Hello! Currently preparing for HF interviews and have a few more fundamental questions on the cornerstone piece of the stock pitch, the variant view.
I'm struggling with the concept of variant vs. market/ street/ consensus view. I understand the purpose is to beat the market by having a unique perspective, but what I don't understand is how we can ascertain (with a high degree of certainty) whether and how this view differs from the market (other than just the obvious observation of the stock price). Say we come up with our independent view via a DCF and say the implied stock price is $100. It currently trades at $80. Sell side consensus is $100 too.
1- How do I know what price drivers differ from the street/ market? Sure, the stock price differs, but that's not going to be sufficient for an investment thesis with a well thought through variant view. Sure, we can do some desk research and find a single perspective on when we think a competitive product is going to be launched or take mgmt guidance (in as far as mgmt discloses), but how could we be certain that that is actually the street/ market view? In the thesis, we would say (simplified): 'We expect revenue to be X and margins to be Z, WHILE market expects Y and W, and that is why the stock is mispriced'. But I struggle to understand where we get the information for Y and W from. Isn't that the most important to know? Otherwise we're coming up with a view in a vacuum and that view might be distorted as we don't know where we exceed/ fall short of market expectations?
2- In the pitches I've seen references to 'consensus'. What do we typically mean by that? I'm familiar with sell side consensus (e.g., pulled from CapIQ) and I assume that's what people are referring to. But isn't that the wrong consensus regardless as the sell side is not trading the stock and we wouldn't know what actually is priced in? If that is true, wouldn't we have to know buyside consensus? But how would we find that? Or said differently, if our margin estimate for product XYZ is 50% above sell side consensus, but every investor has priced it in this is nothing more than a, at best, additional data point (like any other).
3- For the investment thesis part of the pitch: how do you guys quantify your views vs. the market? Shouldn't the thesis solve for: here's why we think the stock is undervalued by x% (congruent with base case), and then on top of that, here's why we think there's further upside of x% (congruent with upside case). But going back to 1- and 2-, for this to be true, you'd have to know the actual market/ buyside consensus DCF that encapsulates all the price drivers that drive the price diversion in our variant view and that yields the current stock price?
Appreciate the help.
I’m not sure I can answer all your questions directly, so I would defer to someone who can and has more buy-side experience than myself. With that said, you raise some good points about the material dispersion between the sell-side and buy-side consensus estimates.
What I try to do is work backwards. For example, for a profitable, more mature company that is still growing, if sell-side consensus is X for EPS, and the market is pricing the stock at Y, what is the delta between Y and what X EPS would yield for price target in a model. The market is essentially the buy-side consensus (mixed with some other retail and passive noise), and you can make an argument as to why you expect a company to earn X and why the market price of Y signifies a buy-side consensus of Y EPS. If the gap between your estimates and gauge of buy-side consensus is large and you have good reasons to explain how you arrived at your estimates, then you may have a good contrarian (as you call it, “variant” view).
You can play a similar game with revenue, margins, same stores sales, or whatever line items and KPIs are most important/relevant for the individual company or industry you are looking at.
Thank you. Maybe I'm misunderstanding here, so feel free to throw at me.
Could you explain how exactly you get to gauge EPS Y in your example? Let's call sell side=X, buy side=Y and our own view=Z.
I think what you're trying to solve for is a comparison of EPS Y and EPS Z. But wouldn't we still only have the stock price Y as the input for the buyside consensus? Meaning you'd need to assume a PE to get to EPS Y, right? Or how would you make the argument that EPS Y is what you think it is?
That aside, wouldn't the purest form of what you're describing still remain the comparison of stock prices Y vs Z (potential variant view that we found via the DCF)? If that's true, I wouldn't see a need to estimate EPS Y to compare with EPS Z because the stock price would be the better less convoluted metric?
Separately, let's pick a retail company for the sake of this. Could you explain how you'd apply your logic to infer about topline drivers such as same store sales growth as you say or new store openings?
Response moved in line
Hi curious42,
So, annoyingly, I just spent a long time writing up a super detailed response, didn’t save it anywhere else, and when I posted it, it magically disappeared and didn’t appear on the website. Maybe others can see it as a post, but I’m assuming not. Not sure how/why that happened, but I’ll be copying before posting from now on in case this happens again.
Now, since I’m short on time but want to make the time I already spent writing the original response worthwhile, I’ll try to summarize the most salient points I had cause I would still like to help.
I second what the two commenters below (longandshort & mtnmaster1) said. They shared some very helpful insights. The work of fundamental analysis is as much, if not more, of an art as it is a science.
The way I went about my example/thought experiment from yesterday assumed a restriction of resources, so it would work for someone who is preparing to interview and is not currently in a seat that offers access to more advanced tools, Street “chatter,” or paid-for information, data, etc. If you have access to that stuff, you have other methods for trying to glean the street consensus. Let’s assume you don’t have access to a Bloomberg terminal or anything of the sort in this example.
On solving for a comparison between EPS Y and EPS Z, yes, in this example, the only significant input you have for determining the buyside consensus is stock price Y. So, consequently, you would need to assume a P/E ratio to get to EPS Y, as you correctly point out. However, to do so roughly is not so difficult (doing so precisely is a different story) because you can use the TTM and NTM P/E multiples that the current market price reflects and try to play around with this to determine the multiples that the bear case, base case, and bull case are assigning to the company. The aggregate of this is effectively the buyside consensus you are seeking. Your DCF should give you a view as to what you think a more appropriate multiple for the stock should be (depending on the quality of your assumptions), and so you can then take the consensus multiple (baked into the price) and your multiple (taken from the price Z your DCF yields) and determine whether or not you may have a worthwhile variant investment opportunity from there.
On whether the purest form is instead a comparison of stock prices Y and Z, you should go down that route if it makes you feel most comfortable. Sometimes, however, stock prices are messy and reflect a lot of noise that the buyside is trying to cut out in their consensus anyway. Estimating EPS Y that you can compare with EPS Z may help cut through some of that noise, especially if the company’s stock price is heavily influenced by passive flows and/or has lots of retail interest unconcerned with valuation, earnings estimates, and/or other relevant key metric(s) for evaluating a company’s performance.
For an example that applies my logic (or something adjacent) to infer about topline drivers for a retail company such as same store sales growth or new store openings, I recommend checking out the Value Investors Club write-up on CAVA posted by ThinkAnew on August 13, 2024. Though it’s not a perfect example or exactly what you asked for, I think the short recommendation does a good job of explaining how the Street (in this case, both the sell-side and the buyside) is pricing the stock to perfection as if the company is definitely going to grow into the next Chipotle. I think the author also demonstrates well that the buyside is taking the sell-side’s lofty estimates at face value and pricing the stock as if the most likely outcome is nothing going wrong and everything going as well as it did for Chipotle. Putting aside that the stock has run-up more since the report was posted, the write-up itself shows that if you revise the very optimistic estimates for both same store sales growth and new store openings to be even slightly more conservative, things start to look a lot less rosy for the stock, and the downside risk in being (unhedged) long CAVA is quite significant. Hopefully, this illustrates what you were looking for when you asked me to come up with my own retail firm example to explain how I’d apply my logic.
I hope this all helps. If you have any more questions or thoughts, please feel free to PM me or follow up in this comments chain, and I’ll try to help where/when I can. Thanks for your engaged response, and take care in the meanwhile! Also, sorry you’ll never see my original reply lost in the abyss. I think it had some additional helpful tidbits I can no longer recall, but I think this message has the most important elements.
Hi curious42,
So, annoyingly, I earlier spent a super long time writing up a detailed response, didn’t save it anywhere else, and when I posted it, it magically disappeared and didn’t appear on the website. Maybe others can see it as a post, but I’m assuming not. Not sure how/why that happened, but I’ll be copying before posting from now on in case this happens again.
Now, since I’m short on time but want to make the time I already spent writing the original response worthwhile, I’ll try to summarize the most salient points I had cause I would still like to help.
I second what the two commenters below (longandshort & mtnmaster1) said. They shared some very helpful insights. The work of fundamental analysis is as much, if not more, of an art as it is a science.
The way I went about my example/thought experiment from yesterday assumed a restriction of resources, so it would work for someone who is preparing to interview and is not currently in a seat that offers access to more advanced tools, Street “chatter,” or paid-for information, data, etc. If you have access to that stuff, you have other methods for trying to glean the street consensus. Let’s assume you don’t have access to a Bloomberg terminal or anything of the sort in this example.
On solving for a comparison between EPS Y and EPS Z, yes, in this example, the only significant input you have for determining the buyside consensus is stock price Y. So, consequently, you would need to assume a P/E ratio to get to EPS Y, as you correctly point out. However, to do so roughly is not so difficult (doing so precisely is a different story) because you can use the TTM and NTM P/E multiples that the current market price reflects and try to play around with this to determine the multiples that the bear case, base case, and bull case are assigning to the company. The aggregate of this is effectively the buyside consensus you are seeking. Your DCF should give you a view as to what you think a more appropriate multiple for the stock should be (depending on the quality of your assumptions), and so you can then take the consensus multiple (baked into the price) and your multiple (taken from the price Z your DCF yields) and determine whether or not you may have a worthwhile variant investment opportunity from there.
On whether the purest form is instead a comparison of stock prices Y and Z, you should go down that route if it makes you feel most comfortable. Sometimes, however, stock prices are messy and reflect a lot of noise that the buyside is trying to cut out in their consensus anyway. Estimating EPS Y that you can compare with EPS Z may help cut through some of that noise, especially if the company’s stock price is heavily influenced by passive flows and/or has lots of retail interest unconcerned with valuation, earnings estimates, and/or other relevant key metric(s) for evaluating a company’s performance.
For an example that applies my logic (or something adjacent) to infer about topline drivers for a retail company such as same store sales growth or new store openings, I recommend checking out the Value Investors Club write-up on CAVA posted by ThinkAnew on August 13, 2024. Though it’s not a perfect example or exactly what you asked for, I think the short recommendation does a good job of explaining how the Street (in this case, both the sell-side and the buyside) is pricing the stock to perfection as if the company is definitely going to grow into the next Chipotle. I think the author also demonstrates well that the buyside is taking the sell-side’s lofty estimates at face value and pricing the stock as if the most likely outcome is nothing going wrong and everything going as well as it did for Chipotle. Putting aside that the stock has run-up more since the report was posted, the write-up itself shows that if you revise the very optimistic estimates for both same store sales growth and new store openings to be even slightly more conservative, things start to look a lot less rosy for the stock, and the downside risk in being (unhedged) long CAVA is quite significant. Hopefully, this illustrates what you were looking for when you asked me to come up with my own retail firm example to explain how I’d apply my logic.
I hope this all helps. If you have any more questions or thoughts, please feel free to PM me or follow up in this comments chain, and I’ll try to help where/when I can. Thanks for your engaged response, and take care in the meanwhile! Also, sorry you’ll never see my original reply lost in the abyss. I think it had some additional helpful tidbits I can no longer recall, but I think this message has the most important elements.
1. Buyside analysts will leverage a bunch of tools (Visible Alpha) and research access (sell side reports) to extract what sort of scenarios exist in consensus. E.g. the Bofa analysts says company A will do $5bn in sales NFY by selling 100mn widgets, while GS says $5.5bn on 110mn widgets.
2. "Consensus" between the two is simply the average (though you can adjust by time, e.g. 4-wk, or weighted by analyst preference) and would be $5.25bn with 105mn widgets being sold.
3. You do your own research and think a certain end market is accelerating, which means there is significant risk of 110mn widgets sold and an uplift to ASP -- your sales estimate is $5.8bn. That is a "variant" perception if it is not a view represented in consensus (e.g. if most analysts aren't citing the end market or commenting on it, then you can "guess" that you have a unique view-- from the street, not necessarily the buy side.)
Initially as an analyst you need to learn to think about your view vs. consensus (do you agree with one of the analysts, do you have your own unique view, or do you agree with the consensus number?). You can then try to compare vs. market price or vs. buy side whispers/bogeys (which is much harder and typically requires talking to spec sales people at major banks).
Very helpful responses. Thank you. Would be extremely curious to learn about the tools that enable HFs to build a real edge on understanding market consensus vs. going through sell side - but I guess I'll have to prove that I'm worthy in my interviews first.
Have two follow-on questions (probably looking towards the PMs/ analysts who are doing this day in an day out) for the pitches that I'm preparing:
1- For the valuations, I've seen DCFs being used most (variable of interest: intrinsic value vs. current value). But I've also seen EPS estimates for the next X years (especially for longer-term/ activist plays) with a PE exit multiple and holding period assumption. I'm new to this, so I want to put my best foot forward, and want to get as close to industry norm as possible. Would be very happy to do multiple approaches, but would expect one primary approach as otherwise bear/base/bull case would get messy quickly. Any guidance here?
2- I'm planning to quantify the different levers of my investment thesis. How do I best do that? From the answers so far, I'm revising my pitch to aim for a base case that is logically coherent and compelling (without paying attention to sell side price targets etc.). This gets me to my base case, which implies upside of say ~30% vs. current price. How do I now best make the argument for the different variable that drive my thesis? Could say sth like: 'Base case assumes X for same store sales growth. This is y% above street consensus, z% above mgmt guidance and here's why I'm confident in my assumptions e.g., peer analogy XYZ, mgmt has historically beat etc. If this growth assumption was wrong and growth was flat, my implied valuation would drop by a% but still show that stock is undervalued by b%.' I would then repeat this with the two other key drivers of my thesis. Could play a very similar game with EPS in 3 years. Would that make sense?
2.1- Connected to 2-, would you expect a pitch to include an IRR bridge? If so, how would best practice look for that? I think relatively clear for the EPS forecast where the 0% IRR case is just EPS in 3 years = EPS LTM, and with manipulation of different ops KPIs we can get to isolated IRR impacts? What about the DCF/ target price methodology though?
"Consensus" is sell side + buy side. There is a lot of research that shows that buy side and sell side views are largely similar, so you can read one to learn the other. From a KPI standpoint, tools like Visible Alpha or MODL help speed up that process (in the old days we would have to manually extract the info from sell side models or reports).
The underlying principle in valuation is that the value of a security is equal to the sum of future cash flows discounted back to present. This is true for both a DCF and multiples method valuation. I recommend learning the ins and outs of a DCF (it's simple -- forecast I/S and working capital, calculate WACC, take l/t growth and EBITDA exit multiple, etc.). Macabacus had a great template. However, most active market participants will use the multiples method because it's very clear as to what the driver of your price target is (is your change in price driven by the metric or multiple?). For most hedge funds, a trade is based upon an expected change in the metric. Because all of the metrics are forward looking, this tells you that at most hedge funds, valuation is about understanding where consensus estimates will go.
Common multiples are EV/Sales, EV/EBITDA, P/E, etc. Become familiar with them all and know how to back into enterprise value and equity value either way.
(1) discuss guidance and consensus first, then (2) your view of the metric and gap vs. consensus and why consensus is wrong, then (3) explain the catalysts that inform the market you are correct, then (4) multiply the stock's current multiple by your forecasted metric to get to delta and see what your price target is if your view is correct, (4) then cover key risks in your thesis of the metric. Keep it very simple at first -- your first draft should be boiled down to 5-8 bullet points. From there, you can add detail that is incremental or explanatory.
Super helpful. I've posted a new topic on tools Pods are using to stay ahead. Anyone can access them. Please add any that I may be missing. This stuff does really help shorten diligence time and get better variance. https://www.wallstreetoasis.com/forum/hedge-fund/key-tools-for-hf-analy…
Mostly answered already, but some additional thoughts here... its sometimes more art than science when it comes to backing into "market implied expectations," because valuation is more art than science, and it can be about relativism at times, especially depending on what game you want to play. Most obvious answer here is just use a data provider's consensus metric (bloomberg, capiq, fact set, visible alpha, etc.). As longshort said, figure out what the key drivers are for the business, and then what cases the sell side are estimating for these drivers (volumes, price, revenues, margins, EPS, FCF, etc.). Ignore sell side price targets for the most part - more a reflection of the underlying drivers and current market environment anyways.
The other side is looking at current valuation, historical trading ranges for itself and peers and similar "set ups," coming to an understanding of what "normalized earnings/xyz" can be, and seeing where things fall on this scale today. This is more of a range than anything else, but its another way to back into things. Your DCF and reverse DCF do this anyways.
Conceptually, the big harry variant perceptions are easy to understand. The data provider aggregate / sell side aggregate for revenue next year is $abc mn, but everyone gets there by extending out mgmt. guidance on capacity for xyz units at current pricing, while the new launch has pricing at 20% higher and new capacity is 10% higher so I'm at $xyz mn or whatever.
But another lens to view things through, which is where a lot of theses can fall, is about relativism and reinforcing/disproving the tails of the core value prop of a stock (kinda like the IR deck pitch).
Today's stock price is the balance of all bear/base/bull views of the stock, ie: a probability distribution - so sometimes you have results that aren't as big of a delta to anything else, and are more about reinforcing views along this probability distribution (and ideally, are hitting more at the tails than anything else). If your job is to trade a defined universe of stocks and be market neutral, you end up expressing views here a bit more. That's why results that fall in the "consensus bull" range can still drive stocks. Also stocks just tend to follow EPS revisions, and relativism with peers feels like it matters more and more these days - maybe less relevant to your question, but I think keeping it in mind can be helpful to understanding the backdrop of what we are comparing our own estimates against.
"Conceptually, the big harry variant perceptions are easy to understand. The data provider aggregate / sell side aggregate for revenue next year is $abc mn, but everyone gets there by extending out mgmt. guidance on capacity for xyz units at current pricing, while the new launch has pricing at 20% higher and new capacity is 10% higher so I'm at $xyz mn or whatever."
So you're hoping that everyone else made a mistake on the company's products? I get this is just a hypothetical example, but it seems like wishful thinking.
Well, building real edges takes a long time and is not something that you may necessarily even have for all the companies you cover.
Jr. analysts (0-2 years of buy side experience) should focus on analyst selection — read all the sell side and build your view around the most compelling 1-2 SS analysts you follow.
Experienced analysts (2-4yrs) should do that + have built out models that incorporate the edges or synthesis that their favorite SS analysts have.
Sr. Analysts (5+ yrs) are running their own process.
Yea obviously a hypothetical and is very rare that you have some scenario that the street misses entirely like that - if anything if you are that far off you are most likely wrong a lot of the time. Which is why I caveated that a lot of the work is more around the edges and reinforcing different parts of the probability distribution. More likely that you see EPS beat by 5% this year on the same general strength that everyone is aware of, but it is enough to drive the story further.
Curious42, I second what longandshort & mtnmaster1 have shared. Fundamental analysis is as much, if not more, of an art than a science.
I don’t think you misunderstood me. I probably didn’t explain it that clearly cause I’m using abstract frameworks to explain my process + my long holiday weekend vibes :) have an impact as well, but I think you got the gist. We may simply have different perspectives and methodologies for solving similar inquires, and that’s fine. Using your method through the model is another path to get to a similar result, but it may not be the same. That’s fine cause it’s not that one way is necessarily better/worse than the other all the time. Largely, it’s going to depend on how well the company is followed (and it’s market cap by extension) and exactly what key metric(s) you are looking to solve for. There is more noise in the price for some stocks than others. Also, valuation and earnings estimates (and other relevant key metrics) are not as big drivers of market price as they used to be. So, trying to isolate for EPS estimates can work well and be less convoluted than the price itself, but, as I said, it’s not guaranteed all the time to be the best method. If you feel more comfortable on a particular name comparing stock price Y and Z, then go for it.
In my particular thought experiment/example from yesterday, yes, I believe stock price Y would be your most significant/reliable, if not only, input for the buyside consensus. This is assuming that one is preparing to interview and not currently in a seat that gives you access to more advanced tools, Street “chatter,” and paid-for data, information, etc. (no Bloomberg terminal or anything of the sort) that can get you alternative sources for helping to piece together a view of the buyside consensus. In this instance, you are relying on free resources and good, independent analysis to try to derive the buyside consensus. If I’m solving for EPS with my only consensus input being price, you correctly point out I would then need to assume a P/E ratio to get to EPS Y. It’s not that hard to do roughly (precisely is a different story) if you look at the TTM and NTM multiples the stock is currently trading at. Depending on the quality of your assumptions, your DCF should give you a view as to what you think a more appropriate multiple should be going forward. I find this helpful and relevant cause I most often screen for investment opportunities with a relative value bend, but I suppose this wouldn’t necessarily work for everyone and is strategy/style dependent. I consider all the most relevant price drivers for a specific stock and then go from there to think about what various views on the buyside are composing the consensus (in this example, what are the prevailing bear, bull, and base cases for earnings). Again, this is more of an art than a science and requires practice. As you do more reps on a specific company or sub-industry, you’ll get better at figuring out the most relevant inputs and views driving the current market price.
I’d prefer not to come up with a detailed example of a retail company now given the long response I’ve already provided. For a relevant pitch that involves an analysis of same store sales growth and new store openings expectations vs the Street, I’d recommend going to Value Investors Club and reading the short recommendation on CAVA by ThinkAnew posted on August 13, 2024. In this pitch, the author’s underlying argument is that the buyside is taking the sell-side consensus at face value since almost everyone covering the stock seems to be pricing it to perfection as if it will definitely be the next Chipotle. ThinkAnew has inferred how the buyside view of these drivers (which in this case happens to be very close to the sell-side) are impacting the stock price and why the variant view presented in the pitch is the more likely outcome (things most likely will not go quite as well for CAVA as they did for Chipotle), so there’s a lot of downside risk in the price. Granted, the stock price has run up even more since then, but, hopefully, this example will go some ways as to clearing up any remaining confusion.
I hope all this helps, and feel free to PM me with any more questions. I’ll try my best to help more where and when I can. Gonna enjoy the rest of my Sunday afternoon now. Peace out :)
I don’t think you necessarily need to be a contrarian to generate alpha
Yeah, you don’t, but it’s usually a good way to do so
Yea I didn’t say it’s a bad way but I’m saying in the context of an interview you don’t have to come up with a mind blowing thesis on something. You have to be able to defend it and provide a good explanation for your conviction.
To anyone who notices my multiple relatively similar comments from yesterday, my apologies! I was experiencing some technical difficulties when posting, and my comments kept getting auto-removed for whatever reason. It seems they are all live now 😬 (oops!)
There is a lot your post, and I'll try to address it all, from the general to the specific. But I won't get too specific: I think there's a risk that focusing on the nitty gritty distracts from the main point.
After 20+ years I summarize a good investment thusly:
This gets at the essential thing: what do you see that 'consensus' does not? A few tools for understanding 'consensus' or 'the market' would be: based on what you know about the business, what does the current market price imply about earning power? What do you think of earning power, and how do these differ? What is being said / written , both sell-side and elsewhere, and how might that impact the current market for the investment?
Remember, the 'market' or 'consensus' impounds all the price targets that are out there ... and they are often at variance with the market price. So, yes, when you talk about 'consensus earnings' that might be a data pull (FY25E for example), but 'what's in the market/consensus' is different.
So framing 'consensus' as 'what makes the market price make sense' vs. 'investment thesis' or 'how I differ' as 'what I think this company can REALLY deliver and how that should shape value' is the way forward.
Of course life begins with analysis and models, and these are the basic foundation for understanding, but they are tools. DCF likewise is a tool, and a particularly fickle one at that.
Very few, perhaps no, great investments are based on a more accurate/precise/prettier model/spreadsheet. The insight into the business, management, industry, etc is the decisive thing.
Hope this helps.
Thank you!
100%!
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