Transcription
I wrote investment research at Goldman Sachs. I was a stock analyst at one of the world's largest funds. And I've sold investment research to various hedge funds.
Today, I'm going to teach you everything I know about how to research a stock. So, we're going to split this video up into four parts. The first part is where to start. The second part is going to be what to look for. The third part is going to be crafting an investment thesis. And then finally is going to be part four, which is how to find it. How to find the information we're looking for.
So, right before we get into it, I first want to give a little bit of a disclaimer, which is that I have been researching stocks for so long, I've kind of forgotten a little bit about what it's like when you're just starting out and you kind of don't really know exactly where to go with everything. And so I'm going to do my best to provide a sort of formula for you and give you kind of guardrails of where to go with this. Except I I want to give the disclaimer that you should get to the point that you move beyond a formula that you move beyond kind of copying anything. It should become natural to you. And so one example is when you learn to drive, there's probably a lot of ideas in your head about how you should drive the car, the proper way to stop, how much distance there should be. But eventually you got to the point where all of that was automatic and you didn't have to think about when you should stop the car. It should be the same thing when you get to researching a company. You should get beyond needing to put in a little box, the SWAT analysis, you know, the strength, weaknesses, opportunities, and threats. You should get to the point that all of these things just become very apparent to you, kind of obvious a little bit. Now, that's not to say you're not going to always continue to be learning and getting better as an investor, but there's going to be things that you no longer need a formula for because they stick out to you like a bright red flag. And so, a lot of this does have to do with repetition and practice. But some of it also has to do with strategy. And so, I'm going to give you a detailed layout as to how you can actually research a stock. But not just do that. actually get to the point that you'll no longer need a formula and you will become a better investor.
So the first place is where to start. Now a lot of times when you are a newer investor, you're trying to figure out what stocks do I research? Where is my time best spent? And so you kind of are are stuck with these four different ways you can find stocks. And so the first way is going to be a stock screener. Now I personally don't find this to be the most compelling way to find stocks. However, this is exactly where I started. I went to Yahoo Finance stock screener. Uh, at some point I even used the Joel Greenblat Magic Formula. That's a stock screening site that screens for earnings yield and uh, ROIC on various stocks. And I just started looking at those businesses. Now, I don't think this is the best way to find stocks, but if you're just looking for places to start, it works.
Uh, the second place to find stocks is going to be 13F. So whenever you're an investment manager probably already know you have to file something called a 13F which will disclose what your positions are at least if they're uh in the US and that will give you an idea of what some of the best investors are doing and so you could copy them basically look at the businesses they're looking at.
Uh the third thing you could do is you could go to Twitter or Substack and just look at different people's ideas. That's actually a great source of ideas right now because on Twitter or or X and Substack, a lot of people now are writing about various investment ideas and so you could just read those and see theirs. In fact, one of my friends or or he became a friend uh wrote a Substack called mostly borrowed ideas and the name that Substack gets right to the point which is that when you're looking uh for different investments as an investor, a lot of times you're going to be taking other ideas that you've heard other people talk about. Uh, also check that substack out if you want a source of ideas and some good research.
Uh, the fourth thing though that you could do, and I really do recommend this, do not overlook this, which is that look at the things you're using in your everyday life, everyday products, and see if it's a public company. And so, if it's a product you're really enjoying and you're liking, especially if it's a newer product, I think this could be an edge that a lot of consumers have, uh, retail investors we could say, have versus professionals. Because as a consumer, you know, if you really like a product and if you really like a product, then there could be something called consumer surplus there, which basically means they're providing more value for you than they're taking in terms of pricing. And whenever that's the case with a business, it tends to be a good sign. Now, this is not a foolproof way to invest. There are no foolproof ways to invest, but it could be a pretty good way to source ideas. And so maybe you found out a decade ago that you really like this thing called Chipotle and they seem like they run a pretty good operation and you wanted to look into that stock. Or like myself, I really like the iPhone. I really liked Apple products and I realized that there was a narrative out there at the time that uh Apple products were going to be replaced by cheaper alternatives from PC, from Dell, from uh an Android phone made by Samsung. And this to me was crazy because I hated those other products so much. And I love the iPhone. Everything about it, it just worked so much better. And if you ever picked up an Android in 2013, 2014, you're like, "What is this?" It was a slower experience. And I just couldn't fathom how people thought these were substitutable products. And so that was how I initially found Apple and and decided to invest in that company. It was because of my experience as a consumer.
And that's just the beginning though. Right now, what we're starting with is where do you start? And so what you want to do in this stage though when you're deciding what stocks to look for is you want to kick stocks out as quickly as possible. So if it's something you feel like you're not going to be able to understand, you should just kick it out right now. Of course, you know, you could continue to learn new industries and I think it's great. I'm a big uh encourager of of people learning new things and moving outside their circle of competence. But if we're talking strictly from what stocks should you invest in and research more, for now you should really be staying with stocks that you feel like you could fully understand. Now, if you do want to look up a stock like, you know, a biotech stock, you know, a pharmaceutical stock, something like that, maybe, you know, an advanced technology semiconductor stock, you could certainly go ahead and do that. Just understand a lot of your research is going to first just start with understanding the basics of not even the business, but what even the product is. If you're talking about biotech, you kind of have to know the science, especially if it's an unproven product. If you're talking about semiconductors, you're going to also want to have a pretty good sense of the technology and science there. So, you have to have this very strong kind of fundamental uh basis before you could even really properly look at a semiconductor stock. So, if you do want to go off in these more advanced areas, that's fine. Uh, understand that you don't proceed to the rest of what we're going to talk in this video. You kind of pause right here and you don't do the rest of this video and instead you go and you do a deep dive on semiconductors, you know, pull up semiconductors 101, understand the basics of how they work. Uh, do the same thing for chemistry. If you're trying to learn uh how pharmaceutical uh drugs, whether or not they're going to be successful or not. But for most people, I would advise you just step away from that for now. stay within your circle of competence which could be you know retail companies pretty easy to understand food service companies pretty easy to understand even a lot of technology companies depending on the company but a lot of them can be relatively easy to understand I think you can understand Google and Amazon uh Nvidia might be a little bit harder though so uh that is something that you're going to kind of have to figure out what you're really comfortable with it so on this first stage what we're doing is we're kicking out companies that we're not comfortable with and it's a little tricky though because you might have a list of, you know, a dozen companies, two dozen companies, a hundred to look at and you might ask the question, well, which one should I actually look at first? Where should I start? And this problem actually exists in science, too. A scientist may have a lot of iterations of an experiment they want to run and they may have all of these different hypothesis to test, but there's no way to actually scientifically figure out where to start the test of which hypothesis first. And so this is where intuition is really going to come into play. Maybe there's some stock you see is trading at a much lower multiple. Maybe there's a lot of talk of it in the news and that's kind of gripping you a little bit more. It's drawing you more towards that because you feel like this sentiment around it, it's not going to last forever and so you want to start your research there. That's something I would kind of recommend you do. Uh otherwise, you could just look at a stock before it actually sells off necessarily. Even if it's an expensive stock, you could should look at some really great companies. Even if you're not necessarily going to invest in them now because they're high valuations, you should still look at them and analyze the business. And you know, they could sell off in the future. But it also could be a good way for you to learn what a great company looks like. And one last thing you could do too to kind of weed out a lot of companies on your list is I recommend going and just looking at their financials, the P&L, the balance sheet, seeing if the company has a lot of debt, seeing if they're loss generating. If it's a loss generating business and it's been consistently loss generating, just understand that's going to be a harder sort of investment to look at. You could certainly do it and I've invested in plenty of businesses that are loss generating. It's just going to be a harder analysis you're going to have to do. And if it's a business that you're also kind of new to, maybe you pass on that one for now. But, uh, if you do want to really quickly kind of just look at financials, I use Fiscal AI a lot. That's fiscal.ai. Uh, they're actually a sponsor of the show. uh you get a promo code if you uh use the link in the show notes below and you get a discount. But I like them because it's just very well formatted and all of the financials going back, you know, from the beginning. And very quickly I can just scan, you know, operating income, where that's going. Is revenue growth going up or down? Uh I could go to the balance sheet. How does uh the debt look over time? Do they have a lot of debt? Uh what does cash balances look like? Okay, let me go to the operating cash flow line item. Is is stock-based comp egregious? do they have a lot of capex and just very quickly grab a lot of numbers.
So when you're a beginner though fully understand this is going to be kind of overwhelming for you in a way because you're not going to be entirely sure what to look for and that's normal. That's that's totally normal. What's going to happen over time is you're going to look at more and more businesses and you're going to see more and more sort of different scenarios and you're going to start to create kind of a pattern, your own map of things that look good and things that look bad. you're going to be able to gravitate towards a few things like operating income versus loss, you know, the revenue growth direction, but there's going to be some other stuff that you're going to miss here. And so, just accept that at this point. Um, and you're going to get a lot better over time. You're going to recognize things and that's going to improve your ability to kind of spot things that work and don't work. Now, even though I do like fiscal AI and I think it's very good for kind of a pre-screening, I'm still going to recommend you actually go to the actual annual report, the 10K, uh, later on. And so we we'll talk more about that in this next section.
Okay. So now you narrow down your list of stocks. You have a business that you want to research more. What do you look for? So isn't that the question? This is not an easy question to answer because it kind of contains everything regarding investment and business analysis. There is almost everything at some point will come up as either being problematic or critical to an investment thesis. And of course we can't list everything. And so I'm going to give you guiding principles that are going to help you think these things through on your own because I've read a lot of like investment checklist books. You know, some of them they'll they'll be like the 52 things, the hundred things to check on every single investment. And I'm not doing that. I'm not going through a checklist of a hundred different things every time I look at a business. Instead, I've looked at enough businesses and things that look wrong, they just pop out to me a lot clearer and pretty soon, too. And that's what I want you to be able to develop. I don't want you to have to have a rulebook you're constantly referring to all of the time in order to figure out whether or not this investment makes sense. I want things to just pop out to you to become more and more obvious. And the way you do this, it is through a lot of practice. But I'm going to give you these kind of guiding principles now.
So the three things I want you to think about is first what is the business? What is the product? So very simple starting point is just what business are they in? Why do customers come to them? What do customers value about them? You know, in the past, I talked about this kind of framework I created called the consumer hierarchy of preferences. It's a very simple idea. Basically, when you buy something, you have a lot of different preferences that are getting fulfilled. And so, if you go to Chipotle, you're buying Chipotle because, you know, it's healthy enough, it's quick, it's convenient, and uh it's relatively cheap. And so, these are the preferences that are being fulfilled. And you want to understand that about the customer, right? You want to understand what is the business selling? What are the things they need to be good at? Now, this is just very, you know, easy boilerplate stuff, but honestly, a lot of time people do not take uh the time it takes to actually put this together, to realize why a customer is going to one business versus another. If I were to ask you, why does someone go to Moody's uh versus S&P Global to get their uh credit rated versus going to Fitch or one of the other alternatives? because there actually are I believe there's 12 that are licensed and are able to uh provide a rating. Why don't they go to any of the other ones? Do you have a good answer for me? Do you understand why that they don't just go to S&P Global and an alternative that's cheaper? Do you understand why they don't do that? And so just understanding kind of the the basic boilerplate stuff of this business and and asking questions and continuing to ask questions till you really hit something that you're confident in and makes sense to you. That is going to be the the first kind of piece of advice I have here.
The second one is going to be how do they make money? So again, pretty simple stuff. Uh but do you really understand how some of these businesses make money? You think Meta just sells advertising? Uh maybe that's true, but let's get a little more direct with that. What are they really selling? Are they just taking a budget from an advertiser and then posting an ad somewhere in the app or are they selling them on a specific return on ad spend? Get more into kind of the monetization mechanism of the businesses. And so there's going to be this idea maybe where you're looking at you could even be something like Amazon kind of a simple business right they just take a percent commission on the items they sell. Okay. Well how is that commission divvied up? How is that taken? Turns out there's a different commission on products across different categories. On top of that, there's different fees for logistics services. Then there's also different fees for advertising services. Okay, that's three different businesses we just unpacked. So, you could kind of go deeper on a lot of these businesses to really understand what it is they're actually monetizing and what it is they're selling.
Uh the third thing is going to be how defensible it is. And so, this is getting to this idea of moes. Is this business doing anything anyone else couldn't do? This is a very important question you need to ask. What is preventing competitors from doing this exact same thing? And you should be able to come up with good answers to that. Or if there's no great answers to that, then that in of itself is an answer to you. And so we could reframe all of this, make it a little more catchy. And the way I like to think about it is a great company creates value, captures a portion of that value, and then protects that value that they capture. And so you want to see how is a business creating value for a customer, how are they capturing it? That's how they're monetizing it. And then uh ultimately how they're protecting it. What are the moes involved in that? So I want you to do all of this from first principles. I don't want to give you all these rules and just say, you know, make sure you check if they have a network effect. Uh, do they have a resource advantage? Do they have a scale advantage? You know, there's list of all of these different competitive advantages. And you could look them up, but I want you to think through everything like you know nothing. And this is actually going to make you a better investor because when you go to a list and you kind of just hit a check mark on it, you're not really critically thinking through. And when you're not critically thinking, uh, you're not going to actually be able to catch if there's any nuance in a situation. And so, you know, you could say, oh, you know, eBay, it has a network effect. Uh, that means it has a great competitive moat, right? Are you sure about that one? Uh, let's think about that a little bit more. And so if you went to kind of this traditional sort of analysis, you could check the box on a lot of these things, but uh you wouldn't necessarily get you to the point that you could really understand what the moes in the business are. And so I prefer that you look through everything from first principles, which is another way of saying pretend you don't know anything. forget everything you've learned about investing and just stick to those three principles I just told you of how is a company creating value, how are they capturing that value, and how are they protecting it? And I promise if you do that analysis for eBay, you'll come up with a very different answer than if I told you to do, you know, a Porter's five forces or a SWAT analysis, which are kind of like MBA traditional um ways of analyzing a business. And so that is going to be a big thing to think about when you're looking at what to look for in a business.
Now I'm going to tell you there is the frame problem and this makes it tricky. So the frame problem is this idea that you don't actually know what is relevant when you're initially starting. And so this comes from, you know, computer science and it's kind of a silly example, but I'll tell you it. Basically, there's a bomb in a battery in a room and it's sitting on a wagon. This is the actual example that that most people use when they talk about the frame problem. So, there's a bomb and a battery sitting on a wagon. It's in a room and for some reason the wagon's tied to a wall. I don't come up with this stuff. Uh, the frame problem is you go to a robot, you know, some super AI robot and you say, "Can you remove the battery from the room and the robot doesn't know what is relevant or not? What are the relevant facts? Uh, is it a relevant fact that the bomb is on the wagon? Is it a relevant fact that the battery is on the wagon? Is it relevant that the wagon is tied to the wall? Uh, is it relevant that that I can pull the wagon and there's still wheels and I'm still able to do that because I could calculate my strength and and on and on and on. And so, what are the facts that matter in this? And so, the question the frame problem is really getting at is what are the relevant facts here? And so, in this example, they have different robots and some of them are stupider than others and apparently a lot of them just pull on the wagon and when it pulls on the wagon, it brings the wall down and the ceiling falls on the robot and it blows up. Whatever. Again, not my story. Uh the point I want to make to you is when you're going through an annual report, you're going through an investor day, you're going to hear a lot a lot of facts and a lot of things to remember. And you have your own sort of frame problem issue of what is relevant. What are the wagons in the story? What are the batteries in the story? What's the bomb in the story? You're going to have to be able to tell because there's only so many different avenues you could go through and research. And what you're going to find is sometimes you're going to come up with like an ad hoc thesis like within looking at a company like maybe it's Mercado Libre and you say, "Hey, that's a little suspicious that and I'm not saying this is necessarily true, but it's a thought I had. Uh that's a little suspicious how much they're increasing, you know, their credit cards. Uh is there any concern that maybe they're lowering their risk standards?" And then you go and investigate that and you go do what you can to investigate that. That's called like pulling on a thread. Basically, certain things that you see kind of put up an alarm bell and you want to go research that more to see whether or not that is really an issue or whether or not it's a non-issue. And sometimes you may not be able to get to a satisfactory conclusion. And not that this is the question I'm asking right now, but you will eventually face this question of how much research is enough. And this right here, this problem right here of not knowing whether or not there's certain things in the research that are worth pulling on that you missed is going to be the thing that I don't want to say haunts you, but that's going to be something you're going to have to figure out at some point whether or not that's enough research or too much research. I'll also tell you, you could go off on, you know, rabbit chases that don't lead to anywhere. In fact, that happens very, very often and expect that to happen. If you're doing your job well, you should come from this position that you want to destroy this investment, right? You want to come up with reasons why not to invest in this. And the best way to do that is to try to come up with crazy kind of hypothesises and then go and test them with the business. Maybe going back to the credit example, you go and you check their delinquencies. you go and you look for other information that uh, you know, lending standards have becoming looser or maybe the competitive environment is becoming even worse and interest rates are falling and now the interest rates are falling too much to offset you know, the credit risk premium whatever it is you could come up with your own ideas and the more you businesses you look at the more history you read the easier it is to be for you to come up with these and then you investigate them and a lot of times they lead nowhere that means you're doing your job well and you do this enough that you start to build confidence in the business. Uh when I researched uh Meta, this was back in January 2023, there was a lot of issues with Meta. You know, they had TikTok competition, they had app tracking transparency, which was Apple killing uh the signal from the phones and so Meta had less data. Uh you had the FTC coming after them asking for a divestiture. You also had uh issues with the EU and then on top of that, you also had them plummeting a lot of money into Reality Labs. Even on top of that, you had the transition to uh Reels. And uh the transition to Reels meant that they were actually showing negative revenue because uh they weren't monetizing Reels yet and they weren't sure whether or not it would monetize at the same rate as their feed. So a lot going on. You basically at a first figure out every single one of those issues that was kind of facing the company at the time. Then you had to come up with an opinion on each of them. And that is what would be key to you having confidence in owning Meta at that time. you would go one by one and say, "I'm not worried about the FTC. I don't think they're going to divest it." Or, you know, maybe you'll say, "Even if they do divest it, it's going to be worth, you know, more split up than together." Whatever you want to say on that. Uh, you would go each by each of those layers and kind of come up with your own ideas about this. So, this is going to be all under kind of building a narrative. And so, you know, what to look for, you know, how is the company creating value? How is it capturing it? How is it protecting it? Then you kind of want to build a little bit of an idea around this. This is going to be your hypothesis, which will lead into our next section. And then you want to start to destroy this hypothesis, right? What can go wrong with this? How am I wrong about this? And you want to read enough information that you're starting to find these different threads to pull on in the research process. And the most critical thing I want to leave you with here is I want you to get to the point you build kind of common sense or we could call it like common business sense, right? If I were to tell you that I have a new business plan and uh what we're going to do is we're going to bring cupcakes to dogs in space. Doesn't take you very long to tell me that's that's a pretty bad idea, Drew. You know, you did this business channel for a long time. I thought you would have come up with something better than that. Why do you know that that's a bad idea? Why is that so instinctually quick for you? Right? Over time, you're going to read about more and more businesses and investments that you're going to the same way you had that reaction to that business plan I just proposed to you, you're going to also have that same ability for other investments. Maybe there's going to be some you miss on, maybe there's going to be some that you have less of a strong adverse reaction to, but you're going to develop this ability more and more. What sounds like a good idea, what doesn't sound like a good idea. Um, not to pick on Melly again, but uh, we're going to give credit cards to tens of millions of people that have never had credit ever before. Does that sound like a great idea or not? Now, I actually think in their case, it's a very different scenario. You could go watch, you know, the deep dive video on that, but that's going to be an example of a bias that I certainly would have that then you have to go and do more research to see whether or not you're actually going to be comfortable with it. Because most times when you extend a lot of credit and credit is growing very quickly and you accelerate the rate that you grow credit and you do that to um borrowers without any history, it just usually doesn't end well. And so a lot of this too is just building up enough uh understanding of history, enough uh understanding of different businesses and what's worked and what hasn't worked in the past and you're kind of just applying this to a new situation. Uh you're basically looking at a novel situation, maybe something like SpaceX. This has never happened before. Businesses have never tried to scale, you know, a business in space on the final frontier. This is all a new one. But what you can do is you can look at past businesses, past industries, and the history to try to get some understanding of how this could all unfold. You're trying to contextualize it a little bit and that is kind of going to be key to this. So going back to this idea, build your business common sense. So that is something I really want you to take away from this.
So now this leads us to crafting an investment thesis part three. So by time you're kind of through with this research process. This has already kind of happened naturally. I I've never actually sat down and been like what is my investment thesis on on this stock. Not since I did, you know, a stock pitch in in college have I actually done this because when you're researching it's going to kind of just come out a little bit. And if someone asked you to articulate it, you should be able to. But you don't necessarily need to spend a lot of time to have a very novel sort of idea. Uh if you're doing, you know, research on Meta, for instance, you don't need to come up with this crazy novel, you know, here's all the things every other investor is missing right now about Meta. It could be pretty simple. It could be, you know, this is the valuation of the business. I think that earnings are going to continue to grow. I don't think they're going to spend all their cash flow into oblivion um on the metaverse or on Reality Labs or on AI. And, you know, by the way, maybe the AI capex is going to have a good return on ad spend. You could make it more succinct than that, but uh that could be your investment thesis and that's fine. I think a lot of times, uh people get caught. they feel like they need to have like a really kind of creative thing like AI is going to be you know this big thing and there's going to be bottlenecks in AI and memory is going to actually be the bottleneck because what's going to end up happening is that all of these hyperscalers are going to buy the data centers and then uh there's already enough capacity for GPU chips but not enough for the memory and so the memory is actually going to be the next bottleneck and so you know Micron is going to have a 65 plus% operating margin uh because of the pricing power they're going to be able to have. I think a lot of people think that that's, you know, what an investment thesis should look like. And most of the time, uh, this actually gets back to an idea of David Deutsch where the the more specific you are, uh, in anything you say in an a thesis, uh, the more likely you are to be wrong. And so that might sound really smart because this person was able to figure out and put all these facts together, but it actually uh, opened up the door for more areas where they could be wrong. uh if anything kind of went differently in this process, it could have led to a poor result. Now, some people in invest that way and there's certainly nothing wrong with it. If you caught, you know, Micron and you saw this coming 3 years ago, congratulations. Hats off to you. That's not how I invest because I just don't think it's that realistic. I think you would have literally had to have been like stuck in semiconductors looking at Micron looking at the memory companies and then very specifically looking at you know these different bottlenecks and AI and most of the time when people have that level of a narrow of focus maybe it works once you know in a career and and that's all they need and that's great but thereafter it doesn't tend to work so well you know we can not that I want to pick on anyone but a lot of the people who got uh the mortgage crisis right and and were short um MBS s a lot of their kind of trades thereafter were coming from the same sort of angle and they never at least have I seen have been able to translate that into kind of reproducible investment success because that's a trade at the end of the day right one of my favorite books ever by the way is called the greatest trade ever by John Paulson about shorting uh the mortgage back security market but ultimately that's what it is right it's a trade and I'm talking mostly about investing what you can do to uh hopefully find stocks and great businesses in a reproducible way so you can hold them for a long time and continue to reinvest maybe extra capital into other great businesses. I'm not looking for necessarily this next one-off sort of catalyst that could change everything. And I think a lot of times when we talk about investment thesis that kind of at least that's my bias that kind of gets thrown in there. people want like this next trend uh this next thing that is kind of smart and people didn't notice that you know the forex currency trades were moving in this one direction and then the oil flow money from the prochina dollars were moving in whatever garbly goooo at least that's my bias of an investment thesis that it needs to be something really smart and really cute and that's not really the case it could be pretty plain vanilla and simple and that's totally fine you know this is why this is a great company this is why I think it's defensible and the valuation seems attractive to me
Now, the next thing you're going to want to do here, though, is you're going to want to tie your actual investment thesis to numbers. And so, I do this at the end of almost all of uh my business breakdowns on this channel, where I'll throw some numbers out there to see what it could look like in terms of a valuation. Well, I'll say something like, you know, if the company grows X amount, uh revenues grow this much, margins maintain or go up, uh what do earnings look like? Uh you want to get that figure. Then you could either apply a multiple on it, but keep in mind a multiple is just a shorthand for a DCF. A lot of people will ask the question, what multiple is the right multiple that I should pick? So, if that is you, this is what you need to do. You need to create a DCF, a discounted cash flow model. You could look online how to do it. It's super simple and easy. Uh even, you know, Claude can help you with this. Now, uh once you have that done, what I want you to do is adjust the assumption so you're comfortable with it. Then what I want you to do is to to go on Excel to a what-if equation, solve it, and set uh the equation equal to uh so that the output of this DCF when you sum up all of the discounted cash flows, it's going to equal the current market cap, the current market cap value, and then you're going to solve for the discount rate that allows those two numbers to match. So what I basically just said was you're going to have a bunch of cash flows in your DCF and they're going to become discounted back to today. But at what discount rate? I want you to basically ask Excel what discount rate you need to have in order to make the sum of all of these cash flows discounted back equal the current market cap. That's what a reverse DCF is. And so the idea is this is a return that is being priced in today. And you could see that this return being priced in today is going to then allow you to understand whether or not this is attractive or not. because these assumptions that you're making, maybe it's very high growth assumptions and maybe the return is very low. That's not attractive. If you're putting in, you know, pretty low conservative assumptions and you're getting a high return, that could be pretty attractive. So, I want you to do that. And then something else you could do is then you could go out a year and you could see what multiple you're paying for that. And the way you do that is pretty simple. You know, you take your estimate and you take the market cap. And so market cap divided by your earnings estimate. That's your PE multiple, right? And now you're building a sense inherently of the way that returns map to a multiple. And so this is ultimately why we pay multiples for stocks at all. It all goes back to the DCF. And I know I need to do a bigger video on this. So if there's interest in this, I could cover this more in the reverse DCF, but uh that is going to be the investment thesis tying it to actual numbers, getting some sense of the valuation. But for now, you could just tie it back to a multiple. Um, kind of as a rule of thumb, sometimes people want to buy a stock below whatever the current uh stock market multiple is, but if it's growing very quickly, then they're willing to pay up a little bit more. And you could look out a few years to see how many years it takes for the multiple to get below a market multiple. And as a rule of thumb, don't go out more than three years. There's a lot more we could say on that in the future.
Now the last section is how do you find this information? So, the first question you need to ask yourself is, does this information exist or not? So, if you're newer, you're not going to be exactly sure what uh disclosures are common, but also if you've never looked at the business, you don't know what they're disclosing or not disclosing. So, you should start with the annual report. Just get comfortable. The first thing I like to do, by the way, is just skim it. I don't even read it very closely. I just skim the whole thing to just understand what disclosures are there or not. trying to understand just like segmentations, very basics about the business. And then once I've done that and I have a good sense of the business, then I'm gonna want to go a little bit deeper and understand it even more. And so I like if there's an investor day, that tends to be a pretty good source of information. So reading that transcript, uh, pulling up the presentation on that, they tend to kind of just lay out the business very nicely if that exists in that case. Um, and then from there, you know, you could kind of go to the earnings transcripts. you could go back uh read the last year of earning transcripts. Now, sometimes when I do really really deep research and I think I I've decided at some points this can be overkill, but you never know what you don't know. I would read every single uh earnings transcript for a business, every single annual report for the business. So, when I researched a business like Copart, that was over two decades that I had to go through for all that. So, that took a very very long time. I understood the business very very well though and I knew the things they've talked about and the things they haven't talked about before. Uh, I knew that they mentioned market share only twice in their entire history and that unfortunately was in like 2003 and 2004 and never again since. But using that number I was able to tie it to a different disclosure they had and I was able to kind of triangulate market share a little bit. It's not perfect but when you're getting through all of these sources you're going to find a lot of information that other people are missing. Uh, and if you're using AI, it's not going to necessarily know to check that or not. Because I didn't know to ask the question, you know, did they ever disclose market share? Because if I only read the last three years of transcripts and they never talked about it once, I never would have thought that they would have ever disclosed it. And you can't just ask AI to, you know, ask every question you should be asking, which is again kind of back to this this frame problem of relevancy we were talking about. When you're going through a transcript, certain things eventually are going to pop out to you. And so I don't think you necessarily need to read 20 years of transcripts in order to invest in a business. I do think that especially as you're starting though, it might be helpful to uh it could be good to just really get a good understanding of a few businesses and really read everything and understand what research overkill is so that you don't undershoot it because there were definitely times where I did not need to read, you know, the 2007 Q2 Copart transcript, but I did it anyway. Uh now what I'll do a lot of times is I am more of a skimmer. Uh I don't know whether or not this would have worked as well if I tried doing this initially. But especially once I get a sense of how the earning transcripts go, you know, the different things they say on the call, I could get to a sense where he's, you know, I'm starting to read a question. I know what they're going to ask about, you know, tax rate margin for the quarter or something. I don't care about that, you know, about that 5 years ago or something like that. So I can move through them a lot quicker. I do think it helped though building that base initially to know what was research overkill.
So, uh, how to find it, you're going to go to SEC Edgar, that's all the documents there. The companies also have their own investor relations websites. Those are usually prettier versions of the documents. So, you know, if you can read them there, the earnings release is usually prettier graphics. Sometimes, you have to be aware of this, they'll put different disclosures in an earnings release, sometimes in an earnings presentation that don't actually exist in an annual report. It is super annoying. Uh, but that just means you have to check all of these. And these are kind of the the traditional sources we're talking about here. Now, if you are doing research and let's say you're researching Adobe and it kind of hits you that hey, enterprise is actually a lot stronger of a business than consumer for Adobe. Consumer actually has a lot more competition, but enterprise is pretty good. How big of a business is Adobe's enterprise business? So, that is a very very good question to ask. So, now the question is though, does that information exist? And you need to figure that out. So, you're going to go to the 10K, you're going to read the segments, and you're going to search in the 10K. You're not going to find it there. You're going to go through a bunch of earnings transcripts. You're going to find that they kind of said a couple things around this, uh, but
not directly what you're looking for. You know, you check the earnings presentation, nothing there either. Maybe you noticed they changed segments a little bit before. So, you're going to note that in the back of your head that the segment changes. Maybe you'll be able to see like overlap of enterprise or not, or be able to uh carve out some revenue that you know for sure is not enterprise. And so you could kind of put these pieces together.
Uh, otherwise, you can go and look at alternative sources for a question like this. You're probably not going to find an answer to it. Uh, but there are a lot of alternative sources that I do really recommend. So maybe as you're putting together your thesis of is Adobe strong in enterprise, you want to talk to people that use Adobe, you know, suite that are in enterprise, right? And there's going to be different means of going about this. So when it is business-to-business, I will say it gets harder. Uh, I use something called expert call networks, which is basically you talk to an expert at a business, at an advertiser, for instance, or someone at Adobe. Um, I did one of these expert calls with someone from Adobe. It's an expensive research service to get access to. So if you don't have access to this, which is basically going to give you transcripts of people, you know, answering your questions, then you're going to have to get creative. And I didn't have access to this for a long time when I was researching stocks.
So this means one of two things. Either pick businesses that you uh know you're going to be able to have higher confidence in. So maybe avoid business-to-business if there's not a lot of good information out there. Or get creative. You're always welcome to try to talk to people. If you're young and you're a college student, you actually have an advantage in this regard because people are much more likely uh to talk to you as a college student than me calling up, hey, you know, I'm trying to make money off this stock for some clients. Uh, can you answer some of my questions? That's not going to work. But you as a college student trying to learn, they want to hear. So, uh, you could try that. You could, you know, build up your network.
Otherwise, get creative. You know, Reddit is great. Sometimes on YouTube, people are talking about uh different kind of reviews, different products they don't like. Uh, maybe in the business-to-business area as well. Same thing with Reddit. Same thing on Twitter. So, check all these different social media platforms as well. Don't just stop at Google because Google doesn't have access to these like walled gardens.
Uh, the other thing I'll recommend is if you're looking at a company in a different language, search in their local language. So when I looked up Coupang and was researching that, I would search a lot of things in Korean to see if different things would come up. Uh, when I did that research too, I actually commissioned a survey to talk to basically 150, I think it was. It was over a hundred, um, different Korean consumers to understand, you know, I have this idea that it's like the Amazon of South Korea, but is that true? Right? And that actually wasn't that expensive to do. Uh, you know, kind of how to get a little creative getting that done. But uh, these are things you may or may not want to do, or you may, you know, decide to uh, find different alternative research methods to get around that.
So ultimately, you could get creative with this. You have to get to the point though that you're getting your questions answered. And so again, we're back to this Adobe enterprise revenue question. You would have been able to circulate from the disclosures. It's anywhere between 20 to 50% of revenue. That's a pretty wide range of revenue. You know, I think it's probably at the lower end, but I can't prove that. And then it comes to your, um, kind of discretion as an investor, what you're comfortable with, what you're comfortable assuming. And there's also a judgment because you're not going to be able to figure everything out.
You may look at Mercado Libre's, you know, credit uh, history and if anything's going on with them accelerating, you know, credit cards. Is there any notice that maybe uh, losses are going up? And you may not find anything. And so then you have to make a judgment on whether or not you believe in management. You kind of been maybe studying this company for many years, which is also a very helpful thing to do to get a long understanding of the business, how they operate, the managers, the kind of types of people they are. And then you could kind of ask the question, does it make sense that they're going to chase short-term growth and potentially blow up the business and do it this quarter? That's going to be now you're getting to your judgment of these different things and people are going to take different opinions on this.
And so the key thing to keep in mind when you're looking for information is one, does the information exist? So you're going to have to go to the regulatory filings, confirm whether it does or doesn't. And then the second aspect is, can I find it out somewhere else? Right? Can I find it out through a network, uh, through talking to people, through messaging people on LinkedIn, Twitter, Reddit, YouTube, uh, maybe it's in some old news articles. If I use, you know, the Wayback Machine, I can find them. You're going to have to get creative with this. And then if you can't find that information, does it kill the investment thesis for you or not? A lot of times it's very possible you get to a point where you say, "I don't know if I'm confident in this. I don't know how I feel about this one." And that is totally fine. Uh, there's other companies to look at and you get to go back to step one, pick another stock off your list, and go again.
So that is everything involved in the research process and I just really want to emphasize uh learning for yourself, taking a lot of time to practice. You will get better and better and better. I've looked at notes I've had from like stocks I've written up, uh, when I was in college and it is laughably bad. Even stuff from like five years ago is pretty bad. And so you're going to just continue to get better at this. Reputation is going to matter a lot. So, you know, continue to research stocks, but also learn about businesses. Learn about successful businesses in the past. Learn about businesses that have failed. I love doing that because then that helps let you know what you should avoid in the future. And so, there's a lot involved in this research process, but as I say, the best thing to do is to get started.
So, uh, you could get started right now. Check out uh, one of these or one of those uh, business breakdown videos and you could see the actual research process. And maybe you go and you try to copy it yourself. Uh, good luck. Thank you for watching.