“Experts” obsess about irrelevancies, overlook what’s crucial – and are once again prodding the herd towards the risk of large losses.
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.” Whether for individual companies or a market Index, “forecasting (earnings) is the heart of most security analysis as it is practised today.” More than 40 years later, in Australia as well as the U.S. and elsewhere, Dreman’s assessment remains apt. As a result, conventional security analysis has long lacked sound logical and empirical foundations.
Its fatal flaw is two-fold. First, the strength and direction of the influence of earnings upon returns are so erratic that, in the short term, it averages zero. In Do earnings drive stocks’ returns? (22 January 2024) I demonstrated this crucial point with American data; in this article, I corroborate it with Australian data.
The implications are enormous. A pillar of the mainstream’s obsession about “consensus forward earnings” – namely that markets boost the shares of companies whose earnings “beat the consensus estimate” – is generally false. Similarly, investors don’t consistently punish companies whose earnings “miss” expectations. Moreover, companies which provide earnings guidance aren’t valued more highly than those which don’t; nor does their “forward guidance” tamp the volatility of their shares’ prices.
Mainstream security analysis suffers from a second fatal flaw: human beings – including me, you and “expert” analysts – are innately poor forecasters. Everybody occasionally gets lucky, but nobody can reliably foresee companies’ earnings, stocks’ prices, markets’ levels, etc. In particular, nobody can consistently predict these variables’ turning points.
In Contrarian Investment Strategies (2011), Dreman finds that analysts’ ability to foretell earnings reliably is so poor that it’s “impossible to distinguish growth stocks … from average companies … or even from also-rans.” He therefore asks: if earnings estimates “are not (accurate) enough to weed out the also-rans from the real growth stocks, … why (would) anyone pay enormous (earnings) premiums” for alleged growth stocks? His conclusion more than 40 years ago remains sensible: the experts’ consensus of expected earnings “should be viewed with some suspicion.”
My analysis concludes that, for the sake of their financial health, investors should ignore companies’ earnings guidance, analysts’ consensus of forward earnings – and the journalists who parrot them.
I also demonstrate that those who obsess about forward earnings don’t merely err almost continuously and sometimes enormously: they also blunder systematically. The consensus of forward earnings’ level and trend is unable to foresee corrections (and bigger events such as the Crash of 1987, GFC, etc.); but the sudden realisation that expectations have enormously outpaced reality – as it now seems they’re doing – can trigger them. Yet as I’ll also show, if you know where to look, are prepared to think for yourself – and when necessary to defy the crowd – you can act pre-emptively.
Leithner & Company’s awareness of analysts’ tendency to “systematically mispredict” earnings – and our crucial insight that essentially everything the mainstream asserts about earnings is demonstrably false – has on several occasions enabled us to anticipate and take advantage of downturns. Today might be one of those occasions.
Unfortunately, those who heed the consensus have – like the supposed experts who comprise it – repeatedly been caught unawares; accordingly, they’ve often endured – and will likely continue to suffer – significant losses.
Actual (“Trailing”) versus prospective (“Forward”) earnings
It’s vital to distinguish a company’s or index’s actual (“trailing”) earnings for a past period from its prospective (“forward”) earnings for a future period. Trailing earnings during a given month are (1) actual earnings during the previous 12 months. 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.”
In practice, actual earnings are of secondary – and usually of little – interest to analysts. Instead, “forward” earnings preoccupy them. “Consensus forward earnings” during a given month is the mean of analysts’ estimates of a company’s or market index’s earnings during the next 12 months.
Importantly, this consensus doesn’t attempt to foresee GAAP earnings: 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 transient (that is, the estimate for a particular point in time is revised repeatedly as time passes) and subjective at all times. What’s their rationale? 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.”
A brief digression – Which consensus estimate counts?
During the late 1990s, the U.S. Congress enacted legislation that protected companies from liability for statements about their projected performance. To greater or lesser extents, during the next decade, other countries did likewise. As a result, since then CEOs have commonly issued earnings guidance – and analysts have ubiquitously estimated forward earnings. Analysts and CEOs disgorge estimates and guidance because they believe – fervently – that these predictions systematically affect shares’ prices.
What does it mean to beat, hit or miss the consensus estimate of earnings? The uninitiated might think that it’s a straightforward matter, but it isn’t; Koller et al. (“Avoiding the Consensus-Earnings Trap,” mckinseyquarterly.com, January 2013) clarify it.
Suppose that on 15 February 2023 X Ltd reported its actual (trailing) earnings of $2.00 per share for the year ended 31 December 2022. Also on 15 February 2023, the consensus– that is, the average of the brokers covering the stock – forward estimate of earnings for the year to 31 December 2023 was $2.10. By 15 February of this year – well after the conclusion of the period in question, taking into consideration X’s half-year results but before the release of its full-year earnings – the consensus forward estimate for 31 December 2023 had fallen to $1.98. And on 15 February 2024 X reports actual earnings of $2.00 per share for the year ended 31 December 2023.
Did X Ltd’s actual earnings for CY23 exceed the consensus forward estimate? It’s vital to understand that analysts constantly revise their estimates of forward earnings for a given interval; and according to conventional practice, a company (or market) has beaten the consensus estimate if its actual earnings are greater than the final consensus estimate – which almost always appears AFTER the period in question has ended!
Accordingly, in this example X has beaten the consensus estimate of forward earnings, which fell 5.7% during the year, even though its trailing earnings were 4.8% less than the consensus estimate at the beginning of the year!
Do short-term earnings changes consistently drive short-term returns?
Why do analysts, CEOs, investors and journalists obsess about forward earnings? They believe that companies must at least meet (and preferably beat) beat the consensus forward earnings estimate. They hope that if a company consistently produces better-than-expected earnings, then investors will boost the price of its shares. Conversely, adherents to the conventional wisdom fear that if the company reports below-consensus earnings then investors will punish its shares – and, by extension, its CEO.
The reality is very much otherwise: over the short-term (rolling 12-month) periods, the influence of earnings upon returns is so erratic that it’s effectively zero (see also Do earnings drive stocks’ returns? 22 January). In practice, this means that if a company reports better than expected earnings then its stock might fall or even plunge. It also means that if it misses estimates its stock might lift or even soar.
“This,” concludes John Csiszar (“How Stock Prices Correlate with Quarterly Earnings and when You Should Buy,” NASDAQ News and Insights, 16 May 2023), “makes basing an investment strategy around an earnings release date a difficult or even risky strategy.”
If, from one month to the next throughout a given interval, earnings and returns changed identically and in the same direction (but not necessary by the same magnitude each month), then the two series would be perfectly positively correlated and their correlation coefficient (r) would attain its maximum value of 1.0. Conversely, if during each month one series increased by some amount and the other fell by an equivalent magnitude, then the two series would be perfectly negatively correlated and the coefficient would reach its minimum of -1.0. Finally, if the monthly change of one series bears no relation to the change in the other, then their correlation is 0.0.
If the relationship between short-term changes of companies’ earnings and returns is general – that is, if it applies to most companies most of the time – then it will appear at the level of the market index over long stretches of time. That’s an easy proposition to test.
Using data compiled by Standard & Poor’s, Figure 1a plots the correlation coefficient (r) of changes of the S&P/ASX 200 Index’s actual (trailing) earnings and returns, for each rolling 12-month interval since January 2006. Using consensus estimates compiled by Bloomberg, Figure 1b plots the corresponding correlations using the S&P/ASX 200 Index’s forward earnings.
Are the Index’s earnings and returns correlated? They usually are – but they’re anything but consistently correlated: sometimes the correlation is strongly positive and at other times it’s weakly so; but as often it’s strongly or weakly negative. As a result, the average coefficient in Figure 1a is -0.01 and in Figure 1b is -0.23 (which, from a mainstream point of view, is the wrong sign).
Figure 1a: Correlations of the S&P/ASX 200 Index’s Actual Earnings and Return, 12-Month Rolling Intervals, January 2008-February 2024
“Variation explained,” i.e., r × r = r2, measures the percentage by which our bivariate model reduces (“explains”) total return’s variation compared to a univariate model. On average, then, the change of the Index’s trailing earnings during a 12-month interval explains exactly (-0.01) × (-0.01) = 0.0% of the change of its total return; the change of the Index’s prospective earnings during a 12-month interval explains a mere (-0.23) × (-0.23) = 5.3% of the change of its total return. Other factors – including random fluctuations – explain the other 94.7%.
The most charitable interpretation of these results: on average over more than 15 years, short-term noise has overwhelmed short-term signal. The most reasonable reading is that investors have generally responded randomly rather than consistently or systematically to new information about actual or expected earnings.
Figure 1b: Correlations of the S&P/ASX 200 Index’s Forward Earnings and Actual Return, 12-Month Rolling Intervals, January 2008-February 2024
In the short-term, earnings simply don’t consistently drive stocks’ returns. As Koller et al. conclude: “the promise of meeting or beating consensus estimates and the peril of missing them are profoundly overstated.”
Have recent earnings really been “resilient”?
“There has been a positive start to the year for Australian corporate earnings estimates,” reported The Australian on 2 February of this year. “The aggregate earnings per share estimate for the S&P/ASX 200 has been revised up by 1% in January. Except for utilities and energy, all sectors have seen earnings upgrades … Almost 68% of ASX 200 companies have seen net upgrades in January.”
“I think what’s happening here is, for the past few years we’ve all been waiting for the earnings cliff,” said the head of Australian equities research at a major global investment institution. “The much-feared earnings cliff hasn’t materialised and certainly at the beginning of 2024 there’ve been very few companies to provide negative updates to the markets.”
The senior executive continued: this “suggests that the past six months (have) been reasonably good across corporate Australia … (This) is indicative of a stronger earning cycle than most in the market are assuming.”As The Weekend Australian proclaimed on 24-25 February, “a picture of resilience is emerging from Australia’s latest profits reporting season” (see also “Sentiment Upbeat as Earnings Season off to a Great Start,” The Weekend Australian, 17-18 February).
At best, mainstream “analysts” have been as attentive as Mister Magoo; at worst, they’re utterly delusional. The recent course of trailing earnings – which they resolutely ignore – tells a very different story. It flatly repudiates the assertions about “avoiding the earnings cliff;” it also renders upbeat recent assertions about forward earnings highly dubious.
Figure 2a plots the trailing earnings of the S&P/All Ordinaries Index since January 2020; Figure 2b plots these earnings since January 1965. (The All Ords’ trailing earnings are almost identical (r = 0.99) to the S&P/ASX 200’s; for this reason, and in order to maximise the comparability to Figure 2b, in this section I use the All Ords’ earnings).
Figure 2a: Actual Earnings, All Ordinaries Index, Monthly, January 2020-February 2024
After collapsing 75% during the COVID-19 panic, earnings quickly recovered all of their losses and more. On the eve of the pandemic in January 2020, earnings were $355; by April 2021, they’d collapsed to $91; but by February 2022, they’d zoomed to $422.
So-called “experts” appear to be clueless to – or, at a minimum, they’ve refused to plainly confess the fact that – over the past couple of years the trailing earnings of the All Ordinaries Index have sagged almost one-quarter – from $501 in October 2022 to as low as $380 in December 2023 (they bounced slightly, to $391, in February 2024). Is that evidence of resilience?
The course of earnings over the past 60 years also utterly escapes them. The All Ordinaries Index’s trailing earnings have risen from $14.73 in January 1965 to $391 in February of this year; that’s a compound annual growth rate (CAGR) of 5.7%. Adjusted for CPI, they’ve grown from $245 in January 1965 to $391 today; that’s a CAGR of 0.8%.
Figure 2b: Actual Earnings, All Ordinaries Index, Monthly, January 1965-February 2024
For more than 40 years, from the mid-1960s to the eve of the GFC, CPI-adjusted trailing earnings fluctuated without trend and between $200 and $500. They then skyrocketed to their all-time maximum of $722 in October 2008, crashed to $404 in March 2010 and for the next decade fluctuated between $400 and $500. Then came the COVID-19 panic: the Index’s trailing earnings crashed to $104 in April 2021 but then zoomed as high as $530 in October 2022.
Since then, as I’ve already noted, they’ve fallen. On a CPI-adjusted basis, they first reached their present level ($391) in July 2004 – almost 20 years ago! Does that make earnings resilient or stagnant?
Which valuation metric Is best?
“Record highs for Australian shares have investors asking whether it’s time to ride the momentum and buy in anticipation of more gains, or sell and take profits before the market falls,” reported The Australian Financial Review (“The five models that show shares are still good value at record highs,” 12 February 2024). “The best way to judge whether shares are cheap or expensive,” it adds, “is to look at common valuation metrics relative to (their) historical averages.”
The price-to-earnings (PE) ratio, it notes, is one of the most common metrics. The higher is the PE, the more expensive is the stock or market, “as you must pay a higher price for the same amount of profits.” And the lower the multiple, the cheaper is the stock or market. The AFR’s article, like the vast majority of analysts, considers the forward PE almost to the exclusion of all others. On 29 February, the S&P/ASX 200 Index’s forward earnings multiple was 16.1, and since 2006 it’s averaged 15.7. “So,” the AFR quoted Shane Oliver, “it would be hard to describe the Australian sharemarket as cheap today on a (forward) PE basis – in fact, on (that) basis it’s slightly expensive.”
That’s not wrong as far as it goes, but it doesn’t go nearly far enough; accordingly, in key respects it’s misleading. Figure 3a plots monthly observations of the Index’s forward PE since January 2006. Several of its anomalies (I’m tempted to say “absurdities”) highlight the weakness (I’m tempted to say “fatal flaws”) of the forward PE as a measure of value.
Most notably, if before the GFC you had relied upon the consensus and its forward PE ratio, then the Crisis would have caught you – as it did the “experts” – completely unawares.
Figure 3a: Forward PE Ratio, S&P/ASX 200 Index, Monthly, January 2006-February 2024
Between July 2007 and November 2008, the forward PE fell from 16.1 to 9.3. In the latter month and by this measure, the market didn’t merely become considerably cheaper: it was less expensive – and thus more appealing – than it’s been at any time since 2006. If in July 2007 you heeded this strong “buy” signal, then by November 2008 you would’ve lost 39%.
Conversely, between May 2020 and January 2021 the forward PE was very expensive (more than 20 and as high as 26.7). During this interval the Index averaged 6,121. If you had sold during these months and waited to buy until April 2022 (by which time the forward PE had fallen to a much more appealing (15.0, a bit below its long-term average) you would’ve missed the market’s rise of 29%.
What if you had ignored the forward PE and instead taken into consideration the trailing PE and cyclically-adjusted PE (CAPE)? Figure 3b plots these ratios, as well as the forward PE (the trailing ratio rose above 80 during the COVID-19 panic; in order to maximise Figure 3b’s readability, I’ve scaled its y-axis to a maximum of 30).
Figure 3b: Trailing PE Ratios, Monthly, January 1965-February 2024