Investor behaviourMutual fundsDerivatives (F&O)Charles D. Ellis

Most investors don’t lose to the market. They lose to themselves

Published by OneRightAI · 5 min read Download PDF

Maxim: Investing is a loser’s game: win by avoiding mistakes. — Charles D. Ellis

Fifty years ago, a consultant borrowed an idea from amateur tennis to explain why so few investors beat the market. India’s own data now makes his case for him.

For most investors, the fastest way to better returns is not a better pick. It is fewer mistakes.

In 1975, the investment consultant Charles Ellis published an essay in the Financial Analysts Journal called “The Loser’s Game”. The journal reprinted it in 1995, and its abstract still states the argument in one line: professional money management had become a game “one wins by avoiding mistakes rather than by positive achievement” (CFA Institute).

His inspiration was a tennis book by Simon Ramo, a scientist and engineer, called Extraordinary Tennis for the Ordinary Tennis Player. Ramo noticed that professionals and amateurs play two different games. Professionals win points: long rallies of well-placed shots until one of them hits a ball the other cannot reach. Amateurs mostly lose points: into the net, over the baseline, a double fault. As Ellis put it, “Professionals win points, amateurs lose points,” and the amateur “seldom beats his opponent, but he beats himself all the time” (Safal Niveshak).

In a winner’s game, you try to play brilliantly. In a loser’s game, you win by keeping the ball in play and letting the other side make the errors. Ellis’s point was that investing had quietly become the second kind of game, while most people kept playing it like the first.

The professionals are struggling too

If Ellis was right, even skilled fund managers should find it hard to beat a simple index after costs. India’s numbers say they do. S&P Dow Jones Indices’ SPIVA India scorecard for year-end 2025 found that 76.3% of Indian large-cap funds lagged their benchmark over ten years, and 79.0% of mid- and small-cap funds did the same (S&P Dow Jones Indices).

These are not amateurs. They are trained, well-resourced teams with research desks and company access. But they compete mainly against one another, every trade has a cost, and each fund charges a fee that the index does not. Over a decade, small handicaps add up.

The scorecard has limits. Shorter periods look different, and in 2025 only 12.1% of mid- and small-cap funds lagged over one year. Some managers do beat the index, and a few do so for long stretches. The difficulty is identifying them in advance rather than in hindsight. That is the loser’s-game insight applied to fund selection: the safest way to avoid picking the wrong manager is not to need to pick one at all.

Where Indian investors give away points

If professionals find the game hard, individuals who try to hit winners find it brutal. Sebi has now measured this several times. Its study of equity derivatives found that nearly 91% of individual traders made net losses in 2024-25, and their combined loss widened 41% to about ₹1.06 lakh crore, as PTI reported. An earlier Sebi study of intraday trading in shares found that 71% of individual traders lost money in 2022-23, and that among the most frequent traders, those with more than 500 trades a year, the share of loss-makers rose to 80%, according to Business Standard.

That last finding is Ellis’s tennis court in numbers. The more shots the amateur attempts, the more points he loses.

Most long-term investors do not trade options. Their unforced errors are quieter: stopping a SIP in a falling market, piling into last year’s best fund, borrowing to invest, holding a portfolio so concentrated that one bad stock decides the outcome, or paying high costs year after year without noticing. None of these feels dramatic when it happens. Each one is a ball hit into the net.

Even the best players accept that most points are not theirs to control. Roger Federer told Dartmouth’s graduates in June 2024 that he won almost 80% of the 1,526 singles matches he played, yet only about 54% of the points (Dartmouth). A small, steady edge, kept for a long time, was enough. In investing, that edge usually comes from the mistakes you do not make.

Five questions before any move

Playing the loser’s game well is mostly a habit of asking a few dull questions before acting.

  1. Am I trying to hit a winner I do not need? If your goals can be met with steady returns, a high-risk trade adds danger without adding much you need.
  2. What will this cost me every year? Expense ratios, brokerage, taxes on short-term gains and the gap between regular and direct plans are certain. Extra returns are not.
  3. What happens if I am wrong? Leverage, a single large position or money you will need soon can turn an ordinary mistake into one you cannot recover from.
  4. Would I still do this if I could not check the price for five years? If the answer is no, the move is probably about the next few weeks, not your goal.
  5. Is a low-cost index fund my default? Any active fund or stock you add should have to earn its place against that default, not the other way round.

The decision rule follows from Ellis. Make the core of your portfolio something that cannot lose to the market by much, because it is the market, and keep costs low. Then judge every other move by how much damage it could do, not by how clever it feels. If you cannot explain why an action reduces your chance of a big mistake, it is probably an attempt at a winner, and you are allowed to skip it.

Keep the ball in play

Ellis’s essay is now half a century old, and the arithmetic behind it has not changed. Costs are certain. Brilliance is not. And the investor who gives away the fewest points usually ends up ahead of the one who tries for the most spectacular shot.

That is not a counsel of timidity. Holding a broad equity fund through a crash takes more nerve than any trade. It is simply a different idea of skill: not hitting winners, but refusing to hit the ball into the net.

Sources

The Virtual AI Author is an AI writer for OneRightAI.

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