Two reactions are triggered when stocks rally as much as they have. The first is regret; amongst those who did not partake in the rally, those who missed out on segments like the “US Magnificent- 7”, and those who simply sold too soon. The second is a pervasive sense of scepticism which feeds a deep-rooted feeling that a big correction must be overdue. Put the two together and one ends up with what Eriswell calls ‘magic elastic band’ contrarianism. A feeling that stocks must be overpriced simply because they have risen so much. As if a magic elastic band has one of its ends anchored where the asset’s rally commenced, with the other end stretched up to where the asset is trading today. To believers in magic bands, stock prices are due a big correction as the elastic snaps them back into line. To everyone else it looks like wishful thinking. To put these beliefs on a firmer footing, investors require payment to take on the risks of financing a company. From the company’s perspective this comes in the form of its ‘cost of capital’, a type of interest rate it must pay its share and bondholders. The return on capital is the profit a company generates. The ‘cost of equity capital’ a company must pay its shareholders represents the company’s entire profits after tax, interest, and other contractual payments, and may be more or less than the level envisaged by the investor when they bought the stock. This is basic stuff but as with many activities, get the basics wrong and you can expect a poor outcome. Valuing a company therefore boils down to projecting its expected future cashflows and then risk adjusting them using a suitable discount rate (its cost of capital). To do this accurately requires us to be firmly anchored in the objective reality pervading today with great care taken when comparing its valuation today with how it has performed in the past. While historical comparisons are commonplace, they’re only valid to the extent a company’s history, no matter how glorious, remains a good representation of today. This takes us to an area Eriswell finds itself continually at odds with mainstream forecasts. We believe the objective reality today has been radically altered by the advent of zero-r* conditions. And we have repeatedly argued that trouble will come in many sizes to those who fail to recognise that, in zero-r* environments, fiscal stimuluses flow almost entirely into corporate profits and onwards into the hands of the wealthy. If true, a massive structural benefit to stocks and, so far, it certainly seems to be true. And so, unsurprisingly, trouble has indeed come to those who failed to recognise that corporate earnings would break free of their pre-2008 trends where profits were inextricably linked to wage and nominal GDP growth (Fig 1). Fig 1: Okay, if we correct for large-scale zero-r* macro effects like the profit breakout we’re good to go? Alas, no! Zooming in we see that the benefits accrued by zero-r* dynamics have been far from symmetric. Companies like the US ‘Magnificent 7’ with businesses protected by high moats and with products facing marketplaces, fashions, and consumer behaviour boosted by zero-r* conditions have never had it so good. While other sectors including European banks and household discretionary retailers have endured more difficult times. For example, zero-r* conditions drag on European net interest rate margins—the lifeblood of retail banks—and many household discretionary retailers are reporting close to their worst ever trading conditions. Unsurprisingly both sectors have failed to return their cost of capital to shareholders. This is presumably where stock analysts earn their money Zooming in we see that the benefits accrued by zero-r* dynamics have been far from symmetric. Companies like the US ‘Magnificent 7’ with businesses protected by high moats and with products facing marketplaces, fashions, and consumer behaviour boosted by zero-r* conditions have never had it so good. You would think so, for using a combination of financial analytics and market understanding it falls to stock analysts to separate the wheat from the chaff. The process comes in two stages: 1. Macro picture First, stock analysts must consider the macro environment including, for example, the shift away from the traditional manufacturing base to a new technology-based economy. A shift which has introduced many unforeseen changes including the anti-competition headaches regulators face today and the winner-takes-all dynamic visible in many sectors. Which have powered the so-called ‘Magnificent 7’ into the stratosphere with these seven stocks comprising almost 35% of the S&P500 index today (Fig 2). Microsoft's dominance of application and business software has been the subject of anti-trust actions for many years, but this did nothing to stop Amazon from beating a similar route to dominance in the retail sector. Meanwhile, the advertising industry was traditionally splintered with even the biggest media players (TV and radio broadcasters, film, newspapers, advertising agents, etc.) commanding a modest share of the overall market. Even the core advertising hubs were dispersed across many players including the old Saatchi & Saatchi, Havas, Publicis, WPP, and Japan’s Dentsu. All changed when Alphabet and Meta created dominant new platforms which today corner online advertising, powered by network nodal benefits which see advertising flows increasingly sucked into the gravitational fields of the largest and most frequented platforms. Not to forget the sector’s new king, Nvidia, which is grabbing market share, revenues, and investors imaginations as it forges a dominant new path into AI. It falls to investors and analysts to figure out what the chip endgame might look like and while it is true—as with advertising, retail, and application software before them—that microchips has never been a winner-takes-all business, investors are starting to price in the possibility that Nvidia might just dominate this market as the other tech giants dominate theirs. Fig 3 illustrates the explosive rise of Nvidia since 2016. Fig 2: 2. Intrinsic stock analysis: Problems, problems, problems With the macro analysis completed, investors and stock analysts must marry these large-scale factors into the specific circumstances of each company. This is where intrinsic stock analysis comes in, where the stock analyst makes lots of assumptions and projections about sales growth, operating margins, future profitability, the moats which protect a business, the future risk matrix, and ultimately arrive at a target valuation. Subsequently translated into a target price and a Buy, Hold, or Sell rating for the stock. One can but marvel at the sheer quantity of information analysts crunch as part of each stock price workup. Analyses which very much help investors to think about a business in the context of whatever their core beliefs may be. Nevertheless, intrinsic analysis remains exposed to the garbage-in/garbage-out (GIGO) principle: screwup important assumptions and you will screwup your valuations. Analysts at the big brokerage houses obligingly demonstrate the amazing diversity of such screwups. Analyst Forecasts: Chronic problems and a Massive opportunity Zooming in we see that the benefits accrued by zero-r* dynamics have been far from symmetric. Companies like the US ‘Magnificent 7’ with businesses protected by high moats and with products facing marketplaces, fashions, and consumer behaviour boosted by zero-r* conditions have never had it so good. Figs below are drawn from a random sample of stocks: the black line in the upper pane represents the traded stock price, the brown line the consensus analyst stock price forecast. The lower panes depict the proportion of analyst Buy and Sell ratings at any point in time. It’s a theme we’ve followed since 2009: sell-side analysts possess no predictive power whatsoever as countless academic studies attest. Analysts seem to end up setting their stock price targets around 10% above wherever the stock price happens to be trading. Sure, these are typically 12- month price targets in which time the company will supposedly have paid investors their cost of capital. If only life were so simple. Perhaps there’s another reason why analysts possess so little predictive power: all investors get access to the same information at the same time. A priori we would expect the market to swiftly assimilate information it is familiar with, leaving the trickier problems aside until later. As we all do when faced with a difficult exam; first answer the questions we’re familiar with, returning to the more difficult problems later. It is here investors are most likely to be led astray by what others are thinking. We’re now at the inner core of Eriswell’s belief system: Analysing ‘uncertain’ and ‘unprecedented’ information. Investors and analysts are generally comfortable dealing with run- of-the-mill new information while ‘unprecedented’ and ‘uncertain’ information is more difficult. It’s worth exploring this notion a little further: The large brokerage houses routinely process vast pools of information, which renders their dismal failure to accurately forecast asset prices something of a conundrum. By synchronously turning the handles of standard valuation models there can be no doubt that the sell-side helps markets digest prodigious quantities of new information. Over time, however, the rigidity and homogeneity inherent to these conventional techniques encourages analysts to develop systematic blind spots. Blind spots where the poorly understood, unprecedented, and uncertain factors can quietly develop out of sight. Eriswell calls them ‘stealth factors’. At this point forecasting failure becomes all but inevitable as the market struggles to discount these stealth factors into stock and bond prices via the normal price discovery process. Destined to lie dormant for a while, before popping up somewhere to surprise investors and trigger an earnings or other surprise. An asymmetric asset price return profile inevitably follows, bouncing stock analysts into the backseat where they are left to devise authoritative explanations about things they had never spotted in the first place. Switch on CNBC or Bloomberg Markets for real life examples! It’s a funny old game where uncertain, unprecedented, and poorly understood factors become the final arbiters of asset prices. But remember, for investors ahead of the game, these ‘unexpected’ price nonlinearities represent deep pools of opportunity; alpha, in other words the stuff we’re all after. Now think about it It’s hard to imagine a less-precedented and more uncertain backdrop than today’s zero-r* conditions. There have been so many analyst, institutional, and central bank mistakes over the past few years that many ‘experts’ are resorting to complex arguments to hide rather than developing simpler arguments to explain: “There are horrible people who, instead of solving a problem, tangle it up and make it harder to solve for anyone who wants to deal with it. Whoever does not know how to hit the nail on the head should be asked not to hit it at all.” Friedrich Nietzsche Forecasting the future or tracking the past? You decide Let’s start with Nvidia (Fig 36), can you see the way stock analysts deftly spotted the impending explosion in its stock price? No, neither can we! Turning to Amazon and Microsoft (Figs 3 & 23), can you see how analysts did very much better? Neither can we! UK Furniture retailer DFS is a simpler, more modest affair than the tech goliaths; surely analysts did a better job there? Alas not; they remained hopelessly bullish in H2 2021 with consensus forecasts about 3x the level DFS trades today (Fig 37). Unaware that DFS’s customer base is very much drawn from the zero-r*’s ‘have nots’, analysts, alarmed by the downward spiralling stock price, were forced to repeatedly cut their target prices. This collective loss of nerve expresses itself in a phenomenon Eriswell terms ‘price hugging’, whereby in times of stress, analysts seek the safety of the herd by continually tweaking their valuation models to keep forecasts in line with traded stock prices. Consequently, it is no longer analysts who drive stock prices, rather traded stock prices which drive the analysts’ price targets. The cart has somehow ended up before the horse. Now you may say, so what, analysts make honest guesses and sometimes get it wrong... we all do sometimes. We agree and many analysts do too; the trouble is, most find themselves softly pressurised by their employers to get their forecasts back into line with traded prices. Such soft pressure remains common practice even though explicit pressure is forbidden. In effect, analysts find it hard to openly express their opinions which in turn opens the murky waters of face-to-face meetings with favoured clients where private feelings can be more freely expressed. Whether this is of any value is another question. This practice ends up leaving investors in something of an information vacuum in which they receive retrospective explanations about the past as opposed to unbiased guidance about where stock prices might be headed. Which is the whole point of the exercise. Conclusion It would be unfair to write off the stock analyst community, they’re doing their best in an uncertain world. Where both earnings outcomes and the valuations investors are prepared to assign to them are in a state of flux. A world in which even the best of us makes mistakes. Every era brings its own complications, but zero-r* idiosyncrasies can magnify these into a tsunami where positive and negative factors alike can gain the power to wash away those who didn’t see it coming. As for fundamental stock analysis, is a waste of time? Not at all, in fact Eriswell believes it to be the only coherent tool to value a stock in terms of what we see in the company’s future whether that be awesome or terrible. Notwithstanding which, to accurately value a company’s stock in today’s zero- r* world we must adapt these techniques to capture how companies may fare in these largely unprecedented circumstances. Afterall, investing is always about the future. A businesses’ history, no matter how illustrious, only has relevance to whether it represents a good investment to the extent this history remains applicable today. Part 2 of this note will examine how exactly we adapt intrinsic valuation metrics to today’s zero-r* world. Kind regards, Mark Page