1 00:00:09,280 --> 00:00:13,240 Speaker 1: Hello, and welcome to another episode of the All Thoughts podcast. 2 00:00:13,280 --> 00:00:17,440 Speaker 1: I'm Tracy Allaway and I'm Joe Wisenthal. So, Joe, we 3 00:00:17,480 --> 00:00:21,200 Speaker 1: are in the midst of yet another earning season, which 4 00:00:21,239 --> 00:00:25,360 Speaker 1: means everyone is spending their time examining all the income 5 00:00:25,440 --> 00:00:29,120 Speaker 1: statements that big companies are publishing. Right. Yeah, it comes 6 00:00:29,600 --> 00:00:32,040 Speaker 1: four times a year, and it's one of the you know, 7 00:00:32,120 --> 00:00:34,440 Speaker 1: one of the most exciting times of the year, especially 8 00:00:34,440 --> 00:00:37,879 Speaker 1: if you're a stock investor, because it's when you know, 9 00:00:37,960 --> 00:00:41,200 Speaker 1: the companies reveal all of the stuff that they did 10 00:00:41,280 --> 00:00:44,760 Speaker 1: in the last quarter, the revenue, how much they made, 11 00:00:45,360 --> 00:00:48,320 Speaker 1: how much their balance sheet, highlights of the quarter, and 12 00:00:48,320 --> 00:00:50,680 Speaker 1: it's when you really have a chance to dig in 13 00:00:50,760 --> 00:00:53,519 Speaker 1: because you have a fresh snapshot of the state of 14 00:00:53,520 --> 00:00:56,200 Speaker 1: the company. Right. But there's a lot of work that 15 00:00:56,240 --> 00:01:01,639 Speaker 1: goes into estimating earnings results even before they come out, right, Like, 16 00:01:02,160 --> 00:01:05,679 Speaker 1: analysts will be tweaking their models ahead of results season, 17 00:01:05,760 --> 00:01:08,240 Speaker 1: and then they'll be tweaking them after. Everyone is sort 18 00:01:08,240 --> 00:01:11,039 Speaker 1: of digging into the numbers to try to determine how 19 00:01:11,040 --> 00:01:14,480 Speaker 1: well or how badly a company is doing. Absolutely, and 20 00:01:14,520 --> 00:01:16,160 Speaker 1: one of the things that I think a lot of 21 00:01:16,200 --> 00:01:19,280 Speaker 1: people don't get if they're not really active in markets. 22 00:01:19,280 --> 00:01:22,760 Speaker 1: Is that there's no such thing is objectively good or 23 00:01:22,800 --> 00:01:28,520 Speaker 1: bad earnings, because in markets everything is about relative to expectations. 24 00:01:28,520 --> 00:01:31,800 Speaker 1: So you can have a company that doubled their earnings 25 00:01:32,000 --> 00:01:35,040 Speaker 1: and made a billion dollars this year versus a billion 26 00:01:35,080 --> 00:01:37,360 Speaker 1: more than last year, but if the market was expecting 27 00:01:37,440 --> 00:01:39,720 Speaker 1: them to make one point two billion dollars more than 28 00:01:39,720 --> 00:01:42,600 Speaker 1: the stock might tumble. Conversely, you can have companies that 29 00:01:42,920 --> 00:01:46,399 Speaker 1: lose a ton of money, but if people were impressed 30 00:01:46,400 --> 00:01:48,720 Speaker 1: by some you know, their revenue growth, or people were 31 00:01:48,760 --> 00:01:52,080 Speaker 1: impressed that they were expected to lose more, uh, they 32 00:01:52,280 --> 00:01:55,360 Speaker 1: the stock might surge. And as such, it's the sort 33 00:01:55,360 --> 00:01:58,720 Speaker 1: of like the classic kynesie and beauty contest. You don't 34 00:01:58,800 --> 00:02:01,000 Speaker 1: just try to figure out the company is gonna earn, 35 00:02:01,240 --> 00:02:03,240 Speaker 1: but we also try to figure out what the crowd 36 00:02:03,480 --> 00:02:05,920 Speaker 1: thinks the company is going to earn and how the 37 00:02:06,000 --> 00:02:09,919 Speaker 1: actual results match up to expectations. Right, And some people 38 00:02:09,919 --> 00:02:12,840 Speaker 1: say that things have gotten even more complicated in recent 39 00:02:12,919 --> 00:02:15,560 Speaker 1: years because you have companies that sort of try to 40 00:02:15,639 --> 00:02:19,760 Speaker 1: talk down expectations before their results and so inevitably they 41 00:02:19,880 --> 00:02:24,880 Speaker 1: end up beating already low forecasts. So there's lots of 42 00:02:24,919 --> 00:02:27,200 Speaker 1: moving parts to this isn't there. But Joe, what if 43 00:02:27,200 --> 00:02:31,640 Speaker 1: I told you that digging into earnings is a useless exercise. 44 00:02:31,880 --> 00:02:34,399 Speaker 1: If you told me that it was a useless exercise 45 00:02:34,440 --> 00:02:37,040 Speaker 1: to dig in like this, I would be completely crushed 46 00:02:37,080 --> 00:02:39,520 Speaker 1: because a part of my job is to talk about 47 00:02:39,560 --> 00:02:42,560 Speaker 1: this and be One of my first jobs was doing 48 00:02:42,600 --> 00:02:46,480 Speaker 1: equity research for a small portfolio management company, and that's 49 00:02:46,520 --> 00:02:49,360 Speaker 1: what I spent hours and hours going through every one 50 00:02:49,400 --> 00:02:53,280 Speaker 1: of these lines. So please don't tell me now. I'm 51 00:02:53,280 --> 00:02:55,640 Speaker 1: sorry to get scared. Why are you? Why are you 52 00:02:55,760 --> 00:02:59,000 Speaker 1: hinting that maybe it's all the waste of time? Don't 53 00:02:59,000 --> 00:03:01,360 Speaker 1: be scared, Joe. What I mean is it might be 54 00:03:01,480 --> 00:03:05,600 Speaker 1: useless to dig into those earning statements in a sort 55 00:03:05,639 --> 00:03:09,119 Speaker 1: of traditional sense. Basically, there are some people out there 56 00:03:09,120 --> 00:03:13,320 Speaker 1: who think that the way we use current accounting rules 57 00:03:13,320 --> 00:03:16,320 Speaker 1: are the way that accounting rules have been implemented, doesn't 58 00:03:16,360 --> 00:03:21,000 Speaker 1: really match the realities of our modern economy or our 59 00:03:21,200 --> 00:03:26,720 Speaker 1: modern business environment. Okay, so let's get your I'm still 60 00:03:26,760 --> 00:03:29,079 Speaker 1: a sort of waiting for the build up here. You'll 61 00:03:29,120 --> 00:03:32,440 Speaker 1: be fine, You'll be fine. Okay, We're going to talk 62 00:03:32,560 --> 00:03:36,480 Speaker 1: to Baruke Love. He's professor of Accounting and Finance at 63 00:03:36,480 --> 00:03:40,800 Speaker 1: Stern School of Business and Fenggu Associate Professor of Accounting 64 00:03:40,800 --> 00:03:43,920 Speaker 1: at Sunni Buffalo. They put out a paper which was 65 00:03:44,000 --> 00:03:49,080 Speaker 1: fantastic on this exact subject, basically arguing that our accounting 66 00:03:49,280 --> 00:03:53,000 Speaker 1: standards haven't really kept up with big, big changes that 67 00:03:53,080 --> 00:03:55,720 Speaker 1: have overtaken the economy in recent years. So let's get 68 00:03:55,720 --> 00:03:58,680 Speaker 1: over to them. Buruke and Fang, welcome to the show. 69 00:03:59,040 --> 00:04:01,960 Speaker 1: Thank you, thank you, Thank you for having us. So 70 00:04:02,360 --> 00:04:05,800 Speaker 1: was that intro accurate? Is the some of your work 71 00:04:06,080 --> 00:04:12,360 Speaker 1: essentially that accounting methodology hasn't really adjusted to modern realities. 72 00:04:13,000 --> 00:04:15,880 Speaker 1: I would say the intro is very accurate. It's not 73 00:04:16,000 --> 00:04:21,520 Speaker 1: just that we claimed that earnings don't matter. We actually 74 00:04:21,680 --> 00:04:25,839 Speaker 1: prove it. Uh. In a recent article we published, we 75 00:04:26,000 --> 00:04:29,039 Speaker 1: show for all companies that even if you had the 76 00:04:29,240 --> 00:04:34,799 Speaker 1: dream forecasting machine, meaning that you could focus, you could 77 00:04:34,839 --> 00:04:40,640 Speaker 1: identify all the companies that we meet or beat consensus 78 00:04:40,680 --> 00:04:45,480 Speaker 1: analysts focused next quarter. You're not longer to make anybody. 79 00:04:45,720 --> 00:04:48,159 Speaker 1: You're not going to make any money from this. You 80 00:04:48,440 --> 00:04:52,479 Speaker 1: used to in the past, big money, but no longer. 81 00:04:52,640 --> 00:04:57,960 Speaker 1: And most people are not aware of the demise of 82 00:04:58,160 --> 00:05:05,360 Speaker 1: earnings as an indicate of company performance. Evaluated of manager's capabilities. 83 00:05:05,920 --> 00:05:09,239 Speaker 1: So we actually prove it both in a recent book 84 00:05:09,279 --> 00:05:14,120 Speaker 1: that we wrote and in in the article. And this 85 00:05:14,240 --> 00:05:17,960 Speaker 1: is this is really I would say earth shattering, but 86 00:05:18,200 --> 00:05:21,760 Speaker 1: it's effect. This is indeed earth shattering. I mean, this 87 00:05:21,839 --> 00:05:24,480 Speaker 1: is in fury. This blows up the premise of so 88 00:05:24,520 --> 00:05:27,560 Speaker 1: many of our conversations, which as we say, okay, Facebook 89 00:05:27,560 --> 00:05:30,400 Speaker 1: earnings are coming out, or GM earnings are coming out, 90 00:05:30,520 --> 00:05:32,800 Speaker 1: and they're expected to earn a dollar and a penny 91 00:05:32,800 --> 00:05:35,560 Speaker 1: per share, and they earn only nineties seven cents. And 92 00:05:36,080 --> 00:05:38,960 Speaker 1: as you say, we try so hard to get this right. 93 00:05:39,600 --> 00:05:41,440 Speaker 1: Let's say, maybe let's start from thinking, so, where did 94 00:05:41,440 --> 00:05:44,479 Speaker 1: the if it's not right, where did it come from? 95 00:05:44,480 --> 00:05:46,480 Speaker 1: Where did we get this idea of how we traditionally 96 00:05:46,520 --> 00:05:50,599 Speaker 1: talk about earnings. The centrality of earnings comes from the 97 00:05:50,680 --> 00:05:55,080 Speaker 1: work of Graham many years ago. He was the celebrated 98 00:05:55,120 --> 00:05:59,200 Speaker 1: teacher of warm Buffett, and since then earnings are the 99 00:05:59,440 --> 00:06:04,720 Speaker 1: center of all the models that analysts are using. Everything 100 00:06:04,839 --> 00:06:10,880 Speaker 1: is aimed at predicting forthcoming earnings. Managers are pestor to 101 00:06:11,040 --> 00:06:17,159 Speaker 1: provide some guidance for forecasting earnings. Everything revolves around earnings, 102 00:06:17,360 --> 00:06:19,839 Speaker 1: and the reason, of course, a reason why so many 103 00:06:19,839 --> 00:06:23,520 Speaker 1: so much money goes to index fund and to automated 104 00:06:23,720 --> 00:06:29,200 Speaker 1: investment managed funds are not doing well, and we claim 105 00:06:29,279 --> 00:06:31,599 Speaker 1: that the main reason why they're not doing well is 106 00:06:31,680 --> 00:06:37,080 Speaker 1: because their focus on earnings is completely misplaced. Right, And 107 00:06:37,160 --> 00:06:40,240 Speaker 1: you have, like you said earlier, if if someone built 108 00:06:40,279 --> 00:06:45,080 Speaker 1: the perfect earnings prediction machine, there was a time when 109 00:06:45,240 --> 00:06:47,800 Speaker 1: you could have made big money from that, and now 110 00:06:47,839 --> 00:06:51,680 Speaker 1: it doesn't seem to be the case. So what exactly 111 00:06:51,760 --> 00:06:55,240 Speaker 1: has happened there? What happened is that it used to 112 00:06:55,320 --> 00:06:59,880 Speaker 1: be that earnings really indicated performance of companies. Thirty forty 113 00:07:00,040 --> 00:07:07,000 Speaker 1: years ago, earnings basically indicated revenues minus real costs. Since then, 114 00:07:07,200 --> 00:07:11,640 Speaker 1: there was a revolution in the business models of companies 115 00:07:12,440 --> 00:07:16,840 Speaker 1: from tangible to intangible assets. You don't make money anymore 116 00:07:16,960 --> 00:07:21,400 Speaker 1: from machines and equipment and building. You make money from 117 00:07:21,520 --> 00:07:27,920 Speaker 1: patents and brands and information technologies and human resources. Everyone 118 00:07:28,040 --> 00:07:32,080 Speaker 1: knows it, everyone uses it, except for accountants that were 119 00:07:32,120 --> 00:07:35,680 Speaker 1: really asleep at the wheel and still are. And all 120 00:07:35,760 --> 00:07:41,280 Speaker 1: those huge expenses of companies in intangibles are expensed in 121 00:07:41,400 --> 00:07:46,120 Speaker 1: the income statement, meaning they are charged against earnings. So 122 00:07:46,200 --> 00:07:51,200 Speaker 1: the earnings that you get today are completely misstated. For 123 00:07:51,280 --> 00:07:55,800 Speaker 1: some companies, they are overstated. For other companies they are understated. 124 00:07:56,560 --> 00:07:59,320 Speaker 1: Just think about the Amazon in the last four or 125 00:07:59,360 --> 00:08:05,480 Speaker 1: five years, they missed half their consensus earnings. Nothing happened 126 00:08:05,480 --> 00:08:08,120 Speaker 1: to them. That's of course a marvelous companies with a 127 00:08:08,240 --> 00:08:15,240 Speaker 1: huge market value. Think about Tesla, incredible brand, with accumulated 128 00:08:15,360 --> 00:08:19,320 Speaker 1: losses of one and a half billion dollars because they 129 00:08:19,320 --> 00:08:23,800 Speaker 1: are forced to expense all their investments. A much smaller, 130 00:08:23,960 --> 00:08:28,480 Speaker 1: less known company like Kite Farmer, which works on very 131 00:08:28,520 --> 00:08:34,640 Speaker 1: advanced cancer research. You look at the financial reports accumulated 132 00:08:34,760 --> 00:08:38,040 Speaker 1: losses of six hundred million dollars. They were just a 133 00:08:38,080 --> 00:08:42,280 Speaker 1: week ago bought by gilly Out Sciences for twelve billion dollars. 134 00:08:43,040 --> 00:08:48,920 Speaker 1: I mean, the financial reports completely mistaked the picture of 135 00:08:49,040 --> 00:08:54,000 Speaker 1: the company, the performance of the company, the future prospects 136 00:08:54,160 --> 00:08:57,800 Speaker 1: of the company. And that's where we are now. And 137 00:08:57,920 --> 00:09:01,480 Speaker 1: that's why, that's the reasons of the failure of the 138 00:09:01,600 --> 00:09:06,800 Speaker 1: traditional analges of companies focusing on earnings. Again, these are 139 00:09:06,840 --> 00:09:10,560 Speaker 1: not just claims that we make article. We demonstrate that 140 00:09:10,920 --> 00:09:14,160 Speaker 1: the lass of earnings relevance over time is really driven 141 00:09:14,320 --> 00:09:18,400 Speaker 1: by companies that invest a lot of money intangible assets. 142 00:09:18,480 --> 00:09:24,520 Speaker 1: So Over time, investors eventually realize that the earnings information, 143 00:09:24,679 --> 00:09:28,000 Speaker 1: the profit laws, and the balance and information investors look 144 00:09:28,040 --> 00:09:33,080 Speaker 1: at is no longer relevant for evaluating the performance and 145 00:09:33,120 --> 00:09:35,960 Speaker 1: the value of these companies. So to be clear, just 146 00:09:36,000 --> 00:09:39,000 Speaker 1: to clarify that a little further, there was a point 147 00:09:39,160 --> 00:09:41,959 Speaker 1: in which that magic earnings oracle would have made you 148 00:09:42,000 --> 00:09:44,560 Speaker 1: a lot of money had you had it. And you 149 00:09:44,679 --> 00:09:48,720 Speaker 1: demonstrate in your paper that the value of that information 150 00:09:48,880 --> 00:09:51,200 Speaker 1: in advance has declined. Can you talk us through a 151 00:09:51,240 --> 00:09:53,920 Speaker 1: little bit that's sort of the quantitative evidence you show 152 00:09:54,080 --> 00:09:57,680 Speaker 1: that that isn't useful information anymore. Sure, Going back to 153 00:09:57,760 --> 00:10:01,520 Speaker 1: the late eighties and early nineties, um, the gains from 154 00:10:01,559 --> 00:10:06,400 Speaker 1: this dream machine of perfectly predicting future earnings would allow 155 00:10:06,440 --> 00:10:09,960 Speaker 1: you to earn access profit in the magnitude of twenty 156 00:10:10,040 --> 00:10:14,280 Speaker 1: five percent each year. This is in access of market 157 00:10:14,360 --> 00:10:17,600 Speaker 1: and risk adjusted returns. So those were the good days 158 00:10:17,640 --> 00:10:21,800 Speaker 1: of playing this earnings prediction game. Now, moving to the 159 00:10:21,840 --> 00:10:24,800 Speaker 1: current time, as off the end of two thousand fifteen, 160 00:10:25,360 --> 00:10:28,080 Speaker 1: the same process would earn you no more than two 161 00:10:28,080 --> 00:10:31,000 Speaker 1: percent of access return. And there are of course a 162 00:10:31,000 --> 00:10:34,480 Speaker 1: lot of treating strategies that can earn you even better 163 00:10:35,360 --> 00:10:48,680 Speaker 1: access returns at much lower cost. Before we get into 164 00:10:49,200 --> 00:10:50,959 Speaker 1: you know, I will obviously I want to talk about 165 00:10:50,960 --> 00:10:53,720 Speaker 1: what we should be looking at instead of the traditional earnings. 166 00:10:53,720 --> 00:10:56,120 Speaker 1: But before we get into that, it's still you know, 167 00:10:56,160 --> 00:10:59,080 Speaker 1: it makes me uncomfortable because even with all of the 168 00:10:59,240 --> 00:11:03,600 Speaker 1: changes in business models an intangible assets, it still seems 169 00:11:03,640 --> 00:11:06,679 Speaker 1: like an intuitive basis that the measure of a company 170 00:11:06,760 --> 00:11:09,040 Speaker 1: is like, okay, but did you make money or not 171 00:11:09,200 --> 00:11:11,800 Speaker 1: in this quarter? And how much money do you have today? 172 00:11:11,840 --> 00:11:14,560 Speaker 1: And how much money do you have three months from now, 173 00:11:14,679 --> 00:11:17,560 Speaker 1: and that ultimately, for as weird and as different as 174 00:11:17,600 --> 00:11:21,560 Speaker 1: business models get, profit is still the point of business. 175 00:11:21,679 --> 00:11:24,160 Speaker 1: It sits in a little bit uneasy with me that 176 00:11:24,320 --> 00:11:27,559 Speaker 1: ultimately it still wouldn't come back to just how much 177 00:11:27,559 --> 00:11:31,200 Speaker 1: money they made. You're right about the importance of how 178 00:11:31,320 --> 00:11:35,160 Speaker 1: much money you're you're making now and of course even 179 00:11:35,200 --> 00:11:37,600 Speaker 1: more important, how much money you'll make in the future. 180 00:11:38,520 --> 00:11:42,559 Speaker 1: What we claim is that earnings measured according to the 181 00:11:42,559 --> 00:11:48,120 Speaker 1: accounting rules today don't even reflect this. That's why, for example, 182 00:11:48,160 --> 00:11:50,640 Speaker 1: in our in our recent book The End of Accounting, 183 00:11:50,760 --> 00:11:55,480 Speaker 1: we show that if you base your analysis on cash flows, 184 00:11:55,600 --> 00:11:58,160 Speaker 1: you will be better off then if you'll do it 185 00:11:58,240 --> 00:12:01,720 Speaker 1: on earnings. So you're perfectly right. It's of course of 186 00:12:01,760 --> 00:12:06,920 Speaker 1: great importance how much money you make, but reported earnings 187 00:12:07,000 --> 00:12:10,560 Speaker 1: don't measure how much money you make by the way 188 00:12:10,920 --> 00:12:14,880 Speaker 1: managers know it, and that's the major reason why they 189 00:12:14,920 --> 00:12:20,120 Speaker 1: release all those non gap earnings which are so derided 190 00:12:20,280 --> 00:12:24,000 Speaker 1: by our people. Some of them are, of course a 191 00:12:24,080 --> 00:12:28,920 Speaker 1: little massage manipulated, but by and large this is a 192 00:12:29,000 --> 00:12:34,319 Speaker 1: manager will response to the inability of currently measured earnings 193 00:12:34,360 --> 00:12:39,760 Speaker 1: to reflect what actually happens in corporations. Right, So it 194 00:12:39,800 --> 00:12:43,280 Speaker 1: feels like every earning season we get a news article 195 00:12:43,400 --> 00:12:50,400 Speaker 1: about how reported gap figures are veering away from adjusted earnings, 196 00:12:50,440 --> 00:12:54,800 Speaker 1: and lots of people have problems with adjusted earnings because 197 00:12:54,800 --> 00:12:59,760 Speaker 1: they think they're they're vulnerable to manipulation either by managers 198 00:12:59,880 --> 00:13:03,240 Speaker 1: or analysts might read too much into them. But you're 199 00:13:03,360 --> 00:13:08,600 Speaker 1: arguing that there are more accurate representation than traditional gap accounting, 200 00:13:08,880 --> 00:13:12,720 Speaker 1: or that they feel a sort of gap left by gap. 201 00:13:13,000 --> 00:13:17,480 Speaker 1: I guess again, it's not. It's not just my argument. 202 00:13:18,840 --> 00:13:22,840 Speaker 1: It's the result of lots of research projects that are 203 00:13:22,920 --> 00:13:29,880 Speaker 1: confirmed that investors react more strongly, most forcefully to non 204 00:13:30,000 --> 00:13:36,479 Speaker 1: gap earnings than gap earnings. So investors find by enlarge, 205 00:13:36,720 --> 00:13:41,439 Speaker 1: non gap earnings is much more informative than gap earnings. 206 00:13:41,559 --> 00:13:44,760 Speaker 1: That's again effect. These are things that are very easy 207 00:13:44,800 --> 00:13:48,679 Speaker 1: to research, and these are the findings. Thing I think 208 00:13:48,920 --> 00:13:53,120 Speaker 1: you mentioned Amazon, or maybe we're talking about Amazon and Tesla, 209 00:13:53,760 --> 00:13:57,520 Speaker 1: and of course Amazon is sort of famous for people 210 00:13:58,200 --> 00:14:02,280 Speaker 1: discarding their earnings or even their non gap earnings that 211 00:14:02,400 --> 00:14:04,559 Speaker 1: you can have these quarters will they'll lose money and 212 00:14:04,600 --> 00:14:08,439 Speaker 1: the stock shoots up, or they'll give a guidance range 213 00:14:08,520 --> 00:14:10,960 Speaker 1: that's so wide is to be laughable, but it doesn't 214 00:14:11,000 --> 00:14:14,240 Speaker 1: really matter to people, and people keep buying. The story 215 00:14:14,679 --> 00:14:18,280 Speaker 1: that pundits like to tell about Amazon is that Jeff 216 00:14:18,320 --> 00:14:22,080 Speaker 1: Bezos has done such a good job training Wall Street 217 00:14:22,120 --> 00:14:25,480 Speaker 1: to not care about quarter to quarter profits that they 218 00:14:25,480 --> 00:14:29,400 Speaker 1: can get away with huge investments and huge losses from 219 00:14:29,400 --> 00:14:32,160 Speaker 1: time to time. But it sounds like what you guys 220 00:14:32,160 --> 00:14:35,160 Speaker 1: are saying is that the way we characterize Amazon is 221 00:14:35,160 --> 00:14:38,280 Speaker 1: a little too pat and that actually Wall Streets response 222 00:14:38,400 --> 00:14:41,400 Speaker 1: is not about some training or anything like that, but 223 00:14:41,600 --> 00:14:45,960 Speaker 1: essentially about investors just sort of understanding, like in any company, 224 00:14:46,280 --> 00:14:48,720 Speaker 1: the numbers that really matter, and that earnings aren't really it. 225 00:14:49,360 --> 00:14:52,640 Speaker 1: That's that's absolutely true. So what we have advocated in 226 00:14:52,720 --> 00:14:54,840 Speaker 1: a book as well as the article, is this notion 227 00:14:55,280 --> 00:14:59,200 Speaker 1: of strategic assets. What really matters to accompany success and 228 00:14:59,240 --> 00:15:02,960 Speaker 1: the competitive at UH is not just current quarters earnings 229 00:15:02,960 --> 00:15:06,840 Speaker 1: of profit. It's UH their strategic asset that give them 230 00:15:06,880 --> 00:15:10,640 Speaker 1: long term value in market competition. So for a company 231 00:15:10,720 --> 00:15:15,040 Speaker 1: like Amazon, what investment has delivered to them is the 232 00:15:15,120 --> 00:15:17,760 Speaker 1: growth of their strategic asset. If you think about their 233 00:15:17,800 --> 00:15:21,400 Speaker 1: market share, their expansion into more and more market territories, 234 00:15:21,920 --> 00:15:26,120 Speaker 1: that's the proof that they're growing their strategic assets very strongly. 235 00:15:26,400 --> 00:15:28,840 Speaker 1: And the investors certainly understand this. At the end of 236 00:15:28,840 --> 00:15:31,040 Speaker 1: the day, they're not just going to look at the 237 00:15:31,120 --> 00:15:34,480 Speaker 1: quotally profit or loss or Instead, they're going to pay 238 00:15:34,560 --> 00:15:38,320 Speaker 1: a lot of attention to amazon strategic assets. All the 239 00:15:38,400 --> 00:15:42,000 Speaker 1: assets have been investment, invested, deployed, and what kind of 240 00:15:42,080 --> 00:15:45,920 Speaker 1: value has been created by these assets. To interject the 241 00:15:46,000 --> 00:15:49,800 Speaker 1: cautionary note here, we are speaking about Amazon and Tesla, 242 00:15:50,240 --> 00:15:54,120 Speaker 1: and investors definitely understand these companies because they are led 243 00:15:54,120 --> 00:16:00,320 Speaker 1: by extremely articulate and charismatic leaders and the men search 244 00:16:00,560 --> 00:16:04,440 Speaker 1: is clear. But there are thousands of companies out there 245 00:16:04,720 --> 00:16:11,040 Speaker 1: without Jeff Bezos and other charismatic leaders that their message 246 00:16:11,080 --> 00:16:15,000 Speaker 1: is not well understood and investors don't see the truth. 247 00:16:15,080 --> 00:16:18,480 Speaker 1: They are still relying on the reported numbers, which are 248 00:16:18,680 --> 00:16:22,680 Speaker 1: misleading them. So that's why I think our message is 249 00:16:22,720 --> 00:16:27,080 Speaker 1: so relevant today. If investors knew everything, we would even 250 00:16:27,080 --> 00:16:31,240 Speaker 1: write this article now, but they are not. It's only 251 00:16:31,280 --> 00:16:36,440 Speaker 1: for a few companies with those very effective CEOs or 252 00:16:36,480 --> 00:16:40,080 Speaker 1: CFOs that can spread this message. The other thing I'm 253 00:16:40,120 --> 00:16:44,800 Speaker 1: wondering is your findings. You know about this perfect earnings 254 00:16:45,000 --> 00:16:47,960 Speaker 1: estimator and the fact that it wouldn't be much of 255 00:16:48,000 --> 00:16:51,000 Speaker 1: an edge in the market nowadays. Does that say more 256 00:16:51,080 --> 00:16:55,160 Speaker 1: about how the market is functioning than the deficiencies of 257 00:16:55,200 --> 00:16:59,000 Speaker 1: the accounting rules themselves, because one of the criticisms of 258 00:16:59,040 --> 00:17:03,320 Speaker 1: the current market is that valuations no longer matter. You know, 259 00:17:03,400 --> 00:17:07,840 Speaker 1: people aren't really investing on fundamental terms. They're just sort 260 00:17:07,880 --> 00:17:12,199 Speaker 1: of following the money and it's all momentum based. So 261 00:17:12,359 --> 00:17:15,240 Speaker 1: you're right, there a lot investing on the fundamentals or 262 00:17:15,359 --> 00:17:18,720 Speaker 1: less than a fewer and fewer people are investing on 263 00:17:18,800 --> 00:17:22,919 Speaker 1: fundamentals because it faces them. I mean, they see the 264 00:17:23,000 --> 00:17:27,400 Speaker 1: results quarter of their quotas and it's it's really not working. 265 00:17:28,000 --> 00:17:33,760 Speaker 1: What we are saying is, don't abandoned fundamental analysis. You 266 00:17:33,880 --> 00:17:37,199 Speaker 1: still have very good information out there. You're focusing on 267 00:17:37,320 --> 00:17:41,359 Speaker 1: the wrong information, but you can shift and focus on 268 00:17:41,400 --> 00:17:46,240 Speaker 1: the right information and you will be much better off. Okay, well, 269 00:17:46,240 --> 00:17:48,520 Speaker 1: you know, before we wrap up, we have to talk 270 00:17:48,560 --> 00:17:52,000 Speaker 1: about what these things are. So okay, you mentioned that, 271 00:17:52,119 --> 00:17:56,280 Speaker 1: for example, it makes sense to not he too closely 272 00:17:56,400 --> 00:18:00,600 Speaker 1: to traditional gap earnings. You also talked about the importance 273 00:18:00,640 --> 00:18:04,080 Speaker 1: of having strategic assets. But for many companies that sounds 274 00:18:04,119 --> 00:18:07,040 Speaker 1: like it would be something that you know, it's unquantitative 275 00:18:07,200 --> 00:18:10,880 Speaker 1: or something fuel based. Let's talk what are the things 276 00:18:10,920 --> 00:18:13,800 Speaker 1: in an earnings report, in anything else that we should 277 00:18:13,840 --> 00:18:17,399 Speaker 1: really be focusing on instead to start building a mental 278 00:18:17,480 --> 00:18:20,400 Speaker 1: model of what a company is worth. So I'll give 279 00:18:20,400 --> 00:18:23,920 Speaker 1: you a couple of examples. If you're talking about pharmaceutical 280 00:18:23,960 --> 00:18:27,600 Speaker 1: and biotech companies and you have a huge number of 281 00:18:27,640 --> 00:18:31,200 Speaker 1: these companies, what they earned last quarter or last year, 282 00:18:31,280 --> 00:18:36,200 Speaker 1: it's completely irrelevant to the future. What is relevant is 283 00:18:36,400 --> 00:18:41,879 Speaker 1: what's called the product pipeline, the drugs, the instruments that 284 00:18:41,920 --> 00:18:47,119 Speaker 1: they are developing. And all companies are providing very detailed 285 00:18:47,119 --> 00:18:50,080 Speaker 1: information page of the page of the page. It's not 286 00:18:50,240 --> 00:18:53,879 Speaker 1: required by accounting rules, but they are doing it on 287 00:18:54,000 --> 00:18:57,600 Speaker 1: the product pipeline. So if the company has products in 288 00:18:57,680 --> 00:19:02,560 Speaker 1: advanced stage of development, is two clinical tests, face three 289 00:19:02,600 --> 00:19:06,120 Speaker 1: clinical tests, they are close to the market, high likelihood 290 00:19:06,119 --> 00:19:09,640 Speaker 1: that new products will come out of them. This company 291 00:19:09,720 --> 00:19:12,760 Speaker 1: is at a very good stage. I would invest in 292 00:19:12,800 --> 00:19:15,560 Speaker 1: such a company. I don't care about the earnings of 293 00:19:15,560 --> 00:19:20,480 Speaker 1: such a company. Talk about my second example, Internet companies, 294 00:19:20,520 --> 00:19:27,080 Speaker 1: even insurance companies, media and entertainment. There's main strategic assets 295 00:19:27,160 --> 00:19:31,359 Speaker 1: are customers. Look at the main data. Look at how 296 00:19:31,440 --> 00:19:35,199 Speaker 1: many customers are being added every quarter. Look at the 297 00:19:35,359 --> 00:19:39,320 Speaker 1: churn rate, which most people are not aware of. Churn 298 00:19:39,440 --> 00:19:43,879 Speaker 1: rate meaning the center of customers they lose every quarter. 299 00:19:44,560 --> 00:19:49,200 Speaker 1: That's what indicates the future, not the current earnings last 300 00:19:49,240 --> 00:19:55,480 Speaker 1: earnings that they report. Basically, for every industry you have 301 00:19:55,720 --> 00:20:02,119 Speaker 1: those fundamental strategic asset that create the you. For most companies, 302 00:20:02,440 --> 00:20:06,000 Speaker 1: this information is given and the focus should be on 303 00:20:06,080 --> 00:20:10,320 Speaker 1: the performance of these assets, the potential of these assets. 304 00:20:10,320 --> 00:20:13,000 Speaker 1: Just just to play Devil's advocate, though, you talk about 305 00:20:13,119 --> 00:20:17,399 Speaker 1: companies with drugs and stage two trials, But even then, 306 00:20:17,560 --> 00:20:20,880 Speaker 1: to value that drug, don't you still have to come 307 00:20:20,960 --> 00:20:23,680 Speaker 1: up with some model of how big the addressable market 308 00:20:23,760 --> 00:20:26,800 Speaker 1: could be how much profit that drug is going to 309 00:20:26,880 --> 00:20:29,600 Speaker 1: I mean, doesn't it still just come back to that 310 00:20:29,680 --> 00:20:31,919 Speaker 1: being a tool to come up with some estimate of 311 00:20:32,240 --> 00:20:35,480 Speaker 1: future earnings. Yes, you can do it and actually think 312 00:20:35,560 --> 00:20:38,879 Speaker 1: and I developed such a model because they are they 313 00:20:38,920 --> 00:20:42,600 Speaker 1: are quite reliable data on the likelihood of drugs in 314 00:20:42,720 --> 00:20:45,919 Speaker 1: phase to get into the market, and then you have 315 00:20:46,119 --> 00:20:49,760 Speaker 1: the market size for the drug. So ultimately you can 316 00:20:49,880 --> 00:20:54,840 Speaker 1: come up with prediction of revenues from the drug. But 317 00:20:54,960 --> 00:20:58,359 Speaker 1: the focus of analysis is not trying to predict just 318 00:20:58,520 --> 00:21:02,359 Speaker 1: the revenues, but looking at the fundamentals what creates the 319 00:21:02,520 --> 00:21:07,800 Speaker 1: value in all tasks. With this new mesthology, we actually 320 00:21:07,800 --> 00:21:11,840 Speaker 1: have seen evidence showing that this different way of evaluating 321 00:21:12,040 --> 00:21:16,680 Speaker 1: from suitable companies fundamental actually produces information signals that lead 322 00:21:17,200 --> 00:21:20,800 Speaker 1: changing their market value. In other words, um, we can 323 00:21:20,840 --> 00:21:24,240 Speaker 1: actually see the change in the value of their product 324 00:21:24,320 --> 00:21:30,720 Speaker 1: pipeline before investors actually realize scenes are becoming different. Well, 325 00:21:30,840 --> 00:21:33,879 Speaker 1: I'm sure we could talk about accounting all day, but 326 00:21:34,000 --> 00:21:36,280 Speaker 1: we have to leave it there. That was baruque love 327 00:21:36,440 --> 00:21:39,040 Speaker 1: and thank Goog, Thank you so much for joining us. 328 00:21:39,560 --> 00:21:53,159 Speaker 1: Thank you, thank you so Joe, does that make you 329 00:21:53,200 --> 00:21:56,679 Speaker 1: feel better or worse? About your previous career as a 330 00:21:56,720 --> 00:21:59,960 Speaker 1: financial analyst. Well, you know, I'm no longer a finance 331 00:22:00,040 --> 00:22:01,920 Speaker 1: chill analyst, So I guess it makes me feel good 332 00:22:01,960 --> 00:22:05,080 Speaker 1: that I left that, you know, had I had. I 333 00:22:05,160 --> 00:22:09,520 Speaker 1: just stuck to trying to estimate EPs and all that stuff. 334 00:22:09,920 --> 00:22:13,200 Speaker 1: But uh no, in all seriousness, it is really interesting. 335 00:22:13,320 --> 00:22:15,919 Speaker 1: I mean, one of the things I wonder is, like, 336 00:22:16,320 --> 00:22:20,840 Speaker 1: to what extent do investors, you know, already sort of 337 00:22:20,920 --> 00:22:24,800 Speaker 1: let these other factors determined I mean, the value of companies. 338 00:22:24,880 --> 00:22:28,320 Speaker 1: It's not like all companies have the same PE ratio, 339 00:22:28,480 --> 00:22:32,160 Speaker 1: the same port forward pe ratio. To some extent, it's 340 00:22:32,200 --> 00:22:36,000 Speaker 1: pretty clear that things like network effects or an internal 341 00:22:36,040 --> 00:22:39,359 Speaker 1: company culture that allows it to produce great drugs you 342 00:22:39,400 --> 00:22:42,720 Speaker 1: would imagine, is already being reflected in a lot of 343 00:22:42,760 --> 00:22:45,720 Speaker 1: people thinking about these companies, right, And you do have 344 00:22:45,760 --> 00:22:48,800 Speaker 1: some pretty big companies out there that are highly valued 345 00:22:48,880 --> 00:22:55,320 Speaker 1: that haven't necessarily had that successful um earnings quarters. I 346 00:22:55,400 --> 00:22:58,439 Speaker 1: guess I think I think what it comes down to 347 00:22:58,520 --> 00:23:02,680 Speaker 1: for me, I think our guests they've identified a problem 348 00:23:02,760 --> 00:23:06,359 Speaker 1: which definitely exists. I think you can say the accounting rules, 349 00:23:06,720 --> 00:23:09,479 Speaker 1: for sure, are not well equipped to deal with the 350 00:23:09,520 --> 00:23:14,160 Speaker 1: realities of an economy that's increasingly about research and development 351 00:23:14,280 --> 00:23:18,560 Speaker 1: and you know, brand value and information technology as opposed 352 00:23:18,600 --> 00:23:22,840 Speaker 1: to um, you know, machinery and manufacturing. I'm not sure 353 00:23:23,440 --> 00:23:27,360 Speaker 1: about the solution, because again, it's one thing to say, oh, 354 00:23:27,840 --> 00:23:31,919 Speaker 1: investors should consider these strategic assets of a company, but 355 00:23:32,119 --> 00:23:34,359 Speaker 1: at some point you do want to see those strategic 356 00:23:34,400 --> 00:23:38,560 Speaker 1: assets converted into some sort of revenue, right, And that's 357 00:23:38,600 --> 00:23:41,320 Speaker 1: sort of like, you know, it seems like a theory 358 00:23:41,359 --> 00:23:44,200 Speaker 1: you should be able to square the circle and say, Okay, 359 00:23:44,320 --> 00:23:46,800 Speaker 1: it's great to have these strategic assets, but you know, 360 00:23:46,840 --> 00:23:50,119 Speaker 1: a strategic asset is only so good unless it produces 361 00:23:50,920 --> 00:23:54,520 Speaker 1: revenue and income. But what I think is valuable here 362 00:23:54,560 --> 00:23:59,359 Speaker 1: to me is like maybe we there's still it's like 363 00:23:59,400 --> 00:24:02,640 Speaker 1: we have so many tuitive understanding that for all companies, 364 00:24:02,680 --> 00:24:05,560 Speaker 1: whether it's an Amazon on one end, or whether it's 365 00:24:05,560 --> 00:24:09,040 Speaker 1: a more standard industrial like a Honeywell or a g 366 00:24:09,200 --> 00:24:12,119 Speaker 1: E on another end, that there's this whole spectrum of 367 00:24:12,160 --> 00:24:16,560 Speaker 1: business models, and we sort of have this intuitive understanding 368 00:24:16,640 --> 00:24:19,199 Speaker 1: that the sort of network effects or the customers are 369 00:24:19,200 --> 00:24:22,560 Speaker 1: the attention of some companies matters a lot more for others. 370 00:24:22,560 --> 00:24:26,640 Speaker 1: But maybe we still overrate the importance of a traditional 371 00:24:26,800 --> 00:24:31,359 Speaker 1: earnings company for for traditional stock, even when it's not 372 00:24:31,440 --> 00:24:34,760 Speaker 1: particularly appropriate, and that we have to sort of adjust 373 00:24:34,840 --> 00:24:38,360 Speaker 1: our dial to recognize that it's not the same thing, 374 00:24:38,600 --> 00:24:40,760 Speaker 1: looking at a sort of P n L statement for 375 00:24:40,800 --> 00:24:44,240 Speaker 1: a traditional industrial versus a P and L statement for 376 00:24:44,640 --> 00:24:48,400 Speaker 1: an Amazon or a Facebook. Yeah, I think that's right 377 00:24:48,640 --> 00:24:51,720 Speaker 1: in any case. It's clearly a complicated topic, but something 378 00:24:51,840 --> 00:24:54,840 Speaker 1: we can all keep in mind as earning season rolls on. 379 00:24:55,080 --> 00:24:57,359 Speaker 1: And I'm very excited to read their book. I have 380 00:24:57,440 --> 00:25:00,439 Speaker 1: it in front of me, The End of Account and 381 00:25:00,480 --> 00:25:03,560 Speaker 1: the Path Forward for Investors and Managers by Baruke Lev 382 00:25:03,680 --> 00:25:07,600 Speaker 1: and Fengu So thanks to them for joining us, and 383 00:25:07,920 --> 00:25:11,639 Speaker 1: maybe we'll I'll read this and I'll get some more insight. 384 00:25:12,160 --> 00:25:15,399 Speaker 1: All right, This has been another edition of the All 385 00:25:15,440 --> 00:25:18,320 Speaker 1: Thoughts Podcast. I'm Tracy Alloway. You can follow me on 386 00:25:18,359 --> 00:25:21,399 Speaker 1: Twitter at Tracy Alloway. And I'm Joe Wisenthal and you 387 00:25:21,440 --> 00:25:24,240 Speaker 1: can follow me on Twitter at The Stalwart. And I 388 00:25:24,359 --> 00:25:28,080 Speaker 1: want to thank our producer Sarah Patterson, who's on Twitter 389 00:25:28,200 --> 00:25:31,080 Speaker 1: at Sarah patt With two Teas. Thanks for listening.