Active managers are feeling the heat.
Years of underperformance are putting intense pressure on their business model. Risk premia strategies, robot-advisors, systematic funds and alternative data usage are gradually disturbing the quiet territory of discretionary investing: a reminder, if it were needed, of the unimpressed view of the FCA regulator in recent asset management industry surveys. In short, active management is going through an existential crisis.
And things might get even uglier. Artificial Intelligence and its sub-components including Machine Learning, Deep Learning, Natural Language Processing, and the list goes on, are threatening to eradicate any form of human decision-making in investment. It is only a matter of time. The almighty portfolio manager is dead. Vive les machines!
How did we get there?
Most would agree that the 21st century has provided an acceleration in information and communications technology (ICT), a revolution which started in the 70’s. We have also seen a significant transformation in everyday life. Information accessibility and velocity is exponential. The impact on the investment industry, driven by information, is more and more difficult to ignore.
Historically, and specifically in the previous century, information was scarce and slower to travel. It was more difficult to access, creating asymmetry between economical agents. Professional investors could do well. Prices discrepancies were numerous and could be spotted by a human brain. Accumulated experience over the years would reinforce the investor’s natural advantage.
But expertise among active portfolio managers kept on rising closer and closer to the limit. In a competitive but highly rewarding environment, this was bound to happen. Computers arrived, the Bloomberg terminal, then the Internet was born, and information asymmetry started to collapse too.
Without disputing the importance of portfolio managers’ expertise, and despite great individual ability, underperformance in active management is more and more in the spotlight. Are we witnessing the beginning of the end?
When lives are at stake, expertise itself is no longer sufficient.
In the early years of aviation, checklists were not needed to take off planes. It became only evident in 1935 when Boing B-17 exploded on its very first test flight, despite having the most experienced pilot at the time . Similarly, checklists in Intense Care Unit (ICU) appeared later. Run by nurses, –and not by doctors, please note the organizational revolution! – checklists became necessary because very capable surgeons operating in highly stressful environment would evidently and occasionally overlook a simple check or procedure, leading to a deadly outcome.
In the medical or aviation industry, counter terrorism or military operations, the amount of accumulated knowledge and world complexity is just too overwhelming for a single individual expert’s memory or attention capacity. The concept of process exists and goes from simple checklists to structured analysis, where information is constantly weighted to feed and update different scenarii . Coordination is organized, usually supported by information technology, and yields to better outcomes.
Asset managers’ websites and marketing materials are flowery when it comes to the investing process and one might expect a similar sophistication when billions are being poured in markets. Is it the case?
The use of research
Research information fuels the investing engine.
Besides freezing the European research market –hopefully temporarily-, the first few weeks of MiFID II unbundling have been largely informative about one thing: how is research really used.
In the wake of having to absorb research costs, European investment firms have conducted last minute surveys among portfolio managers to collect their opinions about which research providers are needed. At best, a consensus was established and the research franchise perimeter left mostly untouched, largely helped by plummeting written research prices pushed by global investment banks. In less favorable cases for the portfolio manager, cheap (almost free in reality) bank portals were contracted, and most of the higher priced independent research cut off. In other more extreme cases, smaller investment firms are currently doing the courageous exercise of doing without research at all, to find out if it was necessary in the first place!
Regulation reveals the historical ambiguity investment managers have always had with research. The fact of not being able to easily deal with essential questions such as “what research is needed” and “for what price” highlights the complete lack of structure in its use.
In investment firms, almost no proprietary data exists to support these essential questions. It is true that investment processes can equal the number of portfolio managers in a firm, making research a highly versatile material depending on the reader’s investing style. Nevertheless, an industry which does not understand where the value comes from to deliver its business proposition shows structural signs of competitive issues. If no data can be found and used around the investment process most essential inputs, it simply means that tools helping to materialize it are certainly non-existent or inefficient. Measuring the investment decision-making path is impossible, so is repeating and scaling good investment ideas.
Active management seems very ill-equipped to survive the information age. The lack of information technology systems coupled with investment styles relying on opinions and assumptions rather than a structured, analytical approach prevents discretionary managers to benefit from new alpha-generating research, like alternative data. The interest is high but successful implementation still low. Two worlds are colliding, qualitative and quantitative. Is this a lost battle?
The big opportunity
Advances in technology, amplified by over-simplistic media voices, might suggest that we are approaching a shift where mankind will be totally disconnected from the machines’ intelligence. Reality is subtler.
“All models are wrong, but some are useful”
observes the statistician George Box, one of the great statistical minds of the 20th century. Correlations are everywhere, and failing to find a meaningful causal effect is frequent in financial research. Gary Chropuvka, a partner at Goldman Sachs Asset Management’s Quantitative Investment Strategies, explains:
“overfitting is the kryptonite of our industry” .
This is where our critical human brain which decides what to analyze, what correlation between a data set and an asset price would make sense to study is far from being replaced by machines. IBM’s Watson’s chief engineer David Ferrucci explains that machines may get better at “mimicking human meaning,” and thereby better at predicting human behavior, but
`“there’s a difference between mimicking and reflecting meaning, and originating meaning” .
In a series of insightful articles, Estimize CEO Leigh Drogen lays a practical vision of discretionary managers’ future: to survive, quantify. To some extent, the technology part is easily achievable. Technology providers led by Fintechs drive the structuration, new workflows and analysis of data and research information. Software applications can now enhance investors’ capabilities while giving investment firms a data-driven overview of their business process at the same time.
This means performance, like underperformance, can be reviewed analytically rather than through the lens of an opinionated and biased conversation between portfolio managers and analysts. The software -please don’t read excel or a shared drive!- is the minimal framework to the future of investing, where qualitative inputs can be easily quantified and married with any other numerical inputs on a timescale.
But in almost every firm, new tools or process remain a delicate and constant trade between the portfolio manager and the C-levels, where the former must produce and the latter measures. Easy to buy, but how easy to implement?
Organizational structure at the centre
In the 20th century, when print newspapers were ruling, the journalist was god. His work was the absolute source of value for its organization. He was a solist and a maestro. With the advent of the information network, international newspapers nearly died. The decline of print was to be compensated by integrated digital newsroom. The journalist did not disappear but had to reset his working habits from four-night weeks to web-focused day jobs, and to start collaborating with many others very skilled and capable employees to just make sure his message could be relayed.
Threat for management boards of the past century, information digitization brought opportunity to leaders of our time. Kahn raided the New York Times, Bezos the Post, Niel, founder of the French ISP Free, “Le Monde”. They re-organized through new workflows and technology, and turned revenues around.
To lead their investment firms into the future, management teams face similar challenge. They must draft new organizations which fits within a digital work. An organization where the portfolio manager plays center field and no longer libero, and has access to the best possible yet user-friendly software. A multi-talented team to leverage new alternative data and new markets. An investing team where decisions are no longer hierarchical but consensual. A team where financial incentives are aligned between the fundamental analysts, quants, data scientists, computer engineers, risk and portfolio managers.
The Super-hero’s investor
Discretionary investing is certainly not dead. Technology is ready to support and greatly enhance the everyday life of the portfolio manager, torn between information consumption and analysis. But management has a much higher challenge for the forthcoming year: that of reinventing the investing.
At the end of the movie in the title of this article, Superman fights alongside Batman. Wonder Woman offers her last minute support, perhaps as a stark reminder to us that women are still underutilized minority in investment management.
My advice: if you are serious about adapting your investing process, hire Marvel as your next consultant.
 Atul Gawande, The Checklist Manifesto, 2009-2010
 Richards J. Heuer Jr., Randolph H. Pherson, Structured Analytic Techniques for Intelligence Analysis
 Financial Times, Spurious correlations are kryptonite of Wall St’s AI rush, March 14, 2018
 Tetlock, Philip., Superforecasting: The Art and Science of Prediction