How to Use Our DCF Modeling Tool to Analyze Netflix

Hi, this is David Trainer, CEO of New Constructs, and today I'm going to demonstrate to you the power of our valuation models and how they have allowed me to elucidate exactly how overvalued Netflix is. We've written a report on this, we've published a podcast on this, and the point of this webinar is I'm going to actually show you the nitty-gritty that goes into a real discounted cash flow analysis. You're not going to find this kind of work anywhere else. You're going to be astounded. You're going to be blown away by the amount of detail and rigor that goes into this work. And the reason we're showing this, the reason we're going to give this away for free, is because we want everyone to know how much work goes into our research. Now, we've developed technology and we've been refining it for over a decade, but that technology is what makes us smarter and faster. It's designed to make machines do the things that humans don't want to do. So I'm going to jump right in. All you got to do is, you know, log into our website. And by the way, these, these are features that are not available to, um, everybody in the system. You have to be a subscriber. You have to be an institutional subscriber. And when you are, you're going to be able to have access to not just all of our portfolios where, you know, if you, you, you know, and this is a feature that everyone has, but if you want to add a ticker, right, you just tick it in here, type enter. Oh, it's already in the portfolio. There it is. If you want to get more details, you click here and you see what's going on with the rating. Institutional investor clients can also just look at things one-off, like we're going to look here with Netflix, get details on that rating. Now, everyone gets to see all the information here at the bottom of the page where we show you all the adjustments we make. But let's get to the really nitty-gritty part, the valuation, right? Because in my podcast and our report, We point out that in order to justify its stock price, the current stock price, right, Netflix has to do some serious growth in revenues and really more importantly subscribers. Like we pointed out in our first scenario that to justify current stock price, they got to grow revenues at 20% compounded annually, which gets them to revenues of around $928 billion, which means they got to have 9 point— almost 9.7 billion subscribers. Right. To justify the price. Now I want to show you exactly how our discounted cash flow model gets to that, right? So we got 3 scenarios that we talked about in our report. Scenario 1 is pessimistic. This is my discounted cash flow model on the pessimistic scenario. And I told you it took about 29 years or 30 years to get to the current stock price. And what you'll see on this page— and I'm going to flip over to a PDF So you can highlight things a little bit more easily. But what you see here is exactly what I mean. What we've run through the model in terms of revenue growth rates, and it's a little bit higher than 20%, right? Because you can see here the first few years we're using the consensus estimates for the first couple years, right? But then we drop, drop it down to 20% and we go all the way out for 29 years, right? And 29 years is the first year that the DCF generates A present value of future cash flows per share that's still closest to but less than the current stock price. That's what happens in year 29, which is why we highlight that. All right, you can see the margin is 5.3. Now the margin is based on what the company's done historically. All right, we said maintain status quo. All right, so our margin assumption here for the default, and more importantly in our analysis here for our pessimistic scenario or Scenario 1, is this 5.3%. It's a little bit low, the 0.054 here, but it's, you know, it's, it's, it's still, I think, a very, a very good margin considering the fact that we pointed out that margins are actually declining at Netflix and are probably going to continue to decline. Um, but that's, that's sort of beside the point. It's essentially the status quo, right? And you can see the revenue estimates in here. In order to change these estimates, all you do is click the Edit button. You can put in whatever kind of scenario you want. Right, right. And you can see here again, I've got the 3 scenarios we talked about in our report. We've got the pessimistic at 5.3, we got the optimistic at pretty much 16. Now the report only shows 15 because I wanted to simplify the, the, the, the double and the triple, right? I'm sorry, that's not— that's scenario 3, which is 3 times. That's the 16. Scenario 2 is the neutral, right, uh, scenario here, which is where we double margins from 5.3 to 10.6. That really could line up to an 11, but again, in our report we're being conservative, right? Because the numbers speak strong enough for themselves. The point is you can create whatever kind of scenario you want, you can change whatever you want in our system, and it quantifies exactly what the future growth implications have to be. So for example, again, going back to Scenario 1 where we've got the 5.3% margin, we've got the growth rate that we pointed out in the report as well, And you can see how that gets to the 928 billion number that we were talking about, right? And when you divide 928 billion by $8 a month, right, or $96 a year, it's gonna take you 9.7 billion subscribers. That's how we get to that. Now, if we wanted to look at scenario 2, or where the margins are 10.6%, Right. We would just here go to the neutral scenario, and that's the one that is Scenario 2. The DCF will— should give us the ability to look at the neutral scenario here. And you can see same estimates for revenue growth, double the pretax profit margin, everything else stays the same. I'm going to use a PDF here, and these are available in our report as well to simplify. What we're talking about. You can see it's exactly the same as what it— what's on, what's on our, on the web page here, right? But in year 16, right, at the revenue growth rate for the duration of growth required to get a price that's still less than but closest to the current stock price, about $446— that's as of yesterday's close, and I'm doing this on January 27th Right, 2015. So this is the revenue number you can also see in our report, about $87 billion, right? You divide that by $96 and you gotta have 452 million subscribers in order to justify the current stock price. And again, I think that's more than the number of people in the United States. So you'd have to have really strong penetration in the United States and pretty good penetration in the rest— and a little penetration in the rest of the world. Anyway, the point is it's a pretty ridiculous number to expect any company that, as we pointed out, is a commoditized business as Netflix is. Now let's go to the 3rd scenario where we triple the margins. That's what we're going to call optimistic here. And you can see same revenue growth assumptions, and here's the triple: 5.3 times 3, 15.9%. Here's a PDF so we can kind of a little more easily just look at everything apples to apples. Right? And that gets us to the $34.9 billion in revenue. You divide that by $96 a year, and that means you got to have 121 million, or a little over twice as many subscribers as Netflix has today. So this is exactly how we used our DCF model to provide this scenario analysis on Netflix and to quantify for our readers and our clients exactly how overvalued the stock is. And I want to point out, this is the kind of work that you can do on any of the models in our system. You could go into any of the companies. Here's a company called the Advisory Board Company, ticker ABCO. They were in the danger zone recently, right? And one of the things we pointed out is the significant amount of growth required to justify their stock price as well. Every model comes with a default scenario, which we'll start with. The default scenarios are based on effectively consensus numbers and consensus estimates, that is, as well as sort of just conservative estimates. We're not ever going to throw into the default scenario anything that we believe to be an extraordinary assumption. We want the extraordinariness of the valuation to be fleshed out when we quantify expectations. So we don't need to put in extraordinary expectations. But here you can see for the Advisory Board Company, which is been a fairly fast-growing company, most of this by acquisition, right? It's got to do 14.4% compounded revenue growth for 22 years, all the while improving their return on cost— return on capital versus cost of capital spread from -0.08% in the last fiscal year to 3.1%, right? Even though 14% is not as high as what the company has done in the past here You know, it's still a pretty good clip for 22 years straight. This chart down below here in the decision page plots the DCF results. Remember the DCF results I was showing you for Netflix? Well, we have the same thing for any one of our models, right? So we've got a neutral and a pessimistic for ABCO and a default. And you can see the neutral scenario here, and you can see the implied shareholder value per share prices over the multiple time frames. Right? And that's based on the present value of free cash flow, the cumulative present value of free cash flow, terminal value— it's a no-growth terminal value— and the present value of the terminal value to get to a corporate value. We make all these adjustments, we get the shareholder value per share, and when you're at the decision page, you get to compare one performance scenario to another and see the implication of higher margins and higher growth on valuation. That's the beauty, I believe, of the new construct system. Is that you get to see exactly what the valuation implications are of your models and your assumptions so that you can make the most informed decision possible. That's what we did with Netflix. That's what we used to produce the report that we showed you. That's what we used to produce the multiple scenarios that you see in our model. Here you can see the neutral scenario at 16 years is pretty crazy. Let's put in the pessimistic, which is Scenario 1. Compare those two scenarios, right? You can see the long-term growth implications get pretty out of control when we when we that's just because we put 20% into the model far into the future. We could easily take that out. So let's for example, let's go to the neutral scenario, edit that, and let's just let's knock down this growth in the outer years because we don't need it, right? Like after year 16, we're good, right? So. Let's knock this down to— let's knock this out to like long-term GDP is like 6%. So let's put in 6% there and 6% here. And you'll see quickly how the chart is different now. So after lowering the long-term growth rate for the neutral scenario, even though it has a much higher margin assumption, You can see a much more meaningful number here in terms of valuation implication. And now that the pessimistic scenario looks crazy because it has those long-term high growth rates. So let's go back and knock those down to something a little bit more reasonable, as we did for the neutral scenario. And remember, we got to go out 30 years to quantify expectations for the neutral scenario. I'm sorry, for the pessimistic scenario. So let's Let's see here, let's put that to 6% and see what that does. We can't really change the 26 to 50-year timeframe because, well, that's what we needed in order to get to $446, or we needed that much time to get to the $446 range. So you can see again, instead of $17,500 or so is the top end of the range, you can see a big drop-off here in the long-term. and the value for the long-term growth horizons. Now, people always ask, why do you have a 100-year DCF? I don't have a 100-year DCF for any— because I want to have a 100-year DCF. I have one just to make sure that I've got a model that's big enough to quantify expectations. And in this case, you know, we're only going out 29 and 16 years, so I could have maybe built a 50-year. But you'll be surprised, and if you read our reports, you will find there are many stocks whose expectations go out for more than 50 years. So, So, to be honest, when I first built these models when I was on Wall Street, we started with a 25-year timeframe. And then the tech bubble came, and we blew everything out past 25, and it was— everything was 25+. And so when I started New Constructs, I decided, you know what, I think I'm going to build a model, you know, that's so big that I don't have to build another one, or that I'm never going to wish that it's too far or too short. So I just made it 100 years. And again, all that is is making sure that we cast the net wide enough and far enough to quantify market expectations. We're not predicting stock prices. We don't have to. The market does that for us every day. Instead, we quantify the expectations baked into stock prices. And I hope this webinar was helpful. And I hope that you will check back with us and look at our reports, because we provide this kind of expectation quantification for every single one of the 10,000 securities we cover, whether it's a mutual fund, ETF, or stock. This is the kind of diligence we do to make sure our clients have the best protection and best information available in the marketplace. Thank you very much for your time.