The Indian stock market has been remarkably resilient in the wake of slowing earnings growth and elevated valuations. Experts attribute it to the sustained flows into mutual funds by retail investors who are supposedly less discerning about valuations and fundamentals. But many believe in Benjamin Graham’s quote that the market is a voting machine in the short run and a weighing machine in the long run, i.e, market prices eventually converge to fundamentals.
The Efficient Market Hypothesis which posits that the market price of an asset reflects all available information, has had its share of critics in the past including the likes of Warren Buffett and Daniel Kahneman. Intuitively, the critics are right. Information available today should help drive judgements about future cashflows but that judgement in itself is prone to cognitive biases of the market participants which results in different assessments of value of an asset even with the same information. This blog takes the critics’ argument further and suggests a way for practitioners to deal with this inefficiency.
First, the author highlights how even professional analysts have wide ranging target prices of a stock:
“These are not estimates of retail traders firing from the hip. These are highly trained, highly-paid professionals operating in a hyper-competitive industry—each with access to the best information available. And yet the dispersion is staggering: Tesla’s 12-month targets range from $85 to $400—a difference of 371%. NVIDIA’s 12-month targets range from $400 to $1,400—a difference of 250%. And these figures vastly understate the differences in valuations among analysts because these are only 12-month targets. If you were to take a survey of the fundamental value of each stock, the variations would be far more massive. To take just one example, the analyst team at ARK Innovation ETF (ARKK) has estimated Tesla’s intrinsic value to be well over $2000, while other analysts estimate the intrinsic value of the company to be below $50.
If the EMH means anything at all, it must mean that under conditions approaching its own assumptions—rational, well-informed professionals with instant access to information and few frictions—valuations should converge tightly. They don’t.
This is not an anomaly. It is the rule. Even in the most-watched stocks in the world, disagreement is wide, persistent, and irreducible.”
He then goes onto support his argument citing an experimental study by Vernon Smith and case studies by arguably the world’s most accomplished practitioner of security analysis Benjamin Graham himself, who uses a wide range of intrinsic value estimates.
Then, he introduces his Optimistic Fringe Principle to debunk another argument of those who believe in Efficient Markets:
“…defenders of the EMH sometimes retreat to their final line of defense: that the market price aggregates these diverse valuations in a manner that generates an informationally efficient price. The claim is that the double auction synthesizes all divergent opinions and produces a single estimate of value that is better than any single analyst is capable of producing on their own.
The problem is that this line of defense is mere rhetoric: there is no mechanism for this miracle. The EMH does not have a theory of price formation that can explain how it is that the market aggregates disparate valuations and somehow is able to select one that is the “best” or “most unbiased” one. The reality is that the market mechanism is not a “weighing machine”, that somehow considers all possible valuations and arrives at the best one. The mechanism that determines price in the stock market is a double auction. And in a double auction, the price is determined not by averaging or weighing opinions but by matching the highest bid with any offer that is at least equal to it. As I have explained in multiple articles and in my extensive FAQ, the margin where supply meets demand, where the ask meets the bid, and where the price is actually transacted is ALWAYS located at the extreme fringe—the optimistic fringe—of the distribution of valuations for that particular stock.
This means that, contrary to what the EMH suggests, the market price is always drawn from a biased sample of opinion. If the price systematically reflects the most hopeful participants and ignores that of its most cautious, it cannot be the “unbiased estimate” the EMH promises. Furthermore, a price that procedurally disregards the information, knowledge, and opinions of the vast majority of market participants cannot be “informationally efficient.””
Finally, he ends with practical advice for practitioners:
“Here are just a few actionable implications of the analysis in this article and their relation to the Optimistic Fringe Principle of price formation:
1. Stop chasing a number; map the range. Intrinsic value is never a point; it is a spectrum. Like Graham, build ranges based on different scenarios. Understand that today’s price will reflect assumptions that are based on the most optimistic scenarios that are believed within the market at that particular point in time.
2. Identify the fringe’s story. The market price is not based on a consensus; it is the price that the most optimistic are willing to pay for. Your task is to understand the story that justifies the price.
3. Reverse-engineer the price. Work backward from the current price to reveal the assumptions of the fringe: growth, returns on capital, terminal values, and discount rates. Then stress-test their plausibility. The implicit assumptions will generally reflect the most optimistic assumptions that are considered to be plausible at that point in time by market participants. Are these assumptions optimistic enough, given your analysis? And if they are more optimistic than your own analysis suggests, are they at least plausible?
4. Act when the story is set to change. The biggest opportunities arise when the dominant narrative is about to shift. For example, the optimistic fringe may not be optimistic enough about upside if certain contingencies materialize. Alternatively, the valuation of the stock may reflect assumptions that not even the most optimistic value-conscious investors in the market sincerely believe, leaving the stock vulnerable to contingencies that may soon render the most bullish scenarios, believed by the most bullish market participants, implausible.
5. The current market outlook. The wide dispersion in the valuation of some of the market’s top stocks—e.g., NVIDIA and Tesla—is an indicator of the structural fragility of the market. It suggests that there is a discontinuity in the structure of demand. If the current optimistic fringe were to “lose faith” for any reason and exit, sellers would face an “air pocket” due to the wide dispersal of valuations. In the event of substantial selling, value-sensitive demand (new members of the optimistic fringe) will only stabilize the market for those stocks at much lower levels.”
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Note: The above material is neither investment research, nor financial advice. Marcellus does not seek payment for or business from this publication in any shape or form. The information provided is intended for educational purposes only. Marcellus Investment Managers is regulated by the Securities and Exchange Board of India (SEBI) and is also an FME (Non-Retail) with the International Financial Services Centres Authority (IFSCA) as a provider of Portfolio Management Services. Additionally, Marcellus is also registered with US Securities and Exchange Commission (“US SEC”) as an Investment Advisor.
