Fundamental investment

Understanding company financial reports and calculating stock valuations, together with fundamental analysis of industries, companies, technologies and business models, are some of the requisites in security selection for portfolio management.

At first glance, these disciplines appear to be entirely mathematical and rules-based; surely the most consistent and accurate application of logic should deliver the best estimates of relative value between stocks and result in the optimal portfolio, shouldn’t it?

Not quite. This description is narrow, and oversimplifies the task. While history may teach us valuable lessons about the future, it is not an accurate sextant by which to navigate a course.

The “science” of investment also has a soft side, an “art” or “fuzzy logic” sometimes attributed to “gut feeling”, which requires a rather different skill set. Creative thinking and an understanding of human psychology to understand why people behave how they do in the real world and to evaluate every possible scenario and its implications to the investor is also needed. Understanding both sides – the maths and the art – and their symbiotic relationship, is a craft.

Inside every forecast for a business and the valuation of its equity are a multifarious range of estimates and assumptions about the future. How far can a company grow, how much market share can they take, how much room is there for a business to improve its operating efficiency and capital structure? To what extent does a company enjoy economies of scope and scale? Does it have pricing power and power over its suppliers?

Working out all the possible opportunities for a business to grow together with potential hurdles requires imagination. Anticipating disruptive changes in technology, shifts in competitive landscape and regulations, and understanding the nature of systemic risks as well as company specific risks takes creativity and a deep understanding of industries, technologies, business models and strategies.

Combining hard logic skills with the creativity required to produce a balanced estimate of future returns, and then constructing a balanced portfolio with enough diversification to avoid volatility spikes, yet with enough conviction holdings to deliver above market long-term returns, that is the real craft of long-term thematic investing.

The efficient market hypothesis (“EMH”) states that asset prices reflect all publicly available information and, since this process is dynamic, constant and immediate, it should not be possible to profit from information-based investment decisions.

This hypothesis may be true to an extent, and it fits well with the idea that investment is logical, scientific and maths-based. However, there are a number of holes in the theory. For example, there are approximately 50,000 listed equity securities on global stock exchanges¹. The portfolio manager, however much endowed with sharp analytical skills, who attempts to analyse this many stocks, faces an impossibly large task and is likely to come unstuck due to lack of time to build any depth of knowledge in any stock, or simply from overwork, or both. As we know, a little knowledge can be a dangerous thing.

We would rather know a lot about a few stocks, rather than little about many. Narrowing the investment universe into a smaller subset of stocks therefore – particularly stocks that share similar traits, such as industry, technology, business model or theme – allows more time for in-depth analysis and considered judgement. By extension, if the lens is focused far enough, it may allow the portfolio manager, assisted by experts from industry and academia, to become a subject-matter expert.

A “pure-play” approach² to thematic investing therefore not only produces portfolios with high exposure to favoured themes, but also concentrates the investment universe down to a size which allows for such an information advantage.

A simple example of the importance of industry and technology expertise, is the ability to understand context and jargon. So much information is so heavily codified that important news headlines in the world of biotech, semiconductors, enterprise software, and many other industries, requires significant sector-specific insight to understand. News which represents fall-off-your-seat, shocking and valuable investment information to some market participants, might not even register as significant to others.

Therefore, even if the EMH is correct in its assertion that all information is available to all investors at the same time, it is undeniable that some investors are likely to be better placed than others to understand the significance of the information. By analogy, a daily train commuter is likely to be able to react to delays and service disruptions more quickly and efficiently than a tourist riding the train and visiting the country for the first time.

Our team has a wealth of experience of investing into their designated theme. They are also supported in their analysis and understanding of the technology and industry-specific dynamics by an "Advisory Board" selected from industry and academia.

Neoclassical economic theory shares some common traits with the efficient market hypothesis, at least in its assumption of uniform and rational behaviour. Specifically, it assumes people have well defined preferences based on price and scarcity, and make well-informed, self-interested decisions based on these preferences.

The trouble with this is that people often behave irrationally. They break the model. They are drawn to high prices thanks to the implicit perception of quality. They make purchases based on nostalgia, the need to attain status, or simply to be different.

A quote attributed to David Ogilvy CBE, founder of Ogilvy & Mather and often described as the father of advertising, sums up the problem of trying to rationalise human behaviour: “Consumers don't think how they feel, they don't say what they think, and they don't do what they say."

If our underlying motivations for doing something are different to what we tell people and perhaps even different to what we tell ourselves, then this might explain why so many apparently economically rationale theories do not work in the real world. If economics is itself a soft science, in the sense that it is a study of human behaviour, then perhaps more of the task of fundamental analysis and stock selection is art rather than science. Put another way, and to quote Ogilvy’s colleague Rory Sutherland, “The fatal issue with logic is that it always gets you to exactly the same place as your competitors.”

On the surface, investment analysis appears cold, logical, mathematical and precise, as many of us perceive economics to be. But under the surface the process is more complex, nuanced and requires creativity, imagination, and in-depth knowledge. This soft science of analysis, prediction, and valuation is a real craft.

In a world of logic-based conformity, quantitative data analysis, and a growing choice of AI-enabled stock selection tools, the softer, creative side of security analysis may prove to be the differentiating factor in alpha generation and the discovery of idiosyncratic value.

¹ Source: Statista, July 12 2024
² Pure-play approach: we focus on companies where more than half of current revenues is derived from goods and services directly related to the theme.