What we mean by evidence based investing

Here at Carbon, we're firm advocates of evidence-based investing. But what does that actually mean?

The financial services industry is full of promises that don't hold up: beating the market, picking winning stocks, timing the market perfectly, guaranteed returns. It's an appealing pitch — who wouldn't want a shortcut to a comfortable retirement? But decades of academic research tell a different story. Consistently outguessing the market isn't a repeatable skill; it's largely down to luck, and the odds are stacked against anyone who tries.

The truth about beating the stock market

Markets are hard to beat consistently. Picking stocks on the belief that their price is wrong is like betting on the horses. It can go either way. Even professional fund managers struggle to time markets successfully. And as for guaranteed returns: if investing carried no risk, why would it offer a return at all?

Evidence-based investing is grounded in empirical research and decades of observation about how markets actually behave. It isn't guesswork, gut feeling, or a belief that any one person holds the key to predicting the future. It's an approach built on verifiable facts and observation.

In a world of slick marketing, spin and hype, the idea of respecting evidence is frequently undervalued. As the great Scottish philosopher David Hume once said, ‘a wise man proportions his belief to the evidence’. The danger of doing otherwise was highlighted by the fictional detective Sherlock Holmes, who said if you theorise before you have the data, you begin to twist facts to suit your theories.

The truth, supported by overwhelming evidence, is that consistently beating the market over the long term is extremely hard. Fund managers who outperform in one year rarely repeat the feat the next. And the small number who do tend to capture those extra returns for themselves through charging higher fees for their apparent skill.

So, why are markets so hard to beat consistently?

Competition. Security prices reflect the aggregated wisdom of millions of buyers and sellers, each with their own view of what a stock is worth. New information, like earnings reports or economic data, are factored into prices almost instantaneously. As information flows faster and trading systems grow more sophisticated, finding a genuine edge gets harder, and holding onto it consistently, day after day, becomes nearly impossible. Prices will inevitably contain mistakes. The question isn't whether mistakes exist, it's whether you can identify them in advance, reliably, every single day. History suggests not.

Arithmetic. Before costs, the market's return in any period is just the average of every investor's return, weighted by how much they hold. So, for every investor who beats that average, another must lag it by the same amount. In aggregate, active investing is a zero-sum game before costs, and a losing one after them.

Cost. Betting against the market isn't cheap. There's the cost of researching individual stocks, the cost of trading, the cost of falling in love with a stock or sector and overpaying for it and, above all, the cost of the salaries and bonuses fund managers demand for the attempt. Beating the market isn't enough on its own; you have to beat it by enough to cover these costs, and do so consistently, year after year. For the end investor, that turns a zero-sum game into something worse than zero-sum.

News. Even a rock-solid view on a stock's value today assumes tomorrow's news won't change the picture. A company's advantage can vanish overnight — through new technology, a disaster, a governance failure, or new legislation etc. Correctly predicting a stock's future price means correctly predicting tomorrow's headlines. Do you know anyone who can do that?

What does the academic evidence tell us about traditional money management?

There's a substantial body of research illustrating how difficult it is for money managers to outperform the market consistently.

The SPIVA (S&P Indices Versus Active) Scorecard compares actively managed funds against their appropriate benchmarks across major global markets [1]. The research highlights a consistent pattern: actively managed funds have tended to underperform their benchmarks over both short and long-term periods, and even where a majority of funds in a category have outperformed over one period, they've usually failed to repeat that over multiple periods.

In the most recent U.S. SPIVA Scorecard, 79% of actively managed large-cap U.S. equity funds underperformed the S&P 500 in 2025, and over the previous 15 years, 90% underperformed [2]. The picture in Europe is similar: over the past 10 years, 97% of funds underperformed the S&P Europe 350 [3].

This isn't a new phenomenon. Professor Eugene Fama (a 2013 Nobel laureate) and his research partner Kenneth French studied the performance of around three thousand US mutual funds from 1984 to 2006 [4]. They found that, on average, fund returns lagged the market by roughly the amount of the fees charged, and that while some individual managers did outperform, it was almost impossible to distinguish genuine skill from luck — with thousands of funds in any given sample, some will always beat the market by chance alone.

If you're new to the idea of evidence-based investing and would like to learn more, why not get in touch? We'd be happy to answer any queries you may have.

[1] SPIVA (S&P Indices Versus Active) Scorecard, by S&P Dow Jones Indices. Available at: https://www.spglobal.com/spdji/en/research-insights/spiva

[2] SPIVA U.S. Scorecard Year-End 2025, by S&P Dow Jones Indices, 2026. Available at: https://www.spglobal.com/spdji/en/documents/spiva/spiva-us-year-end-2025.pdf

[3] SPIVA, Europe region (interactive), 10-year data vs. S&P Europe 350, by S&P Dow Jones Indices. Correct as of July 2026. Available at: https://www.spglobal.com/spdji/en/research-insights/spiva/#europe

[4] Luck Versus Skill in the Cross Section of Mutual Fund Returns, by Fama, Eugene F. and French, Kenneth R., December 2009.