Disruption, disruption

I have been working in the active management industry since leaving school almost 29 years ago. One could be forgiven for thinking that I was entering these latter stages of my career more depressed than when I started it. After all, the news is rife with articles talking about how the influx of passive is inexorable, how numbers of jobs in active management are at decade lows, and how active management firms are consolidating to the point at which there will be few of us left in the brave new world.

Most of these things are true. Our industry is going through a period of disruption that is as fundamental as the disruptions facing the media industry (streaming), the transportation industry (Uber/Lyft), and the automotive industry (electric vehicles/ride-sharing), to name a few.

As with any disruption, there will be winners and losers, and where there is change there is opportunity. So, as a natural contrarian, I see many of these developments as not only healthy but positive for the long-term future of active management. Why am I optimistic? As in other industries that have been disrupted, asset management has seen an exponential increase in the amount of data that we can capture, and in the new approaches to how that data is used.

Information that is differentiated, granular, and, to borrow an overused word, ‘alternative’, has become available, and it has opened up a whole new world of analytical possibilities. In addition to the volume of data available, there are new ways of processing this data, with users pushing past traditional time-series or company accounts analysis to incorporate machine-learning and pattern-recognition techniques that draw out important inferences about company and industry fundamentals.

This creates something that is exciting for active managers: renewed ‘information asymmetry’ – meaning one party has more information than another party. However, the explosion of data is adding to the cacophony of information that active managers are already immersed in (and in some cases overwhelmed by). Therefore, how one filters and analyses the data, and how we draw inferences from it, rather than simply possessing it, will be our competitive advantage.

This idea of informational asymmetry is a powerful one, which is rooted in the origins of active management. Simply put, if a potential investor has information that others do not, it has a competitive advantage.[1] For example, a manager who can read company reports in a foreign language has an advantage over those who cannot. Similarly, an investment manager who can tour a company’s physical locations may see informative sales trends which are undetected by their counterpart who has not visited those locations. A similar argument can be made where a manager has access to information more quickly than someone else. These sources of competitive advantage are important, and have clear parallels with the law of comparative advantage in economics. Of course, there is a third source of competitive advantage: skill in the interpretation of information.

Data overload to active management 2.0

Three factors have helped diminish information asymmetry over the last couple of decades: 1) the near instantaneous dispersion of information on the internet; 2) the ubiquitous use of English as a business language; and 3) regulation requiring standardisation of company accounts. The effect of the reduction in informational asymmetry has been that the competitive advantage has been reduced to delivering a superior interpretation of a limited number of commonly known facts. Essentially, investment managers have been forced to demonstrate their skill (and hence their competitive advantage) by being more insightful in their judgements on a relatively limited number of data points or variables.

The growth of data has now reached a tipping point. We live in an era of data deluge. Data abounds, and it is easier than ever to create new data sets. In fact, there is now so much data that active managers can struggle to make sense of it all. However, once these difficulties are overcome, firms can create proprietary data sets and establish proprietary ways of analysing data, both of which increase information asymmetry. For example, if one has access to a data set about a particular product or service, and can understand the usage (or the breakdown rate) of the product or service at a more detailed level than (or in advance of) the market, one has an informational advantage.

The explosion of data has pushed active managers into new ways of looking at the information they receive. It has required new techniques to filter, combine and analyse that information. Data science, machine learning, artificial intelligence, and related techniques allow us to obtain insights into what drives a company’s success in ways that were not possible before. This, in turn, is hugely exciting for those seeking to ‘beat the market’. In effect, the very same forces that made the market more efficient (a huge increase in publicly available information) now have the potential to make the market less efficient by increasing information asymmetry and greatly expanding the ability to evaluate companies in different ways.

A simple analogy would be to think of the classic game of Tic-Tac-Toe (or Noughts and Crosses, if you live in the UK). When the game is played with a 3×3 matrix, it is very difficult for one player to consistently beat another player – everyone has the same information set, but ways of expressing this skill are limited.[2] Compare that to the equally classic game of Go, where, although each player still knows all the rules which determine how each player can play, the possible combinations (and hence the ways to win) are exponentially greater than those of Tic-Tac-Toe.[3]

This potential for both acquiring an informational advantage and having larger degrees of freedom in the analysis could well usher in a new golden era of active management.

Understanding the world

At Newton, the explosion of data has enabled us to both validate and improve what we have been doing intuitively for more than 40 years – namely investing according to our strongly held belief that the global economy is underpinned by themes that touch many sectors and regions simultaneously and for long periods of time. Often these themes are the result of disruption in the global economy, which is brought about by technological change or the emergence of a supernormal trend driven by natural factors (e.g. demographics, the natural environment). These themes affect multiple sectors and regions of the economy simultaneously, and provide a common factor which affects returns and allows us to think about companies in a differentiated (and superior, we believe) way to the traditional classifications of either sector or region.

By combining machine-learning techniques with increasingly abundant data, we are able to create new in-house data sets and gain insights into how themes affect companies (and economies) in ways that were not previously evident. This is one element of our potential informational advantage. I expect that other active managers will do things that are similar in relation to other topics, and find their own informational advantage. All of this raises the likelihood, we think, that the ability of active managers to ‘beat the market’ will increase over time.[4]

All things change through time, and investing is no different. The world we operate in has changed. Economies are interlinked, and companies, supply chains, and customer bases are increasingly global in nature. Business models are evolving ever more rapidly, and technology, once a sector, is now omnipresent across almost every sector across the economy. This has meant that understanding the big picture, the themes driving the underlying change, is more important than ever.

In this world of change, however, some things remain the same. Good investors are inherently competitive, inquisitive, and diligent, and will always remain so. What has changed is the tools being used to express those traits. The investment management industry has evolved from using an HP-12C calculator to work out the internal rate of return of an investment, to using Python code to scrape words from transcripts in multiple languages. It is as if the game board has opened up, and there are more ways to play than ever before.


[1] Regulators, quite rightly, restrict this to publicly available information, but just because information is in the public domain does not mean it is equally distributed or simultaneously digested.

[2] Indeed, there are 255,168 possible variations of Tic-Tac-Toe.

[3] The number of legal positions in Go on a 19 x19 board is 2.082 X 10170

[4] This is predicated on the fact that any informational advantage whether in source data or the interpretation of that data remains proprietary – if every market participant has the same information we are back to where we were before.

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