1 00:00:10,840 --> 00:00:14,280 Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast. 2 00:00:14,360 --> 00:00:19,560 Speaker 1: I'm Tracy Allaway and I'm Joey. Isn't all so, Joe. 3 00:00:19,680 --> 00:00:23,840 Speaker 1: It's been a while since we've talked about passive investing, 4 00:00:24,120 --> 00:00:27,320 Speaker 1: and I can't decide if that's just because um, so 5 00:00:27,400 --> 00:00:30,280 Speaker 1: much else has been going on in the world, including 6 00:00:30,320 --> 00:00:36,559 Speaker 1: a global pandemic, or if it's because passive investing itself 7 00:00:36,800 --> 00:00:40,960 Speaker 1: seems to have gotten a little boring, like it doesn't 8 00:00:41,000 --> 00:00:44,480 Speaker 1: feel like there's that much happening in the space. Well, 9 00:00:44,560 --> 00:00:47,360 Speaker 1: I know I've said it before, and I don't remember 10 00:00:47,360 --> 00:00:48,879 Speaker 1: the last thing we talked about it, but I know 11 00:00:48,920 --> 00:00:51,880 Speaker 1: I've said it before that in the post Great Financial 12 00:00:51,920 --> 00:00:55,280 Speaker 1: Crisis period, it felt like there was just this overwhelming 13 00:00:55,360 --> 00:00:58,360 Speaker 1: message and there's like through the media and marketing and 14 00:00:58,400 --> 00:01:02,480 Speaker 1: academic research, it's like just go passive, just go you know, 15 00:01:02,560 --> 00:01:06,240 Speaker 1: index whatever, forget about your investments. And it really feels 16 00:01:06,240 --> 00:01:09,480 Speaker 1: like in the last couple of years, even before the pandemic, 17 00:01:09,480 --> 00:01:12,399 Speaker 1: but now especially since the pandemic, it's like there's been 18 00:01:12,480 --> 00:01:16,640 Speaker 1: the like revenge of active management and individual stock selection 19 00:01:16,680 --> 00:01:19,000 Speaker 1: and robin hood and crypto and all that, and it's 20 00:01:19,040 --> 00:01:23,600 Speaker 1: like this repressed desire to trade and invest in individual names. 21 00:01:23,600 --> 00:01:25,880 Speaker 1: It just come like raging back. So I guess that 22 00:01:26,040 --> 00:01:27,759 Speaker 1: sort of asked the question. It's like, okay, well then 23 00:01:27,800 --> 00:01:31,200 Speaker 1: like where does where does the passive fit in? Now? Yeah, totally. 24 00:01:31,240 --> 00:01:33,120 Speaker 1: And the other thing I've been thinking about, just on 25 00:01:33,160 --> 00:01:37,600 Speaker 1: that point, about the message about investing in passive like 26 00:01:37,680 --> 00:01:39,800 Speaker 1: when you start to break it down, this idea of 27 00:01:40,000 --> 00:01:43,560 Speaker 1: just pour all your money into an SMP E t 28 00:01:43,720 --> 00:01:46,880 Speaker 1: F like spy, you know, something like that. If you 29 00:01:46,959 --> 00:01:50,920 Speaker 1: think about it, that's basically telling you to invest your 30 00:01:50,920 --> 00:01:55,200 Speaker 1: money in a technology, like a fun technology that can 31 00:01:55,240 --> 00:01:59,560 Speaker 1: trace its origins back to the early And it's kind 32 00:01:59,560 --> 00:02:02,720 Speaker 1: of crazy with all the technological advances that we've seen 33 00:02:02,760 --> 00:02:07,240 Speaker 1: since then, that the biggest um or the most prominent 34 00:02:07,280 --> 00:02:11,800 Speaker 1: advice is to just dump everything in an E t F. Yeah. 35 00:02:11,840 --> 00:02:14,799 Speaker 1: I like your characterizatione that as a technology, and this 36 00:02:14,880 --> 00:02:17,120 Speaker 1: is something that I think about a lot. Like, Okay, 37 00:02:17,160 --> 00:02:22,200 Speaker 1: we call say index investing passive investing, and it's pretty passive. 38 00:02:22,720 --> 00:02:25,560 Speaker 1: But prior to the advent of the index fund and 39 00:02:25,639 --> 00:02:28,000 Speaker 1: especially like E t F, it was not like a 40 00:02:28,040 --> 00:02:31,240 Speaker 1: trivial thing to do. So the academic research might say, 41 00:02:31,360 --> 00:02:33,560 Speaker 1: by the SNP or by some big basket and forget 42 00:02:33,600 --> 00:02:37,040 Speaker 1: about it. But prior to like some easy way to 43 00:02:37,160 --> 00:02:39,440 Speaker 1: just sort of automatic that like that was not actually 44 00:02:39,440 --> 00:02:42,720 Speaker 1: like a strategy an individual could do. No individual is 45 00:02:42,800 --> 00:02:46,520 Speaker 1: going to like buy all stocks in the SPI and 46 00:02:46,560 --> 00:02:49,359 Speaker 1: re waste com early day and you know, so it's 47 00:02:49,400 --> 00:02:52,760 Speaker 1: like there, it is kind of like a technological breakthrough 48 00:02:53,200 --> 00:02:56,079 Speaker 1: that that happened that we sort of take for granted totally. 49 00:02:56,280 --> 00:02:58,760 Speaker 1: So on that note, today we're going to be talking 50 00:02:58,800 --> 00:03:00,880 Speaker 1: about what a lot of people are saying, is the 51 00:03:00,919 --> 00:03:04,880 Speaker 1: next technological breakthrough in fund management or the next big 52 00:03:04,919 --> 00:03:09,359 Speaker 1: advancement um something that is definitely not boring but does 53 00:03:09,480 --> 00:03:12,440 Speaker 1: count as passive investing sort of as we'll get into 54 00:03:12,880 --> 00:03:16,040 Speaker 1: we're gonna be talking about custom indexing, and there's been 55 00:03:16,080 --> 00:03:20,320 Speaker 1: a lot of action and deals in that space recently, right, 56 00:03:20,360 --> 00:03:22,680 Speaker 1: And of course this gets to the question of like 57 00:03:23,320 --> 00:03:25,680 Speaker 1: you knows again, I think this is something you've pointed 58 00:03:25,720 --> 00:03:29,600 Speaker 1: out a lot. You could buy the sp it's passive ish, 59 00:03:29,680 --> 00:03:32,880 Speaker 1: but you're sort of outsourcing the indexing question or the 60 00:03:32,880 --> 00:03:36,080 Speaker 1: management question to whoever you know in that case, the 61 00:03:36,080 --> 00:03:38,160 Speaker 1: Committee of S and P or if you buy an 62 00:03:38,240 --> 00:03:41,920 Speaker 1: MSc I index, the you're outsourcing investment decisions to mbs 63 00:03:41,920 --> 00:03:44,760 Speaker 1: C I, so what is the future of like essentially 64 00:03:45,160 --> 00:03:49,520 Speaker 1: designing the index exactly? So we have the best guests 65 00:03:49,520 --> 00:03:51,280 Speaker 1: to talk about it, We're going to be speaking with 66 00:03:51,320 --> 00:03:55,840 Speaker 1: Patrick O'Shaughnessy. He's the CEO over at A Shaughnessy Asset Management, 67 00:03:55,880 --> 00:04:00,000 Speaker 1: of course, also the chairman at Colossus and general partner 68 00:04:00,080 --> 00:04:03,960 Speaker 1: or n CEO at Positive Some And in addition to that, 69 00:04:04,080 --> 00:04:07,040 Speaker 1: he is also the host of the invest Like the 70 00:04:07,080 --> 00:04:10,880 Speaker 1: Best podcast. So a fellow podcaster, Patrick, thank you so 71 00:04:10,960 --> 00:04:13,520 Speaker 1: much for coming on. I'm really delighted to be here. 72 00:04:13,520 --> 00:04:15,480 Speaker 1: I love love this show, so thank you for having me. 73 00:04:16,560 --> 00:04:19,480 Speaker 1: Thank you. So maybe just to begin with, we should 74 00:04:19,520 --> 00:04:23,200 Speaker 1: start with the obvious question, uh, and I should mention 75 00:04:23,320 --> 00:04:26,880 Speaker 1: here that your company, oh Sam, it has its own 76 00:04:27,040 --> 00:04:32,080 Speaker 1: custom indexing platform called Canvas. What exactly is a custom 77 00:04:32,160 --> 00:04:36,880 Speaker 1: index and what does your platform do? Sure? Thank you 78 00:04:36,920 --> 00:04:40,040 Speaker 1: for having me. I love where you started the conversation 79 00:04:40,080 --> 00:04:43,080 Speaker 1: around technology and innovation and that's how I think about 80 00:04:43,240 --> 00:04:46,640 Speaker 1: this entire story. And custom indexing is just one point 81 00:04:46,880 --> 00:04:49,320 Speaker 1: in in the timeline. And I think you raised the 82 00:04:49,360 --> 00:04:51,240 Speaker 1: right ones. Which are I think of as a code? 83 00:04:51,240 --> 00:04:54,040 Speaker 1: I think of code mingled funds as a technology or innovation. 84 00:04:54,120 --> 00:04:57,200 Speaker 1: I think of Vanguard's mutual structure that allowed for much 85 00:04:57,200 --> 00:05:00,719 Speaker 1: lower cost for investors as a great innovation in this timeline. 86 00:05:00,880 --> 00:05:03,279 Speaker 1: Ditto for E t F s. I think custom indexing 87 00:05:03,400 --> 00:05:06,960 Speaker 1: is just the next natural uh stop in that journey. 88 00:05:07,040 --> 00:05:10,159 Speaker 1: And when I say journey, I mean better, cheaper, more 89 00:05:10,200 --> 00:05:15,120 Speaker 1: convenient investing, more tailored investing for each individual investor. So 90 00:05:15,320 --> 00:05:17,680 Speaker 1: in the past, it's E t f s in general 91 00:05:17,680 --> 00:05:19,839 Speaker 1: and just index funds in general have been sort of 92 00:05:19,880 --> 00:05:21,520 Speaker 1: like the model T You can have any color you 93 00:05:21,520 --> 00:05:23,919 Speaker 1: want as long as it's black. And I think that 94 00:05:24,080 --> 00:05:26,359 Speaker 1: is obviously going to change, and the reason it's going 95 00:05:26,400 --> 00:05:29,280 Speaker 1: to change is because of technology. So I always like 96 00:05:29,360 --> 00:05:32,040 Speaker 1: to look at what I call directional arrows of progress, 97 00:05:32,040 --> 00:05:34,680 Speaker 1: the term I learned from my friend Josh Wolfe, and 98 00:05:34,880 --> 00:05:37,360 Speaker 1: see where the world's going. So we already know that 99 00:05:37,520 --> 00:05:40,120 Speaker 1: trading is now free thanks to Robin Hood and all 100 00:05:40,120 --> 00:05:42,760 Speaker 1: the other brokerages that have followed suit. We know that 101 00:05:42,800 --> 00:05:45,640 Speaker 1: the cost of operating your own separate account in at 102 00:05:45,640 --> 00:05:49,080 Speaker 1: a brokerage like a Schwab or wherever is falling in 103 00:05:49,200 --> 00:05:51,920 Speaker 1: cost every single year for asset managers like us that 104 00:05:51,920 --> 00:05:54,120 Speaker 1: that work with those firms, and we know that in 105 00:05:54,160 --> 00:05:57,400 Speaker 1: the future we're gonna have fully fractionalized shares. So the 106 00:05:57,640 --> 00:06:00,920 Speaker 1: all three of those were huge impediments to owning your 107 00:06:00,960 --> 00:06:04,280 Speaker 1: own basket of stocks directly, not through a fond or 108 00:06:04,279 --> 00:06:07,560 Speaker 1: any t f but directly, and all those cost curves 109 00:06:07,640 --> 00:06:10,160 Speaker 1: are either at zero or going towards zero, or going 110 00:06:10,160 --> 00:06:12,760 Speaker 1: to be very possible. And in a world where it 111 00:06:12,800 --> 00:06:15,000 Speaker 1: doesn't cost anything to trade, it costs very little to 112 00:06:15,040 --> 00:06:17,440 Speaker 1: have a brokerage account and have an asset manager like 113 00:06:17,640 --> 00:06:20,760 Speaker 1: us or a black Rock or a Vanguard whoever, trade 114 00:06:20,760 --> 00:06:23,600 Speaker 1: on your behalf, and you can own fractional shares. What 115 00:06:23,760 --> 00:06:26,800 Speaker 1: seems really obvious to me in that world is this 116 00:06:26,880 --> 00:06:29,480 Speaker 1: idea of custom indexing, a term that that I'm proud 117 00:06:29,520 --> 00:06:32,440 Speaker 1: that we we coined a couple of years back. And 118 00:06:32,800 --> 00:06:34,960 Speaker 1: this the idea is very simple, which is that why 119 00:06:35,040 --> 00:06:37,919 Speaker 1: why should everybody own the same five stocks in the 120 00:06:38,000 --> 00:06:40,960 Speaker 1: SMP five hundred. Why wouldn't it be easy to adjust 121 00:06:41,040 --> 00:06:43,960 Speaker 1: for little things and big things such as I don't 122 00:06:44,000 --> 00:06:46,520 Speaker 1: want to own stocks with certain characteristics. For me, I 123 00:06:46,560 --> 00:06:49,239 Speaker 1: work in capital markets, as you just mentioned my my CV, 124 00:06:49,680 --> 00:06:52,320 Speaker 1: I don't really want to own more capital markets exposure. 125 00:06:52,320 --> 00:06:54,320 Speaker 1: I've got plenty of that in my human capital in 126 00:06:54,360 --> 00:06:56,520 Speaker 1: my day to day job. I don't want to own 127 00:06:56,520 --> 00:06:59,040 Speaker 1: tobacco stocks. That's just a personal thing for me. It's 128 00:06:59,040 --> 00:07:00,600 Speaker 1: a very small part of market cap, but I don't 129 00:07:00,640 --> 00:07:03,320 Speaker 1: want them. Very easy to adjust for in something like 130 00:07:03,360 --> 00:07:07,359 Speaker 1: a custom index. Perhaps the most important thing that custom 131 00:07:07,400 --> 00:07:10,560 Speaker 1: and also direct indexing unlocks is the ability to do 132 00:07:10,600 --> 00:07:13,720 Speaker 1: better after taxes as well. What we've learned is that 133 00:07:14,160 --> 00:07:17,960 Speaker 1: everybody has a very specific and personal tax situation. No 134 00:07:18,000 --> 00:07:21,160 Speaker 1: one likes paying taxes. Everyone wants a better after tax return. 135 00:07:21,240 --> 00:07:22,960 Speaker 1: That's the if you ask me. That's one of the 136 00:07:23,000 --> 00:07:25,640 Speaker 1: key geniuses of the index fund is that it's low turnover, 137 00:07:25,720 --> 00:07:28,040 Speaker 1: so you don't have a huge tax bill when you 138 00:07:28,080 --> 00:07:30,960 Speaker 1: own SPY or own Vanguards Total Market d t F 139 00:07:31,320 --> 00:07:33,480 Speaker 1: or fund or something like this. What you can do 140 00:07:33,520 --> 00:07:35,840 Speaker 1: when you own each of the underlying securities let's just 141 00:07:35,840 --> 00:07:39,160 Speaker 1: stick with the SMP five, is you can sell positions 142 00:07:39,200 --> 00:07:41,120 Speaker 1: that are at a loss and you can use that 143 00:07:41,200 --> 00:07:44,200 Speaker 1: loss to offset gains elsewhere in your portfolio and actually 144 00:07:44,200 --> 00:07:47,040 Speaker 1: come out ahead on an after tax basis. We call 145 00:07:47,120 --> 00:07:49,520 Speaker 1: this tax loss harvesting. It's been around for a while, 146 00:07:49,600 --> 00:07:51,720 Speaker 1: typically for just the very very wealthy because you need 147 00:07:51,800 --> 00:07:55,280 Speaker 1: very big accounts. But again, as the costs fall, this 148 00:07:55,640 --> 00:07:59,360 Speaker 1: opportunity to create losses and create better after tax returns 149 00:07:59,600 --> 00:08:03,679 Speaker 1: will to you know, more mass market uh individuals as well. 150 00:08:03,960 --> 00:08:07,040 Speaker 1: So custom indexing is the prospect of why would I 151 00:08:07,160 --> 00:08:10,280 Speaker 1: have the same strategy as everybody else when my circumstances, 152 00:08:10,360 --> 00:08:13,560 Speaker 1: my preferences are different, They're unique to me. And I 153 00:08:13,560 --> 00:08:17,080 Speaker 1: think personalization is a big trend, not just in in investing, 154 00:08:17,080 --> 00:08:19,640 Speaker 1: but in everywhere writing, whether it's in clothing or other 155 00:08:19,680 --> 00:08:22,560 Speaker 1: areas of technology, and that that will come to investing. 156 00:08:22,560 --> 00:08:24,400 Speaker 1: Two and and you know, we're proud to be at 157 00:08:24,440 --> 00:08:27,320 Speaker 1: sort of the vanguard of pun intended of the custom 158 00:08:27,360 --> 00:08:29,920 Speaker 1: indexing trend. So I sort of hinted at this in 159 00:08:29,960 --> 00:08:31,960 Speaker 1: the beginning, and there's always this debate and you see 160 00:08:31,960 --> 00:08:36,480 Speaker 1: it on Twitter elsewhere. It's like this passive investing actually exist. 161 00:08:37,040 --> 00:08:39,960 Speaker 1: And by that it's like, Okay, uh, is the S 162 00:08:40,000 --> 00:08:42,040 Speaker 1: and P If you buy S P Y, is that 163 00:08:42,120 --> 00:08:44,880 Speaker 1: truly passive? Because Okay, that's only five stocks and there 164 00:08:44,880 --> 00:08:48,240 Speaker 1: are thousands of stocks. Committee had to select them. And 165 00:08:48,280 --> 00:08:50,480 Speaker 1: the way I think about this question is that it's 166 00:08:50,520 --> 00:08:53,000 Speaker 1: sort of a false binary, and that there's like basically 167 00:08:53,040 --> 00:08:56,480 Speaker 1: a spectrum, and that buying the SMP five or buying 168 00:08:56,559 --> 00:08:59,480 Speaker 1: spy is you know, just like buying a little bit 169 00:08:59,520 --> 00:09:01,679 Speaker 1: every month or never, say, more passive than some other 170 00:09:01,720 --> 00:09:04,280 Speaker 1: strategy where you try to like pick twenty stocks or whatever. 171 00:09:04,360 --> 00:09:08,439 Speaker 1: And it sounds like to me that with customer indexing, 172 00:09:09,080 --> 00:09:12,880 Speaker 1: it's basically just adjusting where you are on the spectrum 173 00:09:12,920 --> 00:09:15,360 Speaker 1: a little bit. And so rather than going hole hog 174 00:09:15,400 --> 00:09:17,800 Speaker 1: into some sort of like or trying to beat the market, 175 00:09:17,880 --> 00:09:20,319 Speaker 1: it's okay, let's take the premise that for the most 176 00:09:20,400 --> 00:09:23,439 Speaker 1: part we want to just sort of buy something general 177 00:09:23,559 --> 00:09:27,080 Speaker 1: and stable and diversified, but it can be tweaked a 178 00:09:27,120 --> 00:09:30,360 Speaker 1: little bit to get some sort of different returns while 179 00:09:30,440 --> 00:09:34,640 Speaker 1: still maintaining the gist of the benefits of wide diversification 180 00:09:34,840 --> 00:09:38,360 Speaker 1: and avoiding some market timing. Yeah. I think this. I 181 00:09:38,400 --> 00:09:41,760 Speaker 1: think this whole committee thing whenever I hear the committee 182 00:09:41,760 --> 00:09:43,720 Speaker 1: at SMP brought up, I sort of laugh. It's just 183 00:09:43,840 --> 00:09:46,760 Speaker 1: it's it's I think it's a very strange argument for 184 00:09:46,760 --> 00:09:49,480 Speaker 1: people to spend any of their time on because if 185 00:09:49,520 --> 00:09:52,319 Speaker 1: instead of uh, using the quote unquote committee, you just 186 00:09:52,360 --> 00:09:55,360 Speaker 1: bought the top five stocks by market cap, it's the 187 00:09:55,400 --> 00:09:59,400 Speaker 1: exact same return. It's the exact same return, and and 188 00:09:59,400 --> 00:10:01,520 Speaker 1: and so I think the key thing here is you 189 00:10:01,559 --> 00:10:04,600 Speaker 1: want to own roughly the market in its market cap 190 00:10:04,600 --> 00:10:08,400 Speaker 1: weights roughly to get the market return, and even if 191 00:10:08,440 --> 00:10:11,440 Speaker 1: you deviate that from that, whether it's via committee or 192 00:10:11,520 --> 00:10:14,160 Speaker 1: via a fancy term stratified sampling, which is what a 193 00:10:14,160 --> 00:10:16,320 Speaker 1: lot of firms like us do, where you own most 194 00:10:16,320 --> 00:10:18,000 Speaker 1: of the securities in the market, but you don't need 195 00:10:18,040 --> 00:10:20,280 Speaker 1: to own them all. You know, the the last ten 196 00:10:20,320 --> 00:10:23,560 Speaker 1: stocks in the SMP make up a tiny miniscule weight 197 00:10:23,720 --> 00:10:27,000 Speaker 1: even combined, and not owning them will not materially change 198 00:10:27,280 --> 00:10:30,000 Speaker 1: your overall return. So I think the key here is 199 00:10:30,080 --> 00:10:32,160 Speaker 1: you want to be broadly diversified. You want to roughly 200 00:10:32,200 --> 00:10:35,120 Speaker 1: look like the market. But with customer indexing you can 201 00:10:35,160 --> 00:10:38,560 Speaker 1: then also make these adjustments and and you'll, yeah, you'll 202 00:10:38,559 --> 00:10:40,199 Speaker 1: perform a little bit differently, but that's sort of the 203 00:10:40,240 --> 00:10:43,120 Speaker 1: trade you're willing to make to customize something to your 204 00:10:43,160 --> 00:10:46,760 Speaker 1: specific circumstances and preferences. Again, so in my view this 205 00:10:46,880 --> 00:10:49,960 Speaker 1: all these arguments about like what is passive are just silly. 206 00:10:49,960 --> 00:10:52,600 Speaker 1: I mean, technically passive would just be a market cap 207 00:10:52,640 --> 00:10:55,320 Speaker 1: weighted total market every stock in the market um for 208 00:10:55,360 --> 00:10:58,320 Speaker 1: equities globally, but most of the things that people argue 209 00:10:58,360 --> 00:11:01,720 Speaker 1: about look very very close to that. So this feeds 210 00:11:01,760 --> 00:11:04,880 Speaker 1: into something I wanted to ask you. But with custom indexing, 211 00:11:05,440 --> 00:11:09,880 Speaker 1: what do people actually benchmark themselves against? Or does it 212 00:11:10,000 --> 00:11:14,800 Speaker 1: not really matter anymore? Like does your performance compared to 213 00:11:15,200 --> 00:11:18,200 Speaker 1: a broader index or a specific index like just not 214 00:11:18,320 --> 00:11:22,280 Speaker 1: come into the equation as much. So there's two ways 215 00:11:22,280 --> 00:11:24,440 Speaker 1: to do it, and they're both very very simple. One 216 00:11:24,520 --> 00:11:26,520 Speaker 1: is just to use a broad market index. It could 217 00:11:26,520 --> 00:11:28,680 Speaker 1: be the Russell three thousand, and it could be you know, 218 00:11:28,720 --> 00:11:32,760 Speaker 1: pick your pick your broad benchmark that's market cap weighted 219 00:11:32,800 --> 00:11:35,559 Speaker 1: and very simple to understand. The second would be sort 220 00:11:35,600 --> 00:11:38,040 Speaker 1: of a custom benchmark, and this would be used by 221 00:11:38,200 --> 00:11:41,240 Speaker 1: people who have a very clear deviation from something like 222 00:11:41,280 --> 00:11:43,280 Speaker 1: the Russell three thousand. I'm gonna make up an example. 223 00:11:43,600 --> 00:11:49,560 Speaker 1: Let's say someone's custom index is large cap sixty small cap, 224 00:11:49,720 --> 00:11:52,040 Speaker 1: which that's not what the market looks like at all. 225 00:11:52,080 --> 00:11:55,120 Speaker 1: The markets like large cap five percent small cap by 226 00:11:55,160 --> 00:11:58,120 Speaker 1: market cap. In that scenario, it really wouldn't make sense 227 00:11:58,120 --> 00:12:00,520 Speaker 1: to compare your performance because in this case, you are 228 00:12:00,559 --> 00:12:04,120 Speaker 1: making a very active allocation decision to be way overweight 229 00:12:04,160 --> 00:12:06,480 Speaker 1: small cap. So in that case you might just blend 230 00:12:06,480 --> 00:12:09,240 Speaker 1: a benchmark and say, my benchmark is going to you know, 231 00:12:09,400 --> 00:12:13,840 Speaker 1: sp Russell two thousand or some other small cap benchmark. 232 00:12:14,120 --> 00:12:18,240 Speaker 1: But in every case you're you're using simple, easy to understand, 233 00:12:18,400 --> 00:12:21,960 Speaker 1: broad market benchmarks in some combination or or alone to 234 00:12:22,120 --> 00:12:41,600 Speaker 1: use as your reference for how you're performing. I'm really 235 00:12:41,679 --> 00:12:44,960 Speaker 1: interested in what you said about, you know, if you 236 00:12:45,040 --> 00:12:46,880 Speaker 1: work in capital markets, or if you work in a 237 00:12:46,920 --> 00:12:49,840 Speaker 1: bank in some sort and you own bank stock to 238 00:12:49,840 --> 00:12:52,200 Speaker 1: your kind of like you know, you're kind of doing 239 00:12:52,240 --> 00:12:55,320 Speaker 1: the Texas hedge of betting on a sector that is 240 00:12:55,360 --> 00:12:58,560 Speaker 1: already probably responsible for a lot of your annual income, 241 00:12:59,480 --> 00:13:02,440 Speaker 1: and and so it maybe it may not make sense. 242 00:13:02,440 --> 00:13:04,280 Speaker 1: Can you talk a little bit more. I've always wondered 243 00:13:04,320 --> 00:13:08,959 Speaker 1: about this whether financial advisors think about this question and 244 00:13:09,000 --> 00:13:10,760 Speaker 1: when you and it's because i'd something I just like 245 00:13:10,800 --> 00:13:12,760 Speaker 1: popped into my head before, and that's the first time 246 00:13:12,760 --> 00:13:15,800 Speaker 1: I've heard someone talk about this and tailoring a portfolio 247 00:13:15,920 --> 00:13:19,120 Speaker 1: around someone's um, you know, normal income. Can you talk 248 00:13:19,160 --> 00:13:21,560 Speaker 1: a little bit more about how that's being used in 249 00:13:21,600 --> 00:13:25,440 Speaker 1: some of the ways you see that uh, potentially being used. Sure, so, 250 00:13:25,440 --> 00:13:28,319 Speaker 1: so what is the market but a collection of discounted 251 00:13:28,480 --> 00:13:30,920 Speaker 1: cash flows? You know, theoretically, and maybe there's some problems 252 00:13:30,960 --> 00:13:32,880 Speaker 1: with that conception, but if you look at the SMP five, 253 00:13:33,720 --> 00:13:35,560 Speaker 1: the value of each of those stocks and therefore of 254 00:13:35,600 --> 00:13:38,560 Speaker 1: your portfolio is the market's estimation of how all those 255 00:13:38,559 --> 00:13:40,679 Speaker 1: companies will do in the future, discounted at some rate 256 00:13:40,720 --> 00:13:43,040 Speaker 1: back to today, and that's that's the value of your portfolio. 257 00:13:43,400 --> 00:13:45,839 Speaker 1: Well why why should my human capital be any different 258 00:13:45,880 --> 00:13:48,640 Speaker 1: than that I've got, you know, fifty years or hopefully 259 00:13:48,640 --> 00:13:50,959 Speaker 1: more left to live and work, and there's going to 260 00:13:51,040 --> 00:13:53,560 Speaker 1: be cash flows that I generate from that. And when 261 00:13:53,559 --> 00:13:55,559 Speaker 1: I dig into where those cash flows are going to 262 00:13:55,640 --> 00:13:58,400 Speaker 1: come from, I couldn't be talking about what's one step 263 00:13:58,440 --> 00:14:01,040 Speaker 1: beyond the Texas hedge, like, wouldn't be more all in 264 00:14:01,760 --> 00:14:06,000 Speaker 1: on on capital markets, like the equity market specifically is 265 00:14:06,000 --> 00:14:09,240 Speaker 1: going to be a large determinant of how I do 266 00:14:09,559 --> 00:14:11,720 Speaker 1: in my human capital. So if I think of my 267 00:14:11,800 --> 00:14:14,560 Speaker 1: human capital as discounting my future cash flows into some 268 00:14:14,640 --> 00:14:17,319 Speaker 1: value today, often that is worth a lot more to 269 00:14:17,440 --> 00:14:20,920 Speaker 1: people than they're they're brokerage portfolio is if you actually 270 00:14:20,920 --> 00:14:23,520 Speaker 1: did the math and I certainly think it is in 271 00:14:23,520 --> 00:14:26,680 Speaker 1: my case, So why would I have more exposure to 272 00:14:26,920 --> 00:14:29,720 Speaker 1: the same risk profile that determines you know, a large 273 00:14:29,800 --> 00:14:32,720 Speaker 1: chunk of my human capital portfolio, let's call it. And 274 00:14:32,840 --> 00:14:36,120 Speaker 1: I think simple adjustments like that are just intuitive. It 275 00:14:36,200 --> 00:14:38,960 Speaker 1: just makes sense to me. Um. And you can certainly 276 00:14:38,960 --> 00:14:40,760 Speaker 1: demonstrate it, you know, if you if you do some 277 00:14:40,960 --> 00:14:43,720 Speaker 1: napkin math, you can say, yeah, like, I don't really like, 278 00:14:43,800 --> 00:14:45,680 Speaker 1: let's go back to oh eight, if I if I'm 279 00:14:45,720 --> 00:14:48,440 Speaker 1: working at Lehman. Uh, And it's a ridiculous example, of 280 00:14:48,480 --> 00:14:51,120 Speaker 1: course in hindsight. But if I'm working at Lehman, like, 281 00:14:51,160 --> 00:14:53,560 Speaker 1: it's pretty obvious where my risk is bundled up and 282 00:14:53,680 --> 00:14:55,760 Speaker 1: I don't want more of that same risk. So if 283 00:14:55,960 --> 00:14:59,040 Speaker 1: if indexing in part is great because of diversification, I 284 00:14:59,080 --> 00:15:01,280 Speaker 1: think this is just one way to add another asset 285 00:15:01,320 --> 00:15:04,200 Speaker 1: to the mix, which is your own, your own learnings. Yeah, 286 00:15:04,280 --> 00:15:06,040 Speaker 1: so Joe and I are going to have to steal 287 00:15:06,280 --> 00:15:11,080 Speaker 1: steer clear of financial data stocks. And actually that reminds 288 00:15:11,120 --> 00:15:14,040 Speaker 1: me no facts set for you. I should just mention 289 00:15:14,280 --> 00:15:18,120 Speaker 1: um that Bloomberg does have its own indexing business. In 290 00:15:18,160 --> 00:15:21,480 Speaker 1: the interests of transparency. Um. So now that I've got 291 00:15:21,480 --> 00:15:23,520 Speaker 1: that disclaimer out of the way. Um, one thing I 292 00:15:23,560 --> 00:15:26,320 Speaker 1: wanted to ask was, can you give us an example 293 00:15:26,480 --> 00:15:30,720 Speaker 1: of like the most interesting or unusual custom index that 294 00:15:31,040 --> 00:15:35,040 Speaker 1: you've seen in your time in the space. Sure, so, well, 295 00:15:35,200 --> 00:15:37,320 Speaker 1: I guess the first thing I would say, at an 296 00:15:37,320 --> 00:15:41,000 Speaker 1: even higher level is how popular customization is. So we 297 00:15:41,080 --> 00:15:43,160 Speaker 1: built this platform. It's a web it's software. It's a 298 00:15:43,200 --> 00:15:45,720 Speaker 1: web based platform. So you think about it like building 299 00:15:45,760 --> 00:15:47,440 Speaker 1: a car. So go to like Tesla dot com and 300 00:15:47,480 --> 00:15:49,880 Speaker 1: go through the experience of building a car. There's an 301 00:15:49,920 --> 00:15:52,400 Speaker 1: interior next year, you can you know, tune all these 302 00:15:52,440 --> 00:15:55,240 Speaker 1: old dials or choose options. It feels like that to 303 00:15:55,240 --> 00:15:58,320 Speaker 1: build a customer index with with a bit more options. 304 00:15:58,360 --> 00:16:01,480 Speaker 1: So we don't we don't anyone to do anything, you know, 305 00:16:01,560 --> 00:16:03,960 Speaker 1: the default, Our default would be that you buy the 306 00:16:04,000 --> 00:16:06,640 Speaker 1: broad market, right, that you don't do any customization, that 307 00:16:06,720 --> 00:16:08,800 Speaker 1: you just do low cost indexing, maybe with some tax 308 00:16:08,880 --> 00:16:12,080 Speaker 1: loss harvesting. And we went into this not knowing what 309 00:16:12,120 --> 00:16:14,720 Speaker 1: people would do with this platform. That's the beauty of platforms, 310 00:16:14,720 --> 00:16:16,680 Speaker 1: I think, is to be surprised by how they're used. 311 00:16:17,240 --> 00:16:18,920 Speaker 1: And now we're you know, a year and a half 312 00:16:19,240 --> 00:16:21,160 Speaker 1: click getting in on two years in, we're about two 313 00:16:21,160 --> 00:16:25,280 Speaker 1: billion in assets or approaching that number today on the platform, 314 00:16:25,520 --> 00:16:29,280 Speaker 1: and fully eight or so of the of the indexes 315 00:16:29,320 --> 00:16:31,960 Speaker 1: that are designed are completely unique, meaning they're not they 316 00:16:32,000 --> 00:16:35,200 Speaker 1: have they have different settings than any other custom index 317 00:16:35,240 --> 00:16:37,680 Speaker 1: that's been built to date on the platform. And I 318 00:16:37,680 --> 00:16:39,640 Speaker 1: would definitely I would have taken the under on that. 319 00:16:39,680 --> 00:16:42,400 Speaker 1: Had you set the line at will be fully customed, 320 00:16:42,760 --> 00:16:44,520 Speaker 1: I definitely would have said it's going to be way 321 00:16:44,560 --> 00:16:46,360 Speaker 1: less than that. There's going to be more you know, 322 00:16:46,440 --> 00:16:49,920 Speaker 1: clumpiness around what people do. So I guess the first 323 00:16:49,920 --> 00:16:53,040 Speaker 1: big point is like people really use the customization features, 324 00:16:53,440 --> 00:16:55,440 Speaker 1: and we we've been blown away by some of the 325 00:16:55,440 --> 00:16:58,760 Speaker 1: stuff that people ask us if they can adjust for UM. 326 00:16:58,880 --> 00:17:01,840 Speaker 1: So some thing's are in taxes, So they might say, 327 00:17:02,000 --> 00:17:05,560 Speaker 1: I want to pay zero dollars in capital gains gross. 328 00:17:06,000 --> 00:17:08,199 Speaker 1: I want you to generate a single gain for me. 329 00:17:08,240 --> 00:17:12,040 Speaker 1: I refused to pay taxes. Others might. Others have said, look, 330 00:17:12,080 --> 00:17:14,320 Speaker 1: we're willing to We're willing to spend a hundred thousand 331 00:17:14,359 --> 00:17:16,960 Speaker 1: dollars on capital gains taxes, so do everything you can 332 00:17:17,359 --> 00:17:20,520 Speaker 1: inside that absolute dollar budget. UM. One person came to 333 00:17:20,560 --> 00:17:22,919 Speaker 1: us and said, we don't want to own companies that 334 00:17:23,040 --> 00:17:26,879 Speaker 1: produce sugary drinks because one of our key focuses as 335 00:17:26,920 --> 00:17:31,640 Speaker 1: a family is to avoid or help ameliorate the obesity epidemic, 336 00:17:31,720 --> 00:17:34,000 Speaker 1: and we think sugary drinks are the prime culprit. So 337 00:17:34,040 --> 00:17:36,600 Speaker 1: we had to build a custom quantitative screen for that. 338 00:17:36,880 --> 00:17:39,399 Speaker 1: We've had people say, look, I've got all these and 339 00:17:39,400 --> 00:17:41,480 Speaker 1: this is a more advanced feature that wouldn't be broadly 340 00:17:41,480 --> 00:17:44,040 Speaker 1: available right now, but what we can do. We we've 341 00:17:44,080 --> 00:17:47,560 Speaker 1: got this huge private equity portfolio and clearly kind of 342 00:17:47,600 --> 00:17:49,639 Speaker 1: like the human capital example, I gave like, we've got 343 00:17:49,640 --> 00:17:52,720 Speaker 1: a lot of risk in these fifty portfolio companies, but 344 00:17:52,760 --> 00:17:55,080 Speaker 1: we don't really know how to map them onto public equities. 345 00:17:55,119 --> 00:17:56,879 Speaker 1: Can you do that? And that's where you know, the 346 00:17:56,920 --> 00:17:59,919 Speaker 1: fancier like machine learning modeling type stuff can come in 347 00:18:00,040 --> 00:18:02,600 Speaker 1: and create something really cool so that we can avoid 348 00:18:02,640 --> 00:18:05,640 Speaker 1: public equities that look very very similar when we model 349 00:18:05,720 --> 00:18:08,199 Speaker 1: them to the private equity portfolio. You know, that's just 350 00:18:08,240 --> 00:18:11,359 Speaker 1: four examples, but it's kind of constant, like every everyone 351 00:18:11,400 --> 00:18:13,880 Speaker 1: that we meet, every new client that we bring on, 352 00:18:14,359 --> 00:18:16,960 Speaker 1: has some new question in the form of you know, 353 00:18:17,000 --> 00:18:19,840 Speaker 1: can it also do X? And so I just think 354 00:18:19,840 --> 00:18:23,359 Speaker 1: what we're what we're seeing live is a huge latent 355 00:18:23,400 --> 00:18:27,040 Speaker 1: demand for customization that has gone unfulfilled for a long time, 356 00:18:27,080 --> 00:18:28,480 Speaker 1: so no one talks about it. But I think you'll 357 00:18:28,480 --> 00:18:30,920 Speaker 1: see an explosion of these platforms in the next couple 358 00:18:30,960 --> 00:18:34,520 Speaker 1: of years. Can you talk a little bit more about 359 00:18:34,640 --> 00:18:37,120 Speaker 1: the sort of I don't know, maybe it's trading tech 360 00:18:37,320 --> 00:18:39,880 Speaker 1: or the sort of like other platforms necessary to make 361 00:18:39,880 --> 00:18:43,520 Speaker 1: this work, because, as I mentioned in the introduction, you know, 362 00:18:43,680 --> 00:18:47,080 Speaker 1: even if you go back long enough, by even buying 363 00:18:47,160 --> 00:18:50,000 Speaker 1: just the straight up S ANDP five would would not 364 00:18:50,040 --> 00:18:52,879 Speaker 1: have been a trivial exercise at all for an individual. 365 00:18:52,920 --> 00:18:56,560 Speaker 1: No one can sort of like buys and rebalance them, etcetera. 366 00:18:56,760 --> 00:18:59,800 Speaker 1: And of course that got productized and now it's easy. 367 00:19:00,160 --> 00:19:01,800 Speaker 1: But like, okay, let's say I want to buy I 368 00:19:01,840 --> 00:19:05,480 Speaker 1: don't know how many financials are in the SMP five hundred, 369 00:19:05,560 --> 00:19:06,920 Speaker 1: but let's say I want to buy you know, four 370 00:19:07,000 --> 00:19:11,080 Speaker 1: hundred and sixty of the spire excluding all the financials. 371 00:19:11,480 --> 00:19:13,600 Speaker 1: Could you talk a little bit about the text act 372 00:19:13,720 --> 00:19:16,680 Speaker 1: that makes it possible for someone to set that index 373 00:19:17,119 --> 00:19:20,679 Speaker 1: using your software or any software, and then how that 374 00:19:20,880 --> 00:19:24,080 Speaker 1: how it can after that decision has made get the 375 00:19:24,119 --> 00:19:27,480 Speaker 1: sort of like you know, cheap trading and replication of 376 00:19:27,840 --> 00:19:30,960 Speaker 1: that part of the index. Sure, and it brings to 377 00:19:31,040 --> 00:19:34,399 Speaker 1: mind a really cool idea from a gentleman named Eric Bistria, 378 00:19:34,480 --> 00:19:38,159 Speaker 1: who's an early stage technology investator from called Benchmark. He 379 00:19:38,280 --> 00:19:41,520 Speaker 1: uses this term competitive frontier, which is the sort of 380 00:19:41,560 --> 00:19:45,000 Speaker 1: the battlegrounds if you will, that an industry will fight 381 00:19:45,119 --> 00:19:47,719 Speaker 1: on and where things will be lost or one. So 382 00:19:47,760 --> 00:19:50,160 Speaker 1: you have to be good in these competitive frontiers to 383 00:19:50,160 --> 00:19:53,320 Speaker 1: to compete in a changing era. I think those two 384 00:19:53,359 --> 00:19:55,960 Speaker 1: competitive frontiers for for this segment of the market for 385 00:19:56,000 --> 00:20:00,160 Speaker 1: indexing and and of course custom indexing are quantitative research 386 00:20:00,200 --> 00:20:03,840 Speaker 1: and software development, and those are very different probably than 387 00:20:04,000 --> 00:20:07,880 Speaker 1: what has won or determined the winners in indexing at 388 00:20:07,960 --> 00:20:11,160 Speaker 1: large for a very long time. And it's the answer 389 00:20:11,200 --> 00:20:13,520 Speaker 1: to your question, which is that it requires a lot 390 00:20:13,760 --> 00:20:18,600 Speaker 1: of technology. We honestly sort of fell backwards into this 391 00:20:18,680 --> 00:20:22,920 Speaker 1: opportunity because we just by luck, had built so much 392 00:20:23,240 --> 00:20:26,399 Speaker 1: trading software for our our core firm, which is a quantitative, 393 00:20:26,680 --> 00:20:30,440 Speaker 1: quantitative investing firm over the last you know, ten plus years. 394 00:20:30,800 --> 00:20:33,480 Speaker 1: So we were a quant firm that was managing active 395 00:20:33,520 --> 00:20:37,159 Speaker 1: strategies that managed thousands and thousands of separate accounts. To 396 00:20:37,200 --> 00:20:39,800 Speaker 1: be able to do that at scale across brokerages and 397 00:20:39,840 --> 00:20:43,520 Speaker 1: across custodians, etcetera, you have to build software that you 398 00:20:43,520 --> 00:20:46,239 Speaker 1: can't do it manually with a database. So we had 399 00:20:46,240 --> 00:20:49,959 Speaker 1: built we had built an entirely custom piece of trading software, 400 00:20:49,960 --> 00:20:52,960 Speaker 1: an entirely custom piece of something called workbenches is like 401 00:20:53,000 --> 00:20:55,960 Speaker 1: account management and settings management software for all of our 402 00:20:56,119 --> 00:21:00,280 Speaker 1: separate account strategies. Um, so it requires the technolo alogy 403 00:21:00,280 --> 00:21:02,560 Speaker 1: that I talked about, like building a Tesla, that's just 404 00:21:02,640 --> 00:21:05,280 Speaker 1: the front end that sits on top of these other systems. 405 00:21:05,760 --> 00:21:08,840 Speaker 1: And so so I think that the answer is a lot. 406 00:21:08,880 --> 00:21:12,600 Speaker 1: It requires a lot. It's it's effectively pure software and 407 00:21:12,600 --> 00:21:16,119 Speaker 1: technology that's required. And the twist on this is that 408 00:21:16,200 --> 00:21:18,040 Speaker 1: to be really good at this, you have to be 409 00:21:18,040 --> 00:21:21,400 Speaker 1: good at quantitative research, which is just different than software development. 410 00:21:21,720 --> 00:21:24,400 Speaker 1: Bring the best software development people in the world, they're 411 00:21:24,400 --> 00:21:25,720 Speaker 1: not going to be able to do some of the 412 00:21:25,760 --> 00:21:29,520 Speaker 1: stuff that's required for custom indexing. That's a data science function. 413 00:21:29,920 --> 00:21:32,120 Speaker 1: And that's the second function that I think is will 414 00:21:32,119 --> 00:21:36,760 Speaker 1: be critically important. So just on the competitive frontier idea, 415 00:21:36,960 --> 00:21:39,240 Speaker 1: I mean, there has been a lot of activity in 416 00:21:39,320 --> 00:21:43,119 Speaker 1: the direct indexing space um which we mentioned intro. But 417 00:21:43,280 --> 00:21:45,840 Speaker 1: you know, I think JP Morgan bought open invest and 418 00:21:46,000 --> 00:21:50,040 Speaker 1: black Rock and Morgan Stanley have also been buying indux platforms. 419 00:21:50,480 --> 00:21:54,480 Speaker 1: How intense is the competition at the moment. What are 420 00:21:54,480 --> 00:22:00,600 Speaker 1: the sort of variations in strategies being pursued by different players? Uh? 421 00:22:00,640 --> 00:22:03,760 Speaker 1: And and what can make you sort of stand out 422 00:22:03,760 --> 00:22:07,760 Speaker 1: from the crowd, like what makes a custom index platform 423 00:22:07,960 --> 00:22:13,320 Speaker 1: better than another one? So so direct indexing to define that, 424 00:22:13,440 --> 00:22:15,760 Speaker 1: since we've used the term a few times, I think 425 00:22:15,800 --> 00:22:18,960 Speaker 1: of as picking a reference index supplied by somebody else, 426 00:22:19,080 --> 00:22:21,320 Speaker 1: S and P Russell and S C I whatever, and 427 00:22:21,320 --> 00:22:24,399 Speaker 1: then running a tax loss harvesting strategy on top of it. 428 00:22:24,640 --> 00:22:27,560 Speaker 1: And sometimes that's just you know, simple market cap index 429 00:22:27,680 --> 00:22:30,479 Speaker 1: is probably most of the assets indirect indexing firms like 430 00:22:30,520 --> 00:22:34,080 Speaker 1: a Parametric or Imperio which were bought as you mentioned 431 00:22:34,080 --> 00:22:37,000 Speaker 1: by some of the big players. That it's it's very simple. 432 00:22:37,040 --> 00:22:39,440 Speaker 1: You just try to generate after tax returns. You sell 433 00:22:39,840 --> 00:22:43,119 Speaker 1: positions at a loss. It's a complicated optimization and algorithm 434 00:22:43,119 --> 00:22:44,800 Speaker 1: to be clear, so it requires a lot of work 435 00:22:44,840 --> 00:22:47,240 Speaker 1: on their part, but it's it's sort of one thing 436 00:22:47,280 --> 00:22:50,040 Speaker 1: that you can do. Uh. In a portfolio, I think 437 00:22:50,040 --> 00:22:53,439 Speaker 1: of customer indexing is the natural next uh progression in that. 438 00:22:53,520 --> 00:22:55,719 Speaker 1: So if if if we're painting on a blank canvas, 439 00:22:55,760 --> 00:22:57,960 Speaker 1: so to speak, as a reason we call our system canvas. 440 00:22:58,320 --> 00:23:00,200 Speaker 1: If you're planning on a blank canvas, direct indect seeing 441 00:23:00,200 --> 00:23:01,760 Speaker 1: a sort of like one tube of paint. It's it's 442 00:23:01,760 --> 00:23:04,040 Speaker 1: one of the things that you can do in your portfolio. 443 00:23:04,600 --> 00:23:08,040 Speaker 1: I think for us, staying competitive and being competitive first 444 00:23:08,119 --> 00:23:10,680 Speaker 1: was arriving at the party first or getting the party started. 445 00:23:11,040 --> 00:23:14,120 Speaker 1: So most of those direct indexing firms can't do anything 446 00:23:14,280 --> 00:23:17,320 Speaker 1: remotely close to the kind of customization driven by our 447 00:23:17,400 --> 00:23:20,760 Speaker 1: quant research capabilities that that I've described so far. So 448 00:23:21,119 --> 00:23:23,080 Speaker 1: you can you basically get to pick your index and 449 00:23:23,080 --> 00:23:25,919 Speaker 1: and that's that's your pick. But it's typically supplied by 450 00:23:25,920 --> 00:23:28,280 Speaker 1: a third party. Our viue is it should be first party, 451 00:23:28,280 --> 00:23:30,720 Speaker 1: Like we should design these things, not not SMP. We 452 00:23:30,760 --> 00:23:32,240 Speaker 1: can move a lot faster, we can be a lot 453 00:23:32,320 --> 00:23:34,520 Speaker 1: more specific to the individual. We can we can use 454 00:23:34,520 --> 00:23:37,840 Speaker 1: our quant research muscle to do so. So those two 455 00:23:37,880 --> 00:23:40,359 Speaker 1: competitive frontiers are what we're focused on. Like, if you 456 00:23:40,359 --> 00:23:42,560 Speaker 1: look at who are hiring our last you know five 457 00:23:42,640 --> 00:23:47,480 Speaker 1: hires are three software developers to quantitative research experts, and 458 00:23:47,520 --> 00:23:50,679 Speaker 1: if we can keep pushing the envelope on what we 459 00:23:50,760 --> 00:23:53,720 Speaker 1: can do at low cost. We haven't talked about costs, 460 00:23:53,720 --> 00:23:56,080 Speaker 1: but these things are are very low cost. What we 461 00:23:56,080 --> 00:23:58,200 Speaker 1: can do at low costs, then we should stay at 462 00:23:58,200 --> 00:24:01,440 Speaker 1: the at the forefront of this trend. Can you actually 463 00:24:01,520 --> 00:24:05,000 Speaker 1: just explain a little bit further the quant researching component. 464 00:24:05,040 --> 00:24:08,080 Speaker 1: I mean, you mentioned the two component trading software and 465 00:24:08,240 --> 00:24:10,960 Speaker 1: quand I kind of I think I intuitively get the 466 00:24:10,960 --> 00:24:14,880 Speaker 1: trading software. Look, talk a little bit more about um 467 00:24:15,000 --> 00:24:17,919 Speaker 1: what the quant research aspect is and why that's so 468 00:24:18,000 --> 00:24:20,040 Speaker 1: pivotal to make this work. Yeah, you know, I think 469 00:24:20,080 --> 00:24:22,480 Speaker 1: this is something way beyond just investing too. You're you're 470 00:24:22,480 --> 00:24:26,199 Speaker 1: seeing data science pop up as something that used to 471 00:24:26,200 --> 00:24:27,760 Speaker 1: be no one talked about or knew what it was. 472 00:24:27,800 --> 00:24:30,320 Speaker 1: Now it's a central function in like every company, and 473 00:24:30,480 --> 00:24:35,320 Speaker 1: it's not complicated, it's very simple. There there's some quantitative outcome, 474 00:24:35,560 --> 00:24:38,400 Speaker 1: some measurable outcome that matters to people, and I'm talking 475 00:24:38,440 --> 00:24:41,240 Speaker 1: big picture here, not just investing, and you you build 476 00:24:41,240 --> 00:24:43,760 Speaker 1: a model that that does a good job of predicting 477 00:24:43,760 --> 00:24:46,960 Speaker 1: that outcome. And this happened in sports with the moneyball trend. 478 00:24:47,040 --> 00:24:49,520 Speaker 1: You know, we figured out that obviously you want runs, 479 00:24:49,560 --> 00:24:50,800 Speaker 1: you want to score points, and you don't want to 480 00:24:50,800 --> 00:24:52,560 Speaker 1: give up you don't want to give up runs in 481 00:24:52,600 --> 00:24:55,480 Speaker 1: any sport, and certain things relate to that. On base 482 00:24:55,520 --> 00:24:59,359 Speaker 1: percentage was the example in in moneyball. In in public 483 00:24:59,400 --> 00:25:01,920 Speaker 1: market invest you want good returns, but there's other things 484 00:25:01,920 --> 00:25:04,600 Speaker 1: you want to So anything that you can target, that 485 00:25:04,640 --> 00:25:08,040 Speaker 1: could be companies that sell sugary drinks, well that's a 486 00:25:08,200 --> 00:25:10,760 Speaker 1: that's a measurable outcome. It's hard. You have to get 487 00:25:10,840 --> 00:25:13,080 Speaker 1: data sets, you have to build data sets um but 488 00:25:13,160 --> 00:25:17,679 Speaker 1: you can build predictive models for outcomes that matter or 489 00:25:17,720 --> 00:25:20,679 Speaker 1: information that matters to the individual. And every time you 490 00:25:20,760 --> 00:25:23,560 Speaker 1: do that, you're adding an arrow to your quiver. So 491 00:25:23,760 --> 00:25:26,240 Speaker 1: once we did that, Once the next family that comes 492 00:25:26,280 --> 00:25:28,080 Speaker 1: to us and says we don't want to own sugary drinks, 493 00:25:28,160 --> 00:25:29,960 Speaker 1: we don't have to rebuild that thing from scratch. We 494 00:25:30,000 --> 00:25:33,760 Speaker 1: have the model already. Same thing for the tax loss optimization. 495 00:25:34,200 --> 00:25:36,399 Speaker 1: Every time you build a new model, you sort of 496 00:25:36,440 --> 00:25:40,760 Speaker 1: expand what your platform can do. And quantitative researchers that's 497 00:25:40,800 --> 00:25:43,280 Speaker 1: all they do all day. So they say it's very 498 00:25:43,320 --> 00:25:45,880 Speaker 1: simple terms. There's three things that matter. There's the outcome 499 00:25:46,200 --> 00:25:49,080 Speaker 1: that's called the label in in the data science parlance. 500 00:25:49,400 --> 00:25:52,119 Speaker 1: There's the inputs, the features, what what things are going 501 00:25:52,160 --> 00:25:55,119 Speaker 1: to predict the outcome that we care about and how? 502 00:25:55,160 --> 00:25:57,359 Speaker 1: And what is the model itself. It's you know, people 503 00:25:57,480 --> 00:25:59,800 Speaker 1: listening probably are familiar with something very simple like living 504 00:25:59,800 --> 00:26:02,600 Speaker 1: your aggression or a linear model. These are just much 505 00:26:02,640 --> 00:26:04,600 Speaker 1: fancier models. That's that's all you have to really know 506 00:26:04,640 --> 00:26:07,600 Speaker 1: about it. So there's inputs, there's the model, there's outputs. 507 00:26:08,080 --> 00:26:10,359 Speaker 1: You have to be expert at building those things and 508 00:26:10,400 --> 00:26:13,080 Speaker 1: those three parts of a model and then offering those 509 00:26:13,119 --> 00:26:16,680 Speaker 1: effectively as services or products. To build a custom index 510 00:26:16,720 --> 00:26:18,680 Speaker 1: in this case, or you know, predict what clothes you're 511 00:26:18,680 --> 00:26:20,520 Speaker 1: gonna like in the case of something like stitch fix 512 00:26:20,680 --> 00:26:22,720 Speaker 1: or whatever. It's a function that we just think will 513 00:26:22,760 --> 00:26:25,800 Speaker 1: be embedded everywhere. What does this mean for e t 514 00:26:26,000 --> 00:26:28,840 Speaker 1: f s and mutual funds and the sort of traditional 515 00:26:29,000 --> 00:26:32,720 Speaker 1: players of fund management, because I imagine, as you just mentioned, 516 00:26:32,800 --> 00:26:35,480 Speaker 1: you know this idea that if you build one custom index, 517 00:26:35,520 --> 00:26:38,119 Speaker 1: basically you've created a new product that you can then 518 00:26:38,240 --> 00:26:41,800 Speaker 1: roll out to additional clients. So it seems like a 519 00:26:41,800 --> 00:26:45,560 Speaker 1: pretty efficient way to create you know, almost an infinite 520 00:26:45,680 --> 00:26:51,000 Speaker 1: number of indexes which on the surface would would seem 521 00:26:51,080 --> 00:26:55,240 Speaker 1: to um potentially threaten or at least compete with ETFs 522 00:26:55,280 --> 00:26:59,960 Speaker 1: and mutual funds. I think if you narrow two taxable 523 00:27:00,040 --> 00:27:04,040 Speaker 1: investors where the the underlying strategy that's being designed or 524 00:27:04,080 --> 00:27:08,359 Speaker 1: implemented has has an annual turnover of twenty or less, 525 00:27:08,440 --> 00:27:11,360 Speaker 1: which is sort of the crossover point for taxes, that 526 00:27:11,440 --> 00:27:13,080 Speaker 1: this is a huge threat to e t f s. 527 00:27:13,400 --> 00:27:15,960 Speaker 1: There in my mind, there's really no reason, especially as 528 00:27:16,000 --> 00:27:18,280 Speaker 1: costs continue to fall, and it's not like they're that 529 00:27:18,359 --> 00:27:21,200 Speaker 1: far apart anyway. You know, our lowest prices twenty basis 530 00:27:21,240 --> 00:27:24,280 Speaker 1: points today, um so that additional let's call it ten 531 00:27:24,359 --> 00:27:26,280 Speaker 1: basis points that we might get down to over the 532 00:27:26,280 --> 00:27:28,880 Speaker 1: next ten years. I mean, you comp on ten basis 533 00:27:28,920 --> 00:27:31,600 Speaker 1: points over time, it's not a huge difference. And so 534 00:27:31,760 --> 00:27:34,120 Speaker 1: we're pretty close on cost already. And if you think 535 00:27:34,160 --> 00:27:40,760 Speaker 1: about that whole segment of UH turnover would qualify for 536 00:27:40,800 --> 00:27:43,119 Speaker 1: that and taxable investors that own e t f s, 537 00:27:43,280 --> 00:27:49,160 Speaker 1: that is a huge segment of the market. Now above turnover, 538 00:27:49,400 --> 00:27:52,560 Speaker 1: ETFs remain and I think will remain thanks to the 539 00:27:52,880 --> 00:27:55,000 Speaker 1: sort of law of tax law that governs them the 540 00:27:55,119 --> 00:27:58,520 Speaker 1: ultimate app right, there's just there's there's no beating. Let's 541 00:27:58,520 --> 00:28:00,960 Speaker 1: say you want to invest in a pure momentum strategy 542 00:28:01,000 --> 00:28:03,480 Speaker 1: or something that has a PC annual turnover. There's just 543 00:28:03,560 --> 00:28:05,240 Speaker 1: no better rapper than the e t F because you 544 00:28:05,280 --> 00:28:08,360 Speaker 1: don't have to pay the ongoing taxes as a taxable investor. 545 00:28:08,760 --> 00:28:11,119 Speaker 1: So high turnover strategies I think will always and should 546 00:28:11,119 --> 00:28:13,280 Speaker 1: always live in an e t F S for the 547 00:28:13,280 --> 00:28:16,640 Speaker 1: most part, unless you know, deep customization is really important 548 00:28:16,800 --> 00:28:19,160 Speaker 1: to the investor, in which case they may go custom 549 00:28:19,200 --> 00:28:22,600 Speaker 1: index but below that threshold. And this applies to mutual 550 00:28:22,640 --> 00:28:24,720 Speaker 1: funds too, you know, more of which are converting to 551 00:28:24,760 --> 00:28:26,679 Speaker 1: e t f s or will in the future. I 552 00:28:26,720 --> 00:28:28,960 Speaker 1: think this is a huge This is a huge and 553 00:28:29,080 --> 00:28:32,760 Speaker 1: important uh move and shift, And obviously it's counterpositioned. E 554 00:28:32,840 --> 00:28:35,600 Speaker 1: t F providers other than going into the custom indexing 555 00:28:35,640 --> 00:28:38,560 Speaker 1: business cannot compete against this. I mean, it's the rapper 556 00:28:38,680 --> 00:28:43,160 Speaker 1: itself by definition does not allow for customization. So Patrick, 557 00:28:43,200 --> 00:28:45,360 Speaker 1: I want to uh, you know, I think of you 558 00:28:45,520 --> 00:28:49,600 Speaker 1: as someone who's just sort of like the ultimate markets 559 00:28:49,640 --> 00:28:53,440 Speaker 1: and business omnivore. And even like when Tracy did the intro, 560 00:28:53,520 --> 00:28:56,200 Speaker 1: I mean well, would you have like four titles I 561 00:28:56,240 --> 00:29:00,960 Speaker 1: think you mentioned, including host of a podcast that's a 562 00:29:01,000 --> 00:29:04,200 Speaker 1: competitor to ours, you know, not all partners here but 563 00:29:04,320 --> 00:29:06,320 Speaker 1: uh but no, but in all series is you have 564 00:29:06,360 --> 00:29:10,560 Speaker 1: like an extraordinary like broad ray of interest. And it's 565 00:29:10,640 --> 00:29:13,880 Speaker 1: evident to anyone who follows you. And I'm kind of 566 00:29:13,920 --> 00:29:16,400 Speaker 1: like jealous, I would say, of how open minded you are, 567 00:29:16,560 --> 00:29:21,040 Speaker 1: and whether it's like VC investing or crypto or n 568 00:29:21,120 --> 00:29:23,360 Speaker 1: f T S or anything. I think you just like 569 00:29:23,520 --> 00:29:25,720 Speaker 1: exhibit this sort of like first to learn more. And 570 00:29:26,160 --> 00:29:27,800 Speaker 1: you know, I said in the intro, and I really 571 00:29:27,920 --> 00:29:31,200 Speaker 1: felt this like my career, like as a journalist, really 572 00:29:31,200 --> 00:29:33,800 Speaker 1: started in the wake of a great, great financial crisis. 573 00:29:34,360 --> 00:29:37,320 Speaker 1: You know, like we're just like hammered home this idea 574 00:29:37,320 --> 00:29:41,440 Speaker 1: of like passive passive passive by the index. Forget about it. 575 00:29:41,760 --> 00:29:44,760 Speaker 1: Don't buy individual stocks, don't try to time the market, 576 00:29:44,600 --> 00:29:46,760 Speaker 1: don't try to beat the market. Put some of your 577 00:29:46,760 --> 00:29:49,640 Speaker 1: paycheck at an index fund every two weeks or whatever 578 00:29:49,800 --> 00:29:51,520 Speaker 1: and just said it and forget it and look at 579 00:29:51,560 --> 00:29:53,640 Speaker 1: your four one K maybe twice a year or whatever. Okay, 580 00:29:53,640 --> 00:29:56,280 Speaker 1: so we all know that obviously we live now in 581 00:29:56,320 --> 00:29:58,440 Speaker 1: this world of people buying all kinds of stuff, and 582 00:29:58,440 --> 00:30:01,040 Speaker 1: you've like really dived head first into that. How do 583 00:30:01,080 --> 00:30:03,800 Speaker 1: you think about this question of like, Okay, all the 584 00:30:03,960 --> 00:30:06,960 Speaker 1: academic research says do X and don't try to time 585 00:30:07,000 --> 00:30:08,560 Speaker 1: the market, but we have a lot of people who 586 00:30:08,600 --> 00:30:10,880 Speaker 1: are interested in all this other stuff. How do you 587 00:30:10,920 --> 00:30:14,200 Speaker 1: think about this sort of like tension and how people 588 00:30:14,280 --> 00:30:19,520 Speaker 1: should think about incorporating sort of more concentrated, riskier, far 589 00:30:19,600 --> 00:30:23,000 Speaker 1: out of the risk curve ideas and bets into their portfolio. 590 00:30:23,440 --> 00:30:26,520 Speaker 1: It's a great question, obviously an animating one for me 591 00:30:26,840 --> 00:30:29,160 Speaker 1: when I spend all my time thinking about, you know, 592 00:30:29,640 --> 00:30:32,360 Speaker 1: at my own portfolio. I you know, I'm involved in 593 00:30:32,400 --> 00:30:35,800 Speaker 1: a lot of people's portfolios. It's it's so interesting and important, 594 00:30:36,400 --> 00:30:38,400 Speaker 1: I think, honestly, I think the answer is there's a 595 00:30:38,400 --> 00:30:40,640 Speaker 1: lot of room for all this stuff in in our 596 00:30:40,680 --> 00:30:43,960 Speaker 1: lives and our careers and our portfolios, and that some 597 00:30:44,440 --> 00:30:48,680 Speaker 1: large component of low cost broad market exposure is appropriate 598 00:30:48,720 --> 00:30:52,800 Speaker 1: advice for just about anybody. And I have to say, 599 00:30:52,840 --> 00:30:55,160 Speaker 1: like when I was at when I was thinking learning 600 00:30:55,160 --> 00:30:57,760 Speaker 1: about all this stuff in the early days, the passive 601 00:30:57,800 --> 00:30:59,920 Speaker 1: thing makes complete sense to me. But it's also remark 602 00:31:00,000 --> 00:31:02,840 Speaker 1: comply boring from a career standpoint. I mean like, Okay, 603 00:31:02,920 --> 00:31:04,560 Speaker 1: you can say that and become convinced of it, but 604 00:31:04,600 --> 00:31:07,280 Speaker 1: then go work and you know, manufacturing or something like. 605 00:31:07,320 --> 00:31:09,880 Speaker 1: There's nothing left to do, right. You just described the whole, 606 00:31:10,080 --> 00:31:13,200 Speaker 1: the whole strategy in thirty seconds. And look, I think 607 00:31:13,200 --> 00:31:16,040 Speaker 1: that strategy for like literally for everybody or for the 608 00:31:16,080 --> 00:31:19,320 Speaker 1: vast majority of people is incredibly smart and will produce 609 00:31:19,360 --> 00:31:24,400 Speaker 1: good outcomes. Um, but it's fundamentally ignoring things that are 610 00:31:24,480 --> 00:31:27,800 Speaker 1: changing rapidly where you can access them via an index fund. 611 00:31:28,320 --> 00:31:30,400 Speaker 1: You know, you cannot buy some crypto in these kind 612 00:31:30,440 --> 00:31:33,600 Speaker 1: of cool index like structures, but you certainly can't access 613 00:31:33,640 --> 00:31:36,280 Speaker 1: let's say, early stage technology companies. That's something I'm very 614 00:31:36,320 --> 00:31:39,680 Speaker 1: interested in. I spend most of my time in investing 615 00:31:39,680 --> 00:31:44,240 Speaker 1: in building thinking about software. And I can buy a 616 00:31:44,280 --> 00:31:46,400 Speaker 1: software e t F I suppose, But to me, it's 617 00:31:46,400 --> 00:31:48,920 Speaker 1: far more interesting to build a variety of software companies 618 00:31:48,920 --> 00:31:51,480 Speaker 1: like Canvas. It's far more interesting to form a VC, 619 00:31:51,600 --> 00:31:53,880 Speaker 1: which I did, to invest in early stage companies and 620 00:31:53,880 --> 00:31:56,360 Speaker 1: help them along the way. I I guess I'm just 621 00:31:56,400 --> 00:32:00,680 Speaker 1: defined by change and understanding how systems work, and when 622 00:32:00,680 --> 00:32:03,800 Speaker 1: those two things come together, there's just an unlimited amount 623 00:32:03,800 --> 00:32:06,000 Speaker 1: of cool stuff to learn about. And so you know, 624 00:32:06,040 --> 00:32:08,520 Speaker 1: in I spent a huge amount of time trying to 625 00:32:08,560 --> 00:32:12,160 Speaker 1: understand crypto, and I still do. I just think it's fascinating. Um, 626 00:32:12,200 --> 00:32:14,080 Speaker 1: I don't, I don't. I don't have a huge amount 627 00:32:14,120 --> 00:32:16,360 Speaker 1: of personal exposure to it. I do have some a 628 00:32:16,400 --> 00:32:18,800 Speaker 1: lot more than I used to, just because of market appreciation. 629 00:32:19,320 --> 00:32:22,520 Speaker 1: And and I'm just I just like new stuff that 630 00:32:22,680 --> 00:32:26,320 Speaker 1: is changing, that enables new behavior or new good outcomes 631 00:32:26,360 --> 00:32:29,280 Speaker 1: for for humans, and like to have, like to be 632 00:32:29,320 --> 00:32:31,600 Speaker 1: at the frontiers of these things. And yeah, I've got 633 00:32:31,600 --> 00:32:33,080 Speaker 1: a lot of titles, and you know, it seems like 634 00:32:33,160 --> 00:32:35,160 Speaker 1: I'm doing a lot, but I'm kind of just doing 635 00:32:35,160 --> 00:32:39,080 Speaker 1: one thing, which is trying to understand what's new, what's changing, 636 00:32:39,520 --> 00:32:42,120 Speaker 1: is it interesting or not? What people can help us 637 00:32:42,200 --> 00:32:44,680 Speaker 1: learn about this, you know, can can we expose their 638 00:32:44,720 --> 00:32:47,320 Speaker 1: ideas to the world. Can we share as broadly as 639 00:32:47,320 --> 00:32:50,160 Speaker 1: we can as we learn? And and that's that's very fun. 640 00:32:50,240 --> 00:32:53,720 Speaker 1: It's a lot more fun than you know. By Vanguard, uh, 641 00:32:53,760 --> 00:33:13,360 Speaker 1: and by Vanguard is very very good advice. Still, this 642 00:33:13,440 --> 00:33:15,040 Speaker 1: is something that I think Joe and I both wanted 643 00:33:15,080 --> 00:33:16,640 Speaker 1: to ask you. But what do you see as the 644 00:33:16,760 --> 00:33:21,160 Speaker 1: role of crypto in a portfolio, because you just described 645 00:33:21,280 --> 00:33:23,560 Speaker 1: having a little bit of it more than you used to. 646 00:33:23,800 --> 00:33:26,160 Speaker 1: And I think one way that a lot of investors 647 00:33:26,160 --> 00:33:29,280 Speaker 1: think about it is as a sort of like lottery ticket, 648 00:33:29,440 --> 00:33:31,320 Speaker 1: where you know, you put a little bit of money 649 00:33:31,560 --> 00:33:35,000 Speaker 1: in a particular token or coin or whatever, and you 650 00:33:35,080 --> 00:33:37,520 Speaker 1: kind of hold your breath and hope that it's going 651 00:33:37,560 --> 00:33:40,280 Speaker 1: to be the right one to go up. So how 652 00:33:40,320 --> 00:33:44,160 Speaker 1: are you thinking about it? One of my favorite investing 653 00:33:44,240 --> 00:33:46,480 Speaker 1: quotes I Cammeramer who said it. But but the quote 654 00:33:46,560 --> 00:33:51,640 Speaker 1: is diversification is the only rational deployment of ignorance. And 655 00:33:52,440 --> 00:33:55,480 Speaker 1: I have to claim some like a lot of knowledge 656 00:33:55,520 --> 00:33:58,480 Speaker 1: but but also a lot of ignorance on the topic 657 00:33:58,520 --> 00:34:00,840 Speaker 1: of crypto and what the few sure of it might 658 00:34:00,880 --> 00:34:03,080 Speaker 1: be in a as you said, traditional portfolio. I think 659 00:34:03,120 --> 00:34:06,800 Speaker 1: traditional there is is the operative word. I don't I 660 00:34:06,840 --> 00:34:09,600 Speaker 1: don't know the answer. I can tell you what I've done, 661 00:34:09,640 --> 00:34:12,080 Speaker 1: which is that you know, when I learned about this stuff, 662 00:34:12,400 --> 00:34:16,560 Speaker 1: the exciting core, you know, base level protocols that I 663 00:34:16,560 --> 00:34:19,160 Speaker 1: spent the most time with seemed really interesting to me, 664 00:34:19,200 --> 00:34:21,680 Speaker 1: and I could I could understand a future where they 665 00:34:21,719 --> 00:34:26,000 Speaker 1: are critical components of how the world works. Much like 666 00:34:26,360 --> 00:34:29,600 Speaker 1: http is or or smt P for email. These are 667 00:34:29,600 --> 00:34:32,120 Speaker 1: other protocols that just didn't have any value associated with 668 00:34:32,160 --> 00:34:35,080 Speaker 1: them that have totally changed the world. And in this case, 669 00:34:35,120 --> 00:34:38,040 Speaker 1: the protocols have a value. They have a they have 670 00:34:38,160 --> 00:34:40,640 Speaker 1: a they have a token or a coin or whatever 671 00:34:40,680 --> 00:34:43,440 Speaker 1: you want to call it, a cryptocurrency which quote unquote 672 00:34:43,440 --> 00:34:47,600 Speaker 1: powers the protocol and those things can can have and 673 00:34:47,640 --> 00:34:51,600 Speaker 1: retain value or grow value. And is bitcoin gonna be 674 00:34:51,640 --> 00:34:53,279 Speaker 1: a thing in ten years? You know, I'm not smart 675 00:34:53,360 --> 00:34:55,799 Speaker 1: enough to know, Sure seems like it will be to me? 676 00:34:56,320 --> 00:34:58,520 Speaker 1: Um is ethereum gonna be a thing? It sure seems 677 00:34:58,520 --> 00:35:00,920 Speaker 1: like it to me. Uh as as something that I 678 00:35:00,960 --> 00:35:03,520 Speaker 1: know countless people are using on a daily basis. How 679 00:35:03,560 --> 00:35:06,280 Speaker 1: many products can you say that about with a very clever, 680 00:35:06,640 --> 00:35:10,040 Speaker 1: you know, economic design behind of it, behind it and 681 00:35:10,200 --> 00:35:12,520 Speaker 1: evolving design. So for me, it was it was no 682 00:35:12,560 --> 00:35:16,720 Speaker 1: more complicated than Look like, these are incredibly interesting technologies. 683 00:35:17,120 --> 00:35:19,080 Speaker 1: Many of the smartest people that I've encountered, and I 684 00:35:19,200 --> 00:35:21,839 Speaker 1: encounter a lot of smart people in in the course 685 00:35:21,840 --> 00:35:25,319 Speaker 1: of my life, are are gravitating towards this field. And 686 00:35:25,360 --> 00:35:29,600 Speaker 1: you could see how philosophically these are good ideas that 687 00:35:29,760 --> 00:35:31,880 Speaker 1: could could have and retained values. So I put a 688 00:35:31,920 --> 00:35:34,680 Speaker 1: small position and and have have added a little bit 689 00:35:34,760 --> 00:35:37,560 Speaker 1: and and never really sold anything. And and that's been 690 00:35:37,600 --> 00:35:40,720 Speaker 1: my personal stance. It's not advice, it's just what worked 691 00:35:40,760 --> 00:35:43,359 Speaker 1: for me. But I think of it as diversification, and 692 00:35:43,760 --> 00:35:46,640 Speaker 1: I think everyone agrees to versification is good at some level. 693 00:35:46,719 --> 00:35:48,520 Speaker 1: Like the SP five hunter that we talked about earlier, 694 00:35:48,560 --> 00:35:50,680 Speaker 1: you should own that instead of one stock, one stock 695 00:35:50,719 --> 00:35:53,600 Speaker 1: would be dune. I think there's an argument to be 696 00:35:53,680 --> 00:35:56,720 Speaker 1: made that that idea of diversification needs to extend further 697 00:35:57,200 --> 00:35:59,960 Speaker 1: into things that maybe we don't quite understand yet or 698 00:36:00,120 --> 00:36:02,000 Speaker 1: or we're not sure where they're going to go. But 699 00:36:02,120 --> 00:36:05,239 Speaker 1: seemed to have that kind of promise. You know. I 700 00:36:05,280 --> 00:36:08,560 Speaker 1: was talking to someone a few months ago, I think 701 00:36:08,560 --> 00:36:11,719 Speaker 1: he worked, he did he worked at a macro hedge fund, 702 00:36:11,719 --> 00:36:14,120 Speaker 1: and he was talking about how like they had this 703 00:36:14,239 --> 00:36:18,680 Speaker 1: very tiny crypto allocation in the fund a while back, 704 00:36:19,000 --> 00:36:21,160 Speaker 1: but then over like the course of the last year, 705 00:36:21,760 --> 00:36:26,040 Speaker 1: it became a fairly substantial crypto allocation because of the 706 00:36:26,120 --> 00:36:29,560 Speaker 1: rapid appreciation, and it got to the point quickly where 707 00:36:30,000 --> 00:36:32,399 Speaker 1: not only did it becomes substantial, but on a day 708 00:36:32,400 --> 00:36:34,840 Speaker 1: to day basis, or a week to week basis, the 709 00:36:34,920 --> 00:36:39,920 Speaker 1: funds returns were almost always determined by whether that crypto portion, 710 00:36:40,400 --> 00:36:42,120 Speaker 1: and so I feel like there's a kind of like 711 00:36:42,160 --> 00:36:44,280 Speaker 1: this like weird like I get, you know, mind virus 712 00:36:44,400 --> 00:36:47,879 Speaker 1: aspect where maybe it feels like people dip their toe 713 00:36:47,880 --> 00:36:50,120 Speaker 1: in the water and they're like, oh, I'm just you know, 714 00:36:50,280 --> 00:36:52,520 Speaker 1: gonna have a little bit because I'm curious, and then 715 00:36:52,600 --> 00:36:56,360 Speaker 1: suddenly it like dominates the daily swings in their portfolio, 716 00:36:56,400 --> 00:36:58,000 Speaker 1: and then they can't stop thinking about it and can't 717 00:36:58,000 --> 00:37:00,239 Speaker 1: stop talking about it, And I'm curious, Like mean, you 718 00:37:00,280 --> 00:37:02,800 Speaker 1: talk to people all the time, both on your podcast 719 00:37:02,880 --> 00:37:05,640 Speaker 1: and then professionally and through the VC. I'm curious if 720 00:37:05,640 --> 00:37:08,719 Speaker 1: you see that phenomenon where it's like somehow it's sort 721 00:37:08,760 --> 00:37:11,319 Speaker 1: of they have this like little interest or buy some 722 00:37:11,440 --> 00:37:13,319 Speaker 1: on a lark, and then it next thing, you know, 723 00:37:13,360 --> 00:37:15,920 Speaker 1: it's sort of like dominates their every waking second like 724 00:37:16,200 --> 00:37:18,560 Speaker 1: thinking about it and watching the return. Yeah, it's like 725 00:37:18,560 --> 00:37:20,759 Speaker 1: it's like surpassed you know, being from Texas or going 726 00:37:20,800 --> 00:37:22,919 Speaker 1: to Harvard, Right, is like the first thing you mentioned, right, 727 00:37:23,080 --> 00:37:25,040 Speaker 1: I mean, there's a joke that one of my friends 728 00:37:25,080 --> 00:37:27,080 Speaker 1: who's one of the largest bitcoin owners in the world 729 00:37:27,160 --> 00:37:29,440 Speaker 1: said it was very early in the ecosystem. It's like, 730 00:37:29,920 --> 00:37:32,560 Speaker 1: look like, don't worry. Everyone wishes they had more bitcoin, 731 00:37:32,719 --> 00:37:36,960 Speaker 1: like myself and myself included, and when something especially bit 732 00:37:37,000 --> 00:37:40,600 Speaker 1: Bitcoin is my favorite because ultimately it's tethered to nothing, 733 00:37:40,840 --> 00:37:42,680 Speaker 1: right like the the the use case. The use case 734 00:37:42,840 --> 00:37:45,840 Speaker 1: is the value, and the value is based on perception. 735 00:37:46,400 --> 00:37:48,799 Speaker 1: And unlike ether, which is actually used in a lot 736 00:37:48,880 --> 00:37:50,960 Speaker 1: of you know, like like a utility in a lot 737 00:37:50,960 --> 00:37:53,640 Speaker 1: of ways, for for for functions or for things that 738 00:37:53,680 --> 00:37:56,239 Speaker 1: happen in in on the web, bitcoin is just this 739 00:37:56,360 --> 00:37:58,920 Speaker 1: kind of like it's like a philosophy argument. It's so 740 00:37:58,960 --> 00:38:02,160 Speaker 1: cool and and I think for something like that, if 741 00:38:02,160 --> 00:38:03,920 Speaker 1: you own a lot of it, it's hard not to 742 00:38:04,000 --> 00:38:07,919 Speaker 1: become obsessed with it. And uh, for for wealthy people, 743 00:38:07,960 --> 00:38:10,000 Speaker 1: I have this idea called balance sheet syndrome, which is 744 00:38:10,000 --> 00:38:12,520 Speaker 1: like you get too rich and then you all you 745 00:38:12,560 --> 00:38:14,040 Speaker 1: do is like think about and talk about and worried 746 00:38:14,040 --> 00:38:15,719 Speaker 1: about your balance sheet, which I think is awful by 747 00:38:15,719 --> 00:38:19,440 Speaker 1: the way. Um, and you see that like crazy with 748 00:38:19,440 --> 00:38:22,200 Speaker 1: with holders of a lot of crypto, and it's very 749 00:38:22,320 --> 00:38:25,040 Speaker 1: very religious esque. You know, if you study mass movements 750 00:38:25,120 --> 00:38:27,279 Speaker 1: or religions or history, like there's a lot shared in 751 00:38:27,320 --> 00:38:30,799 Speaker 1: common here, and uh, that's not interesting to me at all, 752 00:38:31,120 --> 00:38:33,439 Speaker 1: Like you know when someone like it's just not it's 753 00:38:33,440 --> 00:38:35,359 Speaker 1: just it's just It's one of those things that if 754 00:38:35,400 --> 00:38:38,040 Speaker 1: someone wants to talk about endlessly, like I lose interest 755 00:38:38,120 --> 00:38:40,719 Speaker 1: very quickly. But I do see it kind of constantly. 756 00:38:41,640 --> 00:38:44,080 Speaker 1: I want to ask about one other thing and another 757 00:38:44,280 --> 00:38:47,520 Speaker 1: project that you're associated with then that sort of joint 758 00:38:47,520 --> 00:38:51,040 Speaker 1: colossus and you do these like deep dive into like 759 00:38:51,200 --> 00:38:55,480 Speaker 1: mechanical understandings of businesses. So it's like we we think 760 00:38:55,520 --> 00:38:58,840 Speaker 1: we understand like how to Polar works or Lululemon works 761 00:38:58,920 --> 00:39:02,200 Speaker 1: or GM works, And this is something you see, um 762 00:39:02,320 --> 00:39:05,480 Speaker 1: that you are clearly very interesting. Is like let's really 763 00:39:05,600 --> 00:39:08,360 Speaker 1: like drill down and like get to know their business 764 00:39:08,400 --> 00:39:11,000 Speaker 1: models and so forth, that how they became, what they did, 765 00:39:11,360 --> 00:39:13,480 Speaker 1: How has that helped you as an investor? And what 766 00:39:13,520 --> 00:39:15,719 Speaker 1: do you think is the importance of that, because I 767 00:39:15,719 --> 00:39:18,120 Speaker 1: don't see a lot of people doing that the way 768 00:39:18,239 --> 00:39:21,720 Speaker 1: you do, like really like getting to know a business. Well, 769 00:39:22,520 --> 00:39:24,200 Speaker 1: talk to us a little bit about what value you've 770 00:39:24,239 --> 00:39:27,319 Speaker 1: gotten from that exercise. Yeah, one one of my one 771 00:39:27,360 --> 00:39:29,440 Speaker 1: of my frustrations with a lot of investors, even the 772 00:39:29,440 --> 00:39:32,839 Speaker 1: great ones. Is that as they get better and better known, 773 00:39:32,960 --> 00:39:36,960 Speaker 1: like they tend towards being philosophers versus you know, on 774 00:39:37,000 --> 00:39:40,120 Speaker 1: the ground thinkers like that. And I just like getting 775 00:39:40,200 --> 00:39:42,359 Speaker 1: on the ground. Like there's that amazing quote. It's like 776 00:39:42,400 --> 00:39:44,279 Speaker 1: one of the painters that says, like, you know, our 777 00:39:44,360 --> 00:39:48,440 Speaker 1: critics are always talking about theory and and and aesthetics 778 00:39:48,480 --> 00:39:50,919 Speaker 1: and whatever, and like painters are talking about like where 779 00:39:50,920 --> 00:39:54,880 Speaker 1: to buy cheap turpentine and and I just like that idea. 780 00:39:55,000 --> 00:39:58,839 Speaker 1: So I personally have learned a lot more. I didn't 781 00:39:58,840 --> 00:40:00,840 Speaker 1: want to. I did we call these business breakdowns? And 782 00:40:00,880 --> 00:40:03,759 Speaker 1: I did one yesterday on on Wyndham Hotels with my 783 00:40:03,800 --> 00:40:06,279 Speaker 1: friend Lauren Taylor Wolf. And you know, we spent an 784 00:40:06,280 --> 00:40:08,120 Speaker 1: hour and a half talking about Windham Hotels, right like 785 00:40:08,160 --> 00:40:11,120 Speaker 1: who cares? But when when when you dive into windhom 786 00:40:11,400 --> 00:40:13,960 Speaker 1: you just learn all this cool stuff about the world, 787 00:40:14,040 --> 00:40:16,480 Speaker 1: like how all their brands like Super eight to this 788 00:40:16,560 --> 00:40:18,960 Speaker 1: kind of lower segment of the market evolved along with 789 00:40:18,960 --> 00:40:22,719 Speaker 1: the interstate highway system in the fifties and sixties, and 790 00:40:22,719 --> 00:40:25,239 Speaker 1: and what the franchise economics look like for someone that 791 00:40:25,320 --> 00:40:27,960 Speaker 1: starts and buys a Windham hotel versus buying a dominoes 792 00:40:28,120 --> 00:40:30,719 Speaker 1: or you know whatever, like these very real on the 793 00:40:30,719 --> 00:40:33,680 Speaker 1: ground things that if you pay seventy bucks for a hotel, 794 00:40:33,800 --> 00:40:35,560 Speaker 1: like now I know where that seventy bucks goes, and 795 00:40:35,560 --> 00:40:38,560 Speaker 1: like what the underlying economics are. And when I'm looking 796 00:40:38,640 --> 00:40:41,280 Speaker 1: at another business to invest in or or to build 797 00:40:41,640 --> 00:40:44,319 Speaker 1: in the future, it feels like I'm just collecting all 798 00:40:44,400 --> 00:40:47,279 Speaker 1: these individual models and I can say, oh, like this 799 00:40:47,360 --> 00:40:50,120 Speaker 1: looks like this piece of software somehow looks like windhom 800 00:40:50,280 --> 00:40:52,520 Speaker 1: you know, doubt that one will happen, But all these 801 00:40:52,560 --> 00:40:55,800 Speaker 1: points of learning in comparison, you know, Harvard is famous 802 00:40:55,800 --> 00:40:57,960 Speaker 1: for its business case studies, which I think are very good. 803 00:40:58,280 --> 00:41:00,200 Speaker 1: And this is just that, you know, for for and 804 00:41:00,200 --> 00:41:03,400 Speaker 1: in the open and in conversation. So I like the 805 00:41:03,400 --> 00:41:09,440 Speaker 1: turpentine approach to learning about business versus the very like haughty, philosophical, 806 00:41:09,880 --> 00:41:12,560 Speaker 1: you know, principled approach. And I was a philosophy major, 807 00:41:12,600 --> 00:41:14,399 Speaker 1: so you know, I know this takes one to know one, 808 00:41:14,400 --> 00:41:16,799 Speaker 1: I guess, and that's why we do it. We we 809 00:41:16,880 --> 00:41:19,560 Speaker 1: just I just like how stuff works, and I find 810 00:41:19,640 --> 00:41:22,840 Speaker 1: all of the detail to be far more interesting in 811 00:41:22,880 --> 00:41:26,640 Speaker 1: a Chipotle than you know, like the source of its Moat, Like, 812 00:41:26,719 --> 00:41:29,160 Speaker 1: I like learning about how the guacamole has made and 813 00:41:29,520 --> 00:41:31,480 Speaker 1: how you can get the cost of guacamole down by 814 00:41:31,480 --> 00:41:34,160 Speaker 1: owning a guacamole farm, and this kind of stuff like 815 00:41:34,239 --> 00:41:36,799 Speaker 1: just more interesting to me. You know, I think for 816 00:41:36,880 --> 00:41:39,000 Speaker 1: Tracy and I that probably that speaks to us because 817 00:41:39,000 --> 00:41:40,920 Speaker 1: we I think some of both of our favorite episodes 818 00:41:40,960 --> 00:41:43,320 Speaker 1: have been like let's talk about how trucking works. It 819 00:41:43,360 --> 00:41:47,120 Speaker 1: reminds me of like uh Bob Dylan's actually his Nobel 820 00:41:47,200 --> 00:41:50,600 Speaker 1: Prize speech where it's like people always talk about Shakespeare, 821 00:41:51,080 --> 00:41:54,480 Speaker 1: you know, something like great literary of playwright, but Shakespeare 822 00:41:54,520 --> 00:41:56,840 Speaker 1: was thinking about the quote is like where am I 823 00:41:56,840 --> 00:41:59,440 Speaker 1: going to get a human skull? Because that needed to 824 00:41:59,440 --> 00:42:01,360 Speaker 1: me and like to put on to put on a 825 00:42:01,400 --> 00:42:04,399 Speaker 1: performance of Hamlet that yorick. So like I feel like 826 00:42:04,880 --> 00:42:08,080 Speaker 1: you know that actually, like understanding what matters for the 827 00:42:08,120 --> 00:42:11,000 Speaker 1: person doing the thing is often way more interesting than 828 00:42:11,040 --> 00:42:13,239 Speaker 1: like the deep theory. I mean we we both talked 829 00:42:13,239 --> 00:42:15,759 Speaker 1: to Ryan Peterson at flex Sport, and you know, you 830 00:42:15,800 --> 00:42:18,239 Speaker 1: talk to someone like that and you're talking, you're talking 831 00:42:18,239 --> 00:42:21,760 Speaker 1: about maritime law and how it came to be, and 832 00:42:21,960 --> 00:42:24,680 Speaker 1: what you realize is, like God, everything's just messy, like 833 00:42:24,760 --> 00:42:27,919 Speaker 1: nothing's neat and tidy, like like Aristotle was right, not 834 00:42:27,920 --> 00:42:30,640 Speaker 1: not Plato. You know, if you know your philosophy, and 835 00:42:30,960 --> 00:42:35,080 Speaker 1: the details matter and path dependence matters, and you just 836 00:42:35,160 --> 00:42:37,920 Speaker 1: like everything is a compromise and you gotta keep pushing, 837 00:42:37,960 --> 00:42:39,959 Speaker 1: like all these great stories like Ryan will tell about 838 00:42:40,000 --> 00:42:43,360 Speaker 1: their business, like he ran headfirst into it, not a 839 00:42:43,360 --> 00:42:45,960 Speaker 1: brick wall of steel, wall of just inertia, and like 840 00:42:46,080 --> 00:42:50,160 Speaker 1: weird paper and pen processes, and he learned about how 841 00:42:50,200 --> 00:42:52,640 Speaker 1: stuff moves around on the ocean and it's way more 842 00:42:52,680 --> 00:42:56,160 Speaker 1: interesting and complicated than you could possibly imagine. And and 843 00:42:56,200 --> 00:42:59,480 Speaker 1: my friend zachs Zack Cantra has an amazing article he 844 00:42:59,520 --> 00:43:02,880 Speaker 1: always sends around called reality has a surprising amount of detail, 845 00:43:03,360 --> 00:43:06,200 Speaker 1: And I just loved I love that idea, like learning 846 00:43:06,239 --> 00:43:10,240 Speaker 1: about maritime law and shipping invoices and why it matters 847 00:43:10,280 --> 00:43:12,560 Speaker 1: to the world. And it's just so much more interesting 848 00:43:12,600 --> 00:43:16,880 Speaker 1: to me than than some you know, broadly applicable concept detail. 849 00:43:17,080 --> 00:43:21,319 Speaker 1: It's more fun. I love that saying, Um, that's really good. 850 00:43:21,320 --> 00:43:23,120 Speaker 1: We're going to have to take that to heart in 851 00:43:23,200 --> 00:43:28,360 Speaker 1: some future Logistics and supply episodes. I think, Okay, well, Patrick, 852 00:43:28,480 --> 00:43:30,319 Speaker 1: we're going to leave it there, but thank you so 853 00:43:30,400 --> 00:43:32,640 Speaker 1: much for coming on. That was really great. Thank you 854 00:43:32,680 --> 00:43:35,440 Speaker 1: guys so much for having me. That was great, Patrick, 855 00:43:35,520 --> 00:43:51,160 Speaker 1: thank you so much. Okay, so that was really enjoyable. 856 00:43:51,200 --> 00:43:54,719 Speaker 1: And obviously, um, Patrick is a pro at podcasting and 857 00:43:54,840 --> 00:43:58,759 Speaker 1: a competitor. UM, so we shouldn't hype his podcast too much, 858 00:43:58,800 --> 00:44:01,000 Speaker 1: although it is very good. Um. But one thing I 859 00:44:01,080 --> 00:44:04,200 Speaker 1: was thinking about is you know that, um, you know 860 00:44:04,280 --> 00:44:07,160 Speaker 1: that last point he was making about, you know, reality 861 00:44:07,239 --> 00:44:10,320 Speaker 1: is sort of full of details, are all about the details, 862 00:44:10,360 --> 00:44:12,200 Speaker 1: And I was sort of thinking about that in the 863 00:44:12,280 --> 00:44:17,000 Speaker 1: context of the custom indexing business itself. So this idea 864 00:44:17,120 --> 00:44:21,200 Speaker 1: that if you want an index that actually reflects the 865 00:44:21,239 --> 00:44:23,719 Speaker 1: world as you see it, or you know, as you 866 00:44:23,760 --> 00:44:25,719 Speaker 1: want it to be reflected, like, you are going to 867 00:44:25,760 --> 00:44:28,600 Speaker 1: have to drill down into specific companies and maybe it 868 00:44:28,640 --> 00:44:31,520 Speaker 1: makes more sense to make your own judgment call on 869 00:44:31,600 --> 00:44:34,759 Speaker 1: what those should be versus actually buying you know, the 870 00:44:34,800 --> 00:44:39,239 Speaker 1: top five hundred firms by market cap. Yeah, I thought, 871 00:44:39,280 --> 00:44:41,279 Speaker 1: I mean, I thought that whole conversation is interesting and 872 00:44:41,320 --> 00:44:43,839 Speaker 1: he was definitely sort of speaking our language at the end. 873 00:44:44,000 --> 00:44:45,400 Speaker 1: I thought you were going to go the other way 874 00:44:45,840 --> 00:44:49,600 Speaker 1: with the point about like, you know, again that buying 875 00:44:49,640 --> 00:44:52,400 Speaker 1: the S and P five hundred seems like the easiest 876 00:44:52,480 --> 00:44:55,440 Speaker 1: like strategy in the world. But as he points out, 877 00:44:55,480 --> 00:44:58,360 Speaker 1: like even that is like and you pointed out in 878 00:44:58,400 --> 00:45:00,680 Speaker 1: the intros, like even that as an doble like feet 879 00:45:00,680 --> 00:45:04,120 Speaker 1: of technology, even though like the technology has been abstracted 880 00:45:04,280 --> 00:45:06,239 Speaker 1: away to the point where we like I don't think 881 00:45:06,280 --> 00:45:11,239 Speaker 1: most people think of like buying spy as a technology thing, 882 00:45:11,640 --> 00:45:13,600 Speaker 1: but even that, like just think about like how messy 883 00:45:13,760 --> 00:45:15,719 Speaker 1: that must have been, like to create a piece of 884 00:45:15,760 --> 00:45:18,960 Speaker 1: software that can like rebalance five stocks every minute or 885 00:45:19,000 --> 00:45:21,320 Speaker 1: every day, Like, given that, it is like sort of 886 00:45:21,320 --> 00:45:24,640 Speaker 1: an extraordinary feet of like detail and attention, you know, 887 00:45:24,719 --> 00:45:27,759 Speaker 1: attention to detail. Yeah, But also it sort of ties 888 00:45:27,800 --> 00:45:31,319 Speaker 1: into his point about diversification as well, which is like 889 00:45:31,440 --> 00:45:36,879 Speaker 1: passive investing isn't necessarily very good at identifying the next 890 00:45:37,000 --> 00:45:40,160 Speaker 1: up and coming thing for obvious reasons. So like there's 891 00:45:40,200 --> 00:45:42,759 Speaker 1: not going to be some sort of crypto play in 892 00:45:42,800 --> 00:45:45,000 Speaker 1: the SMP five hundred um, so you're not going to 893 00:45:45,080 --> 00:45:46,520 Speaker 1: make a lot of money from that, and so you 894 00:45:46,600 --> 00:45:49,640 Speaker 1: kind of have to go out and seek those outside 895 00:45:49,680 --> 00:45:53,799 Speaker 1: of the realms of traditional fund management. I think, well, 896 00:45:54,160 --> 00:45:56,680 Speaker 1: Visa Blood and n f T recently, so they're now 897 00:45:56,880 --> 00:46:01,160 Speaker 1: now they could be okay, but no, no, no, you're 898 00:46:01,200 --> 00:46:05,000 Speaker 1: absolutely right. Yeah, everyone's um buying bitcoin for they're like 899 00:46:05,200 --> 00:46:08,000 Speaker 1: cash reserve, so everything will be a crypto play soon enough. 900 00:46:08,120 --> 00:46:09,920 Speaker 1: But you know, if you wanted to get in early, 901 00:46:10,160 --> 00:46:15,600 Speaker 1: you would have struggled without some sort of absolutely yeah, okay, um, 902 00:46:15,600 --> 00:46:18,040 Speaker 1: shall we leave it there? Let's leave it there. Okay. 903 00:46:18,280 --> 00:46:20,960 Speaker 1: This has been another episode of the All Thoughts podcast. 904 00:46:21,040 --> 00:46:23,640 Speaker 1: I'm Tracy Alloway. You can follow me on Twitter at 905 00:46:23,680 --> 00:46:27,120 Speaker 1: Tracy Alloway and I'm Joe wisn't Thal. You can follow 906 00:46:27,160 --> 00:46:30,400 Speaker 1: me on Twitter at The Stalwart. Follow our guest on Twitter, 907 00:46:30,440 --> 00:46:35,440 Speaker 1: Patrick O'Shaughnessy. He's at Patrick Underscore Oshang. Follow our producer 908 00:46:35,520 --> 00:46:39,240 Speaker 1: Laura Carlson. She's at Laura M. Carlson. Followed the Bloomberg 909 00:46:39,280 --> 00:46:42,839 Speaker 1: head of podcast were incessca Levie at Francesco Today, and 910 00:46:43,000 --> 00:46:45,640 Speaker 1: check out all of our podcasts at Bloomberg under the 911 00:46:45,680 --> 00:47:03,520 Speaker 1: handle at podcasts. Thanks for listening to