How experts’ earnings forecasts harm investors

It’s “an article of faith among Wall Street research departments,” wrote David Dreman in Contrarian Investment Strategy (1979): “nothing is as important in the practice of security analysis as estimating the earnings outlook ... Forecasting is the heart of most security analysis as it is practiced today.” More than 40 years later, not just in Wall Street but around the world including Australia, Dreman’s assessment remains apt. As a result, conventional security analysis has long lacked a sound foundation.

Its fatal flaw is indisputable: human beings – including me, as well as you and any “analyst” or other “expert” whom you might care to name – are innately poor forecasters.

Everybody occasionally gets lucky, but nobody can consistently foresee prices, markets and economies with any reliable degree of precision (see also Experts can’t predict yet investors must plan: What, then, to do?). Dreman understates his conclusion: “the accuracy of earnings forecasts should be viewed with some suspicion.” 

Two Ugly Truths, Two Conclusions – and an Irony

Using American data since 1980, this article updates and reconfirms two ugly truths that virtually no analyst, expert, journalist, etc., ever publicly admits.

1. “Consensus forward earnings” are so woefully inaccurate that they’re not just useless: they’re harmful. Excluding their grossest errors during the GFC, they’ve deviated from subsequent actual earnings by an average of more than 30%; including them, their average error exceeds 50%! Using such fundamentally flawed forecasts, warns Dreman, “can often prove harmful to ... portfolio performance and investment health.”
2. The consensus of experts is also heavily biased in the direction of over-optimism. Unrealistic expectations must eventually confront reality – and when they do, they become nasty surprises. Overconfidence is much more likely to produce financial loss than gain (for details, see Why you’re probably overconfident – and what you can do about it). Experts encourage overconfidence; hence they induce investors to suffer losses.

I conclude that most investors should simply ignore “consensus forward earnings” and the experts who tout them. Yet as I also conclude, analysts don’t merely err almost continuously and sometimes enormously: they also blunder systematically. Indeed – and ironically – their biggest mistakes tend to precede crucial events. The consensus of forward earnings is utterly unable to predict bear markets, corrections, financial crises and recessions – but the non-random nature of experts’ biggest errors allows investors who think for themselves to undertake pre-emptive action.  

Leithner & Company’s awareness of analysts’ “systematic misprediction” of earnings has enabled us to anticipate and take advantage of the current bear market in the U.S. (and, because Oz usually catches cold when America sneezes, the correction on Australian indexes). Unfortunately, those who’ve heeded the consensus have – like the experts, and yet again – been caught unawares; accordingly, they’ve suffered significant losses.

Defining Actual versus “Forward” Earnings

It’s vital to distinguish a market index’s actual (“trailing”) from its prospective (“forward”) earnings. Its trailing earnings during a given month are (1) the actual earnings during the past 12 months of the companies that comprise the index. As such, they’re (2) consistently and (3) strictly defined. In short, they conform to Generally Accepted Accounting Principles. Colloquially, GAAP earnings include “all the bad stuff.”

A market’s actual earnings rarely interest analysts. Instead, “forward” earnings preoccupy them. A market’s “consensus forward earnings” during a given month is the mean of analysts’ estimates during that month regarding the earnings during the next 12 months of the companies that comprise the index. Crucially, this consensus doesn’t attempt to foresee GAAP earnings: their forward estimates routinely incorporate “good stuff” (such as one-off gains) and exclude “bad stuff” (such as allegedly temporary losses, write-downs and write-offs of assets, etc.).

Forward estimates, in short, are inconsistent over time; they’re also subjective and lax at all times. According to Investopedia, “forward earnings are of interest … because stock prices (and market indexes’ levels) are supposed to reflect future earnings prospects discounted to the present … The (economy’s) position in the business cycle, and the state of the economy … can help determine forward earnings numbers.” I doubt it: 

To the extent that they impart anything meaningful, consensus forward earnings quantify experts’ degree of overconfidence – and, at extreme junctures, their delusion. Over-optimism causes financial failure. Most investors should therefore ignore consensus of forward earnings. For a minority, they’re relevant only when their deviation from reality reaches an extreme: at those junctures, they’re a useful warning indicator.

Observing Actual versus “Consensus Forward” Earnings

The Institutional Brokers’ Estimate System (IBES, often written “I/B/E/S”) is a database that collates analysts’ estimates of the future earnings of publicly- traded American companies. Using IBES data, Figure 1 plots their consensus since January 1980 of the forward earnings of the companies comprising the Standard & Poor’s 500 Index. Using data compiled by Standard & Poor’s, it also plots the Index’s actual earnings. In order to compare “like with like,” I’ve matched each month’s prospective earnings to its actual earnings twelve months hence. The consensus of forward earnings for January 1979, for example, estimated what earnings would be in January 1980; I’ve therefore matched this estimate to actual earnings in the latter month, and so on for later months.  

Three relationships among these two series of data are most significant.

First, in virtually every month analysts’ consensus of the Index’s forward earnings has exceeded – often considerably and sometimes massively – the Index’s subsequent actual earnings. For more than 40 years, the consensus has been rigidly biased in the direction of over-optimism.

Figure 1: S&P 500’s Earnings, Actual (12-Month “Trailing”) and 12-Month “Consensus Forward,” Monthly Observations, CPI-Adjusted, January 1980-June 2021

The problem isn’t merely that analysts are human and that humans are unable to predict with any reliable degree of accuracy: if that were the sole explanation of what’s happening, analysts’ consensus would sometimes be too high and at other times too low – and their average error over the years would thus be relatively small.

Partly, the almost-constant excess of consensus forward versus actual earnings reflects the lax definition of forward earnings. More than this, however, although accuracy would benefit their clients, over-optimism better serves analysts’ and their employers’ interests.

According to Investopedia, “buy-side” analysts (who work for investment management companies)

have an incentive to place a buy recommendation on held stocks and a sell recommendation on stocks recently sold. If these suggestions are enough to push the price in the direction that would “justify” the analyst’s research, evidence would suggest that the analyst has profitable stock picking abilities. As a result, the mutual fund or investment firm would experience higher business volumes.

“Sell-side” analysts, on the other hand,

typically work in a transaction-based environment selling their research to the buy-side group, hence their name … While the industry has come a long way, there is still some progress on the sell-side to be made since some of a sell-side analyst’s compensation can come from the transaction fees associated with the companies they cover.

The data in Figure 1 uncover a second key point: actual earnings occasionally decrease, sometimes precipitously, but the consensus of forward earnings decline much less frequently; and when it does, it falls much less markedly and after a lag of several months. 

Reality, in other words, is much more erratic than analysts’ consistently over-optimistic consensus. Less charitably, analysts are prone to stubbornness as well as hubris – and as a result it typically takes a big jolt of reality to rouse them from their complacency.

Thirdly and most significantly, at critical junctures – namely the onset of bear markets and financial crises – consensus forward earnings have egregiously exceeded subsequent actual earnings. 

Considered as a whole, in other words, analysts have invariably been unable to anticipate sharp decreases of actual earnings – and the resultant bear markets, corrections, crises and recessions that crush investors’ portfolios. Precisely when they most need clear vision, analysts are blindest!

Figure 2, which plots in percentage terms the disparity of forward relative to actual earnings, clarifies this third point. When the consensus of forward earnings exceeds actual earnings, the percentage disparity is positive; when actual earnings exceed the consensus, it’s negative; when they coincide, it’s zero. In January 1980, the consensus forward estimate for January 1981 was $59 and in the latter month actual earnings were $47; hence the disparity was ($59 - $47) ÷ $47 = 26%, and likewise for the other months.

A gap appears in Figure 2 between November 2007 and October 2008 because during these months consensus earnings decreased relatively modestly (from $145 to $114, a decrease of 21%) whilst actual earnings collapsed (from $103 to $34, or 67%); as a result, during this interval the disparity skyrocketed as high as 1,321%. In order to avoid a dramatic expansion of the graph’s vertical axis I’ve omitted these extreme observations. 

Figure 2: The Disparity of Forward and Trailing Earnings, January 1981-June 2021

Excluding them, the average disparity between today’s consensus and subsequent actual earnings is considerable (32%); including them, it’s astounding (51%).

Perhaps because the consensus of experts is so woefully inaccurate, the series is heavily mean-regressing: the higher above the mean that the disparity rises, the stronger is the likelihood that it subsequently falls below it; and the further below the mean that the disparity sinks, the stronger is the likelihood that it subsequently rebounds above it. Analysts’ consensus is systematically biased in an overly optimistic direction, but it’s not totally unhinged; when it departs too much from reality, it adjusts. 

Figure 2 demonstrates not merely that analysts err systematically and even predictably: their egregious errors have roughly foreseeable consequences.

When their consensus of forward earnings overshoots actual earnings by 75% or more, a bear market caused by a recession or financial crisis is usually imminent. Errors of this magnitude occurred between July 1990 and October 1991 (a period which roughly encapsulated the recession of the early-1990s), July 2000-May 2002 (Dot Com Crash), May 2007-March 2009 (Global Financial Crisis) and August 2019-January 2020. Immediately preceding the biggest crises of the past generation, the consensus of “forward-looking” experts was as sharp-eyed as Mister Magoo!

Yet this warning sign has often been visible only in retrospect. Only after July 1991, for example, did investors possess the data informing them that the consensus in July 1990 had missed so badly. That was too late to anticipate the recession and bear market. Fortunately, the warning signal was available in July 2001 (sufficient to avoid the worst of the Dot Com Crash) and May 2008 (to avoid the worst of the GFC).  

On the other hand, extremely low disparities give advance warnings of subsequent trouble. The disparity fell below zero from June 1987 to July 1998 – which was plenty of time to anticipate the Crash of 1987 and the subsequent recession and bear market of the early-1990s. Very low disparities provided little or no advance warning of the Dot Com Bust, but those in August 2003-May 2006 provided ample warning of the GFC.

What about Figure 2’s most recent observations? In October 2020, the disparity sagged to 0%. Thereafter it continued to drop, and by June of last year it sank to -24% – the lowest observation in the series. Given its strong tendency not just to regress to the mean, but also to skyrocket well above the mean, it was reasonable to expect that the disparity would subsequently rise dramatically.

 Moreover, in late-2020 it was prudent to note what subsequently happened (in June 1987-July 1998 and August 2003-May 2006) when the disparity plunged well below zero: within two years, a bear market, financial crisis or recession erupted.

This indicator clearly isn’t infallible. False alarms occurred in January 1994-June 1995 and January 2010-March 2011; still, as a warning signal it is (as we’ll see in the next section) far better than most. 

It’s ironic: “expert analysts” are actually “reliable anti-authorities”! Their consensus of forward earnings is utterly unable to predict bear markets, corrections, financial crises and recessions – but the systematic nature of their errors relative actual earnings enables investors to use these mistakes crudely to foresee such events and take corrective action.

Comparing Forward and Trailing PE Ratios

Forward estimates are subjective, inconsistent over time and relatively lax at all times. Moreover, the consensus of analysts is almost always inaccurate, usually significantly so and sometimes wildly so. Furthermore, it almost invariably errs on the side of over-optimism. As a result, the consensus of experts isn’t just continually erroneous: it’s systematically biased.

These facts have another unpleasant implication for investors. Forward PEs are usually lower – and sometimes much lower – than their trailing counterparts. Lower PEs imply more attractive valuations. Forward PEs thereby lull investors into a sense of complacency which reality subsequently dashes.

Figure 3 plots the S&P 500 Index’s forward, trailing and cyclically adjusted price-to-earnings ratios since January 1980. I’ve omitted the trailing PE between January and September 2009 because during these months it zoomed to an average of 100 (maximum of 123.8 in May). The forward PE’s mean is lowest (14.6), the trailing one is higher (mean of 20.2) and the CAPE is highest (22.9). The forward PE also varies least (standard deviation of 4.3), the trailing PE more (7.5) and the CAPE most (8.7). 

Figure 3: Three Price-to-Earnings Ratios, S&P 500 Index, Monthly Data, 1980-2022

None of these PEs provides a consistently-reliable leading indicator (warning sign) of bear markets, corrections and crises. Robert Shiller, the creator of CAPE, has repeatedly disclaimed its predictive ability; clearly, however, it’s superior to the trailing PE, and the trailing PE is superior to the forward PE. Ironically, the “forward-looking” PE’s capacity to foresee the future is the most myopic of the three! In the year preceding the Crash of 1987, the trailing PE rose highest; but none of the three anticipating the recession of the early-1990s. Each increased considerably during the Dot Com Bubble, but CAPE rose highest. Similarly, CAPE was highest before the GFC and on the eve of the Global Viral Crisis (GVC).

By consistently emitting the most bullish signal, the forward PE has been the most aggressive indicator of valuation; and by consistently emitting the most cautious signal, the CAPE has been the most conservative. By varying least over time, the forward PE abets not just over-optimism but complacency; and by fluctuating most, the CAPE encourages alertness as well as caution.

Conclusions and Implications

Analysts’ woeful inability to predict the S&P 500 Index’s earnings is but one instance of a much broader, deeper – and very topical – phenomenon. Adam Creighton (“’Experts’ Have Been So Wrong on Just About Everything,” The Australian, 23 June) summarised today’s sorry state of affairs:

It’s hard to recall a period in history in which experts have been so comprehensively wrong on so many topics in such as short time ... The decade beginning in 2020 appears to have taken institutional wrongness to a higher plane.

Creighton echoed The Wall Street Journal (1 June): 

One hallmark of our era is the collapse of public trust in government and experts of all kinds. But it’s hard to fault the public when so many experts and their policies have failed in such spectacular fashion.

As examples, consider this conga line of experts’ recent colossal blunders:

1. In September of last year, no fewer than 17 Nobel Laureates issued a public letter that, among other things, downplayed concerns about inflation; today in Britain, the U.S. and elsewhere, it has scaled heights not seen since the early-1980s.
2. Earlier this year, experts ignored historical evidence that sanctions short of total war seldom work as intended and often have unintended negative consequences. Instead, succumbing to moral panic, they urged governments to impose sanctions upon Russia in order to punish its invasion of Ukraine. These sanctions haven’t curtailed the war, but on balance have benefited as much as harmed Russia. On 20 June the rouble reached a seven-year high against the $US; the Russian Federation’s 10-year bond’s rate is lower than before the invasion – and its central bank has cut its rates while the Federal Reserve, RBA and others are lifting theirs.
3. These sanctions haven’t merely failed to bring Russia to its knees: they’ve also greatly harmed the West – not least by exacerbating its self-imposed energy crisis. According to Creighton, they’ve “crushed the competitiveness of European industry and slashed the living standards of ordinary Americans and Europeans.”
4.  Late last year, the Governor of the RBA, Philip Lowe, stated that its Overnight Cash Rate wouldn’t rise before 2024. On 5 May, The Canberra Times reported that the RBA “will do what it takes (namely lift the OCR to whatever level is required) to combat inflation, which it expects will rise to a level not seen since the introduction of the goods and services tax in 2000.”
5. And on 21 June, Lowe said: “I don’t see a recession on the horizon.” Is that because one’s not there, or because he’s blind?

As bad as economists have been, they’re not the worst. As Creighton observes,

no group of experts can compete with epidemiologists and other so-called public health experts for being so militantly and repeatedly wrong about every aspect of their supposed speciality, which will go down as one of the greatest fiascos of history.

Ultimately, what’s the problem? “Show me the incentives,” Charlie Munger famously quipped, “and I’ll show you the behaviour.”

Most fundamentally, so many experts in so many fields get things so wrong so often because they have no “skin in the game.” That is, they bear none of their mistakes’ adverse consequences: their clients, customers and the general public do (see also Are you a customer, client or partner?). “The past few years have been a disaster for the reputation of experts,” Creighton notes, “but not for experts themselves.”

Why Do You Ever Listen to These People?

I don’t begrudge analysts’ inability to predict the S&P 500 Index’s (and, by implication, companies’ and other markets’) earnings. Nobody – including me – can, and I readily concede that if I tried I’d probably do even worse. I do, however, resent the fact that very few analysts honestly confess their abject incapacity to predict reliably; even worse, they – and gullible and lazy journalists – maintain the pretence that they can. When it comes to the future, experts have feet of clay, and if they came clean they’d lose status and perhaps their jobs. Who wants to pay a hefty salary to a man (the ostensibly most convincing experts are the most overconfident; men are most prone to hubris; hence most “finance experts” are men) who openly acknowledges the blunt truth that he’s just guessing – and that his guess is no better than yours?

 There’s something deeply embedded in the human psyche that prompts so many people to seek and heed seers – and induces smooth-talkers to become soothsayers. Clairvoyants’ apparent self-assurance comforts those who want desperately to believe that somebody knows the future (even if, deep down, many rightly suspect that nobody really does). If investors admitted it, they’d have to confront one of their innermost fears: the harsh truth that they must ultimately think and act for themselves and accept the consequences – rather than blindly follow an “expert” and blame him when things go wrong.

An even more severe problem stems from the unwillingness to acknowledge that analysts, market strategists and the like can’t divine the future. Under conditions of risk and uncertainty – which in financial markets is all the time – experts are no different from other people: they seek safety in numbers. In other words, they’re no less susceptible to fads, manias, etc., than the people they purport to advise. Career risk rather than market risk is their primary concern; hence they gladly abdicate their independence, surrender their judgement, join the crowd and stampede with the herd. 

As the American banker and economist, Benjamin Anderson, observed in 1949, “the more intense the craze, the higher the type of intellect that succumbs to it.” In the late-1970s, reviewing scholarly literature in finance and other fields, David Dreman concluded: “over and over again, when the degree of consensus was greatest … the extent of the error was most pronounced.” Today it’s no different: the clamour for “climate action” and ESG, to cite two notable examples, will enrich a small minority but cost dearly most investors, taxpayers and people of modest means.

Not merely because human beings are poor forecasters, but also because at critical junctures grossly overconfident experts become colossally inept seers, reality regularly surprises them – and causes their followers to lose considerable amounts of money. Analysts pursue their and their employers’ self-interest: hence the consensus is almost continuously biased in the direction of over-optimism. Unrealistic expectations, in turn, eventually confront reality – and thus become nasty surprises. Overconfidence is thus much more likely to produce financial loss than gain (for details, see Why you’re probably overconfident – and what you can do about it).

“Earnings estimates,” David Dreman concludes, “just aren’t very reliable. Worse than that, the expert consensus ... is frequently far off the mark – so far off, in fact, that using such forecasts can often prove harmful to stock selection, portfolio performance, and investment health.”

How Leithner & Company Profits from Experts’ Blunders

Most investors should ignore the consensus estimates of markets’ earnings, as well as those who peddle them. Leithner & Co. certainly doesn’t heed them – but we note and act when overconfidence becomes extreme. As an example, recall my analysis of Figure 2: in October 2020, the disparity between forward and actual earnings plunged excessively. What occurred previously (namely in June 1987-July 1998 and August 2003-May 2006) when the disparity reached a comparable extreme? 

Within two years, a bear market, financial crisis or recession erupted. For this and other reasons, towards the end of 2020 we began to prepare, and we didn’t keep our views to ourselves (see, for example, Why this market is 33-50% overvalued, 3 September 2020; Will Joe Biden be good for investors? Why I disagree with Geoff Wilson, 6 December 2020; and Speculators are playing with fire; investors, don’t get burnt! 21 December 2020).

Yet at the end of 2020 a bear market, financial crisis or recession was the furthest thing from experts’ minds. The Australian (“Why the Bulls Will Run into the Coming Year,” 11 December) encapsulated the euphoria that prevailed at that time – and the short-term myopia that the mainstream demonstrates at all times. “An exceptionally strong bull market,” it enthused, would continue into 2021. ‘Equities are facing one of the best-ever backdrops for sustained gains,’ said one chief strategist. ‘We expect a ‘market nirvana’ scenario for equities with the melt-up continuing (during the first six months of 2021)’.” 

What underlay this fervour? Partly it was the mainstream’s disinclination to consider anything other than the short-term; mostly it was the immense (ca. $25-30 trillion) torrent of fiscal and monetary “stimulus” which the world’s central banks and governments unleashed in 2020 – and the likelihood that even more would flow during 2021. These measures, bulls rejoiced, plus the distribution of COVID-19 vaccines, relaxation of lockdowns, etc., would trigger a genuine and powerful economic recovery. I also rejected these assertions (see, for example, Central banks don’t dispense “Stimulus” – they peddle poison, 21 September 2020, and Australia’s bogus boom, 20 May 2021).

Leithner & Co. searches relentlessly for extremes: greatly undervalued companies, very overvalued markets, daft ideas, delusional experts, etc. Knowing that at most times it’s sensible to ignore the crowd has certainly given us an advantage; comprehending that at extremes it can be very profitable to defy it has given us an even bigger edge.

When the consensus soars to an ebullient extreme, as it did in late-2020, we raise the drawbridge; when it slumps to a pessimistic one, as it did in June, we lower it. Unlike the herd, which depends upon faulty forecasts, our actions stem from logically and empirically valid premises. One of them is that so-called “experts” are most disastrously wrong and cause the severest damage to investors’ portfolios when they’re most confident.

Freed from the shackles of forecasting, our approach enables us to visualise in the dark – and avoid stumbling over furniture and bumping into walls. The future is always unlit; but with a valid and reliable framework, we can anticipate where major obstacles lie. Over more than 20 years we’ve hardly done so unerringly; equally clearly, we’ve recorded many more successes than failures. And throughout this time, the consensus of analysts and experts has unwittingly but nonetheless greatly helped us.

So I thank them: not just for their overconfidence (which dulls their thinking) and resultant errors (which occasionally causes them to panic), but also for their herd-like behaviour which stifles independent action and occasionally greatly misprices some securities. Most of all, I’m thankful for their mistakes’ regularity, egregious nature at critical junctures and – ironically – roughly predictable consequences. 

Experts’ most recent failings have given Leithner & Co. plenty of time to prepare for today’s correction – and for what might yet become a bear market and recession. Reality has once again mugged analysts and experts, but they haven’t paid the price: their clients and customers have. Many investors are anxious, bewildered and poorer. And the longer they heed consensus earnings forecasts and those who peddle them, the poorer they’ll become.

Wealth creators. Value investors.

At Leithner & Co, we believe in creating wealth through long-term consistent growth, built on trust and transparency. Our value investing approach allows us to learn from the past but keep an eye firmly on the future.

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