Stop kidding yourself: Nobody can “time the market”

Overview

“The distinction between investment and speculation in common stocks,” wrote Benjamin Graham in The Intelligent Investor, “has always been a useful one and its disappearance is a cause for concern. We have often said that Wall Street as an institution would be well advised to reinstate this distinction and to emphasise it in all its dealings with the public. Otherwise the stock exchanges may someday be blamed for heavy speculative losses, which those who suffered them had not been properly warned against.”

Most people are unaware of – or ignore – Graham’s crucial distinction; this article emphasises and elaborates it. I show that although investment is hardly easy, speculation – that is, “timing the market”— is all but impossible. Hence the number of successful traders is likely minuscule.

Specifically, I demonstrate that

1. the short-term, CPI-adjusted total returns of markets (such as the S&P 500 Index, All Ordinaries Index, etc.) and stocks (such as BHP, etc.) are almost perfectly random – and therefore, in effect, completely unpredictable. As a result, and except under very rare conditions, which I specify, virtually nobody can consistently “time the market.”
2. unless you’re a perfectly prescient trader, which nobody ever has been, is or will be, “buy and hold” investment generates higher average short-term returns than speculation;
3. short-term results compound over longer periods: hence investment (“time in the market”) handily beats speculation (“timing the market”).

If you accept that practically all of the time nobody can time the market on a consistently profitable basis, then you must conclude that, for effectively all speculators, traders and market-timers, poor results – and potentially large losses – are all but assured.

“Timing the Market” as a Basis of Speculation

Investors differ fundamentally from market-timers, speculators and traders (Table 1). An investment, contended Graham, promises the safety of an investor’s capital and a satisfactory return on her capital; transactions which fail to meet these criteria are speculations. Investment is a long-term process whose goal is the accumulation, as circumstances permit, of securities at prices equal to or below prudent estimates of their values. The company is the unit of analysis, and the appraisal of its financial and operating history underpins the investor’s estimate of its value. 

Investors own long-term stakes in companies’ equity; speculators, on the other hand, swap fleeting interests in bets over securities’ prices. An investor is an owner; a speculator, in sharp contrast, is a punter.

Table 1: Investors versus Market-Timers, Speculators and Traders

Speculators bet on short-term fluctuations of securities’ prices; gut instincts, market sentiment and recent and ephemeral events typically prompt amateurs’ bets; professionals rely upon algorithms. Because they’re focused almost exclusively upon the short-term (intervals of 12 months or less), speculators ignore the medium and long terms. Accordingly, they often deny the need even to consider – never mind analyse – companies’ financial statements.

Graham regarded speculation as a form of gambling; tellingly, most speculators also gamble in casinos, wager on the results of sports, etc. For both gamblers and speculators, quick profits are the goal – and, over numerous speculations or spins of the roulette wheel, the gambler-speculator almost invariably loses. Yet by chance a percentage of his bets succeeds – and thus whets his appetite for more speculation and further losses. Graham repeatedly warned against speculation: it can be ephemerally exciting but eventually it’s almost always inimical to the accumulation of wealth.

The core difference between investment and speculation is timeframe and objective: investors seek long-term returns through companies’ operations, earnings and dividends; speculators crave short-term gains via fluctuations of securities’ prices.

The phrase “timing the market” refers to the attempt – which is a basis of speculation – to predict the future movements of a security’s price or a market’s level. Market timers claim that they can anticipate and profit from the fluctuations of stocks’ and funds’ prices, markets’ levels, etc., over days, weeks or months. Market timers are therefore speculators. If they can foresee peaks and troughs they can buy low and sell high at optimal times – and thereby outperform a “buy-and-hold” strategy of investment.

The greater is the disparity between today’s price and the market-timer’s prediction of tomorrow’s price, the bigger is the opportunity to speculate. Only secondarily, if at all, does the speculator regard a stock as an equity interest in an actual business; typically, it’s merely a ticker symbol, blip on a screen or squiggly line on a graph.

It’s important to emphasise: Graham regarded market timers as speculators, and speculators as gamblers – and NOT as investors. (The most recent (2024) edition of The Intelligent Investor, including Jason Zweig’s Commentaries after each chapter, provides full details.)

Market-timers aim to profit from the alleged patterns of short-term price fluctuations. The basis of speculation and the source of their losses is their pervasive confusion of chance fluctuations as “trends.” Speculators seek to buy low and soon thereafter to sell high – or, by short selling, reverse the order by selling high and buying low. If a trader believes that a particular stock or the overall market will rise, he buys what he believes will lift with the tide. Conversely, if he anticipates that a market or stock will decline, then he sells what he holds in order to avoid potential losses – and perhaps short-sells what he doesn’t own in order to generate further gains.

If speculators can consistently predict accurately, they’ll benefit from downdraughts as well as upswings.

Specifically, if market-timers can anticipate short-term movements of prices, their returns will greatly exceed “buy-and-hold” investors’. The opposite, however, is seldom mentioned: the less accurate are speculators’ predictions, the poorer will be their returns – both in absolute terms and compared to investors’.

Greatly outweighing speculators’ potentially large upside is their actual – and enormous – downside: it’s usually impossible to foresee short-term market fluctuations. Moreover, the futile attempts to do so initially generate higher costs; later, they encourage emotional and irrational decisions; and ultimately, they generate cumulative losses of varying magnitudes.

Why Market-Timing Is Effectively Impossible

Except under rare circumstances, market-timers can’t consistently speculate successfully. That is, they can’t repeatedly and accurately anticipate short-term movements of a market’s level or a stock’s price, etc. That’s because these fluctuations reflect mere chance. Random movements are irregular variations around a mean. They have no identifiable cause and are trendless; hence they’re unpredictable. Successful speculations are merely lucky guesses; these “successes” are therefore ephemeral.

Market-timing fails because it ignores a fundamental, obvious and insuperable difficulty: stocks’ and markets’ returns are random; by definition, random phenomena are unforeseeable – and nobody can predict what’s inherently unpredictable.

The Standard & Poor’s 500 Index, the leading index of American equities and thus the world’s single most important stock market index, provides an example. Using data compiled by Robert Shiller for his book Irrational Exuberance (Princeton University Press, 1^st ed., 2000) and updated ever since, I’ve computed its CPI-adjusted total 12-month return (that is, including dividends) for January 1871-January 1872, February 1871-February 1872, ... and April 2024-April 2025.

The closer these ca. 1,850 returns’ distribution resembles a normal (that is, bell-shaped) distribution, the more random they are – and the more unpredictable their future 12-month returns will be.

A Quantile-Quantile (“QQ”) plot provides one means to assess the extent to which a variable follows a normal distribution. (A quantile is a value below which a given percentage of data falls.) A QQ plot compares the quantiles of the S&P 500’s 12-month returns to those of a normal distribution whose mean and standard deviation equal the returns’. If the returns are normally distributed, the points on the QQ plot will fall along a straight line.

Figure 1 shows that, except at the extremes, the S&P 500’s 12-month returns over the past 150 years have been almost perfectly normally distributed. The distribution does, however, have “fat tails.”

Figure 1: Quantile-Quantile Plot, S&P 500 Index’s CPI-Adjusted Total 12-Month Returns, January 1872-April 2025

Accordingly, except on the rare occasions when its 12-month gains or losses are extremely high, short-term returns are random and thus unpredictable. Only on those very rare (ca. 1% of the time) occasions when the S&P 500’s monthly return soars to extremes (at the nadir of the Great Depression, the 12 months to June 1933, for example, its CPI-adjusted total return attained its all-time maximum of 151%) does market timing become possible. Extremely high or low returns in one 12-month period reliably (but not invariably) beget a subsequent regression towards the returns’ mean (8.7%).

The S&P 500’s short-term returns since January 1900, January 1950 and January 2000 are similarly random. So are the All Ordinaries Index’s CPI-adjusted total 12-month returns since 1975. 

What about individual stocks? Figure 2 provides a QQ plot of BHP’s CPI-adjusted 12-month total return since January 1991. Again, except when its gains or losses are extremely high, BHP’s short-term returns are random and thus unpredictable.

Figure 2: Quantile-Quantile Plot, BHP’s CPI-Adjusted Total 12-Month Returns, January 1991-April 2025

I’ve not found a company whose short-term returns, measured over long intervals such as 20 or more years, aren’t nearly random (albeit with “fat tails”). Accordingly, to my knowledge there’s no company whose CPI-adjusted, total 12-month returns are anything other than unpredictable the vast majority of the time.

Let’s recapitulate – and distinguish what (1) we know, (2) don’t know and (3) can reasonably infer.

We know that the S&P 500 Index’s CPI-adjusted, 12-month total returns over the past ca. 150 years have closely approximated (albeit with “fat tails”) a standard normal distribution; we also know that this distribution’s mean is 8.7% and that its standard deviation is 19.2%.

We don’t, however, know what the Index’s CPI-adjusted total return will be 12 months hence; that’s because we know that past returns have been – and, we infer, future ones will be – random. Assuming that it derives from a normal distribution whose mean is 8.7% and whose standard deviation is 19.2%, we don’t know what the Index’s return over the next 12 months will be, but we can infer the probability that particular returns will occur.

Given the distribution of past returns, and assuming that future returns have the same distribution, mean and standard distribution, there’s a 95% chance that the Index’s 12-month return in a year’s time will lie within ± two standard deviations of its mean, i.e., within the range -29.7% to 45.1%. Hence there’s a 2.5% probability that it will be less than -29.7%, and a 2.5% chance that it’ll be greater than 45.1%. There’s also a ca. one-third probability that the 12-month return will be negative, and a ca. two-thirds chance that it’ll be positive.

Market-timers are trying, perhaps unwittingly, to predict the unpredictable. They’ve been fooled by randomness. That’s why they’re occasionally lucky – but eventually they virtually always lose.

Market-Timing, Trading and Speculation: Three Stylised Examples

We’re now in a position to answer a fundamental question: why, despite the impossibility of consistently predicting the unpredictable, do speculators doggedly pursue their futile attempt to “time” the market?

Let’s compare the actual results of a “buy and hold” investor with the potential results of the imaginary speculator who can anticipate price movements with perfect precision. Consider the S&P 500’s rolling 12-month intervals since January 1871. Assume that on the first day of each of these intervals an investor (1) purchased a portfolio of securities which perfectly mimicked the Index, and (2) held it 12 months, i.e., until the last day of the interval’s last month.

What about the perfectly prescient speculator? Let’s assume that during each of the intervals he can unerringly foresee (1) the Index’s 12-month low and (2) its 12-month high (when the high precedes the low this speculator short-sells). Accordingly, and as befits a speculator, most of the time his results won’t be 12-month results: they’ll cover fewer months. However, in order to maximise comparability with the investor’s actual returns, I’ve calculated both sets of returns on a 12-month basis.

How do the perfect speculator’s results compare to the “buy and hold” investor’s? Table 2 summarises them. Three points are most noteworthy:

1. the perfectly prophetic speculator’s average short-term return (24.4%) is almost three times greater than the investor’s (8.7%);
2. the investor’s worst result is a massive loss (58.1%); the faultless speculator, however, generates NO losses (his minimum return of 4.4%);
3. the standard deviation of the flawless speculator’s returns (15.7%) is lower than the investor’s (19.2%). The perfect speculator hasn’t merely generated a much higher return; he’s also generated a less variable return.

Table 2: CPI-Adjusted 12-Month Total Returns, S&P 500 Index, January 1871-April 2025

Why, for many people, is speculation so enticing? If you’re prepared to ignore its risks, its potential rewards to the perfect speculator are immense. Alas, there’s no such thing as the perfect speculator; moreover, for imperfect ones actual risks far outweigh the potential rewards.

Market-timers must anticipate not merely the timing and direction of what they (mistakenly) regard as short-term price trends, which are actually random fluctuations, but also the magnitudes and durations of fluctuations around these alleged trends.

If a speculator were able to predict these things perfectly accurately, buying at a low price and selling shortly afterwards at a higher price (or, by short-selling, first selling high and then buying low), Table 2 tells that he’d reap huge profits and no losses. I suspect that it’s precisely this tantalising prospect that tempts so many people to speculate, and “experts” to assert that they can “time” the market. What motivates market timers and traders? Ultimately, it’s the allure of fast and easy money.

Alas, in practice it’s effectively impossible to time one’s purchases and sales to the standard of precision that’s required to outperform the buy-and-hold investor.

Three examples demonstrate this vital point. Figure 3, Figure 4 and Figure 5 each depict the prices of three hypothetical stocks at 12 equally-spaced points in time. In each example, speculators have multiple opportunities to buy low and sell high. In Figure 3, the three stocks’ prices at Time #1 and Time #12 are identical: they all increase from $1.00 to $1.50. But the prices at Time #2-11 are random (I’ve used a random number generator to produce them). Moreover, Stock #1’s 12 prices have a standard deviation of 15%, Stock #2’s is 17.5% and Stock #3’s is 22.5%.

Figure 3: Three Stocks’ Rising Prices

Stock #1’s price thus fluctuates least, #2’s more and #3’s most; Stock #1 is thus least attractive, and #3 most attractive, to speculators.

Figure 4: Three Stocks’ Stagnant Prices

In Figure 4, the three stocks’ “trend” is an average price of $1.00 over the 12 time periods. Again, in Time #2-11 I’ve used a random number generator; again, the fluctuation of Stock #1’s price is relatively small (standard deviation of 15%), Stock #2’s price fluctuates more (standard deviation of 17.5%) and Stock #3’s most (standard deviation of 22.5%). In Figure 5, each stock’s price decrease from $1.50 at Time 1 to $1.00 at Time 12; the other prices are random and the SDs remain, respectively, 15%, 17.5% and 22.5%.

In each of these three scenarios, the buy-and-hold investor’s results are easy to calculate. If any of the three stocks in Figure 3 is purchased at Time 1 (i.e., at $1.00), held until Time 12 and then sold (at $1.50), then (ignoring the transactions’ cost and capital gains tax) the capital gain is $1.50 - $1.00 = $0.50 per share and the 12-month return is ($1.50 - $1.00) ÷ $1.00 = 50%. In Figure 4, the capital gain is $0.00 per share and thus the 12-month return is 0%; and in Figure 5, the capital loss is $0.50 per share and the return is ($1.00 - $1.50) ÷ $1.50 = -33%.

Figure 5: Three Stocks’ Falling Prices

Conceptually, the speculator’s results are less straightforward. Let’s start with a simplifying assumption: for each of the three stocks in each of the three scenarios, the perfectly psychic speculator anticipates each of the movements of prices, i.e., from Time #1 to Time #2, from Time #2 to Time #3, ... and from Time #11 to Time #12. From one month to the next, he profits – either by selling high or short-selling low.

The prices in Time #2-11 are random; accordingly, so are his profits from one month to the next. I’ve therefore conducted a simple “Monte Carlo Simulation.” Specifically, I repeatedly generated series of random prices between $1.00 and $1.50, computed each month-to-month gain, summed the total gain at Time 12 for each iteration and computed the average total gain over all iterations. After ca. 30 “runs” the results converged to those summarised in Table 3.

For the sake of simplicity I’ve continued to assume that transactions are costless and that there’s no CGT. I’ve also assumed two varieties of speculator: the first (“perfect”) always identifies the price’s direction of change from one time to the next; he also perfectly foresees the magnitude of each change of price.

The second speculator is imperfect: he can “predict” the direction of change randomly (that is, just 50% of the time, like the toss of a coin) and the movements of prices from one time to the next only within 5% of the actual price; for example, if the actual price is $1.00 he predicts randomly within the range $0.95 to $1.05.

Table 3 summarises the results of this experiment. Not surprisingly, the imaginary “perfect” speculator obtains by far the best results. Under all conditions he handily beats the imperfect speculator – and absolutely thumps the “buy and hold” investor. The perfect speculator performs best in a rising market, not as well in a falling one and least well in a stagnant market. Further, the greater is the extent of price fluctuations, the better, on average, will be the perfect speculator’s results.

Table 3: Comparing Investors’ and Speculators’ Returns

Yet the perfectly clairvoyant speculator is a figment of the imagination. In the real world, Table 3’s results devastate the pretensions of market-timers.

In 6 of the 9 scenarios, the “dumb” (in the sense that she disclaims any ability to foretell prices) buy-and-hold investor’s results exceed the imperfectly omniscient speculator’s (who, presumably, does make such a claim). Buy-and-hold generates a higher return than imperfect speculation in a rising market; in a falling market, it generates a lower loss; and in a stagnant market, it generates an equivalent result.

Across the three scenarios, the buy and hold investor’s average return is 5.7%. The average return of the imperfect speculator – who, remember, predicts actual prices within a range of ± 5% – is 0%. A small deviation from perfect prediction eliminates speculators’ returns.

These experiments tip the scales heavily in the imperfect speculators’ favour – yet the “buy and hold” investor generates better results than the imperfect speculator. How many speculators can invariably foresee price changes which are within ± 5% of the actual price? I strongly suspect that there are very few.

In this experiment, which analysed computer-generated random (and therefore realistic) data, buy and hold investor beat all but the purely imaginary “perfect” market-timer. In the real world, as we’ll now see, investors also outperform speculators.

“Time in the Market” versus “Timing the Market”

I’ve demonstrated that (1) short-term returns are random and therefore that “market timing” is futile, and (2) over multiple iterations the results of “buy and hold” investment usually exceed – and never lag – the returns from imperfect speculation. Accordingly, we’re now in a position to answer another crucial question: why does investment (“time in the market”) beat speculation (“timing the market”)?

The answer is two-fold: because they buy and hold, investors’ unrealised gains tend over time to compound; because they constantly buy and sell in response to random fluctuations) speculators don’t accumulate unrealised gains – and their realised losses compound.

The phrase “time in the market” refers to the strategy of investing for the long term – regardless of markets’ and individual stocks’ short-term fluctuations. It’s effectively a synonym of “buy and hold.” By remaining invested over the long term, rather than trying to time the market by chopping and changing over the short term, investors benefit from returns’ compounding effects and markets’ generally upward long-term trend; they also minimise transaction costs and defer taxes.

Unlike market timing, which attempts to predict the unpredictable and thus almost invariably fails, time in the market reliably underpins long-term investors’ gains.

Let’s again compare the actual results of a “buy and hold” investor with the potential results of the imaginary speculator who can perfectly accurately anticipate price movements. Consider the S&P 500’s rolling 12-month, 60-month and 120-month intervals since January 1871. Assume that on the first day of each of these intervals an investor (1) purchased a portfolio of securities which perfectly mimicked the Index, and (2) held it until the last day of the interval’s last month.

What about the perfectly prescient speculator? Let’s assume that during each of intervals he can foresee (1) the Index’s low and high (again, when the high precedes the low this speculator short-sells). If this assumption is absurdly unrealistic over 12-month intervals, it’s preposterously so over five- and ten-year ones. In other words, I’ve stacked the deck heavily in favour of the mythical “perfect” speculator.

I’ve calculated the investor’s and the perfect speculator’s average 12-month, 5-year and 10-year results; Figure 6 summarises them. For proponents of market timing, they’re the equivalent of a torpedo below the waterline and into the magazine.

Figure 6: CPI-Adjusted Average Total Returns, S&P 500 Index, Long-Term Investor versus Imaginary “Perfect Speculator,” 1871-2025

Firstly, and hardly unexpectedly, the mythical “perfect” market-timer outperforms the buy and hold investor over all intervals. Secondly, however, as the interval lengthens the speculator’s returns erode rapidly: as time in the market rises, even the “perfect” speculator generates ever-lower returns. Thirdly, however, as the interval of time increases the buy and hold investor’s returns erode hardly at all.

As a result, and fourthly, as the interval lengthens the imaginary “perfect” speculator’s advantage over the real-life buy-and-hold investor rapidly diminishes.

Figure 7: Ratio of Buy and Hold Investor’s Average Return to Imaginary “Perfect” Speculator’s

Figure 7 quantifies this effect. For each interval, it plots the ratio of the buy-and-hold investor’s average return to the perfect speculator’s return. Over all 12-month periods, for example, the investor’s return averages 8.7% and the speculator’s averages 24.4%; these returns’ ratio is thus 8.7% ÷ 24.4% = 36%. Bearing in mind that the “perfect” speculator doesn’t exist, the investor – who certainly does – produces an average 12-month return which is 36% of the speculator’s.

As the interval increases to five, ten and 20 years, the real-life investor’s actual return rises relative to the hypothetical perfect speculator’s, and thus the perfect speculator’s falls relative to the buy and hold investor’s: over periods of 20 years, the real-life investor’s CAGR averages almost 80% of the imaginary speculator’s.

As the interval lengthens, in other words, the effect of compounding increasingly overcomes the perfect speculator’s advantage.

There’s never been a perfect market-timer and trader, and so you’ll never be one: but you can obtain most of his result – NOT by speculating, but by investing, that is, buying and holding over the long term!

It’s not just true for the average investor; it’s even true for the perfect speculator: the longer is the interval, the more “time in the market” overcomes the (imaginary) ability to “time the market.”

Conclusions and Implications

In this article, I’ve analysed 150-plus years of actual data, as well as computer-generated but nonetheless realistic (because, like actual short-term returns, they’re random) data. My results corroborate others’.

Investopedia’s assessment is the most charitable. In “Market Timing: What It Is and How It Can Backfire”( 26 August 2024), it stated: “market timing is not impossible ... Short-term trading strategies have been successful for professional day traders, portfolio managers, and full-time investors who use chart analysis, economic forecasts, and even gut feelings to decide the optimal times to buy and sell securities.”

Doesn’t that contradict my conclusion? Not so fast: “however,” Investopedia cautions, “few (traders) have been able to predict market shifts with such consistency that they gain any significant advantage over the buy-and-hold investor.”

William Sharpe, a Nobel Laureate, is much more rigorous – and therefore far less charitable. In a landmark study, he concluded that a market-timer must predict accurately almost three-quarters of the time in order to match a benchmark such as the S&P 500 Index (see “Likely Gains from Market Timing,” Financial Analyst Journal, vol. 31, no. 2, 1975). No speculator can come even close to that standard – never mind surpass it. (The market-timing algorithms of James Simons and Renaissance Technologies, routinely lauded as the world’s greatest speculators, accurately predict barely more than 50% of the time).

Since the 1970s, other studies have addressed this issue; to my satisfaction, none has overturned, or even revised, Sharpe’s conclusion.

Benjamin Graham anticipated Sharpe. “Since our book is not addressed to speculators,” he wrote in The Intelligent Investor in 1973, “it is not meant for those who trade in the market ... In our own stock-market experience and observation, extending over 50 years, we have not known a single person who has consistently or lastingly made money by thus ‘following the market.’ We do not hesitate to declare that this approach is as fallacious as it is popular.”

A comprehensive study published in the Hulbert Financial Digest in January 1994 corroborates this conclusion – which follow-up studies over the past 30 years have corroborated. Of the 108 market timing and economic forecasting newsletters which Hulbert analysed during the preceding five years, the predictions of only two corresponded even crudely to subsequent events.

This number, Hulbert noted, is much smaller than expected by pure chance. It suggests that although alleged “experts” can’t get things systematically right they can and do get things comprehensively wrong. Market-timers, traders and speculators, it seems, are seldom in doubt but virtually always in error!

Warren Buffett and Peter Lynch, two of the most successful investors of the 20^th century, have repeatedly and expressly disclaimed any ability to predict stocks’ prices or markets’ returns. In Lynch’s words, market timers “can’t predict markets with any useful consistency, any more than gizzard squeezers could tell the Roman Emperors when the Huns would attack.”

Buffett doesn’t try to predict markets’ or stocks’ short-term fluctuations; instead, he prepares for downdraughts, bear markets, etc., by maintaining significant holdings of cash and equivalents and being ready to deploy them when opportunities arise.

You’ll likely benefit by emulating Buffett – and lose by speculating, trading and trying to “time” the market (for details, see Naysayers Are Wrong: You CAN Emulate Warren Buffett, 9 June).

Speculators Can’t Tell Investors Anything They Don’t Already Know

Speculators fail because they’re attempting the impossible – namely to predict the unpredictable. Virtually the only thing that a trader or market-timer can legitimately say about the S&P 500’s CPI-adjusted total return over the next 12 months is: “given that these returns over the past 150-plus years have been (1) almost perfectly normally distributed, (2) have averaged 8.7% and (3) have a standard deviation of 19.2%, I infer that there’s a 95% chance that during the next 12 months the Index’s return will fall within the range -29.7% to 45.1%. The Index might soar, it might plummet or it might change little.”

In other words, market-timers can’t tell investors anything the latter don’t already know.

Ancient Gnosticism and Contemporary Speculation

Gnosticism is a collection of ideas which some Christian sects began to espouse in the late-first century AD. Until the mid-second century, when the Church denounced and suppressed it, Gnosticism flourished in parts of Mediterranean Europe and Asia Minor. One of its pillars remains highly pertinent to today’s speculators: Gnostics believed that the acquisition of secret knowledge (“gnosis”), available only to a select few, was essential to one’s salvation.

Similarly, some of today’s speculators are “Gnostics” in the sense that they seem to believe not just that “secret knowledge” about trading and market-timing exists; they also believe that the acquisition of this knowledge is essential to their success. Not surprisingly, some prominent speculators imply or assert that they possess this “secret knowledge” – and if you buy their software or subscribe to their newsletter, etc., these secrets of success will be yours!

In Christian theology, Gnosticism is rubbish: there is no “secret knowledge.” Similarly, market-timers who imply that they’re purveying “secret sauce” are actually peddling snake oil. Don’t buy it!

Many People Think They’re Investors – but Are Actually Speculators

The results of my analysis also uncover two ironies. Firstly, opportunities to speculate are countless but the number of speculators who consistently exploit them profitably is at best minuscule. Secondly, opportunities to invest appear infrequently, yet investors’ odds – unlike speculators’ – are far better than speculators’. Successful investors therefore vastly outnumber successful speculators.

Yet the number of speculators remains very large. As Buffett noted in “The Superinvestors of Graham-and-Doddsville” in 1984, “I have seen no trend toward value investing in the 35 years that I’ve practiced it.” More than 40 years later, I suspect that his assessment remains accurate. I’ve long suspected (and recent research has confirmed) that speculators greatly outnumber investors.

In so, then many people who regard themselves as investors are actually speculators (see Toomas Laarits and Jeffrey Wurgler, “The Research Behavior of Individual Investors,” 20 March 2025).

The perverse persistence of speculation may stem from various factors. Perhaps greed (the speed and alleged ease of potential upside) blinds many people to reality (actual downside). Perhaps traders and market-timers know that they face overwhelming odds, but nonetheless – and grossly overconfidently – believe that they can somehow overcome them. Or perhaps they’re simply ignorant of common sense, basic statistics and inference.

Given speculation’s immense, inherent and insuperable difficulties, it’s thus worth repeating: the number of successful market timers is at best minute. Financial history is littered with the wreckage of temporarily spectacularly successful (and therefore overconfident and even arrogant) speculators who before long failed miserably (see in particular Roger Lowenstein’s superb book When Genius Failed: The Rise and Fall of Long-Term Capital Management, Random House, 2000).

The reality is starkly different: even when one loads the dice very heavily in speculators’ favour, errors of even small magnitudes slash their results well below those achieved by buying-and-holding. Bigger errors can produce much more significant losses.

If Speculators Were Rigorous, Honest and Humble ...

If they’re rigorous, speculators must acknowledge that they’re attempting what’s virtually impossible. Their claim that they can “time the market” is the claim that they can reliably foresee the future – which is laughable. If they’re honest, they must concede that the odds against them are overwhelming; and if they’re humble, they must grant that they won’t beat these odds. Unrepentant traders and market-timers are thus some combination of arrogant and deluded.

If you accept that practically all of the time virtually nobody can time the market, then, you must conclude that, for effectively all traders and market-timers, substandard results (compared to investors) – and potentially large losses – are all but assured.

Speculators, traders and market-timers must thus accept the crucial reality: over time, most investors win and virtually all speculators lose.

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