The Job Market for Analysts: How to Ride a Swinging Pendulum
The role of the analyst is not what it used to be. Changes in business models, advancements in technology, and cost pressures — not to mention new regulations coming down the pike — have all taken their toll on the profession. Today’s job market is more competitive than ever, and reaching the top requires a different skillset than was expected of previous generations of analysts.
Outsourcing has been a major trend in most industry sectors for many years. From manufacturing to financial services, thousands of jobs have been exported overseas. Nowadays, it is common for asset managers to outsource back-office and administrative functions to large banks, which then outsource the work to lower-wage markets. For analysts, that means some modeling work and listening to quarterly phone calls is being done in places where a lower rate of compensation gives analysts a cost advantage over analysts in major financial centers.
“That is an issue when you look at the demographics of the business, where jobs are being created, and how young people will get their experience. Analysts are competing against a global talent pool these days,” says Owen Concannon, CFA, senior vice president and research director at Neuberger Berman in New York and author of CFA Institute Industry Guide The Asset Management Industry.
Another trend is that the flow of money into passive index products with lower fees has increased substantially, coming at the expense of actively managed funds that rely on fundamental research. Morningstar’s 2015 Global Asset Flows Report shows that US index funds attracted about $400 billion of inflows, compared with an outflow of more than $200 million from actively managed funds. The percentage of US equity assets in passive funds reached 37.5% in 2015, up from less than 20% in 2007.
In addition, advances in technology and new regulations are forcing analysts to redefine their value proposition. A couple decades ago, “good” analysts would quickly call their clients when they had new information, building relationships over time the salespeople could then leverage to extract orders. Today, market participants already have near-real-time access to a vast amount of information via the Internet, so a portion of the traditional service offering has become redundant. Further, the Markets in Financial Instruments Directive (MiFID II), which takes effect for EU member states in January 2018, will require research to be unbundled from trading commissions—and some observers believe US regulators will follow suit. The cost of research will soon increasingly come out of the asset management firm’s P&L instead of out of their clients’ funds.
“The days when soft dollars were so much easier to come by are pretty much over. That has huge ramifications for the job market,” says Marietta Miemietz, CFA, a pharmaceutical analyst who is co-founder and director of Primavenue Advisory Services in London. “Analysts no longer need an investment banking platform to take clients’ commissions and run broker voting. An asset manager can just go to a research house and say, ‘OK, we’ll pay you x for providing us with research,’” adds Miemietz, who is also author of CFA Institute Industry Guide The Pharmaceutical Industry.
About a decade ago, brokers started lumping together content origination and distribution because it was easier to monetize road shows, huge conferences, and calls with experts. They even began paying juniors to sit in front at medical meetings and take pictures of the slides that were being presented.
“For an analyst, that is quite frustrating because your role is no longer to come up with insightful research. It is just to facilitate interactions between asset managers and various management teams of experts,” Miemietz says. “That is also going to stop.”
Asset managers may have other reasons for wanting to pay for things like road shows, she admits, but the cost will probably have to come out of their own pocket, and such expenditures cannot be labeled as research.
Ultimately, MiFID II is a catalyst for changes that are already underway. In the past several years, there has been greater discordance between what asset managers want and what the research industry actually supplies. Pricing pressure is forcing brokers to take costs out of the system. It has gotten to the point where the brokers are not making money and the buy side thinks that what the sell side is doing is not useful. In Miemietz’s opinion, it was a mistake for the sell side to concentrate on trying to come up with great stock calls instead of supplying intelligence that would enable clients to make their own decisions.
There is a good chance that the buy side will increasingly conduct more research in-house. That said, some research houses will likely be successful, among them those that hire brilliant analysts to do in-depth research. Global houses that cover all sectors will continue to attract large asset management firms as clients, but the analysts will have to offer value relative to their cost. Finally, there will always be some demand for paid-for research, especially in the small-cap space, but these providers will need to hire analysts cheaply.
“The job markets are going to become more favorable for senior analysts and probably a little bit scary for the mid-level analysts,” Miemietz predicts. “It has been quite hard for the senior analysts to justify to their employer that their work can be monetized, but the pendulum is swinging the other way.”
There is also an opportunity for senior analysts to build their own firms, because they no longer need the investment banking platform. Some may find that an attractive alternative given the potential for financial gain and job satisfaction.
Strong Research, Material Insight
Going forward, investors who are paying for research will expect analysts to have a much more in-depth understanding of the drivers and variables that influence their sector. Firms are already seeking to hire analysts who are industry insiders and practitioners.
“Investors are asking for more,” says Irfan Younus, CFA, analyst in the real estate sector, head of research and strategy (Europe) at Savills Investment Management in London, and author of CFA Institute Industry Guide The REIT Industry. “They are looking for that unique understanding of what is driving the market rather than reactively describing what is happening in the market.”
Analysts need to be able to incorporate the effects of global trends, events, and regulations into their assessments. When the US Federal Reserve makes a decision about interest rates or China changes its overseas investment rules, for example, Younus has to estimate the potential impact on the European property market.
He believes that analysts who want to succeed will need to continually improve their quantitative skills. Though the CFA Program is a good foundation for analysts, it is also important to learn how to use software tools, such as MATLAB and IBM SPSS, for doing quantitative analysis.
“You need to be constantly analyzing a very wide range of data,” he says. “It’s also not possible to just rely on spreadsheets. You need to have better statistical tools to work with.”
Concannon agrees that familiarity with technology and programming skills is essential because data volumes need to be managed. Analysts have a huge amount of structured and unstructured data sources at their disposal, so they need to not only understand what information is available and important but also to be able to obtain it and digest it quickly.
“At the end of the day, the job is going to go back to its roots of having strong fundamental research being backed by smart opinions,” Concannon says. “With so much information out there, the challenge is going to be how to de-clutter it and focus on things that are material.”
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 specialized. 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 behavior and emotional responses.
“Marrying machines and behavioral finance is the next frontier,” says Concannon. “There’s a huge question mark over when those two will converge. Considering how important behavioral 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 recognize 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 modeling 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 skeptical 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%.”
This article originally ran in the November/December 2016 issue of CFA Institute Magazine.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
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Analysts just need to have more common sense. It is simple, but not easy.
CFA ok, and then? You start your own research and understand that instruments you are in your hands from bronze era. You have a huge number of unsystematized numbers from different sourses to be worked. You feel the lack of automatization. Where you will find the team which will help you to go in depth in study of software tools, more complicated then Excel, MATLAB, IBM SPSS for example, basic programming? You dream internship in write place, but nobody want you. You still alone like Jesus on his way, only with your pc and your brain. A lot of my thanks to anybody who can advise on this point.
Really insightful!!!