The Mechanics of a Mispricing
There have been a few other related posts that I have commented on recently that touched on mispricings and catalysts. I wanted to take some time and write something up that brings it all together in one post. This is something that took me a while to understand and come around to when I was starting out, and it would have been helpful if I had come across a post like this, so this written for first-year/still trying to break in me. It might come off as overly academic, but the general framework is essential to generating actionable recommendations as an analyst. Plus coming from a non-target no-name liberal arts school, I sure as fuck didn’t get any exposure to this in undergrad.
It is of paramount importance for an analyst to understand several components of a mispricing in order to have confidence that he/she has identified a truly actionable idea. First, an analyst must have an understanding of EMH (Efficient Market Hypothesis), how/why it can break down, and how it can correct.
What is EMH?
EMH posits that security prices reflect all available information. All available information does not include material non-public information (like an unannounced buyout at a premium) that would be expected to move market prices. Available information consists of plain vanilla public information (10-K’s, other Edgar filings), quasi-public information (technically public, but difficult or costly to obtain, like satellite images or credit card data), and non-material non-public information (would not by itself be expected to move market prices). For this available information to be fully reflected in market prices, it must satisfy 3 conditions. It must be:
- Fully disseminated to a sufficient number of investors (Investors must have the information or be aware that it exists).
- Processed by a sufficient number of investors without systematic error or bias.
- Expressed and incorporated into market prices via a sufficient number of investors acting on their information and trading the security.
This works on the wisdom of crowds principle. There are numerous pieces of literature that support why the wisdom of crowds principle works, but the basic premise is that when a large and diverse group aggregates information, the collective is stronger than any one member of the groups’ individual information. I would encourage you to read more on the wisdom of crowds on your own, deeper discussion is outside the purpose of this post, but the wisdom of crowds is the governing mechanism needed for an efficient market price. There are several characteristics of the crowd that are necessary for market efficiency:
- Information must be available and observed by the crowd.
- The group must have an adequate amount of domain-specific knowledge (facts or expertise).
- The crowd must be diverse (very important).
- Investors must act independently of each other (also very important).
- There cannot be significant impediments to trading (such as a lack of liquidity).
- There must be adequate incentive to express estimates that participants truly believe is accurate (such as an analyst expressing their true estimate of value and not tweaking numbers to get closer to consensus).
When all of the above characteristics are present, it is impossible to beat the consensus and the market price will be fully efficient. The three characteristics that are most likely to be challenged are diversity, independence, and trading impediments.
When Efficiency Breaks Down
I would also encourage you to read up on behavioral finance, I will touch upon it briefly here, but there is much to be aware of that is also outside the scope of this post. Behavioral finance offers insight into the potential errors individual investors can, and will make, when processing information in the context of investment decisions. The market price of a security at any given moment reflects the consensus estimates of intrinsic value. Let me re-iterate this point: At any given moment, the market price of a security reflects the views of participants in the market who have processed all available information and acted on their estimates of value by trading the security.
A change in market price should logically be driven by a change in the consensus estimates of value (the crowd’s view). As expectations evolve and vary over time, market price will/should evolve and change over time. We know through studying behavioral finance, that the crowd’s expectations can at times become too optimistic or too pessimistic, and can be influenced by factors that may, or may not, have a material effect on a company’s underlying fundamentals. When this occurs, a mispriced security follows. The wisdom of the collective can break down due to several factors:
- Crowd diversity is lost: the crowd becomes too focused on the same set of facts or the facts become framed to similarly among participants.
- Independence breaks down: individuals set aside their estimates in favor of following the views of individuals whom they may think have better estimates or better access to private information. (A breakdown of independence is often how bubbles and crashes form)
- An investor arrives at an estimate but does not express it through trading the security (may not have access to adequate liquidity or may not have enough incentive to express a view that is different than consensus. Also may not be confident that their estimate will be realized within an adequate time horizon).
EMH and behavioral finance are often positioned as alternatives or conflicting theories, but in reality, they go hand-in-hand with each other.
Where the Analyst Comes In
In order to outperform the market, an analyst must have a view that is different than consensus, be correct in that variant perspective, and identify a catalyst that will allow the mispricing to correct (thereby realizing the difference in value between their estimate and the security’s intrinsic value). To identify a genuine mispricing, you must identify why EMH has broken down. In other words: what is the market missing; why is the market missing it; and how will the market realize its error and correctly price the security? Knowing how strong the wisdom of crowds principle is, the analyst must have some kind of edge or advantage that allows him/her to have a true variant perspective. There are generally 3 different types of analytical advantage/edge:
- Informational Advantage: you have information that other investors do not have, and as such, has not yet been incorporated into market price due to the lack of dissemination or adequate processing.
- Analytical Advantage: You see things that others do not or believe that the crowd is being systematically influenced via a lack of diversity or independence that is obscuring views (everyone thinks they have an analytical advantage).
- Trading Advantage: You can trade or hold the security when other investors cannot.
The most common way to outperform the market is to combine an informational advantage with an analytical advantage. It is much more difficult to outperform on any one of the above in isolation. Under the mosaic theory, an analyst can gain a legal informational advantage. Further explanation of the mosaic theory would evolve into too much of a post on research process, and this is again outside of what I want this post to accomplish, but the mosaic theory posits that an analyst can obtain a collection of non-material non-public information that in isolation is not considered to be material, but when aggregated allows the analyst to form a material conclusion.
Catalysts
Once you have come up a variant perspective estimate of intrinsic value and correctly identified why market efficiency is breaking down and why you are not subject to the same errors, you now must identify a catalyst. The catalyst is the event that serves to force the market to close the gap between your estimate of intrinsic value and the security’s market price. The catalyst, in its purest form, is information that the market does not have, that becomes fully disseminated, processed, and incorporated into market prices via trading. If you have identified a true mispricing via an informational and analytical advantage, when your information becomes full disseminated or acknowledged by the market, it should work to close the gap between your estimate and market price. Again, a catalyst can be any information that the market does not have, that the market then obtains, and processes without bias.
So this can be a merger, a regulatory approval, better than expected/worse than expected quarters or guidance, a buyout, bankruptcy… a plethora of events could be considered a catalyst; however, there is a big difference between a catalyst you can be confident in (I pretty much know this will happen) and a catalyst you can be hopeful of (this could happen). Legally, if you have information of a merger/buyout, that isn’t something you can trade on if it is not public, but if you think a merger is likely after having conversations with various industry participants, that could be tradable. The question the analyst has to ask is how much confidence can I have in this catalyst coming to fruition? Confidence is strengthened by depth of research and the creation of a stronger mosaic.
Timing
It is not enough to identify the mispricing and the catalyst, you also must be accurate in your assessment of timing. The actual amount of time that it takes for a mispricing to be corrected directly determines your realized annual return. One reason that an investor’s estimates of value may not be incorporated into a security’s market price (causing a breakdown in EMH), is that they may not be able to be confident in the timing of the catalyst (or may not be confident in the catalyst at all). I often will comment that there will always be a place for disciplined investors that can take a long-term time horizon. The reason that investors with longer-term time horizons and lower turnover are proven to generate alpha is that a lot of market participants do not have the luxury of patience.
At many funds, a year or two of underperformance will result in a pink slip. So if an analyst identifies a mispriced security with a catalyst, but said catalyst is uncertain with regards to timing, they may not put the trade on at all (in effect, causing a further breakdown in EMH as their estimates are not incorporated). Further, the more participants that are subject to this line of thinking (a breakdown in independence), the less a security will be traded, which could further cause distortions. Say the security in question has been identified by a participant who DOES have the ability to take a long-term view, but liquidity is insufficient for them to take the position on, the security will become further mispriced. This is why the catalyst, and the timing of said catalyst, is of paramount importance to be accurately identified by an analyst. In absence of a catalyst, a mispricing can persist indefinitely as long as the key tenants of EMH remain broken.
Anyone can find cheap stocks, it is not enough to say this stock is cheap relative to peers or my estimates. You must identify why the stock is mispriced, and what will cause it to become appropriately priced. I’d like to end the post here while it is still mostly focused around the mechanics of a mispricing. I hope this post will help those of you who are searching for names for your stock pitches. The more of the above questions you can address, the better your overall pitch will be and the more confident you can be in a Q&A session. This is my first post of this nature, aimed to give back, as there is some very valuable content on here that helped me when I was first starting out. Perhaps I will do more of these in the future if it gets a good response, but I am by no means an expert on anything. The beauty of being an analyst is that your process constantly evolves, and every day you learn something new. Take what you learn in stride and be ready to at any moment sacrifice what you thought you knew in favor of better information.
Cool write-up. Any recommendations for a good read on behavioral finance?
There's a decent amount of content on behavioral finance in the CFA curriculum, which was my intro. Two others outside of that I've read would be "Manias, Panics, and Crashes" and "Thinking Fast and Slow (not specifically finance but it ties in)
"Thinking, Fast and Slow" was a tremendous book. Three other great books I've read that are heavily influenced by Thinking, Fast and Slow are "Thinking in Bets", "Fooled by Randomness", and "The Most Important Thing".
Definitely read Kahneman. Also, a good survey of the literature that is digestible for the average finance guy is here: https://www.amazon.com/Behavioral-Finance-Understanding-Cognitive-Econo…
A bit more technical, but this is also a good one from one of the big guys (even if it's getting fairly old): https://www.amazon.com/Inefficient-Markets-Introduction-Behavioral-Clar…
Another great book is "Why Zebras don't get ulcers" by Sapolsky
Dude I am a pretty low-quality WSOer.... but whoever is MSing educational threads like this should gas themselves.
Agreed. Of course they MS'ed this too ... there should be a requirement to, you know, say what you don't like about something instead of a hit-and-run MS, like save that stuff for my posts. But I guess toolbags need attention.
Eh. I didn't throw any MS but the OP practically pasted a few textbook chapters without even the courtesy of shortening them.
haha I did my best to only discuss the most important points, it could have been worse. I tried to write something that would have been useful to my younger self to have come across, this shit wasn't in the textbooks I was reading in undergrad.
Thank you
Is this post straight from the book "Pitch the Perfect Investment"?
Tried to organize it the same way, one of the better books out there. There have been a few posts and comments out there recently around the subject of mispricing and whether fundamental guys can still add value. Thought it would be helpful to discuss.
What do you mean technical... like
Let's say SPX 1w ATM vol is bid day before NFP on some -ve growth headline (Trump/China, etc.)...
You observe :
a) there were buyers who pushed up the price for not a good reason
b) your model says the price > (fair value + spread + trading costs etc.)
a) is behavioral and b) is the technical reason? Is b) also technical since other funds would also have models saying the same but have not hit the bid b/c maybe risk/reward not good enough?
Also what's an example of an action that's rational but market-inefficient?
Thanks for the post.
I read something interesting about catalysts in Baupost’s latest letter that I wanted to share. According to Klarman, catalysts help diversify the duration of a portfolio. A portfolio consisting of just equity without catalysts will be at the whims of the market, and this volatility can pressure the investor to sell holdings precisely at the time he/she should be buying. Thus, catalysts increase the probability of your thesis coming to fruition.
The full quote: “We believe another key element in portfolio management is curtailing the duration (the weighted average life) of one’s portfolio through exposure to investments with catalysts for the realization of underlying value. Catalytic events shift the outcome of investments from a reliance on future market multiples and macroeconomic developments (which are not at all under your control) to a dependence on your assessment of the outcomes, probabilities, and implications of announced or anticipated corporate events...”
I'm sorry but am I the only one who gets annoyed at the attempt to use complexity in language / explanation of an otherwise straight forward topic to make it seem more sophisticated / nuanced. Catalysts are straight forward: an identifiable corporate event (bankruptcy filing date, merger closing / announcing, etc.. I really don't see the need to romanticize and make poetry of it. Hedge funds can be such intellectual snobs in my opinion. Just a pet peeve, but you're taking a view on a corporate event, not exactly splitting atoms or saving the manatees here...
Stating the obvious and reinforcing the obvious with academic theories and prose doesn't make you an intellect, it makes you Malcolm Gladwell. Thanks for giving me a quippy thing to say to the next higher and holier than thou analyst.
I think that is absolutely huge. Leaving aside the beta exposure, your thesis can get drowned out by randomness as time passes without a near term event to surface value. I can't mathematize it, but the longer you have to before the price of an investment rises or falls to some perfectly rational intrinsic value, the greater the percentage of your return is due to unforeseeable subsequent events.
Great post Secyh62 - hope you continue on and dive into some of the "other" topics you referred to (research process, behavioral finance etc.).
Great post. Thank you
Guys here is a really good writeup that just came out from Blue Mountain this week. Much more in-depth than my post and very well done IMO. It's long so check it out when you have the time.
https://www.bluemountaincapital.com/wp-content/uploads/2019/02/Who-Is-O…
Can you please expand on these two points?
On having a trading advantage: I think it is easier to visualize with an example: say you're a small cap manager, and you scale a fund from 500M to 5B. Let’s say you generally target 1% of the fund as a starting point to build positions. At 500M, you're talking about 5M entry level position sizing. If you've found a small cap name that you think is mispriced, and say it trades 20M a day in dollar volume, you can probably easily build up your position with a passive algo over 1-3 days without moving the price too much. But now if you're running a 5B fund, your initial position is 50M, more than 2x average daily volume. Now it might not even be worth it for you to do the work on the name because you probably can't build the position to scale without arbitraging away your perceived price inefficiency. So a more agile/smaller investor may be able to hold this when larger investors cannot. Another example from the credit space: If an IG security gets downgraded to HY, there might be immediate forced selling pressure that could lead to a mispricing. Some IG credit funds simply aren’t allowed to hold HY names, and will be forced to blow out. An investor with a more flexible mandate would be able to take advantage of this.
On forming a mosaic: Legally, you can’t trade on material non-public information. Example would be your buddy at JPM IB tells you that a company is being bought out at a significant premium by a larger competitor and they’re the advisors on it. You’re now in possession of material non-public information and can’t do anything unless you want to end up like Martha Stewart. The mosaic theory however, reasons that you can collect and combine material public information, and non-material non-public information, to form a material conclusion. An example here (assuming the JPM conversation never happened) would be you talk to several industry experts who tell you that it would make sense for the large competitor to buy a smaller competitor. You talk to several distributors who say they think companies X Y and Z would make the most sense as targets. You analyze the smaller competitors and try to evaluate which combination would result in the most synergies and be least likely to get an anti-trust challenge. You talk guys up and down each of the three companies’ supply chains and you find out that company Y has put a pause on new orders. You come to the conclusion that company Y is the most likely target and take a position ahead of the potential merger news. All of those pieces of information are not material non-public information in isolation, but when combined, allows the analyst to form a material conclusion that a merger is likely and that company Y is the most likely target.
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