If Everyone Is Optimising, Who Finds The Next Opportunity?

For decades, the investment industry has pursued a remarkably simple objective: build a better portfolio. Every generation of investors has been offered new tools, new models and new frameworks designed to improve returns, reduce risk and allocate capital more efficiently. 

From Modern Portfolio Theory and factor investing to smart beta, risk parity and artificial intelligence, portfolio construction has become more sophisticated than ever.

On the surface, this should be a golden age for investing. Yet there is a paradox sitting at the heart of modern portfolio management that receives surprisingly little attention.

What happens if everyone is trying to optimise their portfolios in broadly the same way?
 

When better tools create similar answers

The logic behind optimisation is difficult to argue with. Investors naturally seek high-quality companies, strong balance sheets, attractive returns on capital, durable competitive advantages and predictable earnings growth. 

Advisers, institutions, fund selectors, and algorithms are often seeking many of the same characteristics because, historically, those characteristics have been associated with successful long-term investing.

The problem is that optimisation does not happen in isolation. 

As more investors gain access to the same information, screening tools and analytical techniques, portfolios can begin to converge. The result is not necessarily poor decision-making, but a market that becomes increasingly concentrated around a relatively small number of companies, sectors and investment themes. 

Recent years have provided a visible example of this trend, with a small number of large technology companies exerting an increasingly significant influence over major global equity indices. 

That is partly what optimisation is designed to do. If certain characteristics have historically produced stronger returns, capital naturally gravitates towards them. 

The difficulty arises when vast amounts of capital reach the same conclusion simultaneously.
 

When great companies become crowded trades

A great company does not automatically become a great investment. At some point, the quality of the business becomes less important than the expectations already embedded within its valuation. 

If investors increasingly identify the same companies as the optimal destinations for capital, future returns can gradually be pulled forward into today's share prices.

This is not an argument that today's market leaders are weak businesses. Many are exceptional companies with dominant market positions, impressive earnings growth and significant competitive advantages. The question is whether their quality is still underappreciated, or whether it has already become the central organising assumption of the market.

The same tension has appeared before. Japan looked almost unchallengeable in the late 1980s. Technology looked impossible to ignore in 1999. Property and credit appeared far less risky than they really were before 2008. 

In each case, the problem was not that investors had identified something irrelevant. It was that the story became so widely accepted that price, risk and expectation began to separate from reality.

Today, investors can build portfolios with extraordinary precision, but precision alone does not guarantee opportunity. In some respects, it may simply increase competition for the same opportunities.
 

Why markets still need disagreement

Markets function because investors hold different views of the future. Every trade requires a buyer and a seller who disagree on value, growth prospects, timing or risk. Without that disagreement, price discovery becomes less effective and opportunities become harder to uncover.

The irony is that optimisation can push investors towards greater consensus rather than greater diversity of thought. The more sophisticated the models become, the greater the temptation to focus on the same factors, data points and definitions of quality. 

Over time, investors may find themselves competing intensely for smaller advantages while holding portfolios that look more alike than different.

If everyone is searching for the same answer, fewer investors may be asking different questions. Yet markets have a habit of rewarding those who identify what others have overlooked rather than those who simply confirm what is already widely believed.
 

The forgotten value of looking wrong

Many of the best investment opportunities start by looking uncomfortable. Unfashionable sectors, unpopular markets and misunderstood businesses rarely screen well when prevailing models are built around what has already been rewarded. Yet that discomfort is often where opportunity begins.

Some of the most successful investors built their reputations not by finding the perfect portfolio, but by identifying situations where the market's assumptions were wrong. Their edge came from independent thinking, patience and a willingness to look different before the evidence was obvious enough for everyone else.

That matters because true opportunities rarely arrive looking tidy. By the time a company, sector or theme appears in every optimisation model, much of the opportunity may already have been recognised and reflected in valuations.
 

The never-ending optimisation race

Perhaps the greatest irony is that optimisation has no natural endpoint. Every improvement creates demand for the next improvement, every model encourages a more sophisticated model and every analytical advantage eventually becomes widely adopted and reflected in market prices.

The investment industry may therefore be engaged in a race that becomes increasingly difficult to win. Enormous resources are devoted to extracting ever-smaller advantages, while portfolio similarity continues to rise. Investors may be working harder than ever to achieve outcomes that become progressively harder to differentiate.

The greater risk may be that optimisation is becoming less a search for originality and more a process of refining consensus. 

Because if everyone is searching for the optimal portfolio, who is left to discover the next opportunity? 

Markets often reward what is not yet fully recognised rather than what is already obvious, which raises the possibility that the next source of opportunity may emerge from precisely the places optimisation models are least likely to look. 

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