1 00:00:11,280 --> 00:00:15,120 Speaker 1: Hello, and welcome to another episode of the All Thoughts Podcast. 2 00:00:15,240 --> 00:00:19,480 Speaker 1: I'm Tracy Alloway and I'm Joe Wisenthal. So, Joe, when 3 00:00:19,520 --> 00:00:25,040 Speaker 1: you think about value investing, what what springs to mind? Um? 4 00:00:25,120 --> 00:00:29,120 Speaker 1: I guess probably immediately the image of Warren Buffett floats 5 00:00:29,120 --> 00:00:31,000 Speaker 1: into my head as soon as I hear that term, 6 00:00:31,160 --> 00:00:35,040 Speaker 1: or maybe that big um Benjamin Graham book that I 7 00:00:35,080 --> 00:00:37,600 Speaker 1: bought when I was like early on in my career 8 00:00:37,640 --> 00:00:39,120 Speaker 1: and never read. But it's like one of the most 9 00:00:39,120 --> 00:00:42,239 Speaker 1: famous investing books about how to invest, like how they 10 00:00:42,280 --> 00:00:45,159 Speaker 1: did back when they bought like bonds from Brooklyn Railways 11 00:00:45,200 --> 00:00:48,400 Speaker 1: and stuff like that. At least you're honest about it. 12 00:00:48,640 --> 00:00:51,200 Speaker 1: But I think for most people, it's definitely that image 13 00:00:51,200 --> 00:00:55,320 Speaker 1: of Warren Buffett and someone sort of seeking out these 14 00:00:55,440 --> 00:00:58,600 Speaker 1: undervalued stocks in the market that are going to generate 15 00:00:58,680 --> 00:01:01,880 Speaker 1: longer term gains and making loads of money from it. 16 00:01:01,960 --> 00:01:06,120 Speaker 1: That's sort of the classic value investing paradigm. Yeah, And 17 00:01:06,160 --> 00:01:10,080 Speaker 1: I think like when I first became aware of how 18 00:01:10,120 --> 00:01:12,800 Speaker 1: the world of investing worked, I sort of thought that 19 00:01:12,920 --> 00:01:15,360 Speaker 1: was essentially the essence of it, that you're supposed to 20 00:01:15,400 --> 00:01:18,640 Speaker 1: find cheap stocks and look at the stocks that had 21 00:01:18,640 --> 00:01:21,720 Speaker 1: low pe ratios and low price to book ratios and 22 00:01:21,760 --> 00:01:23,760 Speaker 1: if there was a good one that had some nice 23 00:01:23,800 --> 00:01:26,200 Speaker 1: low ratios, then those were the stocks to buy. And 24 00:01:26,240 --> 00:01:28,959 Speaker 1: that's basically what investing is. And I know there are 25 00:01:28,959 --> 00:01:31,120 Speaker 1: a lot of people who are still adherance of that approach, 26 00:01:31,400 --> 00:01:33,120 Speaker 1: but over the years, I've learned that there's sort of 27 00:01:33,360 --> 00:01:38,200 Speaker 1: multiple approaches to doing well in the stock market. Yes, indeed, 28 00:01:38,200 --> 00:01:41,280 Speaker 1: and the big headwind I would say for value investing 29 00:01:41,400 --> 00:01:44,080 Speaker 1: over the past uh, well, it's been more than a 30 00:01:44,120 --> 00:01:49,040 Speaker 1: decade actually, but basically since the start of the financial 31 00:01:49,080 --> 00:01:53,960 Speaker 1: crisis sort of two thousand seven, value investing has massively, 32 00:01:54,320 --> 00:01:58,320 Speaker 1: massively underperformed a lot of other investing styles. And this 33 00:01:58,400 --> 00:02:00,440 Speaker 1: means that a bunch of people have been watching their 34 00:02:00,440 --> 00:02:04,240 Speaker 1: heads trying to figure out exactly why this is happening. Yeah, 35 00:02:04,240 --> 00:02:07,880 Speaker 1: there's a lot of consternation among people for whom they 36 00:02:07,880 --> 00:02:11,080 Speaker 1: look at the data. And historically it says if you 37 00:02:11,160 --> 00:02:13,760 Speaker 1: buy lots of companies, a basket of companies with the 38 00:02:13,800 --> 00:02:16,639 Speaker 1: low price to book ratio or low PE ratio, they 39 00:02:16,680 --> 00:02:21,160 Speaker 1: should eventually outperform um. But they haven't. And that's sort 40 00:02:21,200 --> 00:02:23,640 Speaker 1: of been one of the main stories post crisis, is 41 00:02:23,639 --> 00:02:28,320 Speaker 1: this persistent underperformance of the so called value factor, and 42 00:02:28,360 --> 00:02:31,640 Speaker 1: people keep trying to call the turn. They now the 43 00:02:31,639 --> 00:02:34,560 Speaker 1: fetters raising race. Okay, the value factors gonna perform. Oh, 44 00:02:34,600 --> 00:02:36,799 Speaker 1: we're going into a bit of a downturn. This is 45 00:02:36,840 --> 00:02:40,720 Speaker 1: the moment. And it keeps eluding the adherence of this view, 46 00:02:40,880 --> 00:02:43,520 Speaker 1: and you have some people saying value is dead or 47 00:02:43,560 --> 00:02:46,600 Speaker 1: this style is never going to work again. But of 48 00:02:46,639 --> 00:02:49,480 Speaker 1: course you have people holding out that eventually this approach 49 00:02:49,480 --> 00:02:53,120 Speaker 1: will come back and vogue. Yeah, exactly, and you sort 50 00:02:53,120 --> 00:02:55,120 Speaker 1: of alluded to it just then. But there are all 51 00:02:55,160 --> 00:02:58,440 Speaker 1: these theories about why exactly value has been underperforming. The 52 00:02:58,440 --> 00:03:01,600 Speaker 1: big one, of course, is central banks and low interest rates. 53 00:03:01,760 --> 00:03:06,480 Speaker 1: But one explanation, uh that doesn't get as much attention 54 00:03:06,680 --> 00:03:10,880 Speaker 1: has to do with technology. And this is a really 55 00:03:10,919 --> 00:03:13,560 Speaker 1: interesting one I think. Um, you know, some analysts have 56 00:03:13,560 --> 00:03:17,000 Speaker 1: talked about it a bit before, but the notion that 57 00:03:17,160 --> 00:03:22,520 Speaker 1: big technological discoveries or turns can basically lead to under 58 00:03:22,520 --> 00:03:26,040 Speaker 1: performance and value is one that I think is worth exploring, 59 00:03:26,639 --> 00:03:28,960 Speaker 1: right And you know, it's interesting because obviously, I think 60 00:03:28,960 --> 00:03:30,799 Speaker 1: a lot of people know that the best stocks of 61 00:03:30,840 --> 00:03:34,800 Speaker 1: the last several years have been this these high flying 62 00:03:34,880 --> 00:03:38,839 Speaker 1: tech stocks like Amazon or Facebook or whatever, Netflix, which 63 00:03:38,840 --> 00:03:42,760 Speaker 1: are nobody's idea. Very few people would characterize them as 64 00:03:43,160 --> 00:03:46,920 Speaker 1: value stocks, at least under the traditional notion. But I guess, uh, 65 00:03:46,960 --> 00:03:49,119 Speaker 1: and we're going to talk about this on today's episode, 66 00:03:49,400 --> 00:03:52,200 Speaker 1: that this isn't that rare, that there are these periods 67 00:03:52,400 --> 00:03:54,680 Speaker 1: of times when there can be a companies on the 68 00:03:54,720 --> 00:04:00,640 Speaker 1: vanguard of a new technology, trading at extraordinary multiples, outperforming value, 69 00:04:00,680 --> 00:04:03,760 Speaker 1: but it doesn't last forever. This isn't the first time, 70 00:04:03,800 --> 00:04:07,360 Speaker 1: I guess that we've seen companies like Amazon and Netflix 71 00:04:08,800 --> 00:04:13,280 Speaker 1: help expensive stocks be the big winners. Yeah, exactly, So 72 00:04:13,400 --> 00:04:15,240 Speaker 1: I guess, without further ado, I should bring on the 73 00:04:15,280 --> 00:04:19,840 Speaker 1: guest for the episode. It is Chris Meredith. He's co 74 00:04:20,040 --> 00:04:23,200 Speaker 1: c I O over at O'Shaughnessy Asset Management and also 75 00:04:23,279 --> 00:04:27,080 Speaker 1: a visiting lecture at Cornell University. Chris, thanks so much 76 00:04:27,120 --> 00:04:30,320 Speaker 1: for coming on. Thank you for having me. So I 77 00:04:30,320 --> 00:04:32,600 Speaker 1: should just mention the reason we're having you on is 78 00:04:32,880 --> 00:04:37,680 Speaker 1: actually a suggestion from your your co researcher on a 79 00:04:37,720 --> 00:04:41,920 Speaker 1: recent paper, Mr Jamie Catherwood, who was of course a 80 00:04:42,040 --> 00:04:44,680 Speaker 1: previous odd lots guests. Lots of people will know him 81 00:04:44,680 --> 00:04:48,880 Speaker 1: as the finance history guy. He helped you look into 82 00:04:49,200 --> 00:04:53,600 Speaker 1: whether or not there are historic parallels for under performance 83 00:04:53,640 --> 00:04:57,279 Speaker 1: in value investing. Just to step back initially, can I 84 00:04:57,320 --> 00:05:00,919 Speaker 1: ask why you decided to to go on the hunt 85 00:05:01,000 --> 00:05:05,719 Speaker 1: for those historic parallels. Well, obviously it's borne out of 86 00:05:05,720 --> 00:05:08,640 Speaker 1: what you were talking about earlier, where value has underperformed. 87 00:05:08,760 --> 00:05:11,800 Speaker 1: Value is one of the bedrock principles at O'shaughnessysset Management. 88 00:05:12,160 --> 00:05:14,960 Speaker 1: And obviously it's been a difficult, you know, time since 89 00:05:14,960 --> 00:05:17,240 Speaker 1: the beginning of two thousand seven. To set it in context, 90 00:05:17,760 --> 00:05:19,640 Speaker 1: some of the style benchmarks that are used in the 91 00:05:19,720 --> 00:05:23,120 Speaker 1: large cap like Russell one thousand, value versus growth over 92 00:05:23,160 --> 00:05:24,960 Speaker 1: that time period from the beginning in two thousand seven 93 00:05:24,960 --> 00:05:27,400 Speaker 1: to the middle of it's a it's a return gap 94 00:05:27,400 --> 00:05:30,200 Speaker 1: of about thirty six percent, which is a tremendous difference, 95 00:05:30,200 --> 00:05:32,000 Speaker 1: and over the last twenty four months it's an additional 96 00:05:33,279 --> 00:05:37,520 Speaker 1: So that's obviously where clients, allocators, financial advisors, they're all 97 00:05:37,520 --> 00:05:40,400 Speaker 1: looking to us and trying to understand what's going on. 98 00:05:40,480 --> 00:05:43,920 Speaker 1: Anybody who has a value bias against a core benchmark 99 00:05:44,080 --> 00:05:46,640 Speaker 1: or growth managers that are putting value governors on it, 100 00:05:46,640 --> 00:05:48,960 Speaker 1: they're all feeling this as a long term headwind in 101 00:05:49,000 --> 00:05:52,320 Speaker 1: their investment styles and strategies. And so we started taking 102 00:05:52,320 --> 00:05:54,279 Speaker 1: a look, and what we had seen was there's a 103 00:05:54,360 --> 00:05:58,760 Speaker 1: lot of people in industry that are using data I 104 00:05:58,800 --> 00:06:00,760 Speaker 1: call it like a short form aided dump where they 105 00:06:00,800 --> 00:06:02,880 Speaker 1: just take like the Fama French series and they put 106 00:06:02,920 --> 00:06:04,440 Speaker 1: out there and they're saying, look, this is this is 107 00:06:04,480 --> 00:06:07,560 Speaker 1: the worst it's ever been, so it must be broken, right, UM. 108 00:06:07,640 --> 00:06:09,920 Speaker 1: And there's a lot of people that are just just 109 00:06:09,920 --> 00:06:11,160 Speaker 1: just to back up when they say this is the 110 00:06:11,160 --> 00:06:13,360 Speaker 1: worst that's ever been, they say, this is the worst 111 00:06:13,720 --> 00:06:16,760 Speaker 1: under performance of the value factor relatively the market. And 112 00:06:16,960 --> 00:06:18,719 Speaker 1: you know, a lot of times they're dealing with shorter 113 00:06:18,800 --> 00:06:21,839 Speaker 1: data series than than you know, than we have available 114 00:06:21,839 --> 00:06:24,320 Speaker 1: at O'Shaughnessy because we've invested in a research platform that 115 00:06:24,360 --> 00:06:26,960 Speaker 1: lets us test all the way back to ninety six 116 00:06:27,000 --> 00:06:29,719 Speaker 1: and we've spent you know, millions of dollars and million 117 00:06:29,960 --> 00:06:31,800 Speaker 1: over ten years in order to get this platform and 118 00:06:31,800 --> 00:06:34,440 Speaker 1: allowing us to do research. UH. And one of the 119 00:06:34,440 --> 00:06:36,159 Speaker 1: things that we were looking at was saying, okay, let's 120 00:06:36,200 --> 00:06:38,240 Speaker 1: let's use our platform and try to figure out, you know, 121 00:06:38,240 --> 00:06:41,040 Speaker 1: if we've seen a period like this before. UH. And 122 00:06:41,120 --> 00:06:43,200 Speaker 1: you know, we had built out a research data set 123 00:06:43,200 --> 00:06:47,480 Speaker 1: proprietary to osam O'Shaughnessy that we call Deep History, that 124 00:06:47,520 --> 00:06:50,320 Speaker 1: where we took all the Moody's financial statements and we 125 00:06:50,320 --> 00:06:52,240 Speaker 1: we had to actually team overseas type those up and 126 00:06:52,240 --> 00:06:53,880 Speaker 1: put them into our platform. So we were able to 127 00:06:53,880 --> 00:06:56,080 Speaker 1: look at things like net income and sales, and we 128 00:06:56,160 --> 00:06:58,559 Speaker 1: found that there's another period of value under performance similar 129 00:06:58,560 --> 00:07:03,839 Speaker 1: to this one back in nineteen And what's interesting is, 130 00:07:03,920 --> 00:07:06,120 Speaker 1: you know, you start you start looking at those periods, 131 00:07:06,320 --> 00:07:08,039 Speaker 1: um you know, and I've I've heard people say, you know, 132 00:07:08,520 --> 00:07:10,520 Speaker 1: what would that time period have anything to do with today? 133 00:07:10,520 --> 00:07:13,680 Speaker 1: It's obviously it's incredibly different, um And and there are 134 00:07:13,680 --> 00:07:17,000 Speaker 1: differences obviously, but there's also a ton of similarities. And 135 00:07:17,280 --> 00:07:19,200 Speaker 1: when we started looking at it, obviously with you know 136 00:07:19,200 --> 00:07:22,840 Speaker 1: what we see with recession depression that happened, interest rates 137 00:07:22,840 --> 00:07:25,960 Speaker 1: falling to zero and that time frame, but also that 138 00:07:26,080 --> 00:07:29,880 Speaker 1: the the increase of technological shift of that time frame 139 00:07:29,960 --> 00:07:33,200 Speaker 1: is comparable to today. And what really cemented it and 140 00:07:33,200 --> 00:07:35,120 Speaker 1: and and made it come home was when we we 141 00:07:35,160 --> 00:07:38,280 Speaker 1: started first we started looking at what companies were outperforming 142 00:07:38,280 --> 00:07:40,480 Speaker 1: on the growth side versus the value side, and that 143 00:07:40,560 --> 00:07:43,360 Speaker 1: time frame and you you you nailed it. Where today 144 00:07:43,400 --> 00:07:45,480 Speaker 1: it is technology stocks on the growth side that are 145 00:07:45,800 --> 00:07:47,640 Speaker 1: the fang stocks, let's just you know, sum it up 146 00:07:47,640 --> 00:07:49,720 Speaker 1: that way. And on the on the value side, it's 147 00:07:49,720 --> 00:07:52,280 Speaker 1: financial stocks. Right, those have been having a structural headwind 148 00:07:52,280 --> 00:07:56,120 Speaker 1: obviously since two thousand seven. Financial stocks wind up in 149 00:07:56,120 --> 00:07:58,560 Speaker 1: the value ledger, right, So that's part of the split 150 00:07:58,600 --> 00:08:00,960 Speaker 1: there is technology is doing great. Financi stockstone entally that 151 00:08:01,040 --> 00:08:04,920 Speaker 1: time frame forty one, it was manufacturing stocks that were 152 00:08:04,920 --> 00:08:08,320 Speaker 1: the tech stocks of the day and versus utilities and 153 00:08:08,600 --> 00:08:11,200 Speaker 1: which I include railroads and steam railroads and utilities that 154 00:08:11,240 --> 00:08:14,560 Speaker 1: were essentially the ones dragging. And the interesting part was 155 00:08:14,720 --> 00:08:17,400 Speaker 1: what we found was we were doing research and we 156 00:08:17,400 --> 00:08:19,280 Speaker 1: were reading and there was one book that just that 157 00:08:19,400 --> 00:08:21,400 Speaker 1: just cemented and put it home, and it was Carlotta 158 00:08:21,400 --> 00:08:25,760 Speaker 1: Perez's Technological Revolutions and Financial Capital, where she was talking 159 00:08:25,800 --> 00:08:29,400 Speaker 1: through long term economic waves called that short form, they 160 00:08:29,400 --> 00:08:32,920 Speaker 1: call him technological revolutions, and they've identified five of these. 161 00:08:32,960 --> 00:08:35,439 Speaker 1: Historically they're able to identify because the timing of market 162 00:08:35,440 --> 00:08:39,280 Speaker 1: crashes that come along with them. But mainly, what what 163 00:08:39,400 --> 00:08:41,760 Speaker 1: it summed up was that the stocks that we're winning 164 00:08:41,760 --> 00:08:44,640 Speaker 1: in that time period, Uh can be automobile stocks, so 165 00:08:44,679 --> 00:08:47,280 Speaker 1: you're talking about GM. Ford was a privately list of stock, 166 00:08:47,320 --> 00:08:49,000 Speaker 1: but GM was the big one of the of the 167 00:08:49,280 --> 00:08:52,560 Speaker 1: publicly listed at that time frame. And oil stocks like 168 00:08:52,559 --> 00:08:56,200 Speaker 1: standard Oil, which we're supplying gasoline, and then retail stocks 169 00:08:56,240 --> 00:08:58,199 Speaker 1: like Sears and will Worth in manufacturing and all those 170 00:08:58,240 --> 00:09:01,080 Speaker 1: are bundled together with this id you have clusters of 171 00:09:01,080 --> 00:09:05,480 Speaker 1: technological innovations that changed the socioeconomic paradigm of how people 172 00:09:05,480 --> 00:09:07,760 Speaker 1: deploy their capital. And the way to think of that 173 00:09:07,960 --> 00:09:11,000 Speaker 1: is that, you know, back in the nineteen tens, you know, 174 00:09:11,080 --> 00:09:13,599 Speaker 1: people were getting around by the steam railroad and that 175 00:09:13,679 --> 00:09:14,760 Speaker 1: was how they got around, and then it was like 176 00:09:14,800 --> 00:09:16,319 Speaker 1: bicycles for the rest of it, and they hadn't figured 177 00:09:16,320 --> 00:09:19,040 Speaker 1: out that last mile, right. Henry Ford invented the model 178 00:09:19,040 --> 00:09:22,160 Speaker 1: Tea and in particular this idea of mass manufacturing and 179 00:09:22,320 --> 00:09:24,920 Speaker 1: the idea that then automobiles went from zero to zero 180 00:09:24,960 --> 00:09:27,280 Speaker 1: point eight per household in the US, and all of 181 00:09:27,320 --> 00:09:28,960 Speaker 1: a sudden there was this just massive change of how 182 00:09:29,000 --> 00:09:31,920 Speaker 1: everybody got around the country. Was our c A was 183 00:09:31,960 --> 00:09:35,520 Speaker 1: like another like massive stock market winner, the Radio Company. 184 00:09:35,559 --> 00:09:39,040 Speaker 1: And I sort of like when I've read about the twenties. 185 00:09:39,080 --> 00:09:42,079 Speaker 1: I always see like it always feels like the explosion 186 00:09:42,120 --> 00:09:44,600 Speaker 1: of radio is probably similar to the internet today. Was 187 00:09:44,640 --> 00:09:45,920 Speaker 1: that one of the ones that was sort of in 188 00:09:45,920 --> 00:09:48,720 Speaker 1: the growth factor in those years. Radio is another another 189 00:09:48,760 --> 00:09:51,240 Speaker 1: great example of that and the idea of mass manufacturing 190 00:09:51,240 --> 00:09:54,720 Speaker 1: of radios but entertainment as well. But in particular, what's 191 00:09:54,720 --> 00:09:59,160 Speaker 1: interesting is this idea of mass manufacturing led to things 192 00:09:59,200 --> 00:10:01,880 Speaker 1: like Nibisco National Biscuit back in the day, which started 193 00:10:01,880 --> 00:10:04,320 Speaker 1: mass producing food and sending those out with which led 194 00:10:04,360 --> 00:10:09,160 Speaker 1: to national brands, mass culture, and then advertising, which led 195 00:10:09,200 --> 00:10:11,480 Speaker 1: to the advent of radio and entertainments and medium for 196 00:10:11,520 --> 00:10:13,920 Speaker 1: delivering that as well. So that's again it's part of 197 00:10:13,920 --> 00:10:17,400 Speaker 1: that pocket, that cluster of innovation and which again just 198 00:10:17,520 --> 00:10:22,640 Speaker 1: radically changed how people were basically just spending their money. So, 199 00:10:22,920 --> 00:10:28,520 Speaker 1: Chris Uh, you argue that innovation from technological revolution basically 200 00:10:28,600 --> 00:10:31,400 Speaker 1: changes societal behavior in a bunch of different ways, and 201 00:10:31,440 --> 00:10:34,760 Speaker 1: that impacts business and the economy in a bunch of 202 00:10:34,800 --> 00:10:37,319 Speaker 1: different ways. Could you maybe dig in a little bit 203 00:10:37,360 --> 00:10:42,120 Speaker 1: more into exactly how it impacts value investing, Like, what 204 00:10:42,200 --> 00:10:44,840 Speaker 1: was the shift that we would have seen in the 205 00:10:44,920 --> 00:10:48,000 Speaker 1: time period that you just described. Yeah, so let's let's 206 00:10:48,000 --> 00:10:49,800 Speaker 1: back up and talk about value investing a little bit 207 00:10:49,800 --> 00:10:53,000 Speaker 1: and how the value versus growth stocks and what we've 208 00:10:53,000 --> 00:10:55,920 Speaker 1: seen at O'Shaughnessy with our research. We did a research 209 00:10:55,960 --> 00:10:59,440 Speaker 1: paper about eighteen months agoll Ago called Factors from Scratch, 210 00:11:00,000 --> 00:11:02,320 Speaker 1: where we dug into the mechanics of value investing. And 211 00:11:02,320 --> 00:11:04,600 Speaker 1: the way that it works is that, um you get 212 00:11:04,600 --> 00:11:06,960 Speaker 1: compensated as an investor through a couple of avenues. One 213 00:11:07,000 --> 00:11:08,240 Speaker 1: if you think of it as you buy a stock 214 00:11:08,240 --> 00:11:10,480 Speaker 1: and it's got a a pe of ten. As a 215 00:11:10,600 --> 00:11:12,600 Speaker 1: value investor, it's either going to have it where it 216 00:11:12,679 --> 00:11:14,560 Speaker 1: maintains the same earnings and it and it rerates to 217 00:11:14,600 --> 00:11:16,560 Speaker 1: like a higher multiple of a PEU fifteen, which gives 218 00:11:16,559 --> 00:11:18,960 Speaker 1: you get a fifty percent return, or the earnings are 219 00:11:18,960 --> 00:11:21,280 Speaker 1: going to grow in the multiple stays the same and 220 00:11:21,320 --> 00:11:24,160 Speaker 1: you get you know, you get compensated. That way, we 221 00:11:24,280 --> 00:11:26,720 Speaker 1: dug in and built a framework to analyze growth stocks 222 00:11:26,840 --> 00:11:28,839 Speaker 1: versus value stocks, and what happens is value stocks on 223 00:11:28,920 --> 00:11:32,840 Speaker 1: average actually see some short term call it flatness to 224 00:11:32,880 --> 00:11:35,720 Speaker 1: decline and earnings, but then they re rate over time period, right, 225 00:11:35,760 --> 00:11:38,320 Speaker 1: but there's a stabilization where they they decline a little bit, 226 00:11:38,360 --> 00:11:41,000 Speaker 1: but then come back to normal growth levels, right, and 227 00:11:41,040 --> 00:11:43,040 Speaker 1: growth stocks have it where there's this price for these 228 00:11:43,080 --> 00:11:46,760 Speaker 1: incredible future earnings um that they tend to not reach, right. 229 00:11:46,800 --> 00:11:49,120 Speaker 1: And all this is on average over to long time 230 00:11:49,120 --> 00:11:52,440 Speaker 1: periods across you know, thousands millions of stocks that we've 231 00:11:52,440 --> 00:11:55,320 Speaker 1: been looking at historically over our millions over different time periods. 232 00:11:55,400 --> 00:11:58,480 Speaker 1: Right now, what we see is in these periods where 233 00:11:58,480 --> 00:12:01,520 Speaker 1: growth is outperforming value, what happens is the growth stocks 234 00:12:01,520 --> 00:12:03,880 Speaker 1: actually live up to their potential. If you think about 235 00:12:03,920 --> 00:12:07,360 Speaker 1: Amazon right now, Amazon had ten billion, you're talking about 236 00:12:07,360 --> 00:12:10,080 Speaker 1: it had ten billion in net income. Right ten years ago, 237 00:12:10,320 --> 00:12:12,959 Speaker 1: the company was priced about thirty billion dollars, so it 238 00:12:13,000 --> 00:12:14,840 Speaker 1: had a pe of on a four ten year basis 239 00:12:14,880 --> 00:12:17,360 Speaker 1: of about three. Right, So you're saying, would somebody argue 240 00:12:17,360 --> 00:12:20,199 Speaker 1: Amazon's value stock you could argue on a ten year basis, 241 00:12:20,320 --> 00:12:22,440 Speaker 1: you know, Amazon lived up to its value, right. And 242 00:12:22,480 --> 00:12:27,959 Speaker 1: I remember, like, even which is forever ago, people like, oh, 243 00:12:28,120 --> 00:12:30,760 Speaker 1: this's crazy what people are paying for Amazon. And then 244 00:12:30,800 --> 00:12:33,440 Speaker 1: you look now it's like, not only was that not crazy, 245 00:12:33,520 --> 00:12:35,600 Speaker 1: that was cheap based on what the income did over 246 00:12:35,640 --> 00:12:37,240 Speaker 1: the next several years exactly. And so this is the 247 00:12:37,280 --> 00:12:40,319 Speaker 1: idea that there's these changes in technology which leads to 248 00:12:40,360 --> 00:12:42,760 Speaker 1: accelerated growth of companies that lives up to its potential. 249 00:12:42,880 --> 00:12:45,120 Speaker 1: And that's where these technology companies, the fang stocks have 250 00:12:45,120 --> 00:12:47,559 Speaker 1: have earned their their keep. I mean, this is different 251 00:12:47,600 --> 00:12:50,040 Speaker 1: than the dot com bubble, where there was these incredible 252 00:12:50,120 --> 00:12:52,719 Speaker 1: valuations and then the growth wasn't there, right, So that's 253 00:12:52,760 --> 00:12:55,480 Speaker 1: a different time a different time frame, a different outcome 254 00:12:55,640 --> 00:12:58,120 Speaker 1: on this. This experience of growth in value stocks where 255 00:12:58,120 --> 00:13:01,040 Speaker 1: you've seen you know, financial company is obviously struggling with 256 00:13:01,080 --> 00:13:03,880 Speaker 1: what's happened. They have increased regulation, they're unable to increase 257 00:13:03,880 --> 00:13:05,760 Speaker 1: their their growth over time, and they're not they're not 258 00:13:05,760 --> 00:13:08,920 Speaker 1: stabilizing back to normal growth levels. You have energy stocks 259 00:13:08,920 --> 00:13:11,160 Speaker 1: have seen multiple shocks, Retail that's getting a head wind 260 00:13:11,200 --> 00:13:14,680 Speaker 1: from Amazon. All those stocks are having difficulty and that 261 00:13:14,800 --> 00:13:17,640 Speaker 1: idea of maintaining In fact, they've been getting the same discount. 262 00:13:17,960 --> 00:13:19,880 Speaker 1: What we've seen is those discounts have been priced in 263 00:13:20,160 --> 00:13:22,800 Speaker 1: pretty pretty close to what they should have been right now. 264 00:13:22,920 --> 00:13:25,720 Speaker 1: The comparison from the forty one is this idea that 265 00:13:25,920 --> 00:13:29,040 Speaker 1: automobiles were priced this growth stocks, and those actually did great, 266 00:13:29,080 --> 00:13:32,160 Speaker 1: they grew. It was a part of the everybody everybody 267 00:13:32,160 --> 00:13:34,960 Speaker 1: bought one by the time, So that's the comparison and 268 00:13:35,000 --> 00:13:37,679 Speaker 1: the time framing. On the flip side, railroads were once 269 00:13:37,679 --> 00:13:40,040 Speaker 1: that got I got left out peak railroad and passenger 270 00:13:40,080 --> 00:13:43,319 Speaker 1: travel was back in. And so that's one where on 271 00:13:43,360 --> 00:13:45,240 Speaker 1: the value letter they saw a structural decline for what 272 00:13:45,240 --> 00:13:47,000 Speaker 1: happened in their economic Well, I want to ask you 273 00:13:47,000 --> 00:13:51,360 Speaker 1: a question about the definition of value investing or maybe 274 00:13:51,440 --> 00:13:55,120 Speaker 1: different approaches. And I know, like I follow trend Griffin 275 00:13:55,240 --> 00:13:58,040 Speaker 1: on Twitter. He talks a lot about the distinction between 276 00:13:58,559 --> 00:14:01,480 Speaker 1: value as a sort of satistical factor, which is, you know, 277 00:14:01,520 --> 00:14:03,440 Speaker 1: you look at the thousands of stocks out there, and 278 00:14:03,440 --> 00:14:06,720 Speaker 1: then you take the cheapest ones on various multiples, versus 279 00:14:07,520 --> 00:14:12,520 Speaker 1: value as say approached by Warren Buffett of a concentrated portfolio, 280 00:14:12,800 --> 00:14:15,840 Speaker 1: some of which may be cheap on metrics, but some 281 00:14:15,960 --> 00:14:18,640 Speaker 1: of them maybe not so cheap, but he has other 282 00:14:18,720 --> 00:14:20,920 Speaker 1: things that he likes about them, whether great brands or 283 00:14:20,960 --> 00:14:23,920 Speaker 1: great modes or whatever it is. Okay, is there a 284 00:14:23,960 --> 00:14:27,440 Speaker 1: distinction between those two ways in which people use the 285 00:14:27,560 --> 00:14:30,840 Speaker 1: term value investing? Yes, and and and part of it's 286 00:14:30,880 --> 00:14:33,000 Speaker 1: a simple value, right if you just only go off 287 00:14:33,000 --> 00:14:36,520 Speaker 1: of evaluation multiple, we're seeing more of that nowadays with 288 00:14:36,720 --> 00:14:40,440 Speaker 1: these widespread etf that are single value factor or value models, right, 289 00:14:40,480 --> 00:14:42,000 Speaker 1: and they're just basically saying we're only going to give 290 00:14:42,040 --> 00:14:45,280 Speaker 1: you like that, looking at like you said, broadly, a 291 00:14:45,280 --> 00:14:47,160 Speaker 1: couple of metrics maybe and just saying these are we're 292 00:14:47,160 --> 00:14:49,400 Speaker 1: going to buy you the cheapest part of that versus 293 00:14:49,440 --> 00:14:52,320 Speaker 1: the you know, the more the buffet fundamental model, which 294 00:14:52,360 --> 00:14:54,800 Speaker 1: is they tend to look for quality, like you said, 295 00:14:54,920 --> 00:14:59,360 Speaker 1: the good management economic modes, UM, some form of called 296 00:14:59,480 --> 00:15:01,520 Speaker 1: long term trend for why this company would be a 297 00:15:01,560 --> 00:15:04,560 Speaker 1: good value or essentially you know, we have it where 298 00:15:04,760 --> 00:15:08,440 Speaker 1: you're able to get more qualification on that reason for 299 00:15:08,480 --> 00:15:10,520 Speaker 1: the discount and the reason that I should revert back 300 00:15:10,520 --> 00:15:13,800 Speaker 1: to normal multiples and O shaughnessy, we we tend towards 301 00:15:13,800 --> 00:15:16,560 Speaker 1: that side. We look at multiple characteristics of blending those together, 302 00:15:17,000 --> 00:15:19,240 Speaker 1: things like quality of earnings, things like earnings growth to 303 00:15:19,280 --> 00:15:21,760 Speaker 1: try to determine which stocks are more likely to have 304 00:15:21,800 --> 00:15:41,880 Speaker 1: the rebound you mentioned um sort of e t S. 305 00:15:41,920 --> 00:15:44,680 Speaker 1: And I was curious, you know, I'm I think back 306 00:15:44,720 --> 00:15:47,760 Speaker 1: to say twenty years ago, as someone trying to capture 307 00:15:48,120 --> 00:15:51,320 Speaker 1: the value factor within the stock market, and I imagined 308 00:15:51,360 --> 00:15:54,200 Speaker 1: that like required a lot of legwork and a lot 309 00:15:54,320 --> 00:15:56,720 Speaker 1: of people doing a lot of calculations, and probably a 310 00:15:56,720 --> 00:15:59,000 Speaker 1: lot of the kind of investment you're talking about of 311 00:15:59,400 --> 00:16:02,640 Speaker 1: scrubbing the data and just doing it by hand. Now 312 00:16:02,800 --> 00:16:05,480 Speaker 1: I could go on to anyone can sort of go 313 00:16:05,520 --> 00:16:07,600 Speaker 1: into their brokerage account and click I want to buy 314 00:16:07,760 --> 00:16:09,960 Speaker 1: a value et F and then walk away without doing 315 00:16:10,000 --> 00:16:15,520 Speaker 1: any work. Does that change the game? When value investing? 316 00:16:15,560 --> 00:16:18,880 Speaker 1: It's no longer work to sort of even discover the 317 00:16:18,920 --> 00:16:21,040 Speaker 1: value factor is just click of a button. Someone else 318 00:16:21,080 --> 00:16:23,720 Speaker 1: has done it for you. So it is easier to 319 00:16:23,920 --> 00:16:26,680 Speaker 1: access you know, quote unquote value than it has ever 320 00:16:26,760 --> 00:16:28,960 Speaker 1: been before. And that's because of the product proliferation right 321 00:16:29,480 --> 00:16:33,400 Speaker 1: where you're seeing access of our very low fee funds 322 00:16:33,400 --> 00:16:35,880 Speaker 1: that are coming around and and you know, again like 323 00:16:35,920 --> 00:16:37,720 Speaker 1: you said, they are on many platforms. Are et fs 324 00:16:37,760 --> 00:16:40,720 Speaker 1: are easy to buy from our point of view, though 325 00:16:40,880 --> 00:16:43,520 Speaker 1: ease of access doesn't mean that you're getting better investments 326 00:16:43,520 --> 00:16:45,280 Speaker 1: out of it, right, because there's a wide range of 327 00:16:45,280 --> 00:16:47,720 Speaker 1: outcomes that still comes from any of these investment products. 328 00:16:48,120 --> 00:16:51,200 Speaker 1: The difficulty is communicating the transparency of of what the 329 00:16:51,320 --> 00:16:53,160 Speaker 1: what the features are in each of those products. Right, 330 00:16:53,200 --> 00:16:55,960 Speaker 1: So you know, are you buying on book value? Are 331 00:16:56,000 --> 00:16:57,560 Speaker 1: you buying on earnings? By the way, how are you 332 00:16:57,640 --> 00:17:00,360 Speaker 1: calculating earnings? The example we gave we wrote I wrote 333 00:17:00,360 --> 00:17:03,280 Speaker 1: a paper cult Factors and not Commodities a couple of 334 00:17:03,400 --> 00:17:05,600 Speaker 1: years ago, Um, and you were talking about going in 335 00:17:05,720 --> 00:17:08,960 Speaker 1: and getting the data. There's a lot of nuance. And 336 00:17:09,000 --> 00:17:11,480 Speaker 1: again I say nuance in my world from my seat 337 00:17:11,480 --> 00:17:13,280 Speaker 1: on things like even as simple as a PE ratio, 338 00:17:13,320 --> 00:17:15,879 Speaker 1: where you can have companies that will wind up having 339 00:17:15,880 --> 00:17:18,640 Speaker 1: it where you're depending on if you're accounting for extraordinaries, 340 00:17:18,720 --> 00:17:22,400 Speaker 1: preferred dividends, an occasional tax cut that comes around every 341 00:17:22,400 --> 00:17:24,080 Speaker 1: once in a while boosting earnings, right, And if you 342 00:17:24,119 --> 00:17:25,359 Speaker 1: put that all and you can wind up with some 343 00:17:25,440 --> 00:17:29,560 Speaker 1: wildly different outcomes. Kraft Heins had seven million net income 344 00:17:29,560 --> 00:17:32,240 Speaker 1: and then at seven seven billion and met income plus 345 00:17:32,240 --> 00:17:34,840 Speaker 1: a seven billion dollar boost from the tax cut. Right. 346 00:17:35,040 --> 00:17:36,600 Speaker 1: So if you don't account for that or not, you know, 347 00:17:36,640 --> 00:17:38,720 Speaker 1: you wind up having a PE that's half of what 348 00:17:38,800 --> 00:17:41,480 Speaker 1: it should be along the way. So I have a 349 00:17:41,720 --> 00:17:45,480 Speaker 1: sort of big picture existential question. And part of this 350 00:17:45,600 --> 00:17:50,240 Speaker 1: is because I just got done talking with um John Hampton, 351 00:17:50,840 --> 00:17:55,400 Speaker 1: the hedge fund manager, who is pretty dismissive of value investors, 352 00:17:55,520 --> 00:17:58,840 Speaker 1: and he sometimes refers to them as sort of bearded, 353 00:17:59,200 --> 00:18:02,560 Speaker 1: self righteous people who think they're smarter than everyone else. 354 00:18:02,920 --> 00:18:06,159 Speaker 1: I say, I'm in the studio with with Chris right now. 355 00:18:06,240 --> 00:18:07,560 Speaker 1: He does not have a beer. I shaved my beer 356 00:18:07,640 --> 00:18:12,560 Speaker 1: a couple of months. Okay, okay, very important details. So 357 00:18:12,760 --> 00:18:17,960 Speaker 1: my question is why should value investing generate higher returns 358 00:18:18,000 --> 00:18:21,960 Speaker 1: than say, growth stocks, because isn't that basically saying that 359 00:18:22,000 --> 00:18:27,679 Speaker 1: the market has misvalued the companies or um misvalued their 360 00:18:27,720 --> 00:18:30,879 Speaker 1: potential earnings growth. I guess yes, is the is the 361 00:18:30,880 --> 00:18:34,160 Speaker 1: short answer. What happens is over a normal long term 362 00:18:34,200 --> 00:18:36,920 Speaker 1: market cycle, what we have seen, and this again is 363 00:18:36,920 --> 00:18:38,880 Speaker 1: borne out from data we've looked at, you know, over 364 00:18:39,000 --> 00:18:43,120 Speaker 1: ninety two years of value investing to show that on average, 365 00:18:43,160 --> 00:18:48,080 Speaker 1: what happens again is these companies your biomins these incredible discounts. Yes, 366 00:18:48,119 --> 00:18:49,840 Speaker 1: they come with some distress along the way, some near 367 00:18:49,920 --> 00:18:53,199 Speaker 1: term distress where um you'll possibly see earnings decline over 368 00:18:53,280 --> 00:18:57,600 Speaker 1: twelve months, but they'll re essentially get back to a 369 00:18:57,720 --> 00:19:02,000 Speaker 1: normal earning stream and earnings growth level within three years, 370 00:19:02,520 --> 00:19:05,240 Speaker 1: and the market will discount those at thirty percent when 371 00:19:05,240 --> 00:19:08,000 Speaker 1: they should be discounted fiftcent based on earnings. Right, So 372 00:19:08,040 --> 00:19:10,720 Speaker 1: the idea is, like, what you're getting is that discount 373 00:19:10,720 --> 00:19:12,600 Speaker 1: over a three year basis of close to five percent 374 00:19:12,600 --> 00:19:14,760 Speaker 1: a year on average. Now, there are periods of time 375 00:19:14,800 --> 00:19:18,159 Speaker 1: where that distress gets increased and these companies wind up 376 00:19:18,200 --> 00:19:21,960 Speaker 1: having it where their priced effectively and growth stocks have 377 00:19:22,040 --> 00:19:24,879 Speaker 1: the flip side where you know, on average their priced 378 00:19:24,880 --> 00:19:28,399 Speaker 1: to have this incredible growth of like, but they actually 379 00:19:28,400 --> 00:19:31,840 Speaker 1: only achieve twenty percent, right, or so they lose five 380 00:19:31,840 --> 00:19:34,240 Speaker 1: percent on average over those three years. So that's one 381 00:19:34,240 --> 00:19:38,200 Speaker 1: where again if you look over ninety two years, yes, 382 00:19:38,240 --> 00:19:40,680 Speaker 1: that value investing is one that should bear out over time, 383 00:19:40,680 --> 00:19:42,960 Speaker 1: but what we have seen, particularly when extending it back 384 00:19:43,560 --> 00:19:46,440 Speaker 1: to include periods one, is that there can be extent 385 00:19:46,520 --> 00:19:49,520 Speaker 1: periods of time where this gets in burned. So how 386 00:19:49,680 --> 00:19:53,560 Speaker 1: long should investors actually be willing to wait until they 387 00:19:53,600 --> 00:19:58,679 Speaker 1: are rewarded for their value investing? Because as you mentioned before, 388 00:19:58,480 --> 00:20:02,000 Speaker 1: we're now in sort of the twelve fear of under performance, 389 00:20:02,119 --> 00:20:06,800 Speaker 1: it's fairly unprecedented. How much longer should people be waiting? Well, 390 00:20:06,800 --> 00:20:09,159 Speaker 1: for us, that's that's that's the hardest part, which is 391 00:20:09,200 --> 00:20:11,800 Speaker 1: keeping to a discipline when a strategy is working against you. Right. 392 00:20:12,200 --> 00:20:14,960 Speaker 1: Obviously this has been painful, you know, as us having 393 00:20:15,000 --> 00:20:17,679 Speaker 1: a value bias with our strategies and value strategies overall. 394 00:20:17,680 --> 00:20:20,040 Speaker 1: This is one where you know you want to see 395 00:20:20,040 --> 00:20:22,160 Speaker 1: it revert back in a in a in a quicker fashion. 396 00:20:22,200 --> 00:20:24,480 Speaker 1: But obviously the market is held out and these growth 397 00:20:24,840 --> 00:20:27,479 Speaker 1: these growth stocks have continued to outperform for us. What 398 00:20:27,520 --> 00:20:29,160 Speaker 1: we feel would be the worst thing to do would 399 00:20:29,160 --> 00:20:31,240 Speaker 1: be to abandon our principles at this point, right. And 400 00:20:31,280 --> 00:20:34,080 Speaker 1: the idea is that we see that there are signs 401 00:20:34,080 --> 00:20:36,119 Speaker 1: coming around of us working towards the end of this 402 00:20:36,680 --> 00:20:39,879 Speaker 1: one is his formation of oligopolies, where we're seeing these 403 00:20:39,880 --> 00:20:41,520 Speaker 1: companies that come out the fank stocks winner. If you 404 00:20:41,520 --> 00:20:43,639 Speaker 1: look at the change in leadership since two thousand seven, 405 00:20:44,080 --> 00:20:46,159 Speaker 1: the technology stocks are obviously at the top right now. 406 00:20:46,240 --> 00:20:49,080 Speaker 1: But then there's this also component of call it the 407 00:20:49,560 --> 00:20:53,560 Speaker 1: companies out are the previous regime starting to adopt, where 408 00:20:53,560 --> 00:20:55,959 Speaker 1: you're seeing large companies building out their own data science 409 00:20:56,000 --> 00:20:59,479 Speaker 1: teams um and they're starting to catch up. Right. So 410 00:20:59,760 --> 00:21:02,640 Speaker 1: the art that was like the call it the shifting 411 00:21:02,720 --> 00:21:07,080 Speaker 1: moment from the forty one was dieselization of the railroad industry. 412 00:21:07,400 --> 00:21:09,399 Speaker 1: They basically started and they shifted where before it had 413 00:21:09,440 --> 00:21:12,160 Speaker 1: been steam engines that I didn't realize that it took 414 00:21:12,200 --> 00:21:13,639 Speaker 1: like three people a half a day to start up 415 00:21:13,640 --> 00:21:16,800 Speaker 1: in a railroad like a locomotive instead of turning a 416 00:21:16,880 --> 00:21:18,879 Speaker 1: key and starting up an engine. So when they shifted 417 00:21:18,880 --> 00:21:21,480 Speaker 1: to that, they went from again where trucking had suddenly 418 00:21:21,480 --> 00:21:24,879 Speaker 1: had an economic benefit over railroads to now railroads having 419 00:21:24,920 --> 00:21:27,840 Speaker 1: economic you know, benefit over or trucking. And then it 420 00:21:28,119 --> 00:21:30,960 Speaker 1: started going back where value stocks shot the moon. What 421 00:21:31,040 --> 00:21:34,199 Speaker 1: we expect to see happen is that again the technology 422 00:21:34,280 --> 00:21:37,520 Speaker 1: is is embedded. Things like the mobile computing platform is 423 00:21:37,520 --> 00:21:40,560 Speaker 1: is set and standardized, and you're seeing companies like you know, 424 00:21:40,640 --> 00:21:43,320 Speaker 1: Domino's Pizza, who has been killing it in mobile because 425 00:21:43,320 --> 00:21:45,119 Speaker 1: they've sat there and they were there early adopters, and 426 00:21:45,119 --> 00:21:47,960 Speaker 1: they realized everybody was ordering through the web on their phone, 427 00:21:48,000 --> 00:21:49,240 Speaker 1: so they built an app, and all of a sudden, 428 00:21:49,240 --> 00:21:51,120 Speaker 1: now they're they're they're crushing in a mobile platform. You're 429 00:21:51,119 --> 00:21:53,400 Speaker 1: gonna start seeing more and more of that right where 430 00:21:53,440 --> 00:21:56,080 Speaker 1: traditional companies are going to be me seeing the benefits 431 00:21:56,119 --> 00:21:59,040 Speaker 1: of the technology and those values stoction wide about performing 432 00:21:59,119 --> 00:22:02,959 Speaker 1: didn't Domino didn't they come public the same day Google did? Right? 433 00:22:03,040 --> 00:22:04,760 Speaker 1: Isn't that the deal with them? And they've actually I 434 00:22:04,800 --> 00:22:08,000 Speaker 1: think that they've actually outperformed Google. Didn't know that. Maybe 435 00:22:08,000 --> 00:22:09,800 Speaker 1: that's a great story. May be making that up. I 436 00:22:09,840 --> 00:22:12,119 Speaker 1: think that's true, though. I think you're right, Joe, it's 437 00:22:12,119 --> 00:22:14,159 Speaker 1: a good chart. Yeah, we'll have to we'll have to 438 00:22:14,280 --> 00:22:15,480 Speaker 1: go back to look at that one. We'll have to 439 00:22:15,520 --> 00:22:20,560 Speaker 1: accompany that chart Pizza over Internet search. So just further 440 00:22:20,640 --> 00:22:22,879 Speaker 1: to this point, because Tracy kind of anticipated where I 441 00:22:22,920 --> 00:22:25,200 Speaker 1: was going to go with the question, when you look 442 00:22:25,240 --> 00:22:29,840 Speaker 1: at that ninety one period, what were the things that 443 00:22:29,960 --> 00:22:33,440 Speaker 1: happened at the tail end of that, and explicate further 444 00:22:33,600 --> 00:22:37,200 Speaker 1: on what you see is perhaps the end of the 445 00:22:37,280 --> 00:22:40,960 Speaker 1: dominance of these fangs or growth factor because for several years, 446 00:22:41,080 --> 00:22:44,000 Speaker 1: again disbelief that they could continue to grow like this, 447 00:22:44,440 --> 00:22:48,320 Speaker 1: and right now, you know, it's like everyone's been foolish 448 00:22:48,400 --> 00:22:50,520 Speaker 1: trying to predict the end of Netflix or trying to 449 00:22:50,560 --> 00:22:53,720 Speaker 1: predict the end of how fast Google on Facebook can grow. 450 00:22:53,800 --> 00:22:55,800 Speaker 1: So what are some of the signs you look for 451 00:22:56,040 --> 00:23:00,520 Speaker 1: that that period of underperformance for value while growth actually delivers. 452 00:23:00,920 --> 00:23:02,760 Speaker 1: What if what if the end looked like so For 453 00:23:02,760 --> 00:23:05,119 Speaker 1: for me, part of it was established the establishing the 454 00:23:05,119 --> 00:23:06,760 Speaker 1: form factor for how people are gonna be using this 455 00:23:06,800 --> 00:23:09,680 Speaker 1: new socio economic paradigm. And you know, that's one where 456 00:23:09,800 --> 00:23:13,040 Speaker 1: I think the shift that came around was the introduction 457 00:23:13,040 --> 00:23:15,560 Speaker 1: of the iPhone, which just radically changed how people use 458 00:23:15,600 --> 00:23:17,960 Speaker 1: mobile devices. So if you think about it, the way 459 00:23:18,000 --> 00:23:19,600 Speaker 1: I think about what's going on right now is that 460 00:23:19,640 --> 00:23:22,719 Speaker 1: there's this technology and it started off with desktop computing 461 00:23:22,720 --> 00:23:25,960 Speaker 1: in the Internet. Amazon gotten into that and they established 462 00:23:26,000 --> 00:23:27,760 Speaker 1: the trust in that form factor of being able to 463 00:23:28,280 --> 00:23:31,240 Speaker 1: have commerce over with somebody a third party basically over 464 00:23:31,280 --> 00:23:34,080 Speaker 1: the Internet, and have that be a trusted transaction. Uh. 465 00:23:34,119 --> 00:23:37,120 Speaker 1: The iPhone, he basically shifted that all around. And because 466 00:23:37,160 --> 00:23:40,000 Speaker 1: if you think about the adoption curve of that and 467 00:23:40,000 --> 00:23:42,520 Speaker 1: to move people off of the desktop to mobile and 468 00:23:42,600 --> 00:23:45,280 Speaker 1: to the tablet introducing that as well, and that adoption 469 00:23:45,359 --> 00:23:47,960 Speaker 1: rate's hard to bleep. But in there was only people 470 00:23:47,960 --> 00:23:52,000 Speaker 1: with a smartphone, and now it's a of the country 471 00:23:52,040 --> 00:23:54,480 Speaker 1: and you know, I think something like sevent or under 472 00:23:54,520 --> 00:23:55,840 Speaker 1: the age of fourteen, So I tells you like pretty 473 00:23:55,880 --> 00:23:59,000 Speaker 1: much every adult has has a phone right at this 474 00:23:59,040 --> 00:24:01,000 Speaker 1: point has a smart phone, and they're and they're starting 475 00:24:01,000 --> 00:24:02,840 Speaker 1: to use it. So that part where and then iPhone 476 00:24:02,840 --> 00:24:06,760 Speaker 1: sales basically peeked out last year, right, So there's there's 477 00:24:06,800 --> 00:24:09,480 Speaker 1: part where there's this adoption of the standard that's going on, 478 00:24:09,600 --> 00:24:11,520 Speaker 1: and then comes the utilization of it. So in Carlotta 479 00:24:11,520 --> 00:24:14,600 Speaker 1: Perez's framework, there's a installation phase and the deployment phase, 480 00:24:14,640 --> 00:24:17,480 Speaker 1: and the installation phase is all about setting the standards, 481 00:24:17,520 --> 00:24:20,399 Speaker 1: seeing the mass adoption, and then comes the after effect 482 00:24:20,400 --> 00:24:22,320 Speaker 1: to the golden age she calls it, where it's all 483 00:24:22,320 --> 00:24:25,880 Speaker 1: the people utilizing that, and that's where we've seen traditional 484 00:24:26,080 --> 00:24:28,280 Speaker 1: value investing come around. So the signs of this are 485 00:24:28,280 --> 00:24:30,240 Speaker 1: a part of it are, you know, seeing the peak 486 00:24:30,280 --> 00:24:32,720 Speaker 1: on the iPhone, seeing where that form in factor is set, 487 00:24:32,720 --> 00:24:35,880 Speaker 1: and then seeing other companies adopt that platform and being 488 00:24:35,880 --> 00:24:40,159 Speaker 1: able to use that broadly to extend their economic models. 489 00:24:40,200 --> 00:24:42,879 Speaker 1: So when the world is going through a period of 490 00:24:43,440 --> 00:24:47,359 Speaker 1: disruptive new technologies, such as the rollout of the iPhone, 491 00:24:48,119 --> 00:24:55,040 Speaker 1: how do you start differentiating winners and losers among value stocks? 492 00:24:55,119 --> 00:24:58,360 Speaker 1: Because you actually point out in your paper that, for instance, 493 00:24:58,400 --> 00:25:02,919 Speaker 1: BlackBerry at one point basically looked like a value stock 494 00:25:03,040 --> 00:25:07,560 Speaker 1: before being absolutely crushed by various pressures. So how do 495 00:25:07,600 --> 00:25:11,240 Speaker 1: you avoid investing in something like a BlackBerry at precisely 496 00:25:11,280 --> 00:25:13,840 Speaker 1: the wrong moment. This goes back to your point earlier 497 00:25:13,960 --> 00:25:17,520 Speaker 1: about you know, just pure ratios versus having quality themes 498 00:25:17,560 --> 00:25:19,240 Speaker 1: that go along with it in other ways to look 499 00:25:19,680 --> 00:25:22,119 Speaker 1: and again that's where at O'Shaughnessy. What we do is 500 00:25:22,359 --> 00:25:25,440 Speaker 1: it maybe quantitative, but we look across the entire business. 501 00:25:25,440 --> 00:25:26,960 Speaker 1: So part of that is looking at the balance sheet, 502 00:25:26,960 --> 00:25:28,800 Speaker 1: looking at the leveraging side of it, looking at the 503 00:25:28,880 --> 00:25:31,280 Speaker 1: quality of the earnings, which is are they coming from 504 00:25:31,359 --> 00:25:33,280 Speaker 1: cash flows, are they coming from things like you know, 505 00:25:33,320 --> 00:25:38,080 Speaker 1: manipulation of inventoria or depreciation uh, as well as looking 506 00:25:38,119 --> 00:25:40,639 Speaker 1: historical growth of the company, the momentum of the company. 507 00:25:40,680 --> 00:25:43,239 Speaker 1: All these are signals that you blend together, and when 508 00:25:43,280 --> 00:25:45,840 Speaker 1: you do that, you can build a quantitative profile of 509 00:25:45,880 --> 00:25:49,679 Speaker 1: companies that are called value traps versus versus UH. You know, 510 00:25:49,840 --> 00:25:52,200 Speaker 1: growth stocks are value winners, let's call it. I think 511 00:25:52,400 --> 00:25:55,000 Speaker 1: we did a follow up paper two factors from scratch 512 00:25:55,000 --> 00:25:57,159 Speaker 1: called alpha within factors that talked about the difference of 513 00:25:57,200 --> 00:25:59,760 Speaker 1: these and how you're able to use these other characteristics 514 00:26:00,240 --> 00:26:03,520 Speaker 1: to try to forecast future earnings within value companies. So 515 00:26:03,680 --> 00:26:06,239 Speaker 1: in the case of BlackBerry explicitly it would have come 516 00:26:06,280 --> 00:26:09,240 Speaker 1: with terrible negative earnings earnings growth as well as terrible momentum. 517 00:26:09,560 --> 00:26:11,280 Speaker 1: And those were the reasons that I have screened out 518 00:26:11,280 --> 00:26:13,159 Speaker 1: of our process when it was coming through on the 519 00:26:13,200 --> 00:26:18,840 Speaker 1: earnings decline. So is it more about eliminating the losers 520 00:26:18,920 --> 00:26:21,520 Speaker 1: than picking the winners? I would say it's it's on 521 00:26:21,600 --> 00:26:24,720 Speaker 1: both sides of that. But we in our process, we 522 00:26:24,840 --> 00:26:26,600 Speaker 1: have a part where we set the universe. There's an 523 00:26:26,600 --> 00:26:28,520 Speaker 1: explicit part where we rip out companies we think are 524 00:26:28,520 --> 00:26:31,119 Speaker 1: going to underperformed. So, yeah, the losers, those get the 525 00:26:31,119 --> 00:26:33,680 Speaker 1: first swipe of saying these are these have some really 526 00:26:33,800 --> 00:26:36,760 Speaker 1: terrible characteristics. Let's just get rid of those, which is 527 00:26:36,760 --> 00:26:38,640 Speaker 1: one of the benefits I think of an active process 528 00:26:38,680 --> 00:26:41,960 Speaker 1: over over a passive. So let's say we're coming to 529 00:26:42,000 --> 00:26:43,800 Speaker 1: an end, or maybe in a couple of years, we're 530 00:26:43,840 --> 00:26:47,240 Speaker 1: coming to an end of where this explosion of new 531 00:26:47,280 --> 00:26:51,000 Speaker 1: technology allows a handful of growth stocks to just massively 532 00:26:51,119 --> 00:26:54,639 Speaker 1: outperform expectations, and we referred to a period that's a 533 00:26:54,680 --> 00:26:57,920 Speaker 1: little more normal in which the technology is diffused available 534 00:26:57,960 --> 00:27:02,400 Speaker 1: to all. Would we in would you then expect years 535 00:27:02,440 --> 00:27:06,920 Speaker 1: and years and decades potentially of the value factor outperforming. 536 00:27:07,359 --> 00:27:09,680 Speaker 1: That's what we've seen before, right, So I don't want 537 00:27:09,680 --> 00:27:11,879 Speaker 1: to go on and say that value is going to 538 00:27:11,960 --> 00:27:13,560 Speaker 1: go out and have you know, fifty years of out 539 00:27:13,560 --> 00:27:15,800 Speaker 1: performs and and by the way, within that time frame, 540 00:27:16,240 --> 00:27:19,119 Speaker 1: there's obviously shorter periods of time where value works against you. 541 00:27:19,720 --> 00:27:22,280 Speaker 1: What we have seen we use something we call base rates, 542 00:27:23,000 --> 00:27:25,600 Speaker 1: which are the percentage of time over a rolling call it, 543 00:27:25,680 --> 00:27:28,200 Speaker 1: one year, three year, five year, ten year period where 544 00:27:28,280 --> 00:27:31,399 Speaker 1: value has outperformed. Uh. And what we've seen is in 545 00:27:31,440 --> 00:27:36,000 Speaker 1: that call it in between these technological revolutions, it's had 546 00:27:36,040 --> 00:27:38,879 Speaker 1: a significant periods of out performance over rolling ten year basis. 547 00:27:38,880 --> 00:27:42,240 Speaker 1: Like close to mind you on a one year basis, 548 00:27:42,480 --> 00:27:44,919 Speaker 1: it winds up closer in like a sixty to sixty 549 00:27:46,080 --> 00:27:49,960 Speaker 1: I'm curious is regulation the big risk here, because it 550 00:27:50,040 --> 00:27:53,159 Speaker 1: does feel like a lot of technology or innovation at 551 00:27:53,200 --> 00:27:57,640 Speaker 1: least initially starts out as sort of regulatory arbitrage, which 552 00:27:57,680 --> 00:28:01,360 Speaker 1: means it could be affected, um very quickly. Is that 553 00:28:02,000 --> 00:28:04,639 Speaker 1: one thing that you would worry about in this scenario? Actually, 554 00:28:04,640 --> 00:28:06,560 Speaker 1: I think I think I think regulation, Well, let me 555 00:28:06,600 --> 00:28:09,080 Speaker 1: say it's one thing you should think about as an investor. 556 00:28:09,160 --> 00:28:11,560 Speaker 1: For us, we think that that's only gonna if you 557 00:28:11,600 --> 00:28:15,080 Speaker 1: were to call the regulatory risk, it's predominantly on the 558 00:28:15,119 --> 00:28:17,840 Speaker 1: growth side right now, um, because that's where there's going 559 00:28:17,920 --> 00:28:20,760 Speaker 1: to be. You know. Really two parts of that I 560 00:28:20,800 --> 00:28:22,720 Speaker 1: see come through is regulatory risk. One is the anti 561 00:28:22,720 --> 00:28:25,800 Speaker 1: monopolistic where the size of these companies get so big. 562 00:28:25,840 --> 00:28:28,240 Speaker 1: I mean, if Amazon goes through another growth like it 563 00:28:28,280 --> 00:28:30,480 Speaker 1: did over the last ten years, obviously it would wind 564 00:28:30,520 --> 00:28:33,720 Speaker 1: up having with monopolistic anti monopolistic enterprise. But the second one, 565 00:28:34,080 --> 00:28:35,919 Speaker 1: which I think is going to wind up being perhaps 566 00:28:35,960 --> 00:28:40,080 Speaker 1: a little mirror, is this idea of um, people starting 567 00:28:40,080 --> 00:28:42,720 Speaker 1: to understand the trade they're making on their data. UM. 568 00:28:42,760 --> 00:28:44,960 Speaker 1: So that was where Senate it was interesting. I think 569 00:28:45,000 --> 00:28:47,880 Speaker 1: it was within the last month. And again I can't remember. 570 00:28:48,000 --> 00:28:49,640 Speaker 1: I'm terrible with names, so I can't remember who was. 571 00:28:49,840 --> 00:28:51,720 Speaker 1: It was Durban who who have had proposed the bill 572 00:28:51,720 --> 00:28:54,240 Speaker 1: in the Senate where they were going to make transparent 573 00:28:54,520 --> 00:28:58,280 Speaker 1: what people are receiving, you know, for there the value 574 00:28:58,320 --> 00:29:00,440 Speaker 1: of the information you're giving them. Right, this idea of 575 00:29:00,440 --> 00:29:03,760 Speaker 1: people are being tracked on their phones, um, I think 576 00:29:03,760 --> 00:29:05,600 Speaker 1: the general level of awareness of how much is being 577 00:29:05,600 --> 00:29:07,880 Speaker 1: tracked and how much of your of a composite profile 578 00:29:07,960 --> 00:29:10,480 Speaker 1: can be built for you online is being and then 579 00:29:10,520 --> 00:29:13,680 Speaker 1: being utilized. That's going to be potentially where the that's 580 00:29:13,680 --> 00:29:15,600 Speaker 1: gonna have it, where a regulation will come through and 581 00:29:15,960 --> 00:29:18,240 Speaker 1: create transparent to that and perhaps slow that down. I 582 00:29:18,280 --> 00:29:21,520 Speaker 1: wanna shift gears a little bit and throw out a 583 00:29:21,560 --> 00:29:23,800 Speaker 1: theory that someone once told me about the decline of 584 00:29:23,840 --> 00:29:26,560 Speaker 1: the value factor and get your take on it. So 585 00:29:27,200 --> 00:29:29,480 Speaker 1: someone I was years ago was arguing to me was 586 00:29:29,560 --> 00:29:33,160 Speaker 1: that companies can be cheap on a ratios basis for 587 00:29:33,240 --> 00:29:38,320 Speaker 1: multiple reasons. So some companies are doomed like BlackBerry. Others 588 00:29:38,400 --> 00:29:41,920 Speaker 1: are cyclical businesses like mining companies that might be at 589 00:29:41,920 --> 00:29:44,400 Speaker 1: cyclical peaks and so people don't pay too much for 590 00:29:44,480 --> 00:29:49,000 Speaker 1: their earnings. Others are just in unpopular industries such as 591 00:29:49,080 --> 00:29:51,440 Speaker 1: a newspaper and so forth, and they're all different. And 592 00:29:51,520 --> 00:29:54,400 Speaker 1: his argument was that the advantage of investing in that 593 00:29:54,560 --> 00:29:59,720 Speaker 1: basket was that value was essentially a good screen for diversification. Essentially, 594 00:30:00,080 --> 00:30:02,840 Speaker 1: what you guaranteed by buying cheap stocks was that you 595 00:30:02,880 --> 00:30:05,280 Speaker 1: bought a bunch of different companies with different things going on, 596 00:30:05,360 --> 00:30:08,719 Speaker 1: and that was diversified. And that with the emergence of 597 00:30:09,440 --> 00:30:12,800 Speaker 1: value et f s and value funds because people go 598 00:30:12,880 --> 00:30:15,600 Speaker 1: in and out of the factor, they're less diversified. People 599 00:30:15,640 --> 00:30:18,120 Speaker 1: buy all the value stocks at once, and they sell 600 00:30:18,160 --> 00:30:20,120 Speaker 1: them all at once, and they start to correlate more 601 00:30:20,240 --> 00:30:23,120 Speaker 1: merely because they're all in the same funds, and so 602 00:30:23,160 --> 00:30:28,320 Speaker 1: the diversification benefits of value no longer exist because they're 603 00:30:28,360 --> 00:30:30,120 Speaker 1: all tied by the fact that they're all part of 604 00:30:30,160 --> 00:30:33,040 Speaker 1: the same ETFs and the same Does that ring true 605 00:30:33,040 --> 00:30:35,719 Speaker 1: to you at all? Is that something that you've come across, 606 00:30:35,760 --> 00:30:38,320 Speaker 1: like the different reasons why companies are value and whether 607 00:30:38,440 --> 00:30:41,400 Speaker 1: that reduces some of the benefits to the portfolio. You know, 608 00:30:41,440 --> 00:30:44,160 Speaker 1: it's interesting that that. First of all, one, I do 609 00:30:44,240 --> 00:30:46,640 Speaker 1: believe that the original premise that you you said on 610 00:30:46,720 --> 00:30:49,360 Speaker 1: value investing is right. There are stocks within value that 611 00:30:49,400 --> 00:30:53,760 Speaker 1: are secular, cyclical, on popular, you know, doom. I like that, 612 00:30:54,080 --> 00:30:56,560 Speaker 1: I'll keep that one and so that. But there's also 613 00:30:56,640 --> 00:30:59,040 Speaker 1: healthy companies that are priced at a discount because of 614 00:30:59,440 --> 00:31:02,880 Speaker 1: near term fears and that are unfounded. Right, So what 615 00:31:02,880 --> 00:31:04,920 Speaker 1: you're leaving inside of that is that there are healthy 616 00:31:04,960 --> 00:31:07,640 Speaker 1: companies that get you know, baby with bathwater thrown out 617 00:31:07,640 --> 00:31:10,480 Speaker 1: inside of this and can have some significant outperformance along 618 00:31:10,480 --> 00:31:12,480 Speaker 1: the way. That is why it's important to have a 619 00:31:12,480 --> 00:31:14,680 Speaker 1: comprehensive look when looking at value stocks in order to 620 00:31:14,720 --> 00:31:16,959 Speaker 1: have a quality themes that you're putting on top of it. 621 00:31:17,520 --> 00:31:20,280 Speaker 1: Uh and and and a good understanding of of picking 622 00:31:20,320 --> 00:31:22,920 Speaker 1: within value right and understanding which types of stocks you're 623 00:31:22,920 --> 00:31:25,000 Speaker 1: gonna go for and staying away from the doomed right. 624 00:31:25,080 --> 00:31:27,479 Speaker 1: So but on the part value that should be an 625 00:31:27,480 --> 00:31:30,160 Speaker 1: e t F value x doom x doomed. Yes, I 626 00:31:30,200 --> 00:31:34,120 Speaker 1: like that. So but the the part about ETFs essentially 627 00:31:34,320 --> 00:31:37,479 Speaker 1: are being this out right where the benefit of value 628 00:31:38,200 --> 00:31:39,920 Speaker 1: we haven't seen that, right, because what you would expect 629 00:31:39,960 --> 00:31:42,480 Speaker 1: to see is spread scenario um. And what you would 630 00:31:42,480 --> 00:31:45,120 Speaker 1: expect to see is is the number one is spread scenaril. 631 00:31:45,160 --> 00:31:49,000 Speaker 1: But also just knowing how the from my seat, how 632 00:31:49,040 --> 00:31:51,120 Speaker 1: the panoply of ETFs work, which is they wind up 633 00:31:51,120 --> 00:31:53,760 Speaker 1: in different spots, right, so you're gonna wind up with 634 00:31:53,840 --> 00:31:56,000 Speaker 1: some on price to book and yeah, there's some clustering 635 00:31:56,040 --> 00:31:58,440 Speaker 1: around that, and we have concerns about price to book 636 00:31:58,440 --> 00:32:00,760 Speaker 1: as a factor. You know, it's it's better than nothing, 637 00:32:00,840 --> 00:32:03,400 Speaker 1: but there's better value factors that are out there. Um. 638 00:32:03,480 --> 00:32:06,720 Speaker 1: But overall, we have not seen that there's any sort 639 00:32:06,760 --> 00:32:09,320 Speaker 1: of any sort of arbitraging way of the value factor 640 00:32:09,360 --> 00:32:13,760 Speaker 1: from ETFs in those flows. So I have one more question, um, 641 00:32:14,000 --> 00:32:17,720 Speaker 1: And you sort of evaded it earlier, I guess, and 642 00:32:18,080 --> 00:32:22,280 Speaker 1: it's a really tough one. But using all of your 643 00:32:22,440 --> 00:32:25,480 Speaker 1: historical data and the analysis that you've done, which is, 644 00:32:25,720 --> 00:32:28,880 Speaker 1: you know, very detailed, what do you think is going 645 00:32:28,960 --> 00:32:32,280 Speaker 1: to be the turning point in this current cycle that 646 00:32:32,520 --> 00:32:36,320 Speaker 1: is going to actually lead value to outperform once again? 647 00:32:37,680 --> 00:32:40,680 Speaker 1: So the point before I I thought I didn't avoid it. 648 00:32:40,760 --> 00:32:42,320 Speaker 1: I thought I was. I was just being like that. 649 00:32:42,480 --> 00:32:44,240 Speaker 1: It's very listening. At the end of the day, it's 650 00:32:44,240 --> 00:32:47,320 Speaker 1: hard to time. You can't find a specific catalyst where 651 00:32:47,400 --> 00:32:48,920 Speaker 1: that will be it right. You know, it's like, oh, 652 00:32:49,160 --> 00:32:51,360 Speaker 1: you know that, you know Walmart came out with this 653 00:32:51,400 --> 00:32:52,760 Speaker 1: killer app and that did it right? You know, there's 654 00:32:52,800 --> 00:32:54,680 Speaker 1: there's none There's not something like that that I can 655 00:32:54,800 --> 00:32:58,440 Speaker 1: point to. What we have are just looking at the 656 00:32:58,600 --> 00:33:01,120 Speaker 1: trends historically. And this is the benefit of being a 657 00:33:01,200 --> 00:33:03,920 Speaker 1: quant which is I've got ninety two years Dad, I don't. 658 00:33:03,920 --> 00:33:06,040 Speaker 1: I might not have ninety two years of experience, but 659 00:33:06,120 --> 00:33:08,800 Speaker 1: I have ninety two years of data and the ability 660 00:33:08,840 --> 00:33:12,640 Speaker 1: to look with a long historical lens and tie periods 661 00:33:12,680 --> 00:33:17,080 Speaker 1: together and look at what happened, and this idea of yes, 662 00:33:17,160 --> 00:33:20,360 Speaker 1: there are clusters of technological innovation, and yes we're living 663 00:33:20,400 --> 00:33:22,120 Speaker 1: through one of those now right. So at the very least, 664 00:33:22,120 --> 00:33:24,800 Speaker 1: it's giving perspective of we had a period of time 665 00:33:24,800 --> 00:33:27,160 Speaker 1: work growth outperformed value and then it shifted back to 666 00:33:27,200 --> 00:33:29,200 Speaker 1: value out performing growth for a long period of time, 667 00:33:29,280 --> 00:33:31,680 Speaker 1: right and similar So at the very least, that's one perspective. 668 00:33:31,720 --> 00:33:34,080 Speaker 1: If you think there are similarities between those time frames, 669 00:33:34,840 --> 00:33:36,920 Speaker 1: then you know that's one that can give you confidence 670 00:33:36,960 --> 00:33:38,760 Speaker 1: that there was a time frame before where it didn't 671 00:33:38,760 --> 00:33:40,880 Speaker 1: work and then it reverted back. We're living with those 672 00:33:40,960 --> 00:33:43,080 Speaker 1: right now, and there's a chance that I believe a 673 00:33:43,120 --> 00:33:45,640 Speaker 1: strong chance that I will revert back. For the specific 674 00:33:45,720 --> 00:33:48,120 Speaker 1: catalysts on it, we look to a couple of things. 675 00:33:48,200 --> 00:33:50,080 Speaker 1: One is going to be that you see the formation 676 00:33:50,120 --> 00:33:52,720 Speaker 1: of the again, those oligopolies, the winners come out, the 677 00:33:52,800 --> 00:33:55,880 Speaker 1: standards are set. Normal companies, like I say of the 678 00:33:56,080 --> 00:33:59,520 Speaker 1: previous regime, adopt the broad technology and they start having 679 00:33:59,560 --> 00:34:02,200 Speaker 1: it where they participate. And what is the economic boon 680 00:34:02,280 --> 00:34:05,240 Speaker 1: that's created by these new technologies. Yeah, I think about 681 00:34:05,520 --> 00:34:07,680 Speaker 1: Walmart is a good example of a company that a 682 00:34:07,760 --> 00:34:12,720 Speaker 1: lot of people view is actually getting subtraction against Amazon 683 00:34:12,840 --> 00:34:16,640 Speaker 1: for the first time ever. Alright, well, we're going to 684 00:34:16,760 --> 00:34:21,200 Speaker 1: leave it there then, Chris Meredith of O'Shaughnessy Asset Management, 685 00:34:21,239 --> 00:34:37,239 Speaker 1: thanks so much for being on now. Thank you so, Joe. 686 00:34:37,360 --> 00:34:40,640 Speaker 1: One thing I sometimes think about um when we're talking 687 00:34:40,640 --> 00:34:43,840 Speaker 1: about value investing is just like the perception of a 688 00:34:43,920 --> 00:34:47,000 Speaker 1: lot of the value companies as being a bit old fashioned. 689 00:34:47,320 --> 00:34:50,840 Speaker 1: You know, they often make things or produced services, and 690 00:34:51,360 --> 00:34:54,160 Speaker 1: they take up a lot of fixed capital, and when 691 00:34:54,200 --> 00:34:57,239 Speaker 1: you get into a late economic cycle, I think people 692 00:34:57,320 --> 00:34:59,160 Speaker 1: start to think that those companies are going to have 693 00:34:59,480 --> 00:35:04,240 Speaker 1: a really hard timed adapting in a recession or lowering 694 00:35:04,320 --> 00:35:07,480 Speaker 1: their costs. So I often wonder whether or not value 695 00:35:07,520 --> 00:35:10,560 Speaker 1: investings under performance over the past decade or so is 696 00:35:10,640 --> 00:35:14,480 Speaker 1: just about people continuously thinking we're late in the cycle. 697 00:35:15,160 --> 00:35:19,160 Speaker 1: It definitely feels as though the while this cycle or 698 00:35:19,200 --> 00:35:21,879 Speaker 1: this expansion has been one of the longest ever, people 699 00:35:21,960 --> 00:35:24,080 Speaker 1: have been skeptical on it from day one, so people 700 00:35:24,120 --> 00:35:26,960 Speaker 1: were probably calling it late cycle from like two thousand 701 00:35:27,040 --> 00:35:30,799 Speaker 1: eleven or maybe earlier. So there probably is something too 702 00:35:30,880 --> 00:35:34,320 Speaker 1: that I really like the discussion because I think, you know, 703 00:35:34,600 --> 00:35:37,400 Speaker 1: it helps to uh get into sort of some of 704 00:35:37,440 --> 00:35:39,319 Speaker 1: the meat and potatoes of what we talked about when 705 00:35:39,360 --> 00:35:42,400 Speaker 1: we talk about quant stuff or even even value investing 706 00:35:42,680 --> 00:35:45,400 Speaker 1: terms that we throw around, But what are the actual 707 00:35:45,840 --> 00:35:49,000 Speaker 1: component of the trade, What are the signals people are 708 00:35:49,040 --> 00:35:53,080 Speaker 1: trying to find in the data? And you know, it's 709 00:35:53,160 --> 00:35:57,040 Speaker 1: really tempting at a time when Netflix and Facebook are 710 00:35:57,080 --> 00:36:00,160 Speaker 1: ascendant to say, oh, you know, the old company, these 711 00:36:00,160 --> 00:36:02,120 Speaker 1: are doomed and buy the new stuff and sell the 712 00:36:02,160 --> 00:36:05,640 Speaker 1: old stuff. And it takes a lot of discipline. Um 713 00:36:05,680 --> 00:36:07,480 Speaker 1: and some might say it's foolish discipline, but it takes 714 00:36:07,480 --> 00:36:09,799 Speaker 1: a lot of discipline to not just sort of say, oh, 715 00:36:10,080 --> 00:36:12,920 Speaker 1: there's a new paradigm, you gotta dump everything. Yeah, And 716 00:36:13,120 --> 00:36:15,279 Speaker 1: I think, I mean that's basically the crux of this 717 00:36:15,320 --> 00:36:18,320 Speaker 1: whole discussion, right, like is it a cyclical downturn for 718 00:36:18,480 --> 00:36:21,520 Speaker 1: value investing or is it structural? And just on the 719 00:36:21,840 --> 00:36:24,640 Speaker 1: structural point, I mean, there are quite a few things 720 00:36:24,960 --> 00:36:27,560 Speaker 1: that are different this time, one of which is the 721 00:36:27,600 --> 00:36:30,000 Speaker 1: fact that this has been going on for twelve years, 722 00:36:30,080 --> 00:36:32,399 Speaker 1: which I think is unprecedented. But the other big thing 723 00:36:32,520 --> 00:36:36,600 Speaker 1: is if you think that financials are the big underperformers 724 00:36:36,800 --> 00:36:41,120 Speaker 1: of the value investing bucket. In recent years, financials do 725 00:36:41,280 --> 00:36:45,320 Speaker 1: seem to be facing some sort of permanent headwinds to 726 00:36:45,600 --> 00:36:47,839 Speaker 1: their business model, one of which, of course, is low 727 00:36:47,920 --> 00:36:50,440 Speaker 1: interest rates. Right, yeah, Now, I mean this is why 728 00:36:50,520 --> 00:36:52,640 Speaker 1: the debate is so interesting, because I feel like you 729 00:36:52,680 --> 00:36:55,880 Speaker 1: could just go back and forth and make really compelling 730 00:36:55,960 --> 00:37:01,320 Speaker 1: cases either for this time is different or it feels different, 731 00:37:01,760 --> 00:37:05,400 Speaker 1: but it's felt different before. This is sort of like 732 00:37:05,480 --> 00:37:08,279 Speaker 1: the known unknowns quote. We'll have to follow up with 733 00:37:08,400 --> 00:37:10,080 Speaker 1: Chris and ten years and then I think we'll have 734 00:37:10,160 --> 00:37:14,040 Speaker 1: a definitive answer to the debate. Well maybe, or maybe 735 00:37:14,160 --> 00:37:16,759 Speaker 1: we'll still be talking about under performance then who knows? Um? 736 00:37:17,320 --> 00:37:19,239 Speaker 1: All right, shall we leave it there? Let's leave it there, 737 00:37:19,880 --> 00:37:22,560 Speaker 1: all right? This has been another episode of the ad 738 00:37:22,680 --> 00:37:25,520 Speaker 1: Thoughts podcast. I'm Tracy Alloway. You can follow me on 739 00:37:25,680 --> 00:37:28,800 Speaker 1: Twitter at Tracy Alloway and I'm Joe wisn't All. You 740 00:37:28,880 --> 00:37:31,640 Speaker 1: can follow me on Twitter at the Stalwart, and you 741 00:37:31,640 --> 00:37:35,040 Speaker 1: should follow our guest on Twitter, Chris Meredith. He's at 742 00:37:35,160 --> 00:37:38,839 Speaker 1: Chris Meredith twenty three. And be sure to follow our 743 00:37:38,880 --> 00:37:43,080 Speaker 1: producer on Twitter, Laura Carlson. She's at Laura m Carlson, 744 00:37:43,280 --> 00:37:46,560 Speaker 1: as well as the Bloomberg head of podcasts, Francesca Leavi 745 00:37:46,920 --> 00:37:50,480 Speaker 1: at Francesca Today and check out the new home of 746 00:37:50,520 --> 00:37:55,240 Speaker 1: Bloomberg podcast on Twitter with the handle at podcasts. Thanks 747 00:37:55,280 --> 00:38:00,239 Speaker 1: for listening to