I have always been interested in the application of theories, especially if they give greater understanding to financial markets and if they help towards identifying opportunities when investing in equities.
The two most important academic theories that I have encountered have been The Efficient Market Hypothesis (popularised by Eugene Fama[1]) and later works around behavioural economics (Daniel Kahneman, Amos Tversky, Stephen Levitt, Stephen Dubner and Richard Thaler). I have struggled with their relevance in providing a framework to help me identify businesses that can offer attractive investment opportunities.
The ‘Efficient Market Hypothesis’ has several implications, which I have always found uncomfortable, namely, that share prices reflect all available information, financial markets are efficient and that it is impossible to consistently beat markets. I hear you say that maybe all fund managers have this view!
To believe that share prices reflect all available knowledge is a hard one to swallow. I am more inclined to accept the Graham/Buffet view that “In the short run, the market is a voting machine. In the long run, it is a weighing machine[2].” Share prices reflect the value of the share at that moment, it’s a market after all, but it says little about any long-term opportunity or value.
Even large and relatively stable businesses can at times have volatile share prices. Price movements also reflect external risks or opportunities, like falling interest rates, war, political and regulatory upheaval, but at times the movements appear excessive and can reflect an absence of liquidity, rather than any dramatic change in the long-term prospects for the business.
The Costco share price has risen over 60% this year, and the price earnings ratio expended from 40X to 50X, yet their business model is unchanged, and forecasts have not significantly been upgraded. When was the share fair value? At the beginning of the year, now, or somewhere in the middle?
I would agree that financial markets are still reasonably efficient, particularly over the longer term. The frauds are eventually unearthed, but some of these previous ‘glamour shares’ still may have achieved multi-billion valuations on the way! Value eventually wins out, either by persistence or by corporate activity. We have times when fear and greed drive excessive share price movements. In addition, we have interventions, designed to deliberately change market prices, such as zero interest rate policies post the global financial crisis. How can this theory say anything of value in these conditions?
Behavioural economics tried to address some of the human failings of economics, such as recognising that we are not always rational and we have biases that effect our decisions, such as loss aversion compared to profit maximisation. This approach gives insights that seem to more closely reflect real life behaviour, but again I struggle to find much relevance when applied to identifying investment opportunities. Except perhaps in recognising that investors can be irrational and are willing to follow trends in search of easy returns. The value is in understanding the drivers of sentiment and doing the opposite i.e. not following the herd and taking a counter-cyclical approach looking where other investors are not looking!
A weakness in many approaches is the focus on earnings. Most businesses produce ‘adjusted’ or ‘underlying’ earnings. The objective is to strip out anomalies or exceptional items that detract from the underlying performance of the business. The variance in these numbers can be dramatic. For example, Pfizer the US drugs company reported GAAP diluted earnings per share of $0.37 for the year ended 31st December 2023, but adjusted earnings of $1.84, almost 5 times greater. I would argue that both measures are wrong, and that care should be taken to try and interpret what the ‘real’ numbers should be.
It is no surprise that ‘adjusted’ figures are typically higher. While some of the adjustments might seem reasonable, such as the amortisation of certain intangible assets, what about regular restructuring or litigation, which are cash costs to the business? But what about regular restructuring or litigation, which are cash costs to the business? Does the Efficient Market Hypothesis assume that all investors can see through to ‘real ‘earnings? This begs the question, are earnings important and if so what earnings?
Literature from legendary investors such as Graham, Dodd and Buffet offer more clarity by taking a longer-term horizon and focussing on cash, but they suffer to an extent from the changing reality of businesses today. These classic investors are shorter on theory but offer more on principle and more practical guidelines. Any loss of clarity is not from the ideas, but from the more recent relative importance of intangible assets in the success of a business. Smart software and systems are much harder to value than plant and property but are increasingly vital to investment returns and customer retention.
A sense of history or perspective is important. While every day is unique, there are clues in the behaviour of markets and how businesses performed through previous events and economic cycles. The ‘Structure-Conduct-Performance’ paradigm provides a useful framework to assess the competitive position and expected returns. Investors should value barriers to entry or economic moats to protect returns. Porter’s Five Forces is also a useful tool to assist, although many have underestimated the impact of new entrants who through the application of technology have totally changed the shape of an industry (think Amazon or electric vehicles!) If nothing else, taking a step back and looking at the longer-term trends and structure of an industry, may not identify the specific winners, but it might help avoid the value traps.
Trends by their nature can be slow and can be overwhelmed by other factors. Nevertheless, it is easier to have the wind at your back and sectors such as automation, energy efficiency and healthcare will clearly benefit from changes in our demographics and environmental legislation.
A bugbear of mine when meeting undergraduates and asking them to describe what they have learned or what they most enjoyed working on, the typical answer is “my DCF model”. My heart sinks! Typically, these models revel in complexity, to try and estimate beta and the cost of capital, rather than a careful consideration of the assumptions, such as the outlook for the industry and the prospects of the business; it’s the assumptions that are important, not the quantity of the data! Minor changes to the models can often have a big impact on the valuation.
Behavioural economics has a lot-to say about how we perceive risk, but this is rarely applied by fund managers in portfolio construction. Despite protestations of ‘stock picking’ most portfolios exhibit a clear relationship between size of the market, industry and company weightings, rather than seemingly more worthy parameters, such as value and risk.
Return is about buying an undervalued share. Processes vary, but the most successful appear to be based around a longer-term assessment, effective barriers to entry and potential cash generation.
Risk is often perceived as the weighting against a benchmark or index. However, for clients it is typically about losing money! Is risk better described as the opposite of return, namely the possibility of over-paying for an investment and losing money? So why don’t managers run their funds to avoid losses? Clearly there is safety in crowds and avoiding 4th quartile relative performance is important to job security.
An alternative approach might be to consider not just core underlying estimates when calculating the valuation but re-evaluating these assumptions and coming up with a range including a ‘best’ and ‘worst case’ and then to try and assess the potential for these to occur. Sometimes a valuation looks cheap, until operational and financial leverage are conservatively assessed, and the potential ‘worst’ case may result in a complete reassessment of the risk of the investment.
This is of course difficult when dealing with new issues or emerging growth biotech and tech businesses. The ‘worst case’ is often total loss but should be tempered by the potential upside from the realisation of core assumptions and ‘best case’ returns which can be exceptional. When dealing with new technologies, more work is involved to try and understand not just the potential disruption, but also a greater appreciation of the finance and skills required to capture the market. Even the experts’ views can still widely vary and investors may prefer a diversified approach and hope that some of the stones are diamonds that offset the scattering of fools’ gold.
Theories are interesting and may over time, provide a more constructive narrative that can explain market performance. We all know that it looks obvious in hindsight and successful theories often emerge from their fit with this history. Processes are important as it gives managers support in times of stress, to make rational decisions, rather than be subsumed by the madness of crowds. In my opinion, theories have not helped construct a portfolio, identify opportunities or properly appreciate risk in a form that investors appreciate. Too many of the theories explain what has happened, adding complexity does not necessarily improve validity. The hard part is the accuracy of the assumptions and the investors’ awareness of their potential forecasting errors.
Although businesses are now more driven by intangible assets, classic investment practitioners like Graham, Buffet, Lynch, Templeton etc have been successful by taking a long-term and disciplined approach. They have focussed on businesses with strong barriers to entry, high returns, stable cash flow and have been averse to weak balance sheets and high levels of debt. These texts appear to offer a more instructive starting point for investors than the more abstract market theories, plus in my view, they are much more enjoyable to read!
Graham H Campbell
Senior Investment Director
River Global Investors.
[1] Nobel Prize winner and best known for his work on EMH.
IMPORTANT NOTICE
This document has been prepared by River Global Investors LLP (“RGI”). RGI is authorised and regulated in the United Kingdom by the Financial Conduct Authority (Firm Reference No. 453087) and is registered in England (Company No. OC317647), with its registered office at 30 Coleman Street, London EC2R 5AL. This article does not constitute an investment recommendation and should not be used as the basis for any investment decision. Opinions, estimates and projections in this article constitute the current judgement of the author as of the date of this article.