1 00:00:10,000 --> 00:00:13,400 Speaker 1: Hello, and welcome to another episode of the All Thoughts Podcast. 2 00:00:13,480 --> 00:00:16,600 Speaker 1: I'm Tracy Alloway and I'm Joe. Wi isn't the Joe. 3 00:00:16,960 --> 00:00:19,800 Speaker 1: There's been a lot of crazy stuff that's happened over 4 00:00:19,800 --> 00:00:22,919 Speaker 1: the past couple of years. I don't know what what 5 00:00:23,160 --> 00:00:27,800 Speaker 1: what makes you say that? Well, okay, besides literally everything, 6 00:00:27,840 --> 00:00:31,400 Speaker 1: besides everything, the most remarkable thing is when when I 7 00:00:31,440 --> 00:00:35,040 Speaker 1: think about this year and the bottom falling out of 8 00:00:35,080 --> 00:00:38,800 Speaker 1: a whole bunch of stuff, is that this is exactly 9 00:00:38,880 --> 00:00:42,080 Speaker 1: what everyone or what a lot of people said would happen. Right. 10 00:00:42,159 --> 00:00:46,400 Speaker 1: People looked at text stocks, people looked at crypto and 11 00:00:46,440 --> 00:00:50,519 Speaker 1: they said, this looks unsustainable. It looks like a bubble, 12 00:00:50,680 --> 00:00:52,560 Speaker 1: or it looks like a mania. Why in the world 13 00:00:52,640 --> 00:00:55,080 Speaker 1: are people buying this stuff? Well, you know, it's funny 14 00:00:55,240 --> 00:00:58,279 Speaker 1: thinking back to the top of the meme market, like 15 00:00:58,320 --> 00:01:01,840 Speaker 1: in ear and people are like, this has got to 16 00:01:01,880 --> 00:01:05,039 Speaker 1: be the top, rights and it turned out to be 17 00:01:05,160 --> 00:01:07,880 Speaker 1: exactly the top, And that never happens. But I guess 18 00:01:07,920 --> 00:01:09,759 Speaker 1: if you say this has got to be the top enough, 19 00:01:10,120 --> 00:01:11,880 Speaker 1: then eventually will be. But if you look at like 20 00:01:11,920 --> 00:01:15,120 Speaker 1: some of those measures MOREGANA. Stanley puts together this great 21 00:01:15,160 --> 00:01:18,040 Speaker 1: chart of like the cumulative p and L of Robin 22 00:01:18,080 --> 00:01:22,319 Speaker 1: Hood traders since the start of the pandemic, and it 23 00:01:22,360 --> 00:01:25,600 Speaker 1: basically peaked right in February one, and then it's been 24 00:01:25,640 --> 00:01:28,000 Speaker 1: downhill ever since. It really was the top, right, I 25 00:01:28,040 --> 00:01:31,520 Speaker 1: think retail investors basically erase any gains that they made 26 00:01:31,640 --> 00:01:37,720 Speaker 1: from So looking back with the benefit of hindsight, it 27 00:01:37,760 --> 00:01:40,800 Speaker 1: seems inevitable that all of this, you know, would turn 28 00:01:40,880 --> 00:01:44,760 Speaker 1: out this way. But as we were describing, there are 29 00:01:44,760 --> 00:01:47,480 Speaker 1: still people who jump into these things right totally in 30 00:01:47,520 --> 00:01:50,120 Speaker 1: the grand scheme of things. It's like people always joke 31 00:01:50,200 --> 00:01:53,880 Speaker 1: like hindsight is but I've never actually believed that's true. 32 00:01:53,960 --> 00:01:55,480 Speaker 1: And we know that's not true because we look at 33 00:01:55,560 --> 00:01:58,360 Speaker 1: history all the time and dispute what actually happened, right, 34 00:01:58,520 --> 00:02:02,640 Speaker 1: and so there's never actually any agreement. Nonetheless, you know, 35 00:02:02,760 --> 00:02:04,960 Speaker 1: with this sort of like cycle having played out, of 36 00:02:04,960 --> 00:02:07,640 Speaker 1: all these people on during the market getting excited about 37 00:02:07,640 --> 00:02:09,920 Speaker 1: some of the craziest stuff there is everyone calling a 38 00:02:09,960 --> 00:02:13,120 Speaker 1: top and then a downturn, it's probably not too early 39 00:02:13,160 --> 00:02:15,520 Speaker 1: to start asking the question, like, what did we learn 40 00:02:15,600 --> 00:02:17,560 Speaker 1: the last two years about how markets work? Yeah, I 41 00:02:17,560 --> 00:02:20,280 Speaker 1: think that's right, And obviously some stuff is still shaking out. 42 00:02:20,639 --> 00:02:23,359 Speaker 1: But I think we have enough here to at least 43 00:02:23,440 --> 00:02:26,760 Speaker 1: do a review of everything that we've seen over the 44 00:02:26,800 --> 00:02:29,560 Speaker 1: past couple of years and how you know investors can 45 00:02:29,639 --> 00:02:32,800 Speaker 1: avoid some of the mistakes they may have made in 46 00:02:33,120 --> 00:02:36,440 Speaker 1: that period. Time to start learning. Yes, okay, the learning 47 00:02:36,440 --> 00:02:39,200 Speaker 1: hour on All Loots. Well, I'm pleased to say we 48 00:02:39,280 --> 00:02:41,440 Speaker 1: have the perfect person to discuss this. We're going to 49 00:02:41,520 --> 00:02:44,520 Speaker 1: be speaking with Ben Eiffert, who has been on the 50 00:02:44,520 --> 00:02:48,919 Speaker 1: podcast a number of times talking about retail investing, talking 51 00:02:49,000 --> 00:02:52,560 Speaker 1: about derivatives, the impact of retail getting into derivatives on 52 00:02:52,600 --> 00:02:55,480 Speaker 1: the market. He is, of course a managing partner at 53 00:02:55,560 --> 00:02:59,559 Speaker 1: QVR Advisors, which is a boutique hedge fund that specializes 54 00:02:59,600 --> 00:03:03,200 Speaker 1: involved derivative So Ben, thank you so much for coming 55 00:03:03,200 --> 00:03:06,520 Speaker 1: back on all thoughts. Racy, Joe, it's so nice to 56 00:03:06,520 --> 00:03:09,280 Speaker 1: be back. I missed you guys. It's been way too long. 57 00:03:09,960 --> 00:03:14,080 Speaker 1: So maybe to begin with there are so many crazy 58 00:03:14,120 --> 00:03:16,440 Speaker 1: things we could start with. But what do you think 59 00:03:16,520 --> 00:03:18,560 Speaker 1: was the craziest thing that you saw in the market 60 00:03:18,760 --> 00:03:20,720 Speaker 1: over the past couple of years. Was there a moment 61 00:03:20,720 --> 00:03:23,480 Speaker 1: where you were just like, I cannot believe this is happening. 62 00:03:25,080 --> 00:03:28,480 Speaker 1: The absolutely I think the craziest moments of the last 63 00:03:28,520 --> 00:03:30,880 Speaker 1: few years is a really really really tall orator, right, 64 00:03:31,400 --> 00:03:37,160 Speaker 1: I would say, actually, I found the sizes of the 65 00:03:37,320 --> 00:03:41,640 Speaker 1: unsecured loans that very large. And you might have thought 66 00:03:41,800 --> 00:03:47,560 Speaker 1: sophisticated investors and credit organizations were giving to three Arrows 67 00:03:47,600 --> 00:03:49,560 Speaker 1: capital two and a half two and a half billion 68 00:03:49,560 --> 00:03:52,480 Speaker 1: dollars in the Genesis alone with like no collateral, Right. 69 00:03:53,040 --> 00:03:55,040 Speaker 1: I mean you come into this just thinking, look, these 70 00:03:55,040 --> 00:03:58,160 Speaker 1: are these are big boys, These are are wealthy people 71 00:03:58,160 --> 00:04:01,040 Speaker 1: who created a tremendous amount of money, and they wouldn't 72 00:04:01,080 --> 00:04:05,560 Speaker 1: just do completely obviously crazy stuff like that, right, And 73 00:04:05,560 --> 00:04:07,360 Speaker 1: then and then it turns out that the answer is 74 00:04:07,400 --> 00:04:10,400 Speaker 1: and of course they do. Well, that's such a great answer, 75 00:04:10,440 --> 00:04:13,320 Speaker 1: And I'm glad you said that, because obviously we did 76 00:04:13,400 --> 00:04:16,400 Speaker 1: this intro and we talked about like, oh, the retail 77 00:04:16,520 --> 00:04:20,640 Speaker 1: craziness and people buying AMC in GameStop on robin Hood. 78 00:04:20,800 --> 00:04:23,920 Speaker 1: But of course you're right, like, actually these were pros. 79 00:04:24,120 --> 00:04:27,039 Speaker 1: These were people who are like very successful and essentially 80 00:04:27,040 --> 00:04:31,560 Speaker 1: like building an industry and lending billions of dollars unsecured 81 00:04:31,760 --> 00:04:35,120 Speaker 1: to a crypto hedge fund that we know in retrospect 82 00:04:35,200 --> 00:04:39,560 Speaker 1: was not doing anything particularly uh sophisticated. That's actually like 83 00:04:39,600 --> 00:04:43,560 Speaker 1: way crazier than buying shares of game stop. Absolutely, I 84 00:04:43,600 --> 00:04:46,120 Speaker 1: think retail gets all of the attention, and you know, 85 00:04:46,160 --> 00:04:47,640 Speaker 1: we can talk about that all day, and there's all 86 00:04:47,680 --> 00:04:51,080 Speaker 1: kinds of stuff there, but I think people forget that 87 00:04:51,520 --> 00:04:55,520 Speaker 1: the role of institutional investors in this process, and the 88 00:04:55,560 --> 00:04:59,480 Speaker 1: way that institutional investors start to buy into narratives and 89 00:04:59,560 --> 00:05:03,599 Speaker 1: start uh and you start to develop this fear that 90 00:05:03,680 --> 00:05:07,640 Speaker 1: they're missing some huge technological revolution um and then do 91 00:05:08,320 --> 00:05:11,200 Speaker 1: incredibly crazy things in huge size is almost a more 92 00:05:11,240 --> 00:05:14,360 Speaker 1: interesting story. Can you actually talk a little bit more 93 00:05:14,520 --> 00:05:19,599 Speaker 1: about the psychology the sort of institutional fomo, because again, 94 00:05:19,640 --> 00:05:22,960 Speaker 1: like sort of like retail fomo is really obvious. If 95 00:05:23,000 --> 00:05:25,640 Speaker 1: your friend, you know, suddenly made ten tho dollars or 96 00:05:25,680 --> 00:05:29,560 Speaker 1: a hundred thousand or more, like trading call options on 97 00:05:29,640 --> 00:05:31,520 Speaker 1: robin Hood, maybe you want to get into it, but 98 00:05:31,640 --> 00:05:35,640 Speaker 1: you probably assume in your capacity as a hedge fund manager, 99 00:05:35,760 --> 00:05:39,200 Speaker 1: you probably talked to a lot of sophisticated investors institutions. 100 00:05:39,800 --> 00:05:43,479 Speaker 1: You must see like the institutional fomo side in a 101 00:05:43,520 --> 00:05:46,080 Speaker 1: way that the rest of us don't. How does that work? 102 00:05:46,080 --> 00:05:47,680 Speaker 1: How does that thinking and how do they sort of 103 00:05:47,680 --> 00:05:50,960 Speaker 1: like get in the brain space where they become comfortable 104 00:05:51,040 --> 00:05:54,359 Speaker 1: or obsessed with like taking these huge risks. Absolutely, I 105 00:05:54,400 --> 00:05:57,960 Speaker 1: think it's you know, on the face of it, institutions 106 00:05:58,000 --> 00:06:01,840 Speaker 1: are probably better at no to saying things that just 107 00:06:01,920 --> 00:06:04,599 Speaker 1: seem obviously crazy and silly. You know, They're less likely 108 00:06:04,720 --> 00:06:08,800 Speaker 1: to buy into very poorly framed Look, you can make 109 00:06:08,839 --> 00:06:11,440 Speaker 1: a thousand percent a month doing this kind of you know, 110 00:06:11,520 --> 00:06:15,920 Speaker 1: kind of pitches. Right. Institutions have generally speaking, smart fook 111 00:06:15,960 --> 00:06:18,599 Speaker 1: smart people, and they're able to recognize those kind of 112 00:06:18,600 --> 00:06:22,000 Speaker 1: things very quickly. But what I think is really key 113 00:06:22,120 --> 00:06:28,920 Speaker 1: here is that momentum is very dangerous for institutional investors 114 00:06:28,960 --> 00:06:32,120 Speaker 1: precisely because it's a real financial markets phenomena, right. It's 115 00:06:32,120 --> 00:06:35,359 Speaker 1: one that's had tremendous amount of proper academic research for 116 00:06:35,400 --> 00:06:38,560 Speaker 1: a long time. It's clearly an effect that exists in 117 00:06:38,600 --> 00:06:41,240 Speaker 1: a sense, and really and momentum is the tendency of 118 00:06:41,560 --> 00:06:43,800 Speaker 1: things that have been going up lately to keep going 119 00:06:43,880 --> 00:06:46,120 Speaker 1: up in the in the near future, right. And the 120 00:06:46,160 --> 00:06:51,440 Speaker 1: best explanation really, I think for historical momentum effects is 121 00:06:51,480 --> 00:06:56,360 Speaker 1: that something important is changing behind the scenes about the world, right, 122 00:06:56,480 --> 00:07:01,320 Speaker 1: and it's poorly understood and skept eckle, old fashioned or 123 00:07:01,320 --> 00:07:05,120 Speaker 1: grumpy investors try to fight it, right. Warren Buffett says, look, 124 00:07:05,160 --> 00:07:09,000 Speaker 1: I can't own Google or Amazon twenty twelve because look 125 00:07:09,000 --> 00:07:11,120 Speaker 1: at these pe multiples, they're kind of high. I don't 126 00:07:11,120 --> 00:07:13,040 Speaker 1: really understand what these guys are doing. And then they 127 00:07:13,040 --> 00:07:16,000 Speaker 1: turn out to be these huge transformative businesses. Right, And 128 00:07:16,360 --> 00:07:20,640 Speaker 1: that's a real thing, and it results on average in 129 00:07:20,840 --> 00:07:23,720 Speaker 1: various ways. In sometimes it makes sense to own things 130 00:07:23,800 --> 00:07:25,600 Speaker 1: that have been going up, even if you don't totally 131 00:07:25,640 --> 00:07:30,320 Speaker 1: understand why. Right. But the longer that returns momentum builds 132 00:07:30,680 --> 00:07:34,320 Speaker 1: in some particular area, right, the more over time that 133 00:07:34,680 --> 00:07:38,840 Speaker 1: even institutional investors that are generally sophisticated and skeptical feel 134 00:07:38,920 --> 00:07:42,040 Speaker 1: the need to get involved, right because they start to think, look, 135 00:07:42,080 --> 00:07:44,640 Speaker 1: I must be missing out. I don't totally understand this, 136 00:07:44,720 --> 00:07:47,040 Speaker 1: but I must be missing out on something transformative. I 137 00:07:47,080 --> 00:07:49,320 Speaker 1: can't be the guy who's sitting here in this room 138 00:07:49,400 --> 00:07:52,080 Speaker 1: in five or ten years and say, yeah, I didn't 139 00:07:52,120 --> 00:07:54,640 Speaker 1: own Amazon or I didn't get involved in that new thing, 140 00:07:54,880 --> 00:07:57,160 Speaker 1: and I completely missed out, and everybody else made a 141 00:07:57,160 --> 00:07:59,080 Speaker 1: ton of money doing this and I just didn't get it. 142 00:07:59,080 --> 00:08:02,360 Speaker 1: At the time right um. And I think the institutional 143 00:08:02,400 --> 00:08:07,600 Speaker 1: investors also probably have a pretty high tolerance and almost 144 00:08:07,640 --> 00:08:12,360 Speaker 1: sometimes an attraction to complexity. Right It makes makes them 145 00:08:12,440 --> 00:08:15,440 Speaker 1: feel smart, makes them feel in the know about something new, 146 00:08:15,960 --> 00:08:20,320 Speaker 1: and often, of course, complexity can obscure the sources of 147 00:08:20,400 --> 00:08:23,040 Speaker 1: risk that are actually being taken into an investment. So 148 00:08:23,360 --> 00:08:27,120 Speaker 1: just on the idea of momentum, this is something that 149 00:08:27,160 --> 00:08:30,920 Speaker 1: I feel was different about the past couple of years, 150 00:08:30,960 --> 00:08:33,679 Speaker 1: maybe on the institutional side as well as the retail side. 151 00:08:33,720 --> 00:08:38,120 Speaker 1: But it feels to me like people used to if 152 00:08:38,120 --> 00:08:41,040 Speaker 1: they saw something that they thought was a bubble or 153 00:08:41,600 --> 00:08:44,640 Speaker 1: didn't make sense, or you know, it was a mania 154 00:08:44,720 --> 00:08:47,800 Speaker 1: in one form or another, I think people would shy 155 00:08:47,840 --> 00:08:51,200 Speaker 1: away from it, thinking that this is a bad investment. 156 00:08:51,200 --> 00:08:53,160 Speaker 1: But it feels like over the past couple of years, 157 00:08:53,640 --> 00:08:58,560 Speaker 1: people sort of wholeheartedly just jumped in, knowing that a 158 00:08:58,640 --> 00:09:02,520 Speaker 1: lot of the price action was it necessarily justified by fundamentals, 159 00:09:02,640 --> 00:09:04,839 Speaker 1: but thinking that you could go in, you can make 160 00:09:04,840 --> 00:09:06,920 Speaker 1: some money and then hopefully get out on time. In 161 00:09:07,000 --> 00:09:11,360 Speaker 1: your experience, is that behavior that you've observed, Like, is 162 00:09:11,360 --> 00:09:14,840 Speaker 1: it that nihilistic or is it really about the narrative 163 00:09:14,880 --> 00:09:17,440 Speaker 1: and people just not wanting to miss the next big thing. 164 00:09:18,960 --> 00:09:22,280 Speaker 1: I think there's an inherent cyclicality to it, just with 165 00:09:22,840 --> 00:09:27,640 Speaker 1: human memory and institutional memory and the experience of of investors, right. 166 00:09:28,080 --> 00:09:31,839 Speaker 1: I mean, there's just simple important factors here, like how 167 00:09:31,880 --> 00:09:35,240 Speaker 1: long has it been since the last big mania that 168 00:09:35,480 --> 00:09:39,240 Speaker 1: people were piling into that ended really poorly, right, allowing 169 00:09:39,400 --> 00:09:42,360 Speaker 1: the collective consciousness of excess and crash to fade, and 170 00:09:42,760 --> 00:09:45,200 Speaker 1: time for new narratives to build, and time for those 171 00:09:45,200 --> 00:09:48,440 Speaker 1: new narratives to generate returns and to attempt new investors, 172 00:09:48,840 --> 00:09:51,880 Speaker 1: time for new frontiers to emerge. That can we can 173 00:09:51,920 --> 00:09:54,920 Speaker 1: create new narratives around. I mean, if you think back 174 00:09:55,040 --> 00:09:58,160 Speaker 1: really to the last couple of decades, and it's been 175 00:09:58,200 --> 00:10:02,480 Speaker 1: a pretty long, slow bowl market cycle since two thousand 176 00:10:02,520 --> 00:10:04,880 Speaker 1: and nine. Right. We've had some minor disruptions, We had 177 00:10:04,920 --> 00:10:07,160 Speaker 1: some European sovereign debt issues, and we had a few 178 00:10:07,160 --> 00:10:11,000 Speaker 1: other things, but really things have gone really, really really 179 00:10:11,040 --> 00:10:14,560 Speaker 1: well for a long time. And market participants, you know, 180 00:10:14,600 --> 00:10:18,079 Speaker 1: the memory of the tech bust is pretty long faded, 181 00:10:18,120 --> 00:10:21,760 Speaker 1: certainly in terms of actual institutional knowledge of investment organizations 182 00:10:21,840 --> 00:10:23,880 Speaker 1: as opposed to just in lore of the old old 183 00:10:23,920 --> 00:10:28,360 Speaker 1: people right, um, and that leads market participants over time 184 00:10:28,440 --> 00:10:31,440 Speaker 1: to start taking more and more silly risks and to 185 00:10:31,559 --> 00:10:35,200 Speaker 1: become more and more susceptible to creating narratives around you know, 186 00:10:35,280 --> 00:10:37,520 Speaker 1: some of these new things. I think that, you know, 187 00:10:37,600 --> 00:10:39,240 Speaker 1: I think it's going to be much harder, you know, 188 00:10:39,320 --> 00:10:41,319 Speaker 1: in the next three or four years. Probably we won't 189 00:10:41,360 --> 00:10:45,000 Speaker 1: see a bunch of you know, brand new, really you know, 190 00:10:45,040 --> 00:10:47,760 Speaker 1: really crazy things developed famous last words, right, I mean, 191 00:10:47,800 --> 00:11:06,640 Speaker 1: we probably will Because I said that something that I've 192 00:11:06,800 --> 00:11:09,880 Speaker 1: been thinking about two and it really fits with this 193 00:11:10,000 --> 00:11:13,680 Speaker 1: idea of like the sort of like last institutional holdouts, 194 00:11:13,720 --> 00:11:16,640 Speaker 1: the people that fight the new thing, that people that 195 00:11:16,920 --> 00:11:20,040 Speaker 1: are skeptical of tech, the people that are skeptical of crypto, 196 00:11:20,080 --> 00:11:22,720 Speaker 1: and then like eventually they sort of get dragged along 197 00:11:22,760 --> 00:11:26,160 Speaker 1: and then eventually many of them capitulate. Not only does 198 00:11:26,200 --> 00:11:28,920 Speaker 1: it seem like many of them capitulate in some way 199 00:11:29,000 --> 00:11:32,080 Speaker 1: or another, it seems like in the late stages of 200 00:11:32,120 --> 00:11:35,240 Speaker 1: the boom or the bubble specifically, you get the most 201 00:11:35,320 --> 00:11:38,680 Speaker 1: egregious behavior. And I don't remember the exact dates, but 202 00:11:38,720 --> 00:11:41,440 Speaker 1: I'm thinking like some of these loans to like three 203 00:11:41,480 --> 00:11:44,679 Speaker 1: arrows capital or some of these moves into like Luna, 204 00:11:44,880 --> 00:11:48,320 Speaker 1: the stable coin ecosystem that crashed like they happened really 205 00:11:48,440 --> 00:11:51,280 Speaker 1: late in the cycle. It seems like there's this effect 206 00:11:51,280 --> 00:11:54,520 Speaker 1: where not only do the final folks get dragged across 207 00:11:54,559 --> 00:11:57,080 Speaker 1: the line, they seem to really like do it in 208 00:11:57,280 --> 00:12:02,679 Speaker 1: size at the worst possible time. I think that's totally right. 209 00:12:02,720 --> 00:12:04,440 Speaker 1: I mean, if you look back again at this what 210 00:12:04,600 --> 00:12:09,000 Speaker 1: has been a very long, slowish, you know, bullmarket cycle 211 00:12:09,000 --> 00:12:12,280 Speaker 1: where things have been good, it was really only call 212 00:12:12,360 --> 00:12:14,880 Speaker 1: it that was sort of the turning point where all 213 00:12:14,920 --> 00:12:18,040 Speaker 1: of a sudden everything started to just go parabolic together 214 00:12:18,080 --> 00:12:22,319 Speaker 1: at the same time, right across public markets, across private markets. 215 00:12:22,720 --> 00:12:25,440 Speaker 1: You know, I think a big part of the institutional 216 00:12:25,520 --> 00:12:31,280 Speaker 1: role in that really came from this huge psychology around 217 00:12:31,600 --> 00:12:35,960 Speaker 1: private assets and private investments being this fantastic place to be. 218 00:12:36,120 --> 00:12:39,600 Speaker 1: There's big sources of innovation, stable returns because you know, 219 00:12:39,640 --> 00:12:43,320 Speaker 1: without park to market volatility. Right. You saw just really 220 00:12:43,360 --> 00:12:45,880 Speaker 1: in the last few years, you see the formation of 221 00:12:46,000 --> 00:12:49,240 Speaker 1: VC growth funds. Right. So you always used to think 222 00:12:49,280 --> 00:12:52,640 Speaker 1: of venture capital as you know, these nerdy, weird engineers 223 00:12:52,720 --> 00:12:56,560 Speaker 1: doing cool science experiments and backing these early stage companies 224 00:12:56,600 --> 00:12:59,839 Speaker 1: to do really disruptive stuff, Right, whereas growth funds were 225 00:12:59,880 --> 00:13:03,880 Speaker 1: all about raising mega institutional scale capital at full fees 226 00:13:03,920 --> 00:13:07,160 Speaker 1: with long luck and plowing that into companies that were 227 00:13:07,200 --> 00:13:09,440 Speaker 1: already valued at two billion dollars and just had a 228 00:13:09,440 --> 00:13:13,319 Speaker 1: completely different asymmetry to the return profile. Right, And you 229 00:13:13,400 --> 00:13:16,640 Speaker 1: had corporates like soft Bank and hybrid public private headphunes 230 00:13:16,679 --> 00:13:19,840 Speaker 1: like Tiger coming in to compete for deals, to get 231 00:13:19,840 --> 00:13:23,000 Speaker 1: those deals with startups by saying, look, we have bigger 232 00:13:23,080 --> 00:13:25,200 Speaker 1: checks and we're not going to ask you any annoying questions. 233 00:13:25,200 --> 00:13:27,319 Speaker 1: We're not going to do due diligence, like I want 234 00:13:27,400 --> 00:13:29,120 Speaker 1: you to sign the storm sheet in twenty four hours 235 00:13:29,120 --> 00:13:32,560 Speaker 1: that I just sent you, right, And that was really 236 00:13:32,800 --> 00:13:35,640 Speaker 1: you know, where did that a lot of that came from. 237 00:13:35,679 --> 00:13:37,360 Speaker 1: I mean I was and I think I had a 238 00:13:37,360 --> 00:13:41,319 Speaker 1: Twitter post about this, But I would go to conferences 239 00:13:41,360 --> 00:13:43,560 Speaker 1: with big institutional investors and the only thing that you 240 00:13:43,559 --> 00:13:47,400 Speaker 1: would hear about was how big asset owners were taking 241 00:13:47,440 --> 00:13:50,840 Speaker 1: money out of liquid alternative type of investments and put 242 00:13:50,880 --> 00:13:53,480 Speaker 1: and moving them into privates because the returns and privates 243 00:13:53,480 --> 00:13:55,880 Speaker 1: had them so high, and there was such a perception 244 00:13:55,920 --> 00:13:58,600 Speaker 1: of such limited risk and privates. It also seemed tracy, 245 00:13:58,720 --> 00:14:01,040 Speaker 1: like if you look at it Charter like soft Bank 246 00:14:01,480 --> 00:14:04,240 Speaker 1: the stock Like that's how you erased like years and 247 00:14:04,320 --> 00:14:06,520 Speaker 1: years worth. So it's like soft Bank is where it 248 00:14:06,559 --> 00:14:09,760 Speaker 1: was seen, and it's like, yeah, if you like do 249 00:14:09,880 --> 00:14:12,400 Speaker 1: these like big investments late in the game, you just 250 00:14:12,440 --> 00:14:15,560 Speaker 1: like wipe out years of games. So actually, this is 251 00:14:15,600 --> 00:14:17,880 Speaker 1: something that I want to ask. You know, a lot 252 00:14:17,960 --> 00:14:21,200 Speaker 1: of the craziness that we've seen has been focused on 253 00:14:21,400 --> 00:14:25,760 Speaker 1: tech stocks, either in the public market or tech investments 254 00:14:25,760 --> 00:14:28,400 Speaker 1: in the private market through venture capital and things like that. 255 00:14:28,840 --> 00:14:31,640 Speaker 1: And you were talking about narratives earlier and fear of 256 00:14:31,680 --> 00:14:37,160 Speaker 1: missing out. Is there something about tech specifically that makes 257 00:14:37,240 --> 00:14:41,040 Speaker 1: it more vulnerable to people getting very excited about it. 258 00:14:41,280 --> 00:14:43,640 Speaker 1: I guess there's so much technology that has pitched as 259 00:14:44,120 --> 00:14:47,280 Speaker 1: life changing or world changing in one way or another, 260 00:14:47,360 --> 00:14:49,840 Speaker 1: it feels like it's easier maybe to build a big 261 00:14:49,960 --> 00:14:51,960 Speaker 1: narrative out of it to try to get more people 262 00:14:52,000 --> 00:14:55,280 Speaker 1: into it. I think that's exactly right. So, I mean, 263 00:14:55,320 --> 00:14:58,520 Speaker 1: just to be clear, technology itself is not the problem, right, 264 00:14:58,560 --> 00:15:01,640 Speaker 1: I mean, technology, disruptive tech, logical innovation is what drives 265 00:15:01,680 --> 00:15:04,640 Speaker 1: the world forward. And you know, Silicon Valley and venture 266 00:15:04,640 --> 00:15:06,520 Speaker 1: capital like plays a really important role in that and 267 00:15:06,600 --> 00:15:10,240 Speaker 1: that's great, But the technology inherently has this characteristic right 268 00:15:10,240 --> 00:15:13,320 Speaker 1: that you're not selling a current set of cash flows 269 00:15:13,440 --> 00:15:15,640 Speaker 1: or a well trodden path of how you know that 270 00:15:15,720 --> 00:15:18,440 Speaker 1: can be valued by people with spreadsheets and some kind 271 00:15:18,480 --> 00:15:22,400 Speaker 1: of relatively formula. Wait, it's about selling a vision of 272 00:15:22,440 --> 00:15:25,120 Speaker 1: the future and a vision of what could be and 273 00:15:25,480 --> 00:15:28,000 Speaker 1: how that can play into future economics and trying to 274 00:15:28,040 --> 00:15:30,560 Speaker 1: relate that to past innovation. And like that's a very 275 00:15:30,640 --> 00:15:33,440 Speaker 1: nebulous thing in the end, right, And it's something that 276 00:15:33,600 --> 00:15:40,760 Speaker 1: is inherently susceptible to hype and narrative, particularly when the 277 00:15:41,240 --> 00:15:44,720 Speaker 1: I think, as you've seen in recent years, particularly when 278 00:15:45,400 --> 00:15:50,400 Speaker 1: financial markets set up ways for people to get actually 279 00:15:50,440 --> 00:15:53,440 Speaker 1: paid and to monetize that kind of narrative and hype, 280 00:15:53,520 --> 00:15:56,560 Speaker 1: right as opposed to, Hey, I finished building this company, 281 00:15:56,640 --> 00:15:58,520 Speaker 1: and then I it becomes a big company, and then 282 00:15:58,520 --> 00:16:01,280 Speaker 1: I get really rich. Right when it becomes I sell 283 00:16:01,400 --> 00:16:04,520 Speaker 1: this vision of the future that's really disruptive, and then 284 00:16:04,600 --> 00:16:06,800 Speaker 1: I can issue a token and I can sell it 285 00:16:06,840 --> 00:16:09,080 Speaker 1: to retail and I can make a billion dollars just 286 00:16:09,160 --> 00:16:11,920 Speaker 1: by doing that without actually building anything, right, And I 287 00:16:11,960 --> 00:16:14,880 Speaker 1: think that's you know, we're similarly out you know, in 288 00:16:14,880 --> 00:16:18,400 Speaker 1: in technology. If I can create a startup that gets 289 00:16:18,400 --> 00:16:20,680 Speaker 1: about value to three billion dollars, and then I can 290 00:16:20,720 --> 00:16:22,800 Speaker 1: go into the secondary market and I can get liquidity 291 00:16:22,800 --> 00:16:24,560 Speaker 1: as a founder and sell a lot of my shares 292 00:16:24,600 --> 00:16:27,080 Speaker 1: to like institutional investors that want to get some right. 293 00:16:27,440 --> 00:16:30,680 Speaker 1: And I think that's the inherent trick with technology is 294 00:16:30,720 --> 00:16:34,880 Speaker 1: that it is inherently, by its nature much more susceptible 295 00:16:34,920 --> 00:16:40,240 Speaker 1: to narrative driven you know, valuation and narrative driven thinking. Um, 296 00:16:40,280 --> 00:16:42,240 Speaker 1: And that is what it is, right, That's that's not 297 00:16:42,280 --> 00:16:44,000 Speaker 1: something that's going to go away, but it's something that 298 00:16:44,040 --> 00:16:47,840 Speaker 1: investors have to be really cautious about how to differentiate. 299 00:16:48,360 --> 00:16:50,320 Speaker 1: And you get it's like the early phases of a 300 00:16:50,600 --> 00:16:53,920 Speaker 1: technology cycle, right, you get those nerdy engineers building really 301 00:16:53,920 --> 00:16:57,080 Speaker 1: cool stuff in the garage, but then the NBA start 302 00:16:57,120 --> 00:16:59,600 Speaker 1: to show up. Right, It's kind of a classic line 303 00:16:59,600 --> 00:17:01,840 Speaker 1: and sell a valley, right, and you end up with 304 00:17:01,920 --> 00:17:04,720 Speaker 1: a lot of huckster types coming in to kind of 305 00:17:04,840 --> 00:17:07,360 Speaker 1: ride along the wave because there's so much money involved. 306 00:17:07,440 --> 00:17:10,000 Speaker 1: And that's where you get the trouble. Can you explain 307 00:17:10,240 --> 00:17:13,840 Speaker 1: arc to us, like what was that about? Because you 308 00:17:13,880 --> 00:17:16,040 Speaker 1: know Joe mentioned the soft bank chart. If you pull 309 00:17:16,119 --> 00:17:19,240 Speaker 1: up the Arc Innovation E T F it's pretty similar, 310 00:17:19,280 --> 00:17:23,080 Speaker 1: basically erased like two years of gains. But you know, 311 00:17:23,880 --> 00:17:27,600 Speaker 1: Cathy Wood was out there talking about how the technological 312 00:17:27,680 --> 00:17:31,560 Speaker 1: revolution was going to increase GDP growth to like fifty, 313 00:17:32,560 --> 00:17:35,120 Speaker 1: which I think is a number that has never been 314 00:17:35,119 --> 00:17:38,920 Speaker 1: experienced in terms of GDP growth ever in the history 315 00:17:38,960 --> 00:17:42,560 Speaker 1: of the global economy. But like, what was that about? 316 00:17:42,600 --> 00:17:46,919 Speaker 1: And why did people seem to buy into a vision 317 00:17:47,080 --> 00:17:50,480 Speaker 1: that you know, on the surface was pretty easy to 318 00:17:50,520 --> 00:17:55,360 Speaker 1: pick apart. Yeah, I mean it was a perfect storm. 319 00:17:55,440 --> 00:17:59,879 Speaker 1: I think narrative we have to have these like firew 320 00:18:00,000 --> 00:18:04,879 Speaker 1: exchound to go off. It was this perfect storm of 321 00:18:05,240 --> 00:18:11,119 Speaker 1: timing and compelling narrative, right. I mean, retail investors and 322 00:18:11,160 --> 00:18:13,960 Speaker 1: individual investors were just starting to see this huge up 323 00:18:14,000 --> 00:18:17,240 Speaker 1: surge in interest in markets and trading and participation in 324 00:18:17,320 --> 00:18:19,920 Speaker 1: markets that we hadn't seen since the previous tech boom 325 00:18:19,960 --> 00:18:22,800 Speaker 1: back in the nineties, right, And a lot of that 326 00:18:22,920 --> 00:18:29,080 Speaker 1: interest was centered around new new era, new economy technology stocks, 327 00:18:29,119 --> 00:18:32,359 Speaker 1: a lot of the smaller speculative type of names that 328 00:18:32,400 --> 00:18:35,200 Speaker 1: were coming to the market through SPACs. And you know, 329 00:18:35,400 --> 00:18:38,280 Speaker 1: Kathy did a really good job of capitalizing on that 330 00:18:38,400 --> 00:18:42,159 Speaker 1: interest and offering a really simple way to get exposure, 331 00:18:42,520 --> 00:18:44,800 Speaker 1: you know, not to any specific stock, but to this 332 00:18:44,920 --> 00:18:48,560 Speaker 1: idea of disruptive innovation, right, And that's a theme that 333 00:18:48,760 --> 00:18:51,040 Speaker 1: really appeals to a lot of folks, you know, a 334 00:18:51,119 --> 00:18:53,199 Speaker 1: lot of young folks, but not just young folks, right. 335 00:18:53,320 --> 00:18:56,560 Speaker 1: And she uh, you know, she's charismatic, and she doesn't 336 00:18:56,560 --> 00:18:59,800 Speaker 1: did a great job on TV, and she was able 337 00:18:59,840 --> 00:19:03,320 Speaker 1: to tracked huge inflows. And of course the trick with 338 00:19:03,359 --> 00:19:05,360 Speaker 1: all of that is, you know, I mean, she's made 339 00:19:05,359 --> 00:19:07,480 Speaker 1: a tremendous amount of money, and good for her, but 340 00:19:07,640 --> 00:19:10,320 Speaker 1: on on management fees, on those on those vehicles, but 341 00:19:10,359 --> 00:19:12,760 Speaker 1: if you look at kind of the net capital destruction 342 00:19:13,160 --> 00:19:16,399 Speaker 1: in the process, that's been enormous, right, because she was 343 00:19:16,520 --> 00:19:20,520 Speaker 1: you know, those inflows were partly responsible, among lots of 344 00:19:20,520 --> 00:19:23,159 Speaker 1: other types of things for driving up the prices of 345 00:19:23,200 --> 00:19:26,520 Speaker 1: many of those types of companies dramatically and and ultimately 346 00:19:26,560 --> 00:19:28,480 Speaker 1: way way way out of line with any kind of 347 00:19:28,920 --> 00:19:32,400 Speaker 1: probability of success and probability and monetization. I just had 348 00:19:32,440 --> 00:19:35,359 Speaker 1: this sort of realization actually I've never really thought about 349 00:19:35,440 --> 00:19:38,920 Speaker 1: before until Tracy's question about like narratives and wide tech, 350 00:19:38,920 --> 00:19:42,160 Speaker 1: because it seems to me. The other area where you 351 00:19:42,200 --> 00:19:46,040 Speaker 1: see this is commodities, where there's like incredible stories that 352 00:19:46,080 --> 00:19:48,800 Speaker 1: people tell, Like peak oil was a huge one, the 353 00:19:49,200 --> 00:19:52,480 Speaker 1: endless Rise of China was another one. We're not going 354 00:19:52,560 --> 00:19:55,359 Speaker 1: to have enough copper and lithium for the demand for 355 00:19:55,440 --> 00:19:57,720 Speaker 1: evs for the next ten years. And then of course 356 00:19:57,720 --> 00:20:00,480 Speaker 1: you have all like you know, the hucksters and fine 357 00:20:00,920 --> 00:20:03,960 Speaker 1: financiers who's like, you know, give us your money for 358 00:20:04,000 --> 00:20:06,200 Speaker 1: this mining project up with the Yukon where we're gonna 359 00:20:06,200 --> 00:20:08,320 Speaker 1: strike gold or whatever. It feels like in a way 360 00:20:08,359 --> 00:20:11,000 Speaker 1: like commodities and now we're like in this commodity cycle, 361 00:20:11,040 --> 00:20:13,560 Speaker 1: like and like tech are like these like evil twin 362 00:20:13,680 --> 00:20:17,040 Speaker 1: brothers or like distant cousins where it's like, as a society, 363 00:20:17,119 --> 00:20:23,160 Speaker 1: we oscillate between a tech cycle nineties, commodity cycle, two 364 00:20:23,200 --> 00:20:25,919 Speaker 1: thousand's tech, the twenty tens, where we just sort of 365 00:20:25,920 --> 00:20:28,600 Speaker 1: like passed back and forth between, Like are we in 366 00:20:28,640 --> 00:20:31,600 Speaker 1: a tech story cycle or commodity story cycle. I don't 367 00:20:31,600 --> 00:20:33,399 Speaker 1: know if that's a question, just sort of something I'm like, 368 00:20:33,760 --> 00:20:36,280 Speaker 1: it seems like there's like these big, big swings that 369 00:20:36,320 --> 00:20:38,880 Speaker 1: go back and forth between the two. It's totally true. 370 00:20:38,880 --> 00:20:41,240 Speaker 1: I mean commodities since the beginning of time have been 371 00:20:41,359 --> 00:20:45,719 Speaker 1: just the massive, most massive like cyclical boom bust area 372 00:20:45,880 --> 00:20:49,320 Speaker 1: right where you have shortages and prices get driven up 373 00:20:49,359 --> 00:20:54,439 Speaker 1: and people and companies hoarde and then eventually that leads 374 00:20:54,480 --> 00:20:58,920 Speaker 1: to an economic downturn and commodity prices collapse and there's 375 00:20:58,920 --> 00:21:01,159 Speaker 1: a huge gluts. And this is you know, not a 376 00:21:01,200 --> 00:21:03,480 Speaker 1: new thing, and it's a perpetual thing. But to your point, 377 00:21:03,480 --> 00:21:05,840 Speaker 1: it gets tied up in all kinds of narratives that 378 00:21:05,880 --> 00:21:09,360 Speaker 1: people create around how you know, we're going to run 379 00:21:09,359 --> 00:21:11,280 Speaker 1: out of fossil fuels and oil prices are going to 380 00:21:11,359 --> 00:21:14,560 Speaker 1: go to infinity and then the and it goes back 381 00:21:14,600 --> 00:21:16,200 Speaker 1: and forth and back and forth, and we're doing it 382 00:21:16,240 --> 00:21:20,160 Speaker 1: again now of course, right, and I think, um, there's there. 383 00:21:20,160 --> 00:21:22,560 Speaker 1: It's compliments in a in a it's in some sense 384 00:21:22,560 --> 00:21:25,879 Speaker 1: commodities are like this very simple fundamental thing as compared 385 00:21:25,920 --> 00:21:28,880 Speaker 1: to technology, right, But they get tied up in these 386 00:21:28,880 --> 00:21:32,040 Speaker 1: macro stories, which you know, macro is always really hard, 387 00:21:32,119 --> 00:21:34,359 Speaker 1: right because you know the world is changing, and you 388 00:21:34,400 --> 00:21:37,160 Speaker 1: always can have some conception of you know, the way 389 00:21:37,160 --> 00:21:39,240 Speaker 1: in which the world is changing and why it's going 390 00:21:39,280 --> 00:21:42,400 Speaker 1: to lead to this huge extrapolation. So this actually sort 391 00:21:42,440 --> 00:21:44,520 Speaker 1: of gets to my next question, how do you know 392 00:21:44,560 --> 00:21:48,960 Speaker 1: who's just a storyteller in real time versus someone who 393 00:21:49,200 --> 00:21:52,600 Speaker 1: is actually correctly identifying a new trend. Because you know, 394 00:21:52,640 --> 00:21:55,320 Speaker 1: you mentioned Warren Buffett in the beginning. He was wrong 395 00:21:55,840 --> 00:21:59,080 Speaker 1: and it's like not all of like the Curmudgeons on 396 00:21:59,160 --> 00:22:02,399 Speaker 1: a certain area get vindicated in the end. He was 397 00:22:02,480 --> 00:22:06,159 Speaker 1: wrong to dismiss the Googles and the you know, the 398 00:22:06,240 --> 00:22:10,240 Speaker 1: facebooks in he ended up making a fortune on Apple 399 00:22:10,440 --> 00:22:12,879 Speaker 1: and sort of like erased a bunch of like you 400 00:22:12,880 --> 00:22:15,280 Speaker 1: know that compensated for a bunch, But he was wrong 401 00:22:15,359 --> 00:22:19,080 Speaker 1: on this, And so like in real time, investors really 402 00:22:19,160 --> 00:22:22,000 Speaker 1: are faced with a tough decision because, like sometimes the 403 00:22:22,040 --> 00:22:25,520 Speaker 1: world changes, and it can be really hard to disambiguate 404 00:22:25,560 --> 00:22:28,439 Speaker 1: in real time between who is like a huckster trying 405 00:22:28,440 --> 00:22:31,840 Speaker 1: to like you know, sell their token or whatever versus 406 00:22:31,880 --> 00:22:35,760 Speaker 1: someone who's like identifying a real change that's happening. It's 407 00:22:35,840 --> 00:22:38,240 Speaker 1: really really hard in real time to your point, And 408 00:22:38,280 --> 00:22:40,959 Speaker 1: I think that the reason it's really really hard is 409 00:22:41,000 --> 00:22:43,640 Speaker 1: because again, like we talked about, momentum is a real 410 00:22:43,640 --> 00:22:46,720 Speaker 1: phenomenon and structural change in the world, and technological changes 411 00:22:47,000 --> 00:22:48,639 Speaker 1: is a real thing, right, And so you have to 412 00:22:48,720 --> 00:22:51,959 Speaker 1: keep an open mind, and you can't take the curmudgeon approach, 413 00:22:52,040 --> 00:22:54,439 Speaker 1: right where anything that's new or anything that people are 414 00:22:54,440 --> 00:22:56,520 Speaker 1: excited about or that's going up in price sort of 415 00:22:56,600 --> 00:22:58,280 Speaker 1: must be wrong. And you see a lot of that 416 00:22:58,359 --> 00:23:01,360 Speaker 1: kind of thinking, kind of behavior. That's a wrong mental frame, right. 417 00:23:01,600 --> 00:23:05,960 Speaker 1: I think it's easier to think about identifying and screening 418 00:23:05,960 --> 00:23:09,040 Speaker 1: out the stuff that is fair has a lot of 419 00:23:09,040 --> 00:23:12,960 Speaker 1: red flags and is fairly fairly clearly actually a bunch 420 00:23:13,000 --> 00:23:16,320 Speaker 1: of hucksters as opposed to on the margin, So is 421 00:23:16,359 --> 00:23:18,560 Speaker 1: solving the world? Who the Warren Buffett question? Right? You know, 422 00:23:18,680 --> 00:23:20,679 Speaker 1: was Warren Buffett? Was there a path for Warren to 423 00:23:20,720 --> 00:23:22,800 Speaker 1: figure out that Google and Amazon were real things? Back 424 00:23:22,800 --> 00:23:25,439 Speaker 1: in there? Might there might not have been? Right? I 425 00:23:25,480 --> 00:23:29,800 Speaker 1: think that identifying red flags of very likely problems, right. 426 00:23:29,840 --> 00:23:33,520 Speaker 1: I mean, I think you get into things like, okay, 427 00:23:33,560 --> 00:23:36,240 Speaker 1: do do we have projections of returns that are way 428 00:23:36,280 --> 00:23:41,160 Speaker 1: way above historical equity returns? Or based on nonsensical statements 429 00:23:41,240 --> 00:23:43,359 Speaker 1: like theckathy Wood one that we talked about, right, GDP 430 00:23:43,480 --> 00:23:47,080 Speaker 1: growth because of artificial general intelligence? Right, you can fairly 431 00:23:47,160 --> 00:23:50,000 Speaker 1: quickly say okay, I don't know exactly what's going on 432 00:23:50,040 --> 00:23:52,960 Speaker 1: in the world, but like that's not real, right, Um. 433 00:23:53,000 --> 00:23:55,280 Speaker 1: I think another one and and this I think is 434 00:23:55,600 --> 00:24:00,560 Speaker 1: is very important and hits institutions more but lanes of 435 00:24:00,680 --> 00:24:04,800 Speaker 1: returns significantly exceeding you know, the risk free rate, but 436 00:24:05,000 --> 00:24:08,760 Speaker 1: with little or no risk, right. And that's the one 437 00:24:08,840 --> 00:24:11,920 Speaker 1: I think that ends up leading to much bigger problems 438 00:24:11,920 --> 00:24:15,080 Speaker 1: in financial markets and much bigger problems in the global economy. Right, 439 00:24:15,160 --> 00:24:18,280 Speaker 1: because people with nice suits and ties and very big 440 00:24:18,280 --> 00:24:21,200 Speaker 1: offices look at an eight or nine or ten percent 441 00:24:21,320 --> 00:24:23,679 Speaker 1: relatively low risk return, and they think about how they 442 00:24:23,720 --> 00:24:25,600 Speaker 1: can put leverage on that, and they think about how 443 00:24:25,680 --> 00:24:28,080 Speaker 1: they could have a five year run making really good 444 00:24:28,119 --> 00:24:32,040 Speaker 1: money and get paid a lot, right, And that's incredibly appealing. 445 00:24:32,040 --> 00:24:33,879 Speaker 1: And that's actually the nature of a lot of the 446 00:24:33,920 --> 00:24:36,280 Speaker 1: biggest losses that you saw on crypto and so forth. Right. 447 00:24:36,280 --> 00:24:41,040 Speaker 1: It wasn't necessarily folks buying you know, doage coin and 448 00:24:41,160 --> 00:24:44,720 Speaker 1: and losing a catastrophic amount of money. It was people saying, wow, 449 00:24:44,760 --> 00:24:49,240 Speaker 1: this anchor protocol, this thing yields and hard. There's a 450 00:24:49,240 --> 00:24:51,520 Speaker 1: Harvard business yeah, and there's like a Harvard professor that 451 00:24:51,680 --> 00:24:53,880 Speaker 1: wrote the white paper and you know, there's all these 452 00:24:53,880 --> 00:24:56,200 Speaker 1: credible bcs talking about it, and if I can get 453 00:24:56,840 --> 00:24:59,080 Speaker 1: on that, and then if I can borrow ten billion 454 00:24:59,119 --> 00:25:02,080 Speaker 1: dollars to do that, like I can get really rich 455 00:25:02,240 --> 00:25:06,439 Speaker 1: really fast. Yeah, that didn't work out so well. Um, 456 00:25:06,960 --> 00:25:09,520 Speaker 1: just on the topic of leverage, can you talk a 457 00:25:09,560 --> 00:25:13,960 Speaker 1: little bit about what you've seen in derivatives specifically so 458 00:25:14,040 --> 00:25:17,840 Speaker 1: your specialty. So, I know we had retail um jump 459 00:25:17,880 --> 00:25:20,760 Speaker 1: into the options market and that helped to fuel a 460 00:25:20,760 --> 00:25:24,640 Speaker 1: lot of the meme stock investing frenzy. But I'm curious 461 00:25:24,640 --> 00:25:29,120 Speaker 1: what you've seen on the institutional side as well. Yeah, 462 00:25:29,440 --> 00:25:33,440 Speaker 1: there have been some spectacular blow ups in the derivative 463 00:25:33,440 --> 00:25:38,679 Speaker 1: space that were primarily institutional products over the last five years. Again, 464 00:25:38,720 --> 00:25:41,040 Speaker 1: I think all the same root causes where you get 465 00:25:41,240 --> 00:25:44,680 Speaker 1: just nothing bad haven't gone wrong really since two thousand 466 00:25:44,760 --> 00:25:49,320 Speaker 1: and nine, and therefore more and more risk tolerance building up. 467 00:25:49,440 --> 00:25:53,120 Speaker 1: So you know, you can think about, for example, all 468 00:25:53,160 --> 00:25:55,440 Speaker 1: the unstructured alpha is a is a really good example 469 00:25:55,680 --> 00:25:59,920 Speaker 1: where you know, this is a brand name platform, investor 470 00:26:00,040 --> 00:26:02,840 Speaker 1: base was big public pensions and many tens of billions 471 00:26:02,840 --> 00:26:05,560 Speaker 1: of dollars, and you have a case where and you 472 00:26:05,560 --> 00:26:07,960 Speaker 1: can go read about it on the SEC website and 473 00:26:07,960 --> 00:26:11,560 Speaker 1: the d J, where you know, the portfolio managers were 474 00:26:12,160 --> 00:26:15,800 Speaker 1: taking more and more risk, selling leverage tail risk, using 475 00:26:15,840 --> 00:26:19,960 Speaker 1: options in a relatively complicated strategy, and just outright lying 476 00:26:20,000 --> 00:26:22,040 Speaker 1: about the risk they were taking in the positions that 477 00:26:22,080 --> 00:26:24,240 Speaker 1: they had to investors in order to put up a 478 00:26:24,240 --> 00:26:26,200 Speaker 1: return stream that looked pretty good and drew in more 479 00:26:26,200 --> 00:26:30,600 Speaker 1: and more capital um and then eventually blew up in 480 00:26:30,680 --> 00:26:34,600 Speaker 1: March of and resulted in a whole bunch of lawsuits 481 00:26:34,680 --> 00:26:38,440 Speaker 1: and you know, presumably probably prisoned and so forth. Right, 482 00:26:38,440 --> 00:26:41,080 Speaker 1: So it's the kind of thing that lots of big 483 00:26:41,119 --> 00:26:44,000 Speaker 1: investment consultants had looked at that strategy and said, hey, 484 00:26:44,040 --> 00:26:47,879 Speaker 1: this looks good. Lots of big institutional investors fell for 485 00:26:47,920 --> 00:26:50,359 Speaker 1: it for years and years and years and just without 486 00:26:50,400 --> 00:26:53,040 Speaker 1: asking that asking those questions about, well, how can this 487 00:26:53,160 --> 00:26:57,359 Speaker 1: return stream exist? Is this applausible return stream given what 488 00:26:57,520 --> 00:27:00,840 Speaker 1: trades are supposedly in the portfolio and and the answers 489 00:27:00,920 --> 00:27:03,520 Speaker 1: absolutely not, But those questions are critical to be to 490 00:27:03,560 --> 00:27:08,680 Speaker 1: be asked, right. I think similarly, you saw structured tail 491 00:27:08,760 --> 00:27:13,000 Speaker 1: risk selling out of firms like Malachite and some of 492 00:27:13,000 --> 00:27:16,720 Speaker 1: the Canadian pensions like aim Coode that manifested itself as good, 493 00:27:16,720 --> 00:27:21,199 Speaker 1: steady returns, but then in March involved it's you know, 494 00:27:21,200 --> 00:27:24,520 Speaker 1: spectacular blow ups and explosions, sort of taking on toxic 495 00:27:24,520 --> 00:27:29,760 Speaker 1: tail risk that the banks didn't want, and again consultants 496 00:27:29,800 --> 00:27:32,479 Speaker 1: backing these these kind of approaches and saying, yes, this 497 00:27:32,560 --> 00:27:36,560 Speaker 1: is the smart relative value strategy. So I think it 498 00:27:36,640 --> 00:27:41,920 Speaker 1: all comes back to what is this return stream coming from? 499 00:27:42,000 --> 00:27:44,040 Speaker 1: What is the manager telling you about what the return 500 00:27:44,119 --> 00:27:47,800 Speaker 1: stream is coming from. If the answer is it's really complicated, 501 00:27:47,840 --> 00:27:51,320 Speaker 1: we're really smart. We can't tell you. It's not that 502 00:27:51,320 --> 00:27:53,800 Speaker 1: that can't possibly be true, but it should raise a 503 00:27:53,880 --> 00:27:56,440 Speaker 1: lot of scrutiny in terms of how much you feel 504 00:27:56,440 --> 00:27:59,720 Speaker 1: you need to understand right about about the positions. You know, 505 00:28:00,000 --> 00:28:02,400 Speaker 1: blask and I always say things like, look, you should 506 00:28:02,440 --> 00:28:05,240 Speaker 1: be able to get a snapshot of historical positions, not 507 00:28:05,280 --> 00:28:07,439 Speaker 1: necessarily current positions, and you should be able to understand 508 00:28:07,480 --> 00:28:10,320 Speaker 1: exactly what the positions are, what the products are, what 509 00:28:10,400 --> 00:28:12,920 Speaker 1: the risks are, and be able to understand return attribution. 510 00:28:12,960 --> 00:28:15,720 Speaker 1: And if you can't do that, then you just shouldn't 511 00:28:15,760 --> 00:28:17,600 Speaker 1: get involved. You should let the you know, let the 512 00:28:17,640 --> 00:28:20,200 Speaker 1: momentum effect kind of walk away. I want to ask 513 00:28:20,280 --> 00:28:22,480 Speaker 1: another question about the sort of I don't know. I 514 00:28:22,520 --> 00:28:25,040 Speaker 1: guess it's the challenge of fighting the trend or the 515 00:28:25,119 --> 00:28:27,840 Speaker 1: challenge of being skeptical. You know. Another one thing that 516 00:28:27,880 --> 00:28:32,119 Speaker 1: we've seen in the sort of like inflationary maybe like 517 00:28:32,440 --> 00:28:37,240 Speaker 1: peak postmania market is that certain investing strategies that really 518 00:28:37,240 --> 00:28:39,280 Speaker 1: like did terribly in the twenty tents are doing well. 519 00:28:39,320 --> 00:28:42,800 Speaker 1: And I'm like thinking about like some of the strategies 520 00:28:42,840 --> 00:28:45,120 Speaker 1: that are employed by quants, like say like an a 521 00:28:45,240 --> 00:28:48,400 Speaker 1: q R of like long cheap stocks, short expensive stocks, 522 00:28:48,440 --> 00:28:51,640 Speaker 1: those did very poorly throughout much of the tens and 523 00:28:51,640 --> 00:28:54,600 Speaker 1: then but not only did they do poorly, and they've 524 00:28:54,600 --> 00:28:57,040 Speaker 1: now turned around at the very late stages, they did 525 00:28:57,200 --> 00:29:01,520 Speaker 1: absolutely awful, and so they did really terrible in It 526 00:29:01,560 --> 00:29:04,560 Speaker 1: seems to me like part of the problem for any 527 00:29:04,720 --> 00:29:08,160 Speaker 1: institutional investor is not just that it's like costly to 528 00:29:08,320 --> 00:29:11,280 Speaker 1: like hold out for things to revert to the mean 529 00:29:11,440 --> 00:29:13,720 Speaker 1: or for a trading strategy to work out. It's that 530 00:29:14,200 --> 00:29:18,240 Speaker 1: it gets especially costly in the late stages of the thing. 531 00:29:18,360 --> 00:29:21,560 Speaker 1: So like your costs like really go up right before 532 00:29:21,800 --> 00:29:26,360 Speaker 1: the time when it's about to work. Betting against manias 533 00:29:26,560 --> 00:29:31,320 Speaker 1: is really really really hard, right you hear. I think 534 00:29:31,360 --> 00:29:34,360 Speaker 1: about the success stories, like we all loved watching Big Short, 535 00:29:34,560 --> 00:29:38,200 Speaker 1: and that was really fun. And you know, there is 536 00:29:38,240 --> 00:29:42,840 Speaker 1: a a piece of it where it's arguably easier, at 537 00:29:42,880 --> 00:29:47,600 Speaker 1: least to some extent, to bet against a mania or 538 00:29:47,640 --> 00:29:53,120 Speaker 1: a bubble that has certain time dependent catalyst features, like Okay, 539 00:29:53,160 --> 00:29:57,160 Speaker 1: these mortgages are actually all defaulting right now, and there's 540 00:29:57,200 --> 00:29:58,960 Speaker 1: like a timeline for that to feed through into the 541 00:29:58,960 --> 00:30:00,760 Speaker 1: payoffs on these instrument and some like we don't know 542 00:30:00,800 --> 00:30:03,160 Speaker 1: the exact timing, but like you know, it's two thousand 543 00:30:03,200 --> 00:30:04,960 Speaker 1: and seven and it's and it's go time. But even that, 544 00:30:05,080 --> 00:30:06,680 Speaker 1: like a lot of people were early, right, and a 545 00:30:06,680 --> 00:30:08,400 Speaker 1: lot of people you didn't hear about in the Big 546 00:30:08,440 --> 00:30:10,680 Speaker 1: Short put those trades on in two thousand and five 547 00:30:10,880 --> 00:30:14,320 Speaker 1: and got blown out right, seems to be the problem. 548 00:30:14,920 --> 00:30:18,520 Speaker 1: You can't just wait, and that's actually the easier version, right. 549 00:30:18,640 --> 00:30:22,040 Speaker 1: But when there's a mania in things that are equity 550 00:30:22,080 --> 00:30:24,600 Speaker 1: like that have unlimited upside, right, it's not just that 551 00:30:24,680 --> 00:30:27,440 Speaker 1: you're paying some premium to be to be to have 552 00:30:27,480 --> 00:30:29,480 Speaker 1: an option or to be in a credit to follow 553 00:30:29,520 --> 00:30:32,640 Speaker 1: swap or something, but you're trying to like short, gimmy 554 00:30:33,880 --> 00:30:36,720 Speaker 1: that or or or anything else that's you know, short 555 00:30:36,840 --> 00:30:40,600 Speaker 1: a crypto token. Um that you're the risk is wildly 556 00:30:40,640 --> 00:30:44,200 Speaker 1: asymmetric against the short position, right, because that instrument could 557 00:30:44,240 --> 00:30:46,760 Speaker 1: go up by five times or ten times or twenty times, 558 00:30:47,160 --> 00:30:50,000 Speaker 1: and your risk grows exponentially in a short position as 559 00:30:50,000 --> 00:30:52,240 Speaker 1: that happens. But you can only ever make if it 560 00:30:52,280 --> 00:30:54,720 Speaker 1: goes to zero. You make like one time. Right. And 561 00:30:54,800 --> 00:30:58,840 Speaker 1: so to your point, um, it's an extremely difficult game 562 00:30:58,920 --> 00:31:00,880 Speaker 1: that not a lot of people try to play. I mean, 563 00:31:00,920 --> 00:31:03,400 Speaker 1: we would just never touch anything like that, regardless of 564 00:31:03,400 --> 00:31:06,000 Speaker 1: how crazy we think that the world is. And you know, 565 00:31:06,040 --> 00:31:08,280 Speaker 1: there's things you can Okay, maybe I can do limited 566 00:31:08,360 --> 00:31:11,080 Speaker 1: loss trades and options or something, but like options on 567 00:31:11,520 --> 00:31:14,240 Speaker 1: really crazy bubbly things are very expensive for a very 568 00:31:14,240 --> 00:31:17,000 Speaker 1: good reason. Right. So it's I think that's one of 569 00:31:17,040 --> 00:31:19,600 Speaker 1: the inherent tricks. Right. And there's an academic concept called 570 00:31:19,600 --> 00:31:22,440 Speaker 1: the limits to arbitrage that's really important here. I mean, 571 00:31:22,480 --> 00:31:24,560 Speaker 1: and arbitrage is the word that gets thrown around way 572 00:31:24,560 --> 00:31:27,479 Speaker 1: too much. It's kind of almost totally irrelevant to this, right, 573 00:31:27,800 --> 00:31:31,480 Speaker 1: even if something is inherently worthless, there's no arbitrage short. 574 00:31:48,320 --> 00:31:51,880 Speaker 1: One thing we haven't spoken about really yet is whether 575 00:31:51,960 --> 00:31:55,800 Speaker 1: or not there was something in the broader environment or 576 00:31:55,880 --> 00:31:59,959 Speaker 1: the macro situation that made the past couple of years again, 577 00:32:00,120 --> 00:32:03,280 Speaker 1: I guess more vulnerable to these types of manias and 578 00:32:03,600 --> 00:32:06,760 Speaker 1: frauds in some cases, and a lot of people will 579 00:32:06,800 --> 00:32:09,160 Speaker 1: point to in the case of retail investors, people being 580 00:32:09,160 --> 00:32:13,680 Speaker 1: stuck at home getting stimulus checks social media, you know, 581 00:32:13,720 --> 00:32:16,640 Speaker 1: no commissions trading at robin Hood in places like that. 582 00:32:17,160 --> 00:32:19,920 Speaker 1: And then of course you have the very broad backdrop 583 00:32:20,120 --> 00:32:23,160 Speaker 1: of just low interest rates and the cost of capital 584 00:32:23,200 --> 00:32:26,240 Speaker 1: being very low, the cost of money basically being very 585 00:32:26,360 --> 00:32:30,800 Speaker 1: very low, and having plenty of liquidity slashing around the system. 586 00:32:30,920 --> 00:32:34,080 Speaker 1: Is there something that when you look back on the 587 00:32:34,120 --> 00:32:37,200 Speaker 1: past couple of years you would attribute to you know, 588 00:32:37,840 --> 00:32:39,840 Speaker 1: something that is one of the reasons that we saw 589 00:32:40,040 --> 00:32:43,959 Speaker 1: so much froth. I think there are a lot of 590 00:32:44,000 --> 00:32:47,000 Speaker 1: different contributing factors, I think, and I think this is 591 00:32:47,080 --> 00:32:51,120 Speaker 1: usually how things go. So I would say commentators tend 592 00:32:51,160 --> 00:32:55,080 Speaker 1: to focus very, very heavily on low interest rates and 593 00:32:55,160 --> 00:32:58,600 Speaker 1: quantitative using and so forth. I mean, I think there's 594 00:32:58,640 --> 00:33:01,520 Speaker 1: a I think a role for cheap money on the margin, 595 00:33:01,720 --> 00:33:04,080 Speaker 1: especially in areas like real estate. But I think that 596 00:33:04,360 --> 00:33:07,800 Speaker 1: really the direct role of low interest rates or or 597 00:33:07,880 --> 00:33:10,000 Speaker 1: QUI here is very overstated. I mean, you look at 598 00:33:10,000 --> 00:33:14,000 Speaker 1: the history of interest rates and quantitative using geographically around 599 00:33:14,040 --> 00:33:16,480 Speaker 1: the world for the last twenty years, and you know 600 00:33:16,480 --> 00:33:19,720 Speaker 1: there's very little Japan has been doing quei for for 601 00:33:19,760 --> 00:33:22,960 Speaker 1: a very long time. We had low interest rates in 602 00:33:22,960 --> 00:33:26,480 Speaker 1: the US for a long time. Previous manias weren't necessarily 603 00:33:26,480 --> 00:33:28,760 Speaker 1: associated with low interest rates. And one way to think 604 00:33:28,800 --> 00:33:31,360 Speaker 1: about it is like with tech stocks going up a 605 00:33:31,400 --> 00:33:34,720 Speaker 1: hundred percent a year and crypto tokens paying twenty percent yield, 606 00:33:35,040 --> 00:33:36,640 Speaker 1: Like if you have to pay three or four percent 607 00:33:36,680 --> 00:33:39,760 Speaker 1: to get leverage versus one percent, it just doesn't matter 608 00:33:39,800 --> 00:33:41,520 Speaker 1: if you are in the frame of mind that like 609 00:33:41,560 --> 00:33:43,760 Speaker 1: you want to do those kind of maastments, right, I 610 00:33:43,800 --> 00:33:45,360 Speaker 1: mean that the idea and I joke about this on 611 00:33:45,360 --> 00:33:47,040 Speaker 1: Twitter a lot, but you have the idea that, like 612 00:33:47,640 --> 00:33:49,960 Speaker 1: the bitcoin folks would have just bought a bunch of 613 00:33:50,000 --> 00:33:52,440 Speaker 1: treasuries if treasuries paid six or seven percent, is like, 614 00:33:52,520 --> 00:33:57,320 Speaker 1: on its face ridiculous, and they would all tell you that, right, Um, well, 615 00:33:57,400 --> 00:34:00,400 Speaker 1: wait a second, I have I have seen I've seen 616 00:34:00,440 --> 00:34:02,720 Speaker 1: at least one person on Twitter claim that one of 617 00:34:02,720 --> 00:34:05,680 Speaker 1: the reasons bitcoin is down is because everyone's buying um, 618 00:34:05,720 --> 00:34:12,600 Speaker 1: those inflation protected it's it's it's pretty funny, right, I mean, 619 00:34:12,600 --> 00:34:15,960 Speaker 1: I think it's much more about the collective perception of 620 00:34:16,000 --> 00:34:19,239 Speaker 1: relative risk and return and the growth of narratives justifying 621 00:34:19,280 --> 00:34:22,400 Speaker 1: that perception, and then the broad socialization of more and 622 00:34:22,440 --> 00:34:26,040 Speaker 1: more people into that perception. Right. I do think where 623 00:34:26,680 --> 00:34:29,799 Speaker 1: rates and Quwie comes in as perceptions of the role 624 00:34:29,880 --> 00:34:33,520 Speaker 1: of cheap money coordinating investor expectations are kind of the 625 00:34:33,560 --> 00:34:36,360 Speaker 1: money printer Gober, you know, buy everything. Mean, like, I 626 00:34:36,360 --> 00:34:39,279 Speaker 1: think that's actually important. That's probably much more important than 627 00:34:39,320 --> 00:34:41,799 Speaker 1: the direct impact of like rates being a little bit 628 00:34:41,840 --> 00:34:44,640 Speaker 1: lower and being able to get leverage. Right, is this 629 00:34:45,280 --> 00:34:48,360 Speaker 1: the contribution to the narrative that like all of this 630 00:34:48,400 --> 00:34:50,719 Speaker 1: stuff just has to go up? And I do think 631 00:34:50,760 --> 00:34:53,759 Speaker 1: I come back, you know, ultimately, And you pointed out 632 00:34:53,760 --> 00:34:55,840 Speaker 1: other other phenomena that I do think have been important. 633 00:34:55,840 --> 00:34:58,719 Speaker 1: When you look specifically at retail options trading and a 634 00:34:58,719 --> 00:35:02,319 Speaker 1: lot of the aggressive market participation that has showed up 635 00:35:02,320 --> 00:35:04,760 Speaker 1: over the last few years. I do think the pandemic 636 00:35:04,800 --> 00:35:07,839 Speaker 1: played a real role. I think that the the there's 637 00:35:07,840 --> 00:35:12,799 Speaker 1: a self reinforcing dynamic to the social internet aspect to it, right, 638 00:35:12,840 --> 00:35:16,960 Speaker 1: It's not just people sitting at home in their brokerage 639 00:35:16,960 --> 00:35:19,719 Speaker 1: account doing stuff by themselves. They're in They're increasingly in 640 00:35:19,800 --> 00:35:22,200 Speaker 1: discords or on Twitter or in some kind of social 641 00:35:22,239 --> 00:35:24,480 Speaker 1: group or read a Wall Street that's that's like a 642 00:35:24,560 --> 00:35:27,520 Speaker 1: community that's fun where people talk about investing and they 643 00:35:27,760 --> 00:35:31,120 Speaker 1: teach each other stuff and they you know, they overcome 644 00:35:31,200 --> 00:35:33,320 Speaker 1: the activation barrier of like how do you open a 645 00:35:33,360 --> 00:35:35,400 Speaker 1: brokerage account and how do you put money in it? 646 00:35:35,440 --> 00:35:37,200 Speaker 1: And how do you actually click a button to trade 647 00:35:37,239 --> 00:35:39,440 Speaker 1: and all this stuff, and like, once that's there, and 648 00:35:39,480 --> 00:35:43,000 Speaker 1: once it's a fun, entertaining social thing and it has 649 00:35:43,040 --> 00:35:45,600 Speaker 1: a gown group gambling component to it, like it becomes 650 00:35:46,120 --> 00:35:48,279 Speaker 1: much easier to kind of get out of control and 651 00:35:48,360 --> 00:35:50,960 Speaker 1: much longer lasting. Right then, you know it has all 652 00:35:50,960 --> 00:35:54,279 Speaker 1: the power of the of the engagement, you know, click 653 00:35:54,320 --> 00:35:56,400 Speaker 1: bait nous, of the of the internet associated with it. 654 00:35:56,680 --> 00:35:58,520 Speaker 1: I think that was really important. I want to ask 655 00:35:58,520 --> 00:36:00,919 Speaker 1: you follow up on it, but before I forget one point. 656 00:36:00,960 --> 00:36:03,520 Speaker 1: You know, you mentioned this sort of like myth of 657 00:36:03,560 --> 00:36:06,840 Speaker 1: like that it's all about cheap money, and a point 658 00:36:06,960 --> 00:36:10,640 Speaker 1: that Mark Dow who's a trader very active on Twitter, 659 00:36:10,680 --> 00:36:13,320 Speaker 1: often points out is like in the housing bubble in 660 00:36:13,360 --> 00:36:16,279 Speaker 1: the mid twenty tens. You know, some of the most 661 00:36:16,280 --> 00:36:21,080 Speaker 1: agregious like ninja loans and sub prime activity happened like 662 00:36:21,239 --> 00:36:25,240 Speaker 1: two thousand five, two thousand six, well into the hiking cycle. 663 00:36:25,280 --> 00:36:27,319 Speaker 1: So even in real estate, which we all sort of 664 00:36:27,360 --> 00:36:29,840 Speaker 1: can accept it is probably the one area that's most 665 00:36:30,280 --> 00:36:34,280 Speaker 1: linearly connected to interest rates, you still saw like manic 666 00:36:34,360 --> 00:36:37,719 Speaker 1: activity well after the FED started hiking. You know, they 667 00:36:37,760 --> 00:36:40,040 Speaker 1: got as high as like five percent in two thousand 668 00:36:40,000 --> 00:36:42,480 Speaker 1: and six, and there was still all kinds of wild 669 00:36:42,560 --> 00:36:45,960 Speaker 1: stuff going on then. But on the same and the 670 00:36:45,960 --> 00:36:47,560 Speaker 1: same by the way, it was true of the eighties 671 00:36:47,800 --> 00:36:50,800 Speaker 1: Japanese real estate bubble and Scandy real estate, right, So 672 00:36:50,880 --> 00:36:53,480 Speaker 1: it's just it's not just like this like interest rate 673 00:36:53,520 --> 00:36:56,319 Speaker 1: dial that sets the level of spectator frosth But on 674 00:36:56,400 --> 00:36:58,759 Speaker 1: the question of call options, and I think the last 675 00:36:58,760 --> 00:37:01,120 Speaker 1: time we talked, I think it was our one, and 676 00:37:01,120 --> 00:37:03,560 Speaker 1: it was really about this question of like retail call 677 00:37:03,600 --> 00:37:06,839 Speaker 1: buying activity and how it's changing markets. I don't want 678 00:37:06,840 --> 00:37:09,960 Speaker 1: to say distorting, but maybe distorting or changing markets. Just curious, 679 00:37:09,960 --> 00:37:12,680 Speaker 1: like what do you see right now? Are they still 680 00:37:12,719 --> 00:37:15,640 Speaker 1: out there? How big of a presence are they relative 681 00:37:15,680 --> 00:37:17,640 Speaker 1: to where they were last year versus where they were 682 00:37:17,719 --> 00:37:20,960 Speaker 1: maybe twenty eighteen or twenty nineteen and sort of more 683 00:37:21,040 --> 00:37:24,520 Speaker 1: normal market. And are they other people who haven't given 684 00:37:24,600 --> 00:37:26,880 Speaker 1: up yet or haven't capitulated or still trying to do 685 00:37:26,960 --> 00:37:31,480 Speaker 1: like playbook? What do you see now? Yeah, So I 686 00:37:31,520 --> 00:37:33,960 Speaker 1: threw a chart up on that on Twitter, probably a 687 00:37:33,960 --> 00:37:36,360 Speaker 1: couple of weeks ago, and it's you know, it looks 688 00:37:36,440 --> 00:37:40,280 Speaker 1: a lot like the price sharks of Peloton and everything 689 00:37:40,360 --> 00:37:44,000 Speaker 1: like that. Right, So, there was this huge surge in 690 00:37:44,560 --> 00:37:47,319 Speaker 1: retail option trading activity, and not just retail, by the way, 691 00:37:47,360 --> 00:37:50,960 Speaker 1: also institutional options trading activity and volumes. Retail kind of 692 00:37:51,000 --> 00:37:54,120 Speaker 1: moved first, an institutional caught up. An institutional actually peaked 693 00:37:54,120 --> 00:37:56,600 Speaker 1: a little bit later than retail. We peaked in in 694 00:37:56,719 --> 00:37:59,600 Speaker 1: late one actually, so a little bit after you would 695 00:37:59,600 --> 00:38:01,399 Speaker 1: think of a like the peak of the robin hood 696 00:38:01,440 --> 00:38:03,560 Speaker 1: p and L. It was more like November, I think, 697 00:38:04,239 --> 00:38:09,080 Speaker 1: um where And at that time, option trading volumes were 698 00:38:09,480 --> 00:38:12,480 Speaker 1: in the like the ten to twenty times higher than 699 00:38:12,760 --> 00:38:17,200 Speaker 1: baseline range, which is just unbelievable, right, And then what 700 00:38:17,280 --> 00:38:20,719 Speaker 1: happened since was a pretty steady collapse, you know, with 701 00:38:20,800 --> 00:38:24,480 Speaker 1: some some rallyback attempts. But now we're back to maybe 702 00:38:24,520 --> 00:38:28,080 Speaker 1: only two x over baseline, so it's still it's still elevated, 703 00:38:28,480 --> 00:38:30,919 Speaker 1: and I think it will remain somewhat elevated. I think 704 00:38:30,920 --> 00:38:34,840 Speaker 1: back to the kind of the social gambling dynamic I 705 00:38:34,880 --> 00:38:36,839 Speaker 1: think I can't get that has a long tail to it, right. 706 00:38:37,400 --> 00:38:41,440 Speaker 1: People used to ask me a lot in Okay, how 707 00:38:41,560 --> 00:38:43,719 Speaker 1: is this going to end? What's actually going to make 708 00:38:44,320 --> 00:38:47,120 Speaker 1: individual investors, you know, and some of the fast money 709 00:38:47,120 --> 00:38:49,279 Speaker 1: hedge fund types that are starting to trade like this, 710 00:38:49,440 --> 00:38:52,439 Speaker 1: what's going to make them give up? And my view 711 00:38:52,520 --> 00:38:55,400 Speaker 1: was always, look, it's not going to be obviously in 712 00:38:55,400 --> 00:38:59,080 Speaker 1: March event where there's a fast, big market crash and 713 00:38:59,120 --> 00:39:02,040 Speaker 1: then things recover, because that's a lot of this option 714 00:39:02,520 --> 00:39:06,480 Speaker 1: option trading. It's option by right. It's kind of long convexity. 715 00:39:06,600 --> 00:39:08,800 Speaker 1: You pay a small amount of premium to get a 716 00:39:08,840 --> 00:39:10,920 Speaker 1: whole bunch of upside if there's a giant move, and 717 00:39:10,960 --> 00:39:13,000 Speaker 1: that's perfect for crashes, right because you're like, oh, I 718 00:39:13,080 --> 00:39:14,879 Speaker 1: lost you know, I lost my thousand bucks or whatever, 719 00:39:14,920 --> 00:39:17,480 Speaker 1: and then I'll do it again tomorrow. The it's really 720 00:39:17,520 --> 00:39:20,719 Speaker 1: the long, slow grind b market kind of sideways are 721 00:39:20,760 --> 00:39:24,319 Speaker 1: down that eventually drives people out right, because they're spending money, 722 00:39:24,360 --> 00:39:27,600 Speaker 1: they're spending premium, they're spending premium, they're spending premium, and 723 00:39:27,760 --> 00:39:30,160 Speaker 1: it's you know, it's just burning for six months, for 724 00:39:30,200 --> 00:39:32,440 Speaker 1: a year. And I think that's what we've seen. So 725 00:39:32,600 --> 00:39:35,200 Speaker 1: speaking of driving people out, is there is there any 726 00:39:35,280 --> 00:39:39,120 Speaker 1: craziness left or has all the sort of air been 727 00:39:39,400 --> 00:39:41,760 Speaker 1: kicked out of the market's tires? What do you see? 728 00:39:43,200 --> 00:39:46,319 Speaker 1: Excellent question. I mean, I think there's plenty of craziness left. 729 00:39:46,440 --> 00:39:48,680 Speaker 1: So I think both in crypto and in tech, there 730 00:39:48,680 --> 00:39:53,799 Speaker 1: are many funky crypto tokens that are down, but they 731 00:39:53,800 --> 00:40:00,000 Speaker 1: can there, right, yeah, exactly as we as we constantly joke, right, um, 732 00:40:00,000 --> 00:40:02,839 Speaker 1: but whose market cap is still billions and billions of dollars, right, 733 00:40:03,120 --> 00:40:06,880 Speaker 1: and you know they're just jokes. So I think, you know, 734 00:40:06,960 --> 00:40:09,920 Speaker 1: that's hard to argue that that that stuff doesn't eventually 735 00:40:09,960 --> 00:40:12,799 Speaker 1: go to zero. Right. And then within what you would 736 00:40:12,800 --> 00:40:15,360 Speaker 1: think of as like the Arc basket and you know, 737 00:40:15,400 --> 00:40:19,600 Speaker 1: the Goldman SAX index of speculative software stocks, again, there 738 00:40:19,880 --> 00:40:24,320 Speaker 1: were a lot of companies that experienced valuations in private 739 00:40:24,360 --> 00:40:29,920 Speaker 1: markets and sometimes eventually in public markets of thirty dollars 740 00:40:29,960 --> 00:40:32,719 Speaker 1: that just it's very hard to see them ever being 741 00:40:32,760 --> 00:40:35,200 Speaker 1: worth anything, right, And a lot of those names are 742 00:40:35,239 --> 00:40:38,000 Speaker 1: down a lot. They're down, but they're still worth five 743 00:40:38,000 --> 00:40:40,719 Speaker 1: billion dollars or three billion dollars. Right. The things that 744 00:40:40,719 --> 00:40:42,880 Speaker 1: have gone down the most are not always the cheapest, right. 745 00:40:42,920 --> 00:40:45,719 Speaker 1: Sometimes they are, But in this case, I think it's not. 746 00:40:45,840 --> 00:40:48,040 Speaker 1: That's not obvious at all. I think there's a great 747 00:40:48,400 --> 00:40:52,360 Speaker 1: Kindleberger quote that the period of financial distress is a 748 00:40:52,400 --> 00:40:54,880 Speaker 1: gradual decline after the peak of a speculative bubble that 749 00:40:54,960 --> 00:40:57,839 Speaker 1: precedes the final and massive panic and crash, driven by 750 00:40:57,880 --> 00:41:01,480 Speaker 1: the insiders having exited, but the suckers, outsiders hanging on 751 00:41:01,560 --> 00:41:04,160 Speaker 1: and hoping for a revival and then finally giving up. Right, 752 00:41:04,200 --> 00:41:05,719 Speaker 1: And it feels like that's where we are, sort of. 753 00:41:05,760 --> 00:41:08,960 Speaker 1: The insiders have been kind of quietly and steadily getting out. 754 00:41:09,239 --> 00:41:12,360 Speaker 1: There's apparently still quite a lot of demand, for example, 755 00:41:12,960 --> 00:41:15,800 Speaker 1: to sell shares in the secondary market of startups that 756 00:41:15,840 --> 00:41:19,720 Speaker 1: are down. Right, You've got founders that on paper, briefly 757 00:41:19,760 --> 00:41:23,240 Speaker 1: we're worth billion dollars and now they're worth two billion dollars, 758 00:41:23,239 --> 00:41:25,120 Speaker 1: and they're like, you know what, that's still pretty good. 759 00:41:25,960 --> 00:41:27,279 Speaker 1: I don't want to see if I can turn that 760 00:41:27,280 --> 00:41:31,319 Speaker 1: into cold hard cash. You know, speaking of crypto, what 761 00:41:31,360 --> 00:41:34,319 Speaker 1: do you think about it overall? Because, I mean it's 762 00:41:34,360 --> 00:41:37,520 Speaker 1: really tough, Like you have so many you have institutions, 763 00:41:37,800 --> 00:41:40,400 Speaker 1: you have probably some of the smartest people you know 764 00:41:40,560 --> 00:41:43,400 Speaker 1: or that we know, have gone into crypto. There are 765 00:41:43,440 --> 00:41:47,799 Speaker 1: certainly interesting element of decentralization, etcetera. That I think are 766 00:41:47,800 --> 00:41:51,040 Speaker 1: intuitively very appealing. And on the other hand, it's a 767 00:41:51,080 --> 00:41:55,040 Speaker 1: space that's been absolutely riven with every red flag in 768 00:41:55,040 --> 00:41:57,640 Speaker 1: the book basically since to day one. This is something 769 00:41:58,160 --> 00:42:01,279 Speaker 1: that never ceases to amaze me about crypto, which is 770 00:42:01,320 --> 00:42:03,879 Speaker 1: that like one person can look at it and go, 771 00:42:04,280 --> 00:42:08,719 Speaker 1: this is world changing technological disruption, and another person can 772 00:42:08,719 --> 00:42:11,080 Speaker 1: look at it and go, this is clearly a fraud 773 00:42:11,280 --> 00:42:14,080 Speaker 1: and a pond z and you know, people are just 774 00:42:14,120 --> 00:42:18,960 Speaker 1: throwing money into this useless thing. Absolutely So I have 775 00:42:19,080 --> 00:42:22,319 Speaker 1: a lot of very smart friends in crypto, and I 776 00:42:22,760 --> 00:42:24,600 Speaker 1: you know, I try to keep a pretty open mind. 777 00:42:24,719 --> 00:42:27,200 Speaker 1: I mean, I think that my default is there's a 778 00:42:27,239 --> 00:42:32,160 Speaker 1: lot of investment in infrastructure that you might have payoffs 779 00:42:32,200 --> 00:42:34,319 Speaker 1: that are hard for me to predict and know, you know, 780 00:42:34,320 --> 00:42:36,439 Speaker 1: which areas are going to really be important in ten 781 00:42:36,520 --> 00:42:39,120 Speaker 1: or twenty years. And you know, there's a lot of 782 00:42:39,160 --> 00:42:43,000 Speaker 1: work in that. There there are use cases in improving 783 00:42:43,040 --> 00:42:45,479 Speaker 1: settlement and payments and god knows what, and like we'll 784 00:42:45,480 --> 00:42:48,000 Speaker 1: find out in ten or twenty years. My mediaan case 785 00:42:48,040 --> 00:42:50,200 Speaker 1: would be like there's some actually really valuable stuff that 786 00:42:50,239 --> 00:42:53,200 Speaker 1: comes out of that. And again to your point, lots 787 00:42:53,200 --> 00:42:55,879 Speaker 1: of really smart people working there. I think that part 788 00:42:55,880 --> 00:42:59,440 Speaker 1: of the issue is really so much money got made 789 00:42:59,760 --> 00:43:04,120 Speaker 1: or and attracted so much, so many followers on who're 790 00:43:04,120 --> 00:43:06,399 Speaker 1: trying to get rich, right, and then that really came 791 00:43:06,440 --> 00:43:09,359 Speaker 1: to totally dominate the space and everything visible about it, 792 00:43:09,560 --> 00:43:11,720 Speaker 1: and a lot of the you know o g original 793 00:43:11,719 --> 00:43:14,680 Speaker 1: Crypto folks like have been vocal about that too. I 794 00:43:14,719 --> 00:43:19,040 Speaker 1: think ultimately, you know, everything has to ultimately derive value 795 00:43:19,080 --> 00:43:21,400 Speaker 1: from real products and services that people spend money on 796 00:43:21,440 --> 00:43:25,120 Speaker 1: in a sustainable way. But Crypto, I think at the 797 00:43:25,160 --> 00:43:28,799 Speaker 1: core of it, Crypto really owned and brought to the 798 00:43:28,840 --> 00:43:34,600 Speaker 1: forefront this idea that financialization is first, right, and that 799 00:43:34,880 --> 00:43:38,239 Speaker 1: use cases sort of follow, and that you're supposed to have. 800 00:43:38,400 --> 00:43:42,920 Speaker 1: It's this very like pure Chicago Department of Economics efficient 801 00:43:42,920 --> 00:43:46,000 Speaker 1: markets idea, right that like if everything is priced a priori, 802 00:43:46,080 --> 00:43:48,160 Speaker 1: the market is sort of all knowing and all seeing, 803 00:43:48,200 --> 00:43:50,360 Speaker 1: and people will identify the things that are going to 804 00:43:50,400 --> 00:43:52,000 Speaker 1: work and they're going to finance those in like the 805 00:43:52,000 --> 00:43:55,920 Speaker 1: world is going to be utopia, right, And it's completely ridiculous. 806 00:43:55,960 --> 00:43:58,160 Speaker 1: You know what actually happens in practices that if you 807 00:43:58,200 --> 00:44:02,120 Speaker 1: can create a narrator to create a hype cycle around 808 00:44:02,360 --> 00:44:05,120 Speaker 1: your company, and you get the right VC backing and 809 00:44:05,200 --> 00:44:09,080 Speaker 1: whatever it is, and then you can create money by 810 00:44:09,120 --> 00:44:11,480 Speaker 1: issuing a token and you can sell it to retail 811 00:44:11,520 --> 00:44:13,840 Speaker 1: and humongous size, and you can make hundreds of millions 812 00:44:13,920 --> 00:44:16,640 Speaker 1: or billions of dollars for doing absolutely nothing right. And 813 00:44:17,120 --> 00:44:19,600 Speaker 1: that happened over and over and over and over again, 814 00:44:19,680 --> 00:44:22,080 Speaker 1: and it was sort of institutionalized as a business model 815 00:44:22,120 --> 00:44:24,400 Speaker 1: by like certain venture capital firms that you know are 816 00:44:24,440 --> 00:44:26,279 Speaker 1: are big backers of this space, right, And I think 817 00:44:26,320 --> 00:44:29,680 Speaker 1: that's the core issue. Well, I forget who like made 818 00:44:29,920 --> 00:44:34,000 Speaker 1: this point, but yes, like you might say that crypto 819 00:44:34,080 --> 00:44:36,600 Speaker 1: has attracted the best and the brightest of the last 820 00:44:36,600 --> 00:44:39,280 Speaker 1: several years. But if they're the best of the brightest, 821 00:44:39,320 --> 00:44:41,280 Speaker 1: they might be the best of the brightest at figuring 822 00:44:41,320 --> 00:44:43,480 Speaker 1: out how to make life changing amounts of money for 823 00:44:43,760 --> 00:44:47,640 Speaker 1: six months, which is not necessarily the foundation of a 824 00:44:48,160 --> 00:44:51,359 Speaker 1: of a sound new industry. Yeah, you give you give 825 00:44:51,440 --> 00:44:54,799 Speaker 1: people really strong financial incentives, and it's really hard to resist, right, 826 00:44:54,840 --> 00:44:58,240 Speaker 1: Like it's you know, it's easy to obviously point fingers 827 00:44:58,239 --> 00:45:00,560 Speaker 1: at the most egregious people in the space and Dokuan 828 00:45:00,640 --> 00:45:02,719 Speaker 1: and all these guys that, like, if you create a 829 00:45:02,760 --> 00:45:06,760 Speaker 1: world in which it's really easy for charismatic, hustle type 830 00:45:06,760 --> 00:45:09,239 Speaker 1: people to get really rich by scamming people, like they're 831 00:45:09,280 --> 00:45:11,040 Speaker 1: going to do that, and you have to expect that, 832 00:45:11,120 --> 00:45:13,080 Speaker 1: Like that's just how the world is going to be. 833 00:45:13,600 --> 00:45:16,080 Speaker 1: And I think that's what the incentives that we've set 834 00:45:16,160 --> 00:45:21,160 Speaker 1: up in crypto have really done. So what's your big 835 00:45:21,200 --> 00:45:25,680 Speaker 1: advice to investors or anyone listening to this podcast? How 836 00:45:25,719 --> 00:45:29,480 Speaker 1: should they avoid the next mania? What should they watch 837 00:45:29,520 --> 00:45:32,320 Speaker 1: out for? I mean, I think the things that I 838 00:45:32,360 --> 00:45:36,719 Speaker 1: always come back to our again to really look out 839 00:45:36,920 --> 00:45:42,200 Speaker 1: for people credibly trying to credibly claim these astronomical return 840 00:45:42,239 --> 00:45:46,440 Speaker 1: profiles or pretty high returns with very little risk, because 841 00:45:46,560 --> 00:45:48,600 Speaker 1: you just have to think of it as the world 842 00:45:48,719 --> 00:45:52,120 Speaker 1: is full of a lot of very smart, very competitive 843 00:45:52,200 --> 00:45:56,839 Speaker 1: sharks who run very big businesses that really like getting rich. 844 00:45:57,040 --> 00:46:01,279 Speaker 1: And if there was an opportunity to make risk free 845 00:46:01,960 --> 00:46:04,000 Speaker 1: in front of you, they would have already taken that 846 00:46:04,080 --> 00:46:07,239 Speaker 1: away from you and done it first, right. And what 847 00:46:07,400 --> 00:46:09,279 Speaker 1: it means if you see something like that is that 848 00:46:09,320 --> 00:46:12,200 Speaker 1: it's not real, you know, and there's either some kind 849 00:46:12,239 --> 00:46:15,400 Speaker 1: of fraud or there's some kind of extraordinary risk that 850 00:46:15,480 --> 00:46:18,320 Speaker 1: you're not seeing. Right. You have to be really wary 851 00:46:18,400 --> 00:46:21,359 Speaker 1: of extrapolation, right, and that kind of comes back both 852 00:46:21,400 --> 00:46:24,080 Speaker 1: to the commodity story you were talking about and to 853 00:46:24,960 --> 00:46:27,120 Speaker 1: know bitcoin and all kinds of things, right, sort of 854 00:46:27,160 --> 00:46:31,880 Speaker 1: extrapolating recent extreme investment performance into the future. You have 855 00:46:31,960 --> 00:46:36,480 Speaker 1: to really be very skeptical of overly complex investments with 856 00:46:36,600 --> 00:46:39,359 Speaker 1: non transparent sources of return right where people are trying 857 00:46:39,400 --> 00:46:41,759 Speaker 1: to tell you this is really good because it's it's 858 00:46:41,800 --> 00:46:43,880 Speaker 1: really smart, and it's really complicated, and I know you 859 00:46:43,880 --> 00:46:47,040 Speaker 1: don't totally understand it. And you have to also be 860 00:46:47,160 --> 00:46:51,520 Speaker 1: ready to recognize the psychological tricks that the investment world 861 00:46:51,719 --> 00:46:54,120 Speaker 1: plays on you. Right. Again, a lot of these things 862 00:46:54,160 --> 00:46:58,200 Speaker 1: it seems like it should be so obvious, but it's not. Right. 863 00:46:58,360 --> 00:47:03,120 Speaker 1: There's a lot of laundering of credibility, right, legitimization of 864 00:47:03,280 --> 00:47:07,920 Speaker 1: investment schemes by the backing of authoritative people or people 865 00:47:07,960 --> 00:47:11,120 Speaker 1: you feel like you should trust, because especially at peak cycle, 866 00:47:11,400 --> 00:47:14,480 Speaker 1: people are very willing to lend their credibility to uh, 867 00:47:14,520 --> 00:47:16,280 Speaker 1: you know, two things that aren't going to get them paid. 868 00:47:16,719 --> 00:47:19,560 Speaker 1: You know, think of again the Harvard Business School professors 869 00:47:19,560 --> 00:47:24,240 Speaker 1: writing the white papers for Ponzi schemes like anchor, using 870 00:47:24,480 --> 00:47:28,600 Speaker 1: social consensus and group psychology right to normalize ideas and narratives, 871 00:47:28,600 --> 00:47:31,080 Speaker 1: and to pressure people to stop asking questions, you know, 872 00:47:31,120 --> 00:47:33,239 Speaker 1: big Twitter mobs telling you you're an idiot and you're 873 00:47:33,280 --> 00:47:35,600 Speaker 1: not going to make it right. And and then very 874 00:47:35,680 --> 00:47:39,040 Speaker 1: much so kind of scarcity or immediacly like, look, you're 875 00:47:39,040 --> 00:47:40,799 Speaker 1: gonna miss the boat. You don't get it, and it's 876 00:47:40,840 --> 00:47:43,520 Speaker 1: like time to get on board or or miss the boat. Right. 877 00:47:43,600 --> 00:47:46,279 Speaker 1: That's I think really critical. Let me ask you one 878 00:47:46,560 --> 00:47:49,960 Speaker 1: last question, and that the positive spin. And we've had 879 00:47:50,000 --> 00:47:52,720 Speaker 1: guests say this and other people say this, that out 880 00:47:52,760 --> 00:47:57,120 Speaker 1: of this will come a very sophisticated class of investors, 881 00:47:57,200 --> 00:48:00,320 Speaker 1: people who learned about options trading. People love your kind, Tana. 882 00:48:00,360 --> 00:48:03,319 Speaker 1: I saw you know, the Wall Street bets crowd like, uh, 883 00:48:03,360 --> 00:48:05,840 Speaker 1: you know, loves when you jump on there and actually 884 00:48:06,200 --> 00:48:08,560 Speaker 1: walks through the math and walks through some of like 885 00:48:09,160 --> 00:48:11,960 Speaker 1: the risk taking frameworks of this stuff. Do you are 886 00:48:11,960 --> 00:48:14,360 Speaker 1: you optimistic that there will be like a cohort of 887 00:48:14,880 --> 00:48:17,279 Speaker 1: you know, people who maybe got scarred or burned, but 888 00:48:17,400 --> 00:48:19,840 Speaker 1: also like learn some sophisticated stuff that will have a 889 00:48:19,880 --> 00:48:23,800 Speaker 1: good combination of skills and knowledge coming out of this period. 890 00:48:24,360 --> 00:48:26,839 Speaker 1: So I really hope. So, I mean, I'll tell you 891 00:48:27,080 --> 00:48:30,520 Speaker 1: ten or ten or fifteen years ago, I remember working 892 00:48:30,560 --> 00:48:33,640 Speaker 1: with a good friend who's now a VC on ideas 893 00:48:33,760 --> 00:48:36,200 Speaker 1: for like investor education, and how do you get people 894 00:48:36,200 --> 00:48:39,120 Speaker 1: that even care about financial markets and investing and pay attention, 895 00:48:39,120 --> 00:48:41,359 Speaker 1: because back then it was like totally impossible to get 896 00:48:41,400 --> 00:48:43,719 Speaker 1: the young generations to even think about this stuff, right. 897 00:48:43,719 --> 00:48:47,520 Speaker 1: And it's really good that individual investors have gotten interested 898 00:48:47,520 --> 00:48:50,880 Speaker 1: in investing, right, And I know I feel like, you know, 899 00:48:50,960 --> 00:48:54,040 Speaker 1: sometimes I hope I don't give the opposite tone, right, 900 00:48:54,080 --> 00:48:55,840 Speaker 1: because it's so easy for people to get tricked and 901 00:48:55,840 --> 00:48:58,319 Speaker 1: all this kind of stuff, Like it's fantastic, but I 902 00:48:58,360 --> 00:49:01,600 Speaker 1: think a lot of times people have to learn from 903 00:49:01,640 --> 00:49:05,080 Speaker 1: their own experience, right, It's just really hard. I mean, 904 00:49:05,200 --> 00:49:07,920 Speaker 1: you know, Hagel said we learned from history that we 905 00:49:08,040 --> 00:49:11,719 Speaker 1: just can't learn from history, right, Um, people have to, 906 00:49:12,160 --> 00:49:15,719 Speaker 1: one way or another, go through their own experiences of 907 00:49:15,800 --> 00:49:19,640 Speaker 1: mistakes and things not going well to really internalize lessons. 908 00:49:19,680 --> 00:49:22,560 Speaker 1: And what I really hope is that people are able 909 00:49:22,600 --> 00:49:25,240 Speaker 1: to take hold of those lessons and you know, stay 910 00:49:25,239 --> 00:49:27,759 Speaker 1: interested in financial markets and stay interested and invest in 911 00:49:27,800 --> 00:49:29,759 Speaker 1: and learn how to make good decisions as opposed to 912 00:49:29,800 --> 00:49:32,200 Speaker 1: like feeling so scarred by it that they just walk away. 913 00:49:32,840 --> 00:49:35,440 Speaker 1: All right, Ben, it was lovely having you back on 914 00:49:35,480 --> 00:49:38,600 Speaker 1: the show to talk about the lessons of history, recent 915 00:49:38,680 --> 00:49:42,879 Speaker 1: history that I guess we won't necessarily actually learn, but 916 00:49:43,239 --> 00:49:46,080 Speaker 1: it was fun to chat. Let's put it that. Yeah, 917 00:49:46,160 --> 00:50:05,200 Speaker 1: that was funk you absolutely so, Joe. I really enjoyed 918 00:50:05,440 --> 00:50:08,799 Speaker 1: that conversation. It's always great having been on because, like 919 00:50:09,280 --> 00:50:12,400 Speaker 1: I feel like he gives good perspective on detail and 920 00:50:12,480 --> 00:50:15,960 Speaker 1: also on institutional Yeah. One thing that struck me was 921 00:50:16,040 --> 00:50:20,640 Speaker 1: just the last bit of the conversation about you know, 922 00:50:20,800 --> 00:50:25,200 Speaker 1: things that are making money naturally attracting people who want 923 00:50:25,239 --> 00:50:30,800 Speaker 1: to make money. And I guess it seems obvious in retrospect, 924 00:50:30,880 --> 00:50:34,719 Speaker 1: but I do think it's a good reminder. No, it 925 00:50:34,760 --> 00:50:36,719 Speaker 1: really is. And I think, like, look, if you're like 926 00:50:36,880 --> 00:50:40,760 Speaker 1: really smart in any field, but if you're really smart. 927 00:50:40,840 --> 00:50:43,200 Speaker 1: You might you know, people in this space are smart 928 00:50:43,280 --> 00:50:46,400 Speaker 1: enough to like spot the inefficiencies, smart enough to spot 929 00:50:46,480 --> 00:50:50,040 Speaker 1: the suckers, smart enough to figure out like what can 930 00:50:50,520 --> 00:50:52,640 Speaker 1: make life changing amounts of money in a short period 931 00:50:52,680 --> 00:50:54,879 Speaker 1: of time, And a lot of really smart people did. 932 00:50:55,440 --> 00:50:57,759 Speaker 1: But it's really hard, and I think, like you know, 933 00:50:57,880 --> 00:51:01,320 Speaker 1: going back to the middle of the conversation, in real time, 934 00:51:01,960 --> 00:51:04,160 Speaker 1: I think it's just extremely hard to know where you 935 00:51:04,200 --> 00:51:06,480 Speaker 1: are in a cycle and what's the difference between a 936 00:51:06,520 --> 00:51:11,440 Speaker 1: bubble and a new regime or a new a new thing. 937 00:51:11,640 --> 00:51:15,080 Speaker 1: Oh totally. And also even if you correctly pinpoint where 938 00:51:15,120 --> 00:51:17,640 Speaker 1: we are in the cycle, you could still make mistakes. 939 00:51:17,640 --> 00:51:19,840 Speaker 1: So I'm thinking of, you know, all the people who 940 00:51:20,080 --> 00:51:22,479 Speaker 1: thought that inflation was going to rise over the past 941 00:51:22,480 --> 00:51:24,839 Speaker 1: couple of years and they bought bitcoin and gold like 942 00:51:25,200 --> 00:51:28,879 Speaker 1: that hasn't worked out so well. No, it's really hard, 943 00:51:28,960 --> 00:51:31,359 Speaker 1: and you know, like again, a lot of the most 944 00:51:31,920 --> 00:51:35,600 Speaker 1: the costliest errors come in the final stages, whether that's 945 00:51:35,680 --> 00:51:39,600 Speaker 1: jumping in too big, whether it's trying to short the thing. 946 00:51:39,640 --> 00:51:41,399 Speaker 1: I mean, that's like the crazy part. Like to think 947 00:51:41,400 --> 00:51:44,360 Speaker 1: about crypto over the last year, there's two huge ways 948 00:51:44,400 --> 00:51:47,040 Speaker 1: to lose money you could have gone really big in 949 00:51:47,120 --> 00:51:49,840 Speaker 1: at the peak, or you could have like gone short, 950 00:51:49,880 --> 00:51:52,440 Speaker 1: like a few months earlier and gone out of business 951 00:51:52,520 --> 00:51:55,480 Speaker 1: within a few months. So like the ability on either 952 00:51:55,600 --> 00:51:59,720 Speaker 1: side of the trade just tremendous opportunities to lose a fortune. Yeah, 953 00:51:59,840 --> 00:52:02,520 Speaker 1: or you could have gotten out, you know, in like 954 00:52:03,320 --> 00:52:05,919 Speaker 1: sen or something like you know what, you know, my 955 00:52:06,239 --> 00:52:10,440 Speaker 1: red flag is for a scammer. I've told you this, 956 00:52:10,960 --> 00:52:15,000 Speaker 1: someone with a newsletter. Yeah, but well, either a newsletter 957 00:52:15,080 --> 00:52:18,920 Speaker 1: or fund manager who quote Greek philosophers up at the front. 958 00:52:19,080 --> 00:52:21,120 Speaker 1: That's like the big red flag. It's like you see 959 00:52:21,120 --> 00:52:23,720 Speaker 1: an letter in the beginning is like some like quote 960 00:52:23,719 --> 00:52:28,000 Speaker 1: from Marcus Aurelius, I don't know, or like Cicero or 961 00:52:28,080 --> 00:52:31,799 Speaker 1: something like that or whatever it is. It's like, stay away. 962 00:52:31,840 --> 00:52:34,279 Speaker 1: That's that's my trick. It's worked for me. Don't we 963 00:52:34,320 --> 00:52:36,600 Speaker 1: have a newsletter, Yeah, but we don't quote. We don't. 964 00:52:36,640 --> 00:52:42,880 Speaker 1: We don't quote the ancients to volster our volster our claim. Alright, 965 00:52:43,000 --> 00:52:45,520 Speaker 1: let's leave it there, all right, This is bending another 966 00:52:45,600 --> 00:52:48,279 Speaker 1: episode of the All Thoughts podcast. I'm Tracy Alloway. You 967 00:52:48,280 --> 00:52:50,799 Speaker 1: can follow me on Twitter at Tracy Alloway, and I'm 968 00:52:50,880 --> 00:52:53,440 Speaker 1: Joe wasn't, though you could have. Follow me on Twitter 969 00:52:53,560 --> 00:52:57,000 Speaker 1: at the Stalwart. Follow our guest Ben Eiffert. He's on Twitter, 970 00:52:57,080 --> 00:53:00,000 Speaker 1: Ben P. Eiffort at his two Ends in It. Follow 971 00:53:00,000 --> 00:53:03,400 Speaker 1: our producer Carmen Rodriguez at Carmen Arman, and check out 972 00:53:03,440 --> 00:53:07,000 Speaker 1: all of our podcasts at Bloomberg onto the handle at podcasts. 973 00:53:07,120 --> 00:53:07,880 Speaker 1: Thanks for listening,