WEBVTT - A Value Manager on How Most Value Managers Are Getting It All Wrong 0:00:10.880 --> 0:00:14.840 Hello, and welcome to another episode of the Odd Lots Podcast. 0:00:14.920 --> 0:00:18.960 I'm Joe Wisn't Thal and I'm Tracy Hallaway. Tracy, you know, 0:00:19.120 --> 0:00:21.680 one of the things that we discussed a fair number 0:00:21.720 --> 0:00:25.440 of times but also maybe before. It's just sort of 0:00:25.440 --> 0:00:29.480 the I guess you would say permanent state of crisis 0:00:30.240 --> 0:00:34.920 that you might call it in so called value investors. Yes, 0:00:35.320 --> 0:00:39.199 it's been. It's certainly been a long running theme, hasn't it. 0:00:39.240 --> 0:00:41.880 And I feel like we've done quite a few episodes 0:00:42.040 --> 0:00:46.000 on it at this point, but didn't exactly turn things 0:00:46.000 --> 0:00:50.720 around for value investors either. No, definitely not. And I think, 0:00:50.800 --> 0:00:54.400 like you know, there's really two strands that tend to 0:00:54.440 --> 0:00:58.520 emerge in our conversations, and I would characterize them is 0:00:58.640 --> 0:01:02.520 this one is that there is some like cyclical element 0:01:03.160 --> 0:01:06.080 to value investing in this cycle, it just hasn't turned 0:01:06.080 --> 0:01:08.080 around yet. So it's like we have this sort of 0:01:08.200 --> 0:01:13.600 long multiple expansion. It's kind of low growth fed driven 0:01:13.680 --> 0:01:17.600 economy that sort of creates this permanent bid for growth 0:01:17.600 --> 0:01:21.840 companies at the expensive value week GDP growth, etcetera. Just 0:01:21.880 --> 0:01:24.960 like certain industries aren't going to thrive in that environment. 0:01:25.400 --> 0:01:28.000 And then I would say the other half is that no, 0:01:28.200 --> 0:01:31.240 the problem is that we are not good at defining 0:01:31.480 --> 0:01:33.640 value in their people sort of take a more accounting 0:01:33.680 --> 0:01:39.000 approach and say traditional measures of the stocks cheapness, like 0:01:39.120 --> 0:01:42.959 say price to book value. It just these measures don't 0:01:43.000 --> 0:01:46.839 work in a world where so much value is intangible. Right. 0:01:47.080 --> 0:01:51.520 This is the idea that as companies, well the sort 0:01:51.560 --> 0:01:55.440 of successful companies nowadays, are investing a lot, they're investing 0:01:55.440 --> 0:01:58.360 a lot in things like their brands and other intangible 0:01:58.360 --> 0:02:01.160 assets that just aren't captured by price to book value. 0:02:01.200 --> 0:02:05.440 And so a company that's positioning itself for a really 0:02:05.480 --> 0:02:09.880 good future performance might not actually look that way if 0:02:09.880 --> 0:02:13.880 you're just glancing at, you know, something like price to 0:02:13.960 --> 0:02:16.600 book you know, like it's sort of a joke, and 0:02:16.639 --> 0:02:20.400 I think we've talked about it with Michael Mobison last 0:02:20.480 --> 0:02:24.079 year Jared Witdard. But it's like you can rescue value 0:02:24.080 --> 0:02:26.640 investing if you call Netflix of value stock, or if 0:02:26.680 --> 0:02:29.800 you call Facebook a value stode, and someone would say, Okay, 0:02:29.800 --> 0:02:32.639 these companies don't have like big like factories that can 0:02:32.680 --> 0:02:35.639 easily be measured. But if you could somehow like put 0:02:35.680 --> 0:02:40.880 a number on the value of the Facebook network as 0:02:40.919 --> 0:02:44.880 an asset, then you couldn't, then you could theoretically imagine 0:02:44.880 --> 0:02:48.440 a world in which had some traditional value screen Facebook 0:02:48.480 --> 0:02:51.800 comes up right. I mean, the thing that still makes 0:02:51.800 --> 0:02:55.160 me uncomfortable about value stocks is that you're you're still 0:02:55.280 --> 0:02:59.720 investing in something on the basis that the market has 0:02:59.800 --> 0:03:05.919 some how mischaracterized its future, which I think you touched 0:03:05.919 --> 0:03:07.840 on this with with your two narratives. But I think 0:03:07.840 --> 0:03:10.480 in the current environment, where we talk a lot a 0:03:10.520 --> 0:03:14.480 lot about flows based investing, a lot of momentum trading 0:03:14.520 --> 0:03:19.680 things like that, it feels like the market is quite 0:03:19.720 --> 0:03:23.560 consistently directing capital to you know, a few firms, and 0:03:23.560 --> 0:03:26.519 then it just keeps doing that and those firms get 0:03:26.520 --> 0:03:29.520 overvalued and overvalued and overvalued. And if you're not in 0:03:29.560 --> 0:03:32.360 that cycle, I don't know. I just feel like it's 0:03:32.440 --> 0:03:34.400 unlikely that you're going to get back in it. And 0:03:34.639 --> 0:03:36.920 the longer it takes you to get in, the more 0:03:37.000 --> 0:03:40.200 you're sort of losing out in terms of valuations. But anyway, sorry, 0:03:40.240 --> 0:03:42.960 I'm going on a tangent. No, No, it's great, And 0:03:43.040 --> 0:03:44.520 I mean, and the other thing, and I think it's 0:03:44.520 --> 0:03:48.520 sort of related to your point, is you know, it's 0:03:48.600 --> 0:03:51.720 nice to say like, okay, like there's some intangible value 0:03:52.520 --> 0:03:54.840 that we if we could only measure it at Netflix 0:03:55.000 --> 0:03:58.680 or Facebook or whatever it is, but it seems hard 0:03:58.720 --> 0:04:02.760 to know in advance that is there. And so it's like, okay, 0:04:02.800 --> 0:04:05.280 if you have some like factory, then you can at 0:04:05.360 --> 0:04:09.960 least say, okay, this exists, and historically speaking, it will uh, 0:04:10.040 --> 0:04:12.040 you know, we would project it over the next ten years. 0:04:12.040 --> 0:04:13.960 It's going to throw up this cash and that's a 0:04:14.000 --> 0:04:16.920 good value. It feels like with a lot of these 0:04:16.960 --> 0:04:20.440 sort of like backing into the value approach that it's 0:04:20.520 --> 0:04:24.360 very much easier to say in retrospect or expose factor, oh, 0:04:24.440 --> 0:04:27.279 this turned out to be a very valuable asset that 0:04:27.360 --> 0:04:29.280 they have, which is sort of nice, I guess from 0:04:29.320 --> 0:04:32.240 maybe an intellectual standpoint, but it doesn't really help you 0:04:32.320 --> 0:04:35.200 like pick stocks today, which is what people to really 0:04:35.279 --> 0:04:37.600 care about these discussions. It's great to say, Okay, the 0:04:37.680 --> 0:04:40.960 Facebook network is worth a lot of money, but you know, 0:04:41.040 --> 0:04:43.159 I wish you had told me that six years ago. No, 0:04:43.360 --> 0:04:46.520 but it does help a lot of different investment companies 0:04:46.560 --> 0:04:51.760 come up with different strategies and factors to come up 0:04:51.800 --> 0:04:54.920 with different definitions of value that always work when they're 0:04:54.960 --> 0:04:57.760 back tested against historical data. Right. So I guess the 0:04:57.839 --> 0:05:00.840 question is that sarcasm. I don't know my sarcasm is 0:05:00.880 --> 0:05:04.240 coming through on the podcast, but I got it crazy. 0:05:04.360 --> 0:05:08.599 But I guess the thing we're looking for is the 0:05:08.640 --> 0:05:12.520 approach that works in advance, that's not just back tested 0:05:13.080 --> 0:05:16.080 and some you know, some approach that can help us 0:05:16.720 --> 0:05:20.240 identify the sort of deeply under a company intervalue companies 0:05:20.560 --> 0:05:25.120 today using some something whether it's a metric, whether it's 0:05:25.120 --> 0:05:28.240 a screen, whether it's some other intangible measure, something that 0:05:28.279 --> 0:05:31.159 doesn't just help us rationalize the past, but can you know, 0:05:31.600 --> 0:05:35.159 help help me retire a few years earlier. Yeah, and 0:05:35.200 --> 0:05:40.920 also maybe even explain why value investing as it's you know, 0:05:41.160 --> 0:05:46.640 commonly understood has performed so badly for so long. Absolutely 0:05:46.640 --> 0:05:48.400 all right, So I'm very excited. We're going to be 0:05:48.440 --> 0:05:50.960 speaking with someone today who may be able to help 0:05:51.320 --> 0:05:56.360 move this forward, whose work consists of sort of solving 0:05:56.400 --> 0:06:00.440 this problem. An investor, so obviously someone who wants to 0:06:00.440 --> 0:06:03.240 do more than just explain the past but produce good 0:06:03.279 --> 0:06:07.360 returns going forward. We're going to be speaking with Rafael Rassindez. 0:06:07.480 --> 0:06:11.880 He is the co founder of Applied Finance Capital Management, 0:06:12.600 --> 0:06:15.760 which has looked at some of these problems and try 0:06:15.800 --> 0:06:20.840 to identify where the traditional and value investing framework has 0:06:20.920 --> 0:06:24.560 gone wrong. So, Rafael, thank you very much for joining us. 0:06:24.600 --> 0:06:27.200 Great to be here. So I'm curious, I mean, uh, 0:06:27.480 --> 0:06:30.200 you know, I always like to look for validation after 0:06:30.240 --> 0:06:33.080 our introest But that general framework of sort of the 0:06:33.120 --> 0:06:37.640 two stories that people tell about value investing, how does 0:06:37.680 --> 0:06:40.560 that comport with how you see the world right now 0:06:40.560 --> 0:06:44.279 and how you see this sort of ongoing debate. Great, 0:06:44.360 --> 0:06:47.240 great question. So as you, as you know through some 0:06:47.320 --> 0:06:52.440 of our exchanges, applied finance focuses on valuation. I think 0:06:52.480 --> 0:06:56.640 to some degree the term value has been hijacked historically 0:06:56.760 --> 0:07:00.840 with with the advent of the release of the FAMA 0:07:00.920 --> 0:07:04.039 French three factor model back in ninety two and the 0:07:04.120 --> 0:07:07.159 creation of this quote value factor, otherwise known as the 0:07:07.160 --> 0:07:10.800 book to price ratio. I think the term value has 0:07:10.840 --> 0:07:14.040 really been hijacked because book to price, at the end 0:07:14.080 --> 0:07:16.480 of the day, is really nothing more than a cheapness metric, 0:07:16.680 --> 0:07:19.480 as are all the price to something measures. It's measuring 0:07:20.600 --> 0:07:23.800 the price of a stock in relation to some fundamental variable, 0:07:23.880 --> 0:07:27.480 whatever that variable is, or even composites of that variable. 0:07:27.920 --> 0:07:32.160 But it doesn't necessarily relate to the worth of a stock, 0:07:32.880 --> 0:07:35.679 and I think that fundamentally is where things have really 0:07:35.760 --> 0:07:40.000 tended to diverge or go off the rails to some degree. 0:07:40.560 --> 0:07:44.640 In investing finance, the focus has been on cheapness, and 0:07:44.680 --> 0:07:48.520 there hasn't been enough attention paid to understanding intrinsic value 0:07:48.600 --> 0:07:53.720 through more complete valuation approaches, which is what we've specialized 0:07:53.720 --> 0:07:59.120 in since n SO Applied finance has been in existence 0:07:59.160 --> 0:08:02.120 since nineteen ninety five. But we were chatting before we 0:08:02.160 --> 0:08:06.920 started recording the podcast, and you mentioned that your current 0:08:06.960 --> 0:08:11.320 area of focus is something that grabbed your interest because 0:08:11.360 --> 0:08:14.880 of a big debate that was happening in the nineties seventies. 0:08:15.000 --> 0:08:18.400 Could you maybe explain that a little bit? Sure? Sure, so, 0:08:18.480 --> 0:08:22.240 let me just provide a little historic background on how 0:08:22.280 --> 0:08:24.120 we are where we are today. If you think about 0:08:24.480 --> 0:08:27.960 how finance has evolved, you know, in the sixties you 0:08:28.000 --> 0:08:30.600 had a lot of theoretical work on the CAPTEM model, 0:08:30.680 --> 0:08:34.199 which was really exciting, and then in the early seventies 0:08:34.240 --> 0:08:37.920 you started to see this basically this brand new field 0:08:37.960 --> 0:08:42.280 of finance created by Eugene Fama, which is empirical finance, 0:08:42.320 --> 0:08:45.839 and he did amazing work testing and kind of formulating 0:08:46.080 --> 0:08:50.400 the efficient market hypothesis and ushering a whole new era 0:08:50.600 --> 0:08:54.840 of scientific method applied to finance, so to speak. And 0:08:54.880 --> 0:08:58.679 I think prior to that, for the most part, university 0:08:58.760 --> 0:09:02.600 level finance focused on net present value and a lot 0:09:02.640 --> 0:09:06.840 of security analysis. And in a great paper that Farmer wrote, 0:09:06.960 --> 0:09:10.000 I believe it's titled you know, My Memories and Finance, 0:09:10.080 --> 0:09:12.760 or something to that extent, he essentially says, you know, 0:09:12.840 --> 0:09:17.280 when I arrived at Chicago, finance consisted of classes essentially 0:09:17.280 --> 0:09:20.560 teaching people to pick stocks, and in in an efficient 0:09:20.600 --> 0:09:24.880 market world, there's not a lot of value to having 0:09:24.920 --> 0:09:28.680 so many people specialized in that. And what we saw 0:09:28.720 --> 0:09:31.760 in the seventies was this birth of mean variance finance, 0:09:32.000 --> 0:09:36.960 where computer methods and data availability allowed for incredible study 0:09:36.960 --> 0:09:41.200 of properties of stock prices, testing of hypotheses of you know, 0:09:41.480 --> 0:09:44.560 a lot of the mainstream thoughts back then we're biased 0:09:44.559 --> 0:09:47.320 stock just because it's going up. So a lot of 0:09:47.600 --> 0:09:51.319 efficient market tests focused on momentum investing, which is kind 0:09:51.320 --> 0:09:55.200 of ironic given the crave of momentum investing now you know, 0:09:55.440 --> 0:09:59.040 thirty years later, fifty years later, um. And ultimately it 0:09:59.160 --> 0:10:01.920 drove security analysis to a large degree out of finance, 0:10:01.960 --> 0:10:04.120 and you see a lot of security analysis of courses 0:10:04.160 --> 0:10:08.240 now being taught in accounting departments. And what we tried 0:10:08.280 --> 0:10:12.599 to do had applied finance when we started in was 0:10:12.760 --> 0:10:15.720 essentially try to link this notion of mean variance finance 0:10:15.720 --> 0:10:20.959 and security analysis. And we did that through systematically constructing 0:10:21.040 --> 0:10:25.079 security analysis rules to process data on companies and then 0:10:25.200 --> 0:10:29.679 ultimately linking that the output of that those reformulated income 0:10:29.760 --> 0:10:32.199 statements and balance sheets from accounting data into more of 0:10:32.240 --> 0:10:36.040 an economic framework through the calculation of an economic margin, 0:10:36.320 --> 0:10:38.920 which essentially is a firm's return on investment less it's 0:10:38.960 --> 0:10:43.840 cost a capital. We linked that with expected capital growth, risk, 0:10:44.400 --> 0:10:47.920 and competition to value a company. And so we did 0:10:47.960 --> 0:10:51.440 this work from the seventies to ninety five, kind of 0:10:51.440 --> 0:10:54.800 a twenty five year what I'll call an observation window. 0:10:54.800 --> 0:10:56.760 And I think, Tracy, going back to one of your 0:10:56.800 --> 0:10:59.040 statements you made earlier about back testing, it'd be fun 0:10:59.080 --> 0:11:01.080 to get into that. It'll a little bit more depth later, 0:11:01.760 --> 0:11:04.280 but so I'll call it an observation window rather than 0:11:04.320 --> 0:11:06.800 an evidence window. I think there's a big distinction between 0:11:06.800 --> 0:11:11.880 the two. And beginning in nineteen we began calculating intrinsic 0:11:11.960 --> 0:11:16.000 value estimates. First for US companies on an ad hoc basis, 0:11:16.080 --> 0:11:18.160 i'd say monthly and quarterly. When we were early on 0:11:18.200 --> 0:11:20.040 in our company development, we were doing a lot of 0:11:20.080 --> 0:11:24.880 corporate consulting work. We didn't have the full uh infrastructure 0:11:24.880 --> 0:11:29.080 of personnel to handle calculating what i'll call productions of 0:11:29.120 --> 0:11:34.440 intrinsic value consistently. By the company had grown, and we 0:11:34.520 --> 0:11:40.000 began calculating these intrinsic values monthly, and from through today 0:11:40.120 --> 0:11:42.640 we continue doing that. Now we do it globally on 0:11:42.720 --> 0:11:47.480 twenty thousand companies every week. But what's interesting is back 0:11:47.559 --> 0:11:52.079 test observations versus evidence. Since ninety eight, these have all 0:11:52.080 --> 0:11:55.440 been live out of sample estimates of intrinsic value. And 0:11:55.480 --> 0:11:57.360 I think one of the one of the interesting things 0:11:57.480 --> 0:11:59.920 about our data set and what we used to prepare 0:12:00.040 --> 0:12:05.840 this paper called Valuation Beta, is that a lot of finances, well, 0:12:05.880 --> 0:12:08.120 let's go back to nineteen sixty three, and someone will 0:12:08.120 --> 0:12:10.360 say no, let's go back to nineteen thirty and someone 0:12:10.400 --> 0:12:12.640 will say no, I have a data series going back 0:12:12.679 --> 0:12:16.600 to the seventeen hundreds. Well, at some point this data 0:12:16.800 --> 0:12:19.920 is really irrelevant because the world has changed so much. 0:12:20.000 --> 0:12:23.440 Maybe there are these quote fundamental truths, but if you 0:12:23.440 --> 0:12:28.239 look at the factor work. Oftentimes these factors are discovered 0:12:28.920 --> 0:12:31.240 in a back test setting and then when they go 0:12:31.320 --> 0:12:34.520 live they don't work. And certainly that's been an important 0:12:34.559 --> 0:12:37.959 part of the experience with Book to Price since it's 0:12:38.000 --> 0:12:41.360 had prior to ninety two. From six to ninety one, 0:12:41.800 --> 0:12:45.479 it was basically a money making machine. The return attributes 0:12:45.520 --> 0:12:48.920 of that variable or extraordinary. Since ninety two it's had 0:12:48.960 --> 0:12:52.439 a much more spotty record, and the same as as 0:12:52.480 --> 0:12:54.640 if we dig down a little deeper on some of 0:12:54.640 --> 0:12:57.920 these other factor metrics, such as the profitability factor, the 0:12:57.960 --> 0:13:02.920 investment factor. Since they were really Eastern publicly, they've had 0:13:02.960 --> 0:13:05.319 a spotty or record as well. So I think it's important, 0:13:05.400 --> 0:13:08.800 as you said, to differentiate between back testing, which is 0:13:09.080 --> 0:13:13.160 when you're kind of formulating your your ideas, versus evidence, 0:13:13.200 --> 0:13:15.840 which happens after you've released your ideas and you you 0:13:15.920 --> 0:13:18.600 let the let the world run. As Mike Tyson likes 0:13:18.640 --> 0:13:20.440 to say, everyone has a plan to you're punched in 0:13:20.480 --> 0:13:23.880 the face, and for Book to Price and value investing, 0:13:24.400 --> 0:13:26.360 that punch in the face has happened over the last 0:13:26.360 --> 0:13:45.640 decade when it basically hasn't worked. H So you make 0:13:45.720 --> 0:13:52.959 this distinction between value valuation versus cheapness, and as you 0:13:53.440 --> 0:13:56.640 characterize that measures of price to book or really any 0:13:56.640 --> 0:14:00.480 other sort of ratio based valuation, it's not to measure 0:14:00.480 --> 0:14:03.840 of value per se, it's just a measure of cheapness. 0:14:04.720 --> 0:14:07.960 So can you explain a little bit further, like what 0:14:08.120 --> 0:14:14.280 the differences between what your measure of valuation and cheapness 0:14:14.360 --> 0:14:16.920 and why it is in your view that some of 0:14:16.960 --> 0:14:20.280 these traditional metrics measures of cheapness that at one point 0:14:20.360 --> 0:14:24.640 did produce returns have failed to do. So let me 0:14:24.680 --> 0:14:28.280 focus first on explaining our worldview and kind of how 0:14:28.400 --> 0:14:30.600 we get we get to an answer. And there's there's 0:14:30.600 --> 0:14:34.320 probably lots of reasons to speculate about why something doesn't work, 0:14:34.360 --> 0:14:39.400 but I'll offer our view of it as well. So, first, 0:14:40.240 --> 0:14:42.960 as opposed to beginning with some metric of cheapness, what 0:14:43.080 --> 0:14:47.160 we begin our discussion with is an estimate of intrinsic value. 0:14:47.800 --> 0:14:50.200 So how do we go from accounting data to an 0:14:50.280 --> 0:14:53.680 estimate of affirms intrinsic values. So we begin we process 0:14:53.760 --> 0:14:55.720 the data, and there's a lot of around the world, 0:14:55.800 --> 0:14:57.920 there's a lot of accounting issues that we've dealt with 0:14:58.000 --> 0:15:01.320 and tried to incorporate so dramatically in our analysis, but 0:15:01.360 --> 0:15:03.960 I'll just talk about a few that I think make 0:15:04.040 --> 0:15:08.800 for for a quick, interesting discussion. Since since the beginning 0:15:08.840 --> 0:15:12.240 of our of our company, we've viewed research and development 0:15:12.760 --> 0:15:16.280 as an investment rather than an expense. So since we've 0:15:16.360 --> 0:15:20.320 capitalized R and D, and our view is this is 0:15:20.360 --> 0:15:23.240 a piece of operations based cash flow the company is 0:15:23.320 --> 0:15:27.960 generating currently. Another item is the use of operating leases. 0:15:28.360 --> 0:15:31.840 You know, the accountants historically have treated that as an 0:15:31.840 --> 0:15:35.880 expense rather than anything having to do with the balance sheet. Systematically, 0:15:36.520 --> 0:15:38.360 in the last couple of years, fast he has kind 0:15:38.360 --> 0:15:40.000 of come around to our view of thinking and as 0:15:40.120 --> 0:15:44.360 required companies to start capitalizing operating leases. We want to 0:15:44.440 --> 0:15:48.640 view companies on a on a capital structure free basis. 0:15:48.680 --> 0:15:51.880 So we're going to add back interest expense on an 0:15:51.880 --> 0:15:55.120 after tax basis, We're going to make adjustments to the 0:15:55.160 --> 0:15:58.960 balance sheet for inflation. It sounds a little silly now, 0:15:59.720 --> 0:16:03.200 and certainly is silly for technology companies that have very 0:16:03.240 --> 0:16:07.680 little physical plant, but for industrial firms that have assets 0:16:07.680 --> 0:16:10.520 on their books that they acquired in the seventies, inflation 0:16:10.680 --> 0:16:13.560 is a big deal because it's easy to have inflated 0:16:13.600 --> 0:16:17.360 return on investments because the balance sheets reflecting historic cost 0:16:18.040 --> 0:16:22.960 the income is respecting is displaying current values, current dollars values. 0:16:22.960 --> 0:16:25.640 So there's a litany of adjustments we go through. We 0:16:25.720 --> 0:16:28.080 do all that, and one last thing that we we 0:16:28.280 --> 0:16:30.960 account for is how long the company's assets last on 0:16:31.040 --> 0:16:33.360 average to get an asset life. So then we can 0:16:33.400 --> 0:16:37.160 configure a firm as a project and we can calculate 0:16:37.880 --> 0:16:39.840 what we call an economic margin. We don't have to 0:16:39.840 --> 0:16:42.120 get into all the geek speak on that, but essentially, 0:16:42.520 --> 0:16:44.000 at the end of the day, what we end up 0:16:44.040 --> 0:16:48.880 with is a corrected return on investment on an inflation 0:16:48.920 --> 0:16:53.120 adjusted asset based minus acost of capital. That spread or 0:16:53.160 --> 0:16:56.600 economic margin, starts to tell us a lot of things 0:16:56.640 --> 0:16:59.520 about the company. First of all, if you have an 0:16:59.520 --> 0:17:03.120 economic margin that's negative, it tells you the firm is 0:17:03.160 --> 0:17:07.040 investing in projects below its cost of capital. So the 0:17:07.119 --> 0:17:08.800 last thing we'd want to see a firm like that 0:17:08.840 --> 0:17:12.600 do is grow its business. That's what we call wealth destroyers, 0:17:13.240 --> 0:17:16.320 and it's it's a very key piece of how we 0:17:16.359 --> 0:17:19.000 think about analyzing companies and what they're doing. If you 0:17:19.040 --> 0:17:22.480 have a negative spread to your cost of capital. You 0:17:22.520 --> 0:17:25.760 should be shrinking your business or rationalizing what you have 0:17:25.920 --> 0:17:27.439 to figure out how to at least get to a 0:17:27.520 --> 0:17:31.879 zero spread. Companies that have a positive spread, and again 0:17:31.880 --> 0:17:34.359 this is after accounting for things such as investments in 0:17:34.440 --> 0:17:37.040 R and D off, balance sheet releases, on and so on. 0:17:37.640 --> 0:17:40.560 Companies that have a positive spread should grow. And I 0:17:40.600 --> 0:17:42.840 think Joe in one of your tweets a while back 0:17:42.920 --> 0:17:46.719 that that initiated our discussions, you asked a question about Monster, 0:17:46.840 --> 0:17:50.560 and you said, can anyone explain Monster to us? The 0:17:50.600 --> 0:17:53.359 Monster story is pretty simple. This is a firm that 0:17:53.560 --> 0:17:57.119 some people know. This is the the energy drink maker 0:17:57.200 --> 0:17:59.879 with lots of caffeine, that's the best performing stock. Go on, 0:18:00.000 --> 0:18:03.200 I just wanted to, uh, just for people who are great, great, 0:18:03.359 --> 0:18:06.680 it's been an incredible wealth compounding company through the years. 0:18:06.680 --> 0:18:08.960 It's not a it's not a recent thing. You know. 0:18:09.000 --> 0:18:11.240 This is a firm that's earning ten to fift percent 0:18:11.320 --> 0:18:14.280 returns above its cost of capital and has been growing 0:18:14.280 --> 0:18:18.120 its capital based at double digits. So you have This 0:18:18.200 --> 0:18:21.080 is a classic example of what we call a wealth creator, 0:18:21.160 --> 0:18:25.359 a compound wealth creator generally reinvesting in high rates of return, 0:18:25.520 --> 0:18:28.000 creating more and more wealth for the existing shareholders, and 0:18:28.040 --> 0:18:31.760 the company continues growing into its valuation. I think we 0:18:31.840 --> 0:18:35.840 sent you a chart that traces out our estimate of 0:18:35.920 --> 0:18:39.680 Monsters intrinsic value through time, and again these are basically 0:18:39.760 --> 0:18:42.280 live estimates going back. This is in this case going 0:18:42.359 --> 0:18:44.600 back to ten years at least, but it traced out 0:18:44.600 --> 0:18:47.760 our intrinsic value for Monster relative to its traded price. 0:18:47.800 --> 0:18:51.920 And what's interesting is this thought consistently was trading at 0:18:52.040 --> 0:18:54.520 or below its intrinsic value, and even recently with the 0:18:54.560 --> 0:18:58.720 big runs it has, it's not grotesquely overvalued from our perspective, 0:18:59.280 --> 0:19:01.720 which is what what leads to the tension between the 0:19:01.760 --> 0:19:05.600 way we view the world from an intrinsic value perspective. 0:19:05.680 --> 0:19:09.480 Intrinsic values of function of this level of economic profitability 0:19:09.880 --> 0:19:12.080 how much you're able to reinvest in the business to 0:19:12.160 --> 0:19:15.800 create more economic profits. Then we discount that back to 0:19:15.840 --> 0:19:18.720 reflect the firm's risk based on its size and its 0:19:18.800 --> 0:19:23.919 leverage characteristics. And then lastly we incorporate an overlay. And 0:19:23.920 --> 0:19:26.960 this is where we diverge quite a bit from traditional 0:19:27.840 --> 0:19:32.960 DCF methods that say, okay, we're gonna go out five, six, 0:19:33.000 --> 0:19:35.560 seven years, and then put a terminal value or used 0:19:35.560 --> 0:19:38.520 to Gordon growth model to assume that the rest of 0:19:38.520 --> 0:19:41.560 the world is kind of static. We're going to capitalize 0:19:41.600 --> 0:19:45.119 everything back via perpetuity. We think that's kind of a 0:19:45.119 --> 0:19:48.320 crazy assumption, and you can just talk to kmart about 0:19:48.320 --> 0:19:53.200 how valid the world being constant is. And we apply 0:19:53.280 --> 0:19:56.639 what we call an economic profit horizon, which, again based 0:19:56.640 --> 0:20:00.199 on the research we did, we assign every firm a 0:20:00.280 --> 0:20:03.760 factor based on fundamental characteristics that say, how long will 0:20:03.800 --> 0:20:07.399 this economic profit persist? How long can we expect this 0:20:07.640 --> 0:20:11.160 firm to have an economic margin greater than zero. Because 0:20:11.200 --> 0:20:13.960 once the margin, once your returnees, the cost of capital 0:20:14.840 --> 0:20:17.920 just present value. Math says from that point forward growth 0:20:18.040 --> 0:20:20.400 is irrelevant because the net present value of future growth 0:20:20.480 --> 0:20:24.080 of zero. So all of that a lot of different 0:20:24.160 --> 0:20:27.600 complicated concepts going on at once behind each level, but 0:20:27.720 --> 0:20:31.040 at its most basic, we're basically we're saying, let's figure 0:20:31.080 --> 0:20:33.200 out what the true economic return of a firm is. 0:20:34.040 --> 0:20:36.640 Let's get a handle on how much it's reinvesting in itself. 0:20:37.400 --> 0:20:40.440 Let's let's get some idea on how risky these cash 0:20:40.440 --> 0:20:43.200 flows are, so that from a from an a risk 0:20:43.240 --> 0:20:46.680 adjusted basis, we can compare companies on an apples to 0:20:46.720 --> 0:20:50.320 Apple's perspective. And then let's say companies are not going 0:20:50.359 --> 0:20:54.600 to earn economic profits forever because of competition, so we 0:20:54.760 --> 0:20:57.800 combine those to get an estimate for intrinsic value for 0:20:57.880 --> 0:21:01.680 twenty companies around the world every week. That becomes the 0:21:01.760 --> 0:21:05.280 basis for us looking at the world and then sorting 0:21:05.320 --> 0:21:09.320 out portfolios of companies and Dubai's into cells or creating, 0:21:09.640 --> 0:21:12.720 you know, slicing and dicing that to create subsets of 0:21:12.800 --> 0:21:17.360 products for our clients. What do the tech stocks look 0:21:17.480 --> 0:21:21.280 like under that framework? You know, things like an Apple 0:21:21.640 --> 0:21:25.760 or Facebook or a Netflix. I think it's always useful 0:21:25.800 --> 0:21:28.879 when we're talking about differences in how we're measuring intrinsic 0:21:29.000 --> 0:21:33.639 value to actually speak about concrete examples. And the Monster 0:21:33.760 --> 0:21:36.200 one was a great example just then. But I'm thinking 0:21:36.880 --> 0:21:41.119 something like Apple, you have a lot of profits, a 0:21:41.200 --> 0:21:45.719 lot of investment of very low cost of capital. Does 0:21:45.760 --> 0:21:50.359 it look good in your method of intrinsic value? Let 0:21:50.440 --> 0:21:52.959 me go back a little bit in time as well. Uh, 0:21:53.040 --> 0:21:55.400 and again not in the context of a back test 0:21:55.480 --> 0:21:57.679 or observation, but in context of kind of our our 0:21:57.760 --> 0:22:01.720 main strategy portfolio. If we go back to eleven, and 0:22:01.840 --> 0:22:04.200 this is this is an example that week. We presented 0:22:04.280 --> 0:22:06.600 to some clients the other day because they're kind of 0:22:06.680 --> 0:22:12.320 asking the same type of question. In eleven, we purchased three. 0:22:12.480 --> 0:22:15.280 This is a very low turnover portfolio averages less than 0:22:15.600 --> 0:22:17.720 ten percent turnover a year. But in twenty eleven we 0:22:17.800 --> 0:22:22.159 made three purchases in the tech space, Alphabet and Vidia 0:22:22.359 --> 0:22:25.879 and master Card. Okay, at the time, they were trading 0:22:25.960 --> 0:22:29.520 on a multiple basis well above the market median, and 0:22:29.720 --> 0:22:33.720 from a multiple perspective, those multiples only grew more and 0:22:33.840 --> 0:22:37.280 more expensive relative to the market through time. I think 0:22:38.400 --> 0:22:41.920 we added Apple to the portfolio. Uh five years ago. 0:22:41.960 --> 0:22:44.800 I think we added Facebook to the portfolio. So we 0:22:44.960 --> 0:22:47.600 own all of those stocks and they've all been attractive 0:22:47.640 --> 0:22:51.159 to us from an intrinsic value perspective. In Video, we 0:22:51.240 --> 0:22:54.440 bought in twenty eleven and thirteen dollars a share I 0:22:54.480 --> 0:22:58.200 think in eighteen or at the end of the year 0:22:58.320 --> 0:23:00.960 crashed from three hundred to one fifty. People thought we 0:23:01.040 --> 0:23:04.000 were nuts to have owned it at three hundred. I 0:23:04.080 --> 0:23:07.240 remember having a conversation with a with a really prominent 0:23:07.320 --> 0:23:09.479 journalist and he's like, you guys are crazy. How can 0:23:09.520 --> 0:23:12.680 you call that a stock that's undervalued at one fifty 0:23:12.720 --> 0:23:15.679 after the crash, We're like, we believe it's undervalue, We're 0:23:15.680 --> 0:23:17.960 gonna own it, and then we just sold that this 0:23:18.080 --> 0:23:23.880 past August at We continue to own Google, Apple, Facebook, MasterCard, 0:23:24.680 --> 0:23:27.560 um at the same time, we own what you consider 0:23:27.640 --> 0:23:29.920 to be some classic value stocks. We own Intel, we 0:23:30.000 --> 0:23:34.000 own Hewlett Packard, We own Financials, which is a big 0:23:34.119 --> 0:23:38.480 chunk of the of the value universe, so its valuation. 0:23:39.920 --> 0:23:43.800 This whole dichotomy of value versus growth is really a 0:23:43.920 --> 0:23:46.720 false way to think about firms, because every firm is growing, 0:23:46.760 --> 0:23:49.320 whether it's positive or negative. There's growth taking place for 0:23:49.400 --> 0:23:55.720 every firm. And you know Warren Buffett obviously super successful, 0:23:55.800 --> 0:23:57.880 wise guy. Everything is a function of what you're paying 0:23:57.920 --> 0:24:00.200 for in the market. Please, you can have all the 0:24:00.280 --> 0:24:04.919 stocks that represent an incredible investment opportunity just as easily 0:24:05.000 --> 0:24:09.040 as you can have a stock like Monster represent an 0:24:09.080 --> 0:24:13.400