clearly and succinctly. They are good at modelling and methodical in their approach, often using Monte Carlo simulation, to project how valuations might evolve over time. Importantly, they are wary of taking information at face value.
“Companies hire PR firms to make sure that bad news also looks like good news,” Younus says. “You need to be sceptical about what they are trying to say, and you need to be able to extract the underlying messages.”
In addition, the top analysts work well under pressure. News is often released at 7:00 am — just an hour before the markets open. There is only a small window to understand and derive meaning from announcements, update models, and write a one-page summary explaining the impact.
“It’s not a field where you give 50% and get away with it,” says Younus. “You need to give 100%.”
Sherree DeCovny is a freelance journalist specialising in finance and technology. This article originally ran in the November/December 2016 issue of CFA Institute Magazine.