1 00:00:13,600 --> 00:00:17,279 Speaker 1: Hello and welcome to what goes up a weekly markets podcast. 2 00:00:17,480 --> 00:00:19,880 Speaker 1: My name is Mike Reagan, I'm a senior editor at 3 00:00:19,880 --> 00:00:23,160 Speaker 1: Bloomberg and I'm Aldana hike across acid reporter with Bloomberg 4 00:00:23,600 --> 00:00:26,600 Speaker 1: and this week on the show. Well, the Federal Reserve 5 00:00:26,680 --> 00:00:31,680 Speaker 1: surprised investors this week by simultaneously raising their projections for 6 00:00:31,760 --> 00:00:36,640 Speaker 1: interest rates and lowering their projections for economic growth. The 7 00:00:36,680 --> 00:00:40,040 Speaker 1: consensus seems to be that the nightmare for investors in 8 00:00:40,120 --> 00:00:43,640 Speaker 1: both stocks and bonds this year is far from over, 9 00:00:43,840 --> 00:00:49,160 Speaker 1: unfortunately so. With traditional strategies like the sixty forty portfolio 10 00:00:49,200 --> 00:00:53,400 Speaker 1: allocation under continued pressure, what are the options to investors 11 00:00:53,400 --> 00:00:56,400 Speaker 1: really have? We'll talk to a quant at a major 12 00:00:56,440 --> 00:01:00,360 Speaker 1: asset management firm who has some ideas about that. But first, 13 00:01:00,480 --> 00:01:04,440 Speaker 1: vil Donna, it's been a while, UH, two weeks without you. 14 00:01:04,720 --> 00:01:08,840 Speaker 1: We missed you terribly. You had quite an adventure, I did. 15 00:01:08,880 --> 00:01:10,960 Speaker 1: I went to Spain, as you know you did, and 16 00:01:11,160 --> 00:01:13,640 Speaker 1: when you came back I was delighted to see you 17 00:01:13,720 --> 00:01:16,640 Speaker 1: actually did bring me some of that famous Spanish Ham 18 00:01:16,880 --> 00:01:21,120 Speaker 1: don't tell Bryan Duncan from the Illinois Farm Bureau, but 19 00:01:21,200 --> 00:01:23,400 Speaker 1: I snuck some Hammond for you. You suck some of 20 00:01:23,400 --> 00:01:27,199 Speaker 1: that that delicious Iberico Ham. And but when you brought 21 00:01:27,200 --> 00:01:30,679 Speaker 1: it to me, I was thinking, Vildonna does not look herself. 22 00:01:30,720 --> 00:01:34,560 Speaker 1: I thought either she's jet lagged or she's just so 23 00:01:34,680 --> 00:01:37,959 Speaker 1: disgusted by having to bring this ham to me from 24 00:01:38,000 --> 00:01:40,679 Speaker 1: it was the last all the way across, but it 25 00:01:40,800 --> 00:01:44,759 Speaker 1: was actually the third thing. You had covid and luckily 26 00:01:44,800 --> 00:01:48,040 Speaker 1: covid you cannot catch covid from Ham. I've I've determined, 27 00:01:48,120 --> 00:01:50,840 Speaker 1: thank God, thank God you're okay, even though your covid 28 00:01:50,840 --> 00:01:53,200 Speaker 1: germs were all over. The Ham is delicious. That's what 29 00:01:53,240 --> 00:01:57,960 Speaker 1: I get for around Europe. I was very worried about you, 30 00:01:58,000 --> 00:02:00,600 Speaker 1: but now now that I know you're okay, I uh, 31 00:02:00,640 --> 00:02:03,280 Speaker 1: I feel like you can take a little ribbing. But 32 00:02:03,720 --> 00:02:05,920 Speaker 1: how was the COVID adventure? You were pretty sick. Yeah, 33 00:02:05,920 --> 00:02:08,000 Speaker 1: I was kind of sick. I've never had it before 34 00:02:08,040 --> 00:02:10,520 Speaker 1: and I finally caught up with me. I guess it's 35 00:02:10,560 --> 00:02:13,840 Speaker 1: literally what I get for going to Europe and having fun. 36 00:02:16,400 --> 00:02:21,600 Speaker 1: So well, we're glad, so glad you're back feeling good. 37 00:02:21,760 --> 00:02:25,919 Speaker 1: The Ham was absolutely delicious. I know you're disgusted to 38 00:02:26,160 --> 00:02:29,360 Speaker 1: carry around some some swine for me, and it's very surprised. 39 00:02:29,360 --> 00:02:31,120 Speaker 1: I did not actually expect you to actually bring that. 40 00:02:31,320 --> 00:02:33,640 Speaker 1: I got you the top quality version it was. There 41 00:02:33,680 --> 00:02:35,360 Speaker 1: was like a two dollar version and there was like 42 00:02:35,360 --> 00:02:37,560 Speaker 1: a seven dollar version. I got you the seven dollar one. 43 00:02:37,720 --> 00:02:39,600 Speaker 1: In fact, I think you're probably not the only one 44 00:02:39,639 --> 00:02:42,200 Speaker 1: sick over that hand, because I was so hungry going home, 45 00:02:42,240 --> 00:02:44,720 Speaker 1: I actually opened the package and started eating it on 46 00:02:44,760 --> 00:02:48,480 Speaker 1: the subway and I hate. Everyone hates so many eats 47 00:02:48,480 --> 00:02:52,720 Speaker 1: on them, especially a big pile of ham, but I 48 00:02:53,120 --> 00:02:55,720 Speaker 1: appreciate it. It It was delicious good. Well, I do want 49 00:02:55,720 --> 00:02:57,600 Speaker 1: to bring in our guests. Who who? I don't want 50 00:02:57,600 --> 00:03:00,320 Speaker 1: to keep him waiting too long. It's George Patterson. He's 51 00:03:00,320 --> 00:03:04,080 Speaker 1: a chief investment officer at pgim quantitative solutions. So, George, 52 00:03:04,120 --> 00:03:07,160 Speaker 1: thanks so much for joining us this week. Great to 53 00:03:07,200 --> 00:03:10,280 Speaker 1: be here. Thank you for having me and maybe, uh, 54 00:03:10,440 --> 00:03:12,920 Speaker 1: I can start out with just a quick story, which 55 00:03:12,960 --> 00:03:14,920 Speaker 1: is that I met you over the summer at a 56 00:03:14,919 --> 00:03:17,160 Speaker 1: pigym event and we talked a little bit about you 57 00:03:17,160 --> 00:03:20,440 Speaker 1: and about your background, and you have a very interesting background. 58 00:03:20,720 --> 00:03:24,040 Speaker 1: You actually used to work for NASA right. So I'm 59 00:03:24,040 --> 00:03:26,919 Speaker 1: hoping you can just start out talking about your your 60 00:03:27,080 --> 00:03:29,359 Speaker 1: yourself a bit and how you ended up with Pigym 61 00:03:29,400 --> 00:03:33,280 Speaker 1: considering that background. Sure, yeah, well, I'm one of the 62 00:03:33,360 --> 00:03:36,360 Speaker 1: few quantitative investors that can actually say they were a 63 00:03:36,360 --> 00:03:42,200 Speaker 1: real rocket scientist. I studied physics both undergraduate and Graduate 64 00:03:42,240 --> 00:03:46,840 Speaker 1: School and, uh, after graduating, my first opportunity was as 65 00:03:46,880 --> 00:03:50,880 Speaker 1: a post doc at the Jet Propulsion Laboratory in Pasadena, California. 66 00:03:51,160 --> 00:03:54,400 Speaker 1: So I was there for two years. UH, great, very 67 00:03:54,440 --> 00:03:57,520 Speaker 1: great experience. Learned quite a bit. There are no more 68 00:03:58,000 --> 00:04:01,640 Speaker 1: rockets at the Jet Propulsion Laboratory. It was you know 69 00:04:01,680 --> 00:04:03,320 Speaker 1: at this point, but there was a lot of space 70 00:04:03,360 --> 00:04:07,360 Speaker 1: related uh, you know, science and and physics going on. 71 00:04:07,720 --> 00:04:10,400 Speaker 1: My project was maybe a little bit more tangentially related 72 00:04:10,440 --> 00:04:13,120 Speaker 1: to space, but it was a great experience. However, you know, 73 00:04:13,320 --> 00:04:17,720 Speaker 1: after some soul searching, I became interested in quantitative investments 74 00:04:18,360 --> 00:04:21,120 Speaker 1: and Um found, you know, found an organization up in 75 00:04:21,160 --> 00:04:25,360 Speaker 1: San Francisco. What was then wells Fargo Nico Investment Advisors. 76 00:04:25,440 --> 00:04:29,280 Speaker 1: Became Barclay's global investors and was there for quite a 77 00:04:29,480 --> 00:04:32,400 Speaker 1: large portion of my career. I've been doing the same 78 00:04:32,440 --> 00:04:37,080 Speaker 1: thing quantitative investments, you know, typically, you know, focused on 79 00:04:37,200 --> 00:04:40,320 Speaker 1: serving large institutions, and they've been doing that since the 80 00:04:40,320 --> 00:04:43,760 Speaker 1: mid nineties and a number of different organizations at church. 81 00:04:43,839 --> 00:04:48,440 Speaker 1: It's fascinating to me how many people with physics backgrounds, 82 00:04:48,560 --> 00:04:51,480 Speaker 1: m I t types like yourself, end up in quant investing. 83 00:04:51,520 --> 00:04:54,039 Speaker 1: What what is? Is it just the math background or 84 00:04:54,080 --> 00:04:57,560 Speaker 1: there or there's certain sort of principles of physics that 85 00:04:57,600 --> 00:05:00,240 Speaker 1: are just easily applied to markets? Why is it, uh, 86 00:05:00,279 --> 00:05:03,760 Speaker 1: that connection that we see so often? Yeah, I think 87 00:05:03,839 --> 00:05:05,560 Speaker 1: it's I think part of it is the math and 88 00:05:05,680 --> 00:05:10,520 Speaker 1: Statistics and, Um, you know, not being I think the 89 00:05:10,560 --> 00:05:13,160 Speaker 1: great thing about the physics background is is that they 90 00:05:13,200 --> 00:05:16,240 Speaker 1: really teach you not to be afraid of of digging, 91 00:05:16,360 --> 00:05:18,800 Speaker 1: going into a new field where you you know, you 92 00:05:18,839 --> 00:05:21,120 Speaker 1: don't have anything, and really like taking it apart and 93 00:05:21,200 --> 00:05:25,000 Speaker 1: understanding what drives it. So I've had several people who, 94 00:05:25,279 --> 00:05:27,800 Speaker 1: you know, are economists that have, you know, said to 95 00:05:27,839 --> 00:05:30,200 Speaker 1: me like, you know, I remember them saying to me 96 00:05:30,200 --> 00:05:32,680 Speaker 1: at one point like we're, you know, we're so surprised, 97 00:05:32,720 --> 00:05:34,640 Speaker 1: you know, that you've done so well. And I said, well, 98 00:05:34,920 --> 00:05:37,000 Speaker 1: that's because I don't listen to economists who tell me 99 00:05:37,040 --> 00:05:39,719 Speaker 1: something is impossible, because, you know, I need to prove 100 00:05:39,760 --> 00:05:42,920 Speaker 1: to myself that something can't be done. And, Um, you know, 101 00:05:43,040 --> 00:05:45,560 Speaker 1: a lot of times you you know, like you do, 102 00:05:45,640 --> 00:05:46,840 Speaker 1: you don't want to get in the way of someone 103 00:05:46,839 --> 00:05:49,080 Speaker 1: who's trying to solve something that's not that that everyone 104 00:05:49,080 --> 00:05:51,640 Speaker 1: else says is impossible. So I think it's just that 105 00:05:51,680 --> 00:05:54,719 Speaker 1: mentality you get that you need to you know, you 106 00:05:54,760 --> 00:05:58,000 Speaker 1: need to challenge assumptions. You know, you're always looking to 107 00:05:58,080 --> 00:06:01,960 Speaker 1: disprove something and, Um the thing I like, and I've 108 00:06:01,960 --> 00:06:03,719 Speaker 1: got a number of other physicists who worked for me, 109 00:06:04,000 --> 00:06:06,360 Speaker 1: the thing I really like about hiring, you know, people 110 00:06:06,360 --> 00:06:10,040 Speaker 1: with that background is many times in this in this industry, 111 00:06:10,600 --> 00:06:13,320 Speaker 1: you know there's a particular project that's I need someone 112 00:06:13,360 --> 00:06:15,120 Speaker 1: to work on, and I may say go off and, 113 00:06:15,240 --> 00:06:17,680 Speaker 1: you know, look at look at this problem or or 114 00:06:17,720 --> 00:06:20,000 Speaker 1: look at that problem and and a lot of times 115 00:06:20,040 --> 00:06:22,400 Speaker 1: what you find is that, you know, research is not easy, 116 00:06:22,440 --> 00:06:26,599 Speaker 1: it's it's very challenging. You'll find that maybe whatever you 117 00:06:26,640 --> 00:06:30,039 Speaker 1: set out to do is impossible. But when you hire 118 00:06:30,120 --> 00:06:33,520 Speaker 1: someone with a bit of a science background, they'll always 119 00:06:33,560 --> 00:06:35,960 Speaker 1: find something interesting. So they may they'll always come back 120 00:06:35,960 --> 00:06:37,640 Speaker 1: to me and say, Hey, I didn't, we couldn't solve 121 00:06:37,680 --> 00:06:39,840 Speaker 1: the problem, or we we solve the problem, but there's 122 00:06:39,839 --> 00:06:42,560 Speaker 1: no there's no Alpha in it. But we found several 123 00:06:42,600 --> 00:06:46,280 Speaker 1: other interesting things that might be relevant, and sometimes that's 124 00:06:46,320 --> 00:06:47,960 Speaker 1: an important part of the job. You just have to 125 00:06:48,040 --> 00:06:50,760 Speaker 1: kind of follow your nose to see where you know, 126 00:06:50,800 --> 00:06:54,360 Speaker 1: where the opportunities are. Research is not a linear process. 127 00:06:54,400 --> 00:06:56,200 Speaker 1: You don't say, you know, I'm going to go out and, 128 00:06:56,560 --> 00:06:59,640 Speaker 1: you know find uh, you know, a sharp ratio three 129 00:07:00,040 --> 00:07:02,520 Speaker 1: investment idea. You know, you have to you know it 130 00:07:02,560 --> 00:07:04,120 Speaker 1: may be out there, it may not. Part of it 131 00:07:04,160 --> 00:07:07,360 Speaker 1: is discovering it, Um, and it's you know, you have 132 00:07:07,440 --> 00:07:09,720 Speaker 1: to be you have to be open to sometimes not 133 00:07:09,760 --> 00:07:14,840 Speaker 1: necessarily going, you know, where the specific agenda is leading you. Yeah, 134 00:07:14,840 --> 00:07:17,600 Speaker 1: and of course now anytime, uh, someone wants to make 135 00:07:17,600 --> 00:07:19,640 Speaker 1: a stock go up on social media, they use that 136 00:07:19,720 --> 00:07:23,200 Speaker 1: rocket ship Emoji. So some some more synergy there for 137 00:07:23,200 --> 00:07:26,760 Speaker 1: for the rocket scientists, and a lot of overlape. Yeah, 138 00:07:26,800 --> 00:07:30,320 Speaker 1: but George, Um, I know one area you're interested in 139 00:07:30,480 --> 00:07:35,480 Speaker 1: and I'm sort of fascinated with is, um, natural language processing, 140 00:07:35,600 --> 00:07:38,720 Speaker 1: you know, in other words using computers to sort of 141 00:07:38,960 --> 00:07:42,760 Speaker 1: read text uh and interpret it. Uh. And when we 142 00:07:42,840 --> 00:07:45,480 Speaker 1: got a lot of words from Jerome Pal this week, 143 00:07:46,480 --> 00:07:49,960 Speaker 1: a fed statement and a press conference, Um, I feel 144 00:07:49,960 --> 00:07:53,720 Speaker 1: like the you know, his message was was pretty easy 145 00:07:53,760 --> 00:07:56,720 Speaker 1: to understand. You know, we're we're gonna hike rates, WE'RE 146 00:07:56,720 --> 00:08:01,160 Speaker 1: gonna keep hiking rates aggressively until inflation is tamed. But 147 00:08:01,480 --> 00:08:06,040 Speaker 1: I'm wondering, from UH quant perspective, from a natural language 148 00:08:06,080 --> 00:08:10,679 Speaker 1: processing perspective, is there something more that a computer, uh 149 00:08:10,840 --> 00:08:15,240 Speaker 1: program can, can glean from a press conference like that, uh, 150 00:08:15,280 --> 00:08:17,200 Speaker 1: and the statement, or is it just a matter of 151 00:08:17,200 --> 00:08:20,400 Speaker 1: of being able to react quickly to it, uh, with 152 00:08:20,440 --> 00:08:24,000 Speaker 1: trading algorithms? You know, how does how does UH natural 153 00:08:24,080 --> 00:08:27,040 Speaker 1: language processing fit into an event like that this week? 154 00:08:28,280 --> 00:08:31,360 Speaker 1: So so there's several things, Um, that that I would 155 00:08:31,360 --> 00:08:34,160 Speaker 1: say are relevant. Uh. You know, I'm sure there's a 156 00:08:34,200 --> 00:08:37,320 Speaker 1: lot of people out there that are running, you know, 157 00:08:37,520 --> 00:08:41,480 Speaker 1: very short horizon strategies, looking at what words he chooses 158 00:08:41,520 --> 00:08:45,240 Speaker 1: to use and and like specifically, like the questions and 159 00:08:45,320 --> 00:08:47,360 Speaker 1: answers that come out of that, and are looking to 160 00:08:47,480 --> 00:08:51,360 Speaker 1: kind of uh Um, you know, talk, you know, get 161 00:08:51,360 --> 00:08:53,240 Speaker 1: in or out of the market very quickly to take 162 00:08:53,280 --> 00:08:55,880 Speaker 1: advantage of kind of a short term movement. I think 163 00:08:55,920 --> 00:08:59,640 Speaker 1: the real advantage, however, of language processing is just that 164 00:09:00,120 --> 00:09:02,320 Speaker 1: you can go into depth, you know, you can read 165 00:09:02,920 --> 00:09:06,280 Speaker 1: a ten K and and analyze a lot of aspects 166 00:09:06,320 --> 00:09:08,240 Speaker 1: of it and you could do that for two or 167 00:09:08,280 --> 00:09:09,840 Speaker 1: three of them, but it might take you, you know, 168 00:09:09,880 --> 00:09:11,440 Speaker 1: it could easily take you half a day or a 169 00:09:11,520 --> 00:09:14,400 Speaker 1: day each. The advantage of language processing is that you 170 00:09:14,400 --> 00:09:17,320 Speaker 1: get the breath, so you can do three thousand of these, 171 00:09:17,440 --> 00:09:19,720 Speaker 1: you know, in a matter of, you know, minutes or 172 00:09:19,760 --> 00:09:22,360 Speaker 1: maybe half an hour, depending on what what type of 173 00:09:22,360 --> 00:09:25,200 Speaker 1: models you're running. But it's a combination of the breath 174 00:09:25,240 --> 00:09:27,640 Speaker 1: and the timeliness, I would say, that makes it relevant. 175 00:09:28,000 --> 00:09:30,440 Speaker 1: And if you think about humans, like so much of 176 00:09:30,440 --> 00:09:34,120 Speaker 1: our intelligence, so much of our knowledge, is really encoded 177 00:09:34,160 --> 00:09:37,640 Speaker 1: in writing. You know, we've been collecting numerical data for 178 00:09:37,720 --> 00:09:41,120 Speaker 1: some time, but people have been generating written texts, you know, 179 00:09:41,200 --> 00:09:44,080 Speaker 1: since the beginning of of you know, the beginning of 180 00:09:44,160 --> 00:09:47,760 Speaker 1: kind of putting text down on paper. Um. So there's 181 00:09:47,800 --> 00:09:50,000 Speaker 1: just a huge amount of information that comes out and 182 00:09:50,000 --> 00:09:51,920 Speaker 1: there's a lot of value in there. Is What we 183 00:09:51,960 --> 00:09:54,400 Speaker 1: have found. So it's been one of the most uh 184 00:09:55,040 --> 00:09:57,120 Speaker 1: relevant areas for us, you know, over the past few 185 00:09:57,240 --> 00:10:01,560 Speaker 1: years to extract information. Well, one of the words that 186 00:10:02,400 --> 00:10:05,320 Speaker 1: kept coming up quite a bit during the power press 187 00:10:05,360 --> 00:10:07,800 Speaker 1: conference was the word pain, and I read a bunch 188 00:10:07,840 --> 00:10:12,200 Speaker 1: of notes after after his press conference, pointing this out 189 00:10:12,520 --> 00:10:16,120 Speaker 1: specifically because of the market reaction that we saw on 190 00:10:16,320 --> 00:10:19,480 Speaker 1: Wednesday afternoon. So maybe can you just lay out what, 191 00:10:19,600 --> 00:10:23,240 Speaker 1: in your view, actually transpired with the power press conference 192 00:10:23,240 --> 00:10:25,160 Speaker 1: and what we got from from the F O M 193 00:10:25,200 --> 00:10:28,880 Speaker 1: C and what you make of how the market reacted? 194 00:10:29,440 --> 00:10:32,240 Speaker 1: So my view is is that, you know, it over 195 00:10:32,280 --> 00:10:36,640 Speaker 1: the summer with some earlier with some earlier statements from Powell, 196 00:10:36,760 --> 00:10:41,880 Speaker 1: he he tried to portray a very, you know, serious 197 00:10:41,960 --> 00:10:45,520 Speaker 1: view about taming inflation and he came away saying that 198 00:10:45,559 --> 00:10:47,440 Speaker 1: you know, we're gonna WE'RE gonna do it. But he 199 00:10:47,520 --> 00:10:51,240 Speaker 1: was maybe just a little bit too dubbish and you know, 200 00:10:51,320 --> 00:10:54,320 Speaker 1: we saw a very large rally and markets over the 201 00:10:54,360 --> 00:10:56,640 Speaker 1: summer as the result of that, even though a number 202 00:10:56,640 --> 00:11:01,400 Speaker 1: of other fed speakers came out and and really were Um, 203 00:11:01,440 --> 00:11:03,760 Speaker 1: you know, kind of we're much more pessimistic about things. 204 00:11:03,920 --> 00:11:06,000 Speaker 1: So I think really since then what we've seen is 205 00:11:06,040 --> 00:11:09,199 Speaker 1: he has just had to be extremely clear that they 206 00:11:09,200 --> 00:11:12,560 Speaker 1: are gonna get their job done and you know it's 207 00:11:12,559 --> 00:11:14,960 Speaker 1: gonna it is going to cause some disruption. I think. 208 00:11:15,000 --> 00:11:17,440 Speaker 1: I think some of his earlier statements he was trying 209 00:11:17,440 --> 00:11:19,800 Speaker 1: to be a bit more balanced. But I think now, 210 00:11:19,920 --> 00:11:22,160 Speaker 1: given the market's reaction, he has just he has just 211 00:11:22,200 --> 00:11:24,800 Speaker 1: realized that he has to be extremely clear about where 212 00:11:25,000 --> 00:11:27,480 Speaker 1: things going, where he things are, things are going. I 213 00:11:27,520 --> 00:11:31,040 Speaker 1: don't forget it is a challenging economic outlook, but it 214 00:11:31,080 --> 00:11:34,720 Speaker 1: follows several years of huge gains in the market. So 215 00:11:35,040 --> 00:11:37,240 Speaker 1: you know, if you look over a longer period of time, 216 00:11:37,640 --> 00:11:39,200 Speaker 1: you know we've we've had a lot of gains in 217 00:11:39,200 --> 00:11:41,480 Speaker 1: a short period of time. So it's not unrealistic to 218 00:11:41,520 --> 00:11:43,400 Speaker 1: expect a little bit of give back in the next 219 00:11:43,720 --> 00:11:46,960 Speaker 1: you know, the next year or two. Judge, as I 220 00:11:47,000 --> 00:11:49,240 Speaker 1: said in the Intro, uh, you know, brutal year for 221 00:11:49,280 --> 00:11:52,960 Speaker 1: both stocks and bonds. That sort of traditional sixty forty 222 00:11:53,040 --> 00:11:57,920 Speaker 1: portfolio is uh, has hit hard times. Uh, to say 223 00:11:57,920 --> 00:12:00,800 Speaker 1: the least. I imagine for a guy in your position 224 00:12:00,840 --> 00:12:03,520 Speaker 1: there's uh, you know, a lot of clients out there 225 00:12:03,520 --> 00:12:05,520 Speaker 1: saying get me a rocket, scientists on the phone. We 226 00:12:05,600 --> 00:12:09,679 Speaker 1: gotta figure out something else that works. So so from 227 00:12:09,720 --> 00:12:12,880 Speaker 1: a quand perspective. Um, I know there's some stuff that's 228 00:12:12,880 --> 00:12:16,400 Speaker 1: working spectacularly. This year I did a story on trend 229 00:12:16,440 --> 00:12:20,679 Speaker 1: following and mauntaged futures. Commodity trading advisors who are are 230 00:12:20,760 --> 00:12:24,679 Speaker 1: really doing really well this year just by uh, sort of, 231 00:12:24,880 --> 00:12:28,040 Speaker 1: you know, following the chart down when when, uh, you know, 232 00:12:28,160 --> 00:12:30,680 Speaker 1: stocks are going down, when yields are going up, just 233 00:12:30,679 --> 00:12:33,760 Speaker 1: just following the trends. But what else is is um 234 00:12:34,040 --> 00:12:37,559 Speaker 1: sort of a solution from a quant perspective for a 235 00:12:37,679 --> 00:12:40,559 Speaker 1: challenging environment like this? What are you telling those clients 236 00:12:40,880 --> 00:12:43,920 Speaker 1: looking for something to either, you know, get some kind 237 00:12:43,920 --> 00:12:46,199 Speaker 1: of return this year or at least protect the wealth 238 00:12:46,240 --> 00:12:50,559 Speaker 1: they have? Yeah, so, you know, there are several different things. 239 00:12:50,640 --> 00:12:53,120 Speaker 1: I mean, first of all, we do have several offerings 240 00:12:53,160 --> 00:12:56,120 Speaker 1: that that focus on trend following or kind of global 241 00:12:56,160 --> 00:12:59,800 Speaker 1: macro strategies or tail hedging, and you're right, those have 242 00:13:00,240 --> 00:13:03,640 Speaker 1: very successful. This is kind of the perfect economic environment 243 00:13:03,679 --> 00:13:06,360 Speaker 1: where you do have big movements as well as some 244 00:13:06,440 --> 00:13:10,040 Speaker 1: big inconsistencies across the globe. For example, looking at Japan 245 00:13:10,120 --> 00:13:12,880 Speaker 1: and how you know they're, you know, everyone else's raising 246 00:13:12,960 --> 00:13:15,280 Speaker 1: rates in Japan is really not and you know we're 247 00:13:15,280 --> 00:13:16,920 Speaker 1: we hear a little bit now about trying to have 248 00:13:16,960 --> 00:13:19,880 Speaker 1: to defend the end. However, Um, you know, there's a 249 00:13:19,880 --> 00:13:23,040 Speaker 1: couple of other things. One is commodities and and other 250 00:13:23,200 --> 00:13:25,840 Speaker 1: and the other would be real assets in general. Maybe 251 00:13:25,880 --> 00:13:27,360 Speaker 1: the last one I would talk about would be some 252 00:13:27,400 --> 00:13:31,200 Speaker 1: downside protection. So commodities and real assets are, you know, 253 00:13:31,240 --> 00:13:33,360 Speaker 1: we've seen kind of a big run up in commodities 254 00:13:33,400 --> 00:13:35,920 Speaker 1: and a bit of a retracement, but over the long run, 255 00:13:36,080 --> 00:13:38,199 Speaker 1: you know, there's a lot of research that shows that 256 00:13:38,240 --> 00:13:42,480 Speaker 1: commodities do very well in this type of environment. Um, 257 00:13:42,520 --> 00:13:44,760 Speaker 1: you know, we you know, our view is that the 258 00:13:44,800 --> 00:13:47,440 Speaker 1: fit is going to be successful and taming inflation, but 259 00:13:47,480 --> 00:13:49,000 Speaker 1: it's also going to take a little bit of time. 260 00:13:49,040 --> 00:13:52,520 Speaker 1: It's not going to come down very rapidly and you know, 261 00:13:52,559 --> 00:13:55,520 Speaker 1: we think there's a lot of opportunities for commodities in 262 00:13:55,559 --> 00:13:59,520 Speaker 1: someone in in a portfolio. So that's that's one area. Um, 263 00:13:59,640 --> 00:14:02,960 Speaker 1: commod these, I think, also of real assets, you know, Um, 264 00:14:03,000 --> 00:14:06,320 Speaker 1: you know, whether it's real estate or or other, you know, 265 00:14:07,040 --> 00:14:11,840 Speaker 1: direct real investments that are also typically do very well 266 00:14:11,880 --> 00:14:14,720 Speaker 1: in inflationary times. I think the other thing that we 267 00:14:14,760 --> 00:14:17,920 Speaker 1: see a lot of conversations about his downside protection. How 268 00:14:17,960 --> 00:14:20,200 Speaker 1: do you build a strategy that can either hedge a 269 00:14:20,360 --> 00:14:23,720 Speaker 1: hedge tail risk or just, you know, deliver most of 270 00:14:23,760 --> 00:14:26,920 Speaker 1: the upside while limiting the downside? And there again there's 271 00:14:26,920 --> 00:14:29,080 Speaker 1: a number of different solutions we offer in that area. 272 00:14:29,120 --> 00:14:32,240 Speaker 1: So those that say are the main the main subjects 273 00:14:32,240 --> 00:14:35,000 Speaker 1: that we've been talking about. Two clients we've seen the 274 00:14:35,040 --> 00:14:38,000 Speaker 1: most interest in George. Can you talk a little bit 275 00:14:38,000 --> 00:14:39,680 Speaker 1: more about that, because I know you sent us some 276 00:14:39,720 --> 00:14:42,280 Speaker 1: notes before the podcast. You said, Um, it's important for 277 00:14:42,320 --> 00:14:46,320 Speaker 1: investors to consider defensive strategy. So what specifically? Maybe you 278 00:14:46,320 --> 00:14:50,800 Speaker 1: can just go a little bit more into detail. Yeah. So, so, 279 00:14:51,040 --> 00:14:53,280 Speaker 1: you know, a lot of times if you look at 280 00:14:53,280 --> 00:14:57,960 Speaker 1: a long term investor, a long term success and what 281 00:14:58,040 --> 00:15:02,240 Speaker 1: you'll find is that it's it's it's important to participate 282 00:15:02,280 --> 00:15:05,680 Speaker 1: in the upside, but it's probably more important to avoid 283 00:15:06,040 --> 00:15:09,320 Speaker 1: a large draw down. So you know the draw downs 284 00:15:09,320 --> 00:15:11,120 Speaker 1: are very difficult because if you have like a tem 285 00:15:11,160 --> 00:15:14,080 Speaker 1: per cent draw down, you need more than ten percent 286 00:15:14,160 --> 00:15:18,640 Speaker 1: to recoup the return. Just mathematically, a temper cent draw 287 00:15:18,680 --> 00:15:21,240 Speaker 1: down allowed by temper cent gain doesn't get you back 288 00:15:21,280 --> 00:15:24,560 Speaker 1: to where you're started. So if you have some ability 289 00:15:24,680 --> 00:15:28,480 Speaker 1: to either avoid or limit those draw downs over long 290 00:15:28,560 --> 00:15:31,960 Speaker 1: periods of time, that can be very beneficial to uh, 291 00:15:32,000 --> 00:15:34,600 Speaker 1: to to an investor. And if you think about it, 292 00:15:34,600 --> 00:15:37,000 Speaker 1: there you know it's valuable to an institution, but for 293 00:15:37,040 --> 00:15:40,360 Speaker 1: a person. It's even more important, you know, particularly if 294 00:15:40,360 --> 00:15:42,760 Speaker 1: you get into the you know, kind of like five 295 00:15:42,840 --> 00:15:46,000 Speaker 1: to ten years before and after retirement. Um, you have 296 00:15:46,080 --> 00:15:48,320 Speaker 1: to be very careful because that's kind of the period 297 00:15:48,360 --> 00:15:51,120 Speaker 1: of time when, if you have a draw down, uh, 298 00:15:51,240 --> 00:15:54,560 Speaker 1: it could be very detrimental to like retirement savings. So 299 00:15:54,560 --> 00:15:56,560 Speaker 1: so there's a number of different, you know, number of 300 00:15:56,600 --> 00:16:00,600 Speaker 1: different Um ways that you can get into. You developed 301 00:16:00,680 --> 00:16:03,400 Speaker 1: drawing out your strategies that do well. I mean in 302 00:16:03,440 --> 00:16:06,520 Speaker 1: some occasions people look at low ball strategies. We have 303 00:16:06,800 --> 00:16:11,040 Speaker 1: a different approach that kind of combines Um, you know, 304 00:16:11,120 --> 00:16:15,240 Speaker 1: both market and fixed income exposure with with Um with 305 00:16:15,400 --> 00:16:19,560 Speaker 1: some optionality to basically give you downside protection but at 306 00:16:19,560 --> 00:16:23,080 Speaker 1: the same time participate in most of the upside. So 307 00:16:23,240 --> 00:16:26,720 Speaker 1: it's something that, from our perspective, should have a should 308 00:16:26,720 --> 00:16:36,760 Speaker 1: have a place in in many portfolios. You mentioned, uh, 309 00:16:37,080 --> 00:16:40,360 Speaker 1: real assets. I would mind unpacking that a little bit. 310 00:16:40,400 --> 00:16:44,280 Speaker 1: I mean I think there's this this huge uh, curiosity 311 00:16:44,440 --> 00:16:48,680 Speaker 1: and demand for sort of alternatives, liquid alternatives, you know, 312 00:16:49,080 --> 00:16:53,800 Speaker 1: stuff outside of the traditional stocks and bond markets and 313 00:16:54,440 --> 00:16:57,320 Speaker 1: wherever that takes you. But obviously liquidity can be an 314 00:16:57,320 --> 00:17:02,080 Speaker 1: issue with alternative assets. What looks good to you from 315 00:17:02,120 --> 00:17:05,399 Speaker 1: from that perspective, you know, Um, and is it? Is 316 00:17:05,400 --> 00:17:07,600 Speaker 1: it tough for a quant to sort of apply your 317 00:17:07,640 --> 00:17:11,400 Speaker 1: methods to non traditional markets like that? I don't think 318 00:17:11,440 --> 00:17:13,960 Speaker 1: it's tough to you know, they're different structures, but no, 319 00:17:14,160 --> 00:17:16,960 Speaker 1: I think in many ways, you know, being being, having 320 00:17:17,000 --> 00:17:19,639 Speaker 1: a quantitative approach allows us to put some sort of 321 00:17:19,680 --> 00:17:24,159 Speaker 1: consistency across the you know, the different types of asset classes. 322 00:17:24,560 --> 00:17:26,600 Speaker 1: And when we think about things, we think not about 323 00:17:26,680 --> 00:17:29,360 Speaker 1: just risk and return, but we also think about draw down, 324 00:17:29,440 --> 00:17:31,800 Speaker 1: we think about, you know, kind of skewness, we think 325 00:17:31,800 --> 00:17:34,720 Speaker 1: about liquidity. So I mean, from my perspective, from the 326 00:17:34,800 --> 00:17:38,920 Speaker 1: you know, a quantitative approach, you know, definitely compliments Um, 327 00:17:38,960 --> 00:17:43,280 Speaker 1: you know, more more traditional approaches. So I liquid assets. 328 00:17:43,320 --> 00:17:46,080 Speaker 1: You know, private assets has been extremely hot. You know, 329 00:17:46,160 --> 00:17:48,760 Speaker 1: I'd say the last few decades Um, we've seen a 330 00:17:48,840 --> 00:17:51,040 Speaker 1: huge amount of money go into them and you know 331 00:17:51,080 --> 00:17:54,120 Speaker 1: that those assets have done quite well. Your private assets 332 00:17:54,119 --> 00:17:57,359 Speaker 1: definitely have a place in in an institutional investor's portfolio. 333 00:17:57,680 --> 00:18:00,440 Speaker 1: The challenge really, as you mentioned, is liquid it, because 334 00:18:00,480 --> 00:18:03,240 Speaker 1: some of these investments, you know, not only require you 335 00:18:03,240 --> 00:18:06,440 Speaker 1: to make an investional initial investment, but there's also ongoing 336 00:18:06,520 --> 00:18:10,120 Speaker 1: capital calls. So you know, what we have seen some 337 00:18:10,160 --> 00:18:12,520 Speaker 1: clients experience is that you know, if you have a 338 00:18:12,520 --> 00:18:16,080 Speaker 1: combination of liquid and a liquid investments and the liquids 339 00:18:16,080 --> 00:18:19,879 Speaker 1: are requiring capital, you know if you have that, you 340 00:18:19,880 --> 00:18:22,640 Speaker 1: know if you have that money invested in like equities, 341 00:18:22,960 --> 00:18:25,000 Speaker 1: you might have you might be forced to sell equities 342 00:18:25,040 --> 00:18:27,119 Speaker 1: at the worst possible time because you need to make 343 00:18:27,160 --> 00:18:30,679 Speaker 1: a capital call. So so they're the question is not 344 00:18:30,800 --> 00:18:33,760 Speaker 1: so much about looking at what's the maximum return I 345 00:18:33,800 --> 00:18:36,000 Speaker 1: can get, but how does this fit into my portfolio 346 00:18:36,040 --> 00:18:37,439 Speaker 1: and what is this going to cause me to do 347 00:18:37,520 --> 00:18:40,280 Speaker 1: in a in a period of extreme stress? I mean, 348 00:18:40,320 --> 00:18:42,840 Speaker 1: that's really the case. I mean, liquids are great, it's 349 00:18:42,880 --> 00:18:44,439 Speaker 1: just you need to make you need to kind of 350 00:18:44,480 --> 00:18:47,040 Speaker 1: go in the as I say, Eyes Wide Open in 351 00:18:47,160 --> 00:18:50,320 Speaker 1: terms of looking at the opportunity and understanding how it's 352 00:18:50,320 --> 00:18:54,000 Speaker 1: going to fit into your into your objectives. So we 353 00:18:54,119 --> 00:18:57,120 Speaker 1: all know, Tina, there is no alternative and we've all 354 00:18:57,119 --> 00:18:58,840 Speaker 1: been talking about it for such a long time. But 355 00:18:58,920 --> 00:19:01,919 Speaker 1: the thing that I'm hearing out is Tia, which is 356 00:19:01,960 --> 00:19:04,959 Speaker 1: there is an alternative. Two stocks. I don't know if 357 00:19:04,960 --> 00:19:07,320 Speaker 1: you've also been thinking about this or hearing about this, 358 00:19:07,400 --> 00:19:09,840 Speaker 1: but I'm one of you. What you make of this 359 00:19:09,920 --> 00:19:13,240 Speaker 1: idea that there are alternatives now? And you know, somebody 360 00:19:13,280 --> 00:19:15,360 Speaker 1: I spoke with earlier this week said you can hold 361 00:19:15,400 --> 00:19:17,800 Speaker 1: your nose, for instance, and go into high yields. So 362 00:19:18,000 --> 00:19:20,000 Speaker 1: what do you make of some of these alternatives? Now? 363 00:19:20,440 --> 00:19:23,640 Speaker 1: I think it's unfortunate that people are always comparing everything 364 00:19:23,640 --> 00:19:26,040 Speaker 1: to the SMP, right so that the goal is to 365 00:19:26,119 --> 00:19:30,520 Speaker 1: build a portfolio that gives you alternatives and outperforms the SMP, 366 00:19:30,720 --> 00:19:33,040 Speaker 1: and I think that that's that's a little bit of 367 00:19:33,080 --> 00:19:36,119 Speaker 1: a high bar. I think the goal of alternatives is 368 00:19:36,160 --> 00:19:40,399 Speaker 1: more to provide diversification and stability and is and is 369 00:19:40,520 --> 00:19:43,879 Speaker 1: less about can I specifically outperform the SMP or can 370 00:19:43,920 --> 00:19:47,439 Speaker 1: I specifically outperform a specific target? I mean, obviously you 371 00:19:47,480 --> 00:19:50,480 Speaker 1: want your alternatives not to be, you know, to provide 372 00:19:50,480 --> 00:19:53,560 Speaker 1: the diversification, you want them to be reasonably priced and 373 00:19:53,640 --> 00:19:57,239 Speaker 1: obviously want you want solid performance. But sometimes people, I think, 374 00:19:57,240 --> 00:19:59,800 Speaker 1: are a little myopic just saying okay, I want to alternative, 375 00:19:59,800 --> 00:20:02,320 Speaker 1: but us to do better than then this investment or 376 00:20:02,320 --> 00:20:04,959 Speaker 1: that investment. So you know, I think of alternatives much 377 00:20:05,000 --> 00:20:09,240 Speaker 1: more in terms of risk, risk control and um and 378 00:20:09,320 --> 00:20:12,000 Speaker 1: really it's about figuring out what your investment bowl is 379 00:20:12,119 --> 00:20:15,080 Speaker 1: and designing a program that that's going to get you there, 380 00:20:15,119 --> 00:20:17,959 Speaker 1: as opposed to, you know, what's the what's the highest 381 00:20:18,000 --> 00:20:20,080 Speaker 1: possible return I'm going to get over the next month 382 00:20:20,160 --> 00:20:23,480 Speaker 1: or six months? I mean, the world today is amazing 383 00:20:23,480 --> 00:20:25,520 Speaker 1: in terms of what you can get. I mean you 384 00:20:25,760 --> 00:20:27,600 Speaker 1: you know, when I was growing up it was, you know, 385 00:20:27,760 --> 00:20:32,040 Speaker 1: stocks and bonds. Now you know, there's all kinds of uh, 386 00:20:32,040 --> 00:20:36,920 Speaker 1: you know real estate, you know, publicly traded, privately traded. Um, 387 00:20:36,960 --> 00:20:40,080 Speaker 1: you know fractional assets. You know where you can buy 388 00:20:40,119 --> 00:20:43,680 Speaker 1: fractions of real estate or fractions of a painting. And 389 00:20:43,920 --> 00:20:46,400 Speaker 1: I mean we, we've just like the access to these 390 00:20:46,400 --> 00:20:50,000 Speaker 1: things has become, you know, a little scary in all honesty, 391 00:20:50,040 --> 00:20:52,159 Speaker 1: and that like you can really get into many different 392 00:20:52,200 --> 00:20:54,720 Speaker 1: things that, uh, look, some of this I think is 393 00:20:54,760 --> 00:20:56,959 Speaker 1: probably good, but some of it is is maybe stretching 394 00:20:56,960 --> 00:21:00,359 Speaker 1: a little too far. Bildna got me a fract of 395 00:21:00,359 --> 00:21:03,480 Speaker 1: a Spanish hug. That was that's the best asset I've had. 396 00:21:03,520 --> 00:21:06,960 Speaker 1: That was that was a good, yeah, alternative asset. But, 397 00:21:07,000 --> 00:21:10,040 Speaker 1: George Um, you mentioned something earlier on that. I want 398 00:21:10,040 --> 00:21:12,720 Speaker 1: to sort of rewinding. Get back to and that is 399 00:21:12,840 --> 00:21:14,600 Speaker 1: that you said you do think the Fed is going 400 00:21:14,640 --> 00:21:18,560 Speaker 1: to be successful in taming inflation, but it's gonna take 401 00:21:18,560 --> 00:21:20,520 Speaker 1: a while and I don't want to put you on 402 00:21:20,560 --> 00:21:22,520 Speaker 1: the spot, I know, I know no one wants to 403 00:21:22,560 --> 00:21:25,320 Speaker 1: predict that inflation is gonna peak at at this percent 404 00:21:25,480 --> 00:21:29,679 Speaker 1: on this date, but I wonder how you're thinking about 405 00:21:29,800 --> 00:21:34,040 Speaker 1: how that taming of inflation is going to play out. Um, 406 00:21:34,400 --> 00:21:36,639 Speaker 1: you know, are we bound to sort of retest the 407 00:21:36,680 --> 00:21:39,320 Speaker 1: market lows from June and maybe even set new lows? 408 00:21:39,320 --> 00:21:42,439 Speaker 1: And equities, uh, you know, our our bond is going 409 00:21:42,480 --> 00:21:45,440 Speaker 1: to continue to suffer. You know what what's what's sort 410 00:21:45,440 --> 00:21:48,840 Speaker 1: of the near future look like? Uh, to you? As 411 00:21:48,920 --> 00:21:52,240 Speaker 1: far as, uh, what the Fed is doing to fight inflation? 412 00:21:52,760 --> 00:21:55,639 Speaker 1: These are unique times and and I don't have h 413 00:21:56,200 --> 00:22:00,560 Speaker 1: you know, I try to not make specific or term 414 00:22:00,640 --> 00:22:03,119 Speaker 1: predictions because, you know, my view is the way to 415 00:22:03,160 --> 00:22:05,800 Speaker 1: be successful is to have a long term perspective and 416 00:22:05,840 --> 00:22:08,479 Speaker 1: to be focusing on the fundamentals that are driving the market. 417 00:22:09,080 --> 00:22:12,200 Speaker 1: I would say, you know, when we look at inflation, 418 00:22:12,320 --> 00:22:14,680 Speaker 1: we look at the components of inflation. You know, there 419 00:22:14,720 --> 00:22:18,360 Speaker 1: are some components, like housing, that have been driving housing. 420 00:22:18,400 --> 00:22:21,600 Speaker 1: That driving the recent numbers up, and we know that's 421 00:22:21,640 --> 00:22:25,040 Speaker 1: a slow moving component, right. So even if they even 422 00:22:25,080 --> 00:22:28,600 Speaker 1: if they jacked up rates focus style, you know, overnight, 423 00:22:28,880 --> 00:22:31,560 Speaker 1: it's gonna take time for that to flow through. The 424 00:22:31,640 --> 00:22:34,560 Speaker 1: other thing is that, uh, you know, a lot of 425 00:22:34,640 --> 00:22:38,600 Speaker 1: research shows that these increases really take time to impact 426 00:22:38,600 --> 00:22:41,600 Speaker 1: the market. So, you know, we're still, you know, we're 427 00:22:41,600 --> 00:22:45,000 Speaker 1: still raising right now while the first increase is really 428 00:22:45,040 --> 00:22:47,959 Speaker 1: filtering its way through. Something might happen very quickly in 429 00:22:48,000 --> 00:22:50,280 Speaker 1: the in the financial markets, but in terms of like 430 00:22:50,280 --> 00:22:53,880 Speaker 1: how these impact of consumer it takes a long time. So, 431 00:22:54,200 --> 00:22:55,879 Speaker 1: you know, that's part of the reason I think it's 432 00:22:55,880 --> 00:23:00,480 Speaker 1: gonna I mean, I personally think inflation may have peaked. So, however, 433 00:23:00,680 --> 00:23:02,680 Speaker 1: I don't think it's gonna we're not. WE'RE NOT gonna 434 00:23:02,760 --> 00:23:05,520 Speaker 1: Kinda go back down to two percent overnight. I think 435 00:23:05,520 --> 00:23:07,240 Speaker 1: it's gonna be. I think it's gonna Mut be a 436 00:23:07,320 --> 00:23:12,639 Speaker 1: multi year UM multi year trend. I think, you know, 437 00:23:12,760 --> 00:23:15,200 Speaker 1: it is gonna be. As long as you are raising rates, 438 00:23:15,400 --> 00:23:17,879 Speaker 1: you know, and tightening financial conditions, it is going to 439 00:23:17,960 --> 00:23:22,520 Speaker 1: be challenging for Equity Markets and likely mixing about markets. Right. Uh, 440 00:23:22,560 --> 00:23:24,439 Speaker 1: you know, George, you you said something there too that 441 00:23:24,480 --> 00:23:27,679 Speaker 1: I find fascinating. You say it's such a unique environment, 442 00:23:27,840 --> 00:23:29,720 Speaker 1: and I wonder as a as a quant, you know, 443 00:23:29,800 --> 00:23:34,840 Speaker 1: you're so used to dealing with historical data sets, Um Um, 444 00:23:34,880 --> 00:23:37,119 Speaker 1: and when you think of this environment we're on like 445 00:23:37,160 --> 00:23:40,200 Speaker 1: the closest comparison, obviously, like you said, is the eighties. 446 00:23:40,240 --> 00:23:45,200 Speaker 1: That that really high inflation and the Paul vocal fed 447 00:23:45,320 --> 00:23:49,040 Speaker 1: really trying to fight it with with both fists Um. 448 00:23:49,119 --> 00:23:51,479 Speaker 1: But when you go back, you know, when you're running 449 00:23:52,280 --> 00:23:55,440 Speaker 1: regressions and stuff and looking at at your available data, 450 00:23:55,480 --> 00:23:57,919 Speaker 1: when you get to the nineties even and the eighties, 451 00:23:57,960 --> 00:24:01,440 Speaker 1: you know you're so limited in the amount of data 452 00:24:01,600 --> 00:24:04,840 Speaker 1: you're able to sift through. Does that does that make 453 00:24:04,840 --> 00:24:07,679 Speaker 1: it harder for a quant or is it, you know, 454 00:24:07,760 --> 00:24:10,359 Speaker 1: just a matter of like you know, for example, with 455 00:24:10,440 --> 00:24:13,560 Speaker 1: trend following? Well, you don't really care what the fundamental, 456 00:24:13,720 --> 00:24:15,919 Speaker 1: fundamental data was so much back then. If if the 457 00:24:15,960 --> 00:24:18,639 Speaker 1: trends doing this, we're gonna follow it. But you know 458 00:24:18,680 --> 00:24:22,920 Speaker 1: what's what's it like for a quant dealing with unprecedented times, 459 00:24:23,000 --> 00:24:25,800 Speaker 1: or at least times that are unprecedented? Is as far 460 00:24:25,840 --> 00:24:30,000 Speaker 1: as the robust sets of data go. So one of 461 00:24:30,000 --> 00:24:31,960 Speaker 1: the most rewarding parts of my job is getting to 462 00:24:32,000 --> 00:24:35,000 Speaker 1: mentor young people in the field that you know, young 463 00:24:35,040 --> 00:24:38,119 Speaker 1: portfolio managers and researchers on the quant side, and the 464 00:24:38,119 --> 00:24:41,239 Speaker 1: thing I always tell them is, you know, remember you 465 00:24:41,280 --> 00:24:45,119 Speaker 1: are an investor first and a quant second. So you 466 00:24:45,160 --> 00:24:49,200 Speaker 1: know you cannot blindly follow the data. You cannot Um. 467 00:24:49,240 --> 00:24:51,720 Speaker 1: I mean it cannot just because of the historical relationship. 468 00:24:51,800 --> 00:24:53,520 Speaker 1: You can't say we're going to use that. You have 469 00:24:53,600 --> 00:24:58,359 Speaker 1: to think and understand what drove that and is there relevance? 470 00:24:58,680 --> 00:25:00,399 Speaker 1: You know, one of the interesting thing things is when 471 00:25:00,400 --> 00:25:02,760 Speaker 1: you're in the world of academia you want to build 472 00:25:02,760 --> 00:25:07,080 Speaker 1: a model to predict something new. You know, you design 473 00:25:07,119 --> 00:25:08,600 Speaker 1: find a model and say, well, it can I make 474 00:25:08,600 --> 00:25:10,320 Speaker 1: a prediction about some part of the world that no 475 00:25:10,320 --> 00:25:13,280 Speaker 1: one's ever seen and and test whether the models right 476 00:25:13,359 --> 00:25:16,760 Speaker 1: or not. From an investment perspective, I don't want my 477 00:25:16,960 --> 00:25:20,480 Speaker 1: model to have to be encountering new scenarios that have 478 00:25:20,560 --> 00:25:22,720 Speaker 1: never been tested. I want to make sure I've got 479 00:25:22,720 --> 00:25:25,720 Speaker 1: some relevant data. And you're right, it is very challenging 480 00:25:25,800 --> 00:25:28,639 Speaker 1: the further back we go to be able to to 481 00:25:28,720 --> 00:25:31,520 Speaker 1: be able to Um, to use data and say hey, 482 00:25:31,560 --> 00:25:34,560 Speaker 1: I've got I've covered every possible scenario and that's really 483 00:25:34,560 --> 00:25:39,119 Speaker 1: where you have to rely on traditional fundamental investment insights 484 00:25:39,119 --> 00:25:41,560 Speaker 1: and you have to pair those two. Now that's a 485 00:25:41,600 --> 00:25:44,480 Speaker 1: lot less relevant if you're running a high frequency strategy 486 00:25:44,520 --> 00:25:47,080 Speaker 1: that holds stocks like you know, or a fraction of 487 00:25:47,080 --> 00:25:50,160 Speaker 1: a day or a nanosecond. You know, you can you there. 488 00:25:50,200 --> 00:25:52,359 Speaker 1: You could be purely model driven, but if you're thinking 489 00:25:52,520 --> 00:25:55,400 Speaker 1: longer term, you do. You really need to make sure 490 00:25:55,480 --> 00:25:59,280 Speaker 1: that your your model is calibrated but also has been 491 00:25:59,320 --> 00:26:02,160 Speaker 1: exposed to different types of regimes that that you might 492 00:26:02,200 --> 00:26:05,560 Speaker 1: be in. And I don't know if you and your 493 00:26:05,560 --> 00:26:08,240 Speaker 1: team put together projections in terms of what to expect 494 00:26:08,280 --> 00:26:11,480 Speaker 1: from the Fed, for instance, for the remainder of this year. 495 00:26:11,560 --> 00:26:13,479 Speaker 1: Does it look like we're going to get another seventy 496 00:26:13,480 --> 00:26:16,919 Speaker 1: five basis point hike in November and a fifty basis 497 00:26:16,960 --> 00:26:19,760 Speaker 1: point hike in December? What are what are you expecting? 498 00:26:20,720 --> 00:26:23,480 Speaker 1: So so we do? We do monitor kind of how 499 00:26:23,520 --> 00:26:28,440 Speaker 1: futures are pricing the scenario, the different UH projected rate hikes. 500 00:26:28,520 --> 00:26:31,880 Speaker 1: You know, personally, I think you know, there's there's an 501 00:26:31,960 --> 00:26:34,600 Speaker 1: element of this which is mathematical, which is what is 502 00:26:34,600 --> 00:26:36,600 Speaker 1: the rate that they need to obtain. I think there's 503 00:26:36,640 --> 00:26:39,200 Speaker 1: also a psychological aspect to let people know that they're 504 00:26:39,240 --> 00:26:42,280 Speaker 1: very serious. Um. So, you know, we were. We do 505 00:26:42,520 --> 00:26:45,600 Speaker 1: think that they're going to continue the pace of hikes 506 00:26:45,640 --> 00:26:49,000 Speaker 1: really until they see inflation start to materially roll over. 507 00:26:49,359 --> 00:26:51,680 Speaker 1: It looks like some areas have begun to slow but 508 00:26:51,960 --> 00:26:55,200 Speaker 1: it's still it's just it's to the risk for them 509 00:26:55,320 --> 00:26:58,639 Speaker 1: is that they become viewed it as less credible and 510 00:26:58,680 --> 00:27:00,439 Speaker 1: I think that they're going to do what need to do. 511 00:27:00,560 --> 00:27:03,480 Speaker 1: So yeah, I mean, you know, while this isn't particularly 512 00:27:03,480 --> 00:27:05,359 Speaker 1: a how it spew are you know, my personal view 513 00:27:05,480 --> 00:27:08,320 Speaker 1: is I wouldn't be surprised to see another material rate 514 00:27:08,680 --> 00:27:10,800 Speaker 1: just to kind of cement in the fact that they're 515 00:27:10,840 --> 00:27:14,080 Speaker 1: so serious about gaming inflation, which, look, I think is 516 00:27:14,119 --> 00:27:31,040 Speaker 1: good for everyone in the long term. At George, what 517 00:27:31,119 --> 00:27:33,280 Speaker 1: they're gonna and I'm wondering if you've thought about this 518 00:27:33,400 --> 00:27:35,480 Speaker 1: or studied it at all, but one of the big 519 00:27:35,520 --> 00:27:40,760 Speaker 1: themes this year, uh and really recent years, has been 520 00:27:41,520 --> 00:27:44,439 Speaker 1: the options market. Inequities seems to be sort of the 521 00:27:44,440 --> 00:27:47,119 Speaker 1: tail that's wagging the dog sometimes. You know, you have 522 00:27:47,880 --> 00:27:51,159 Speaker 1: options expirations in the middle of the month and all 523 00:27:51,160 --> 00:27:53,960 Speaker 1: of a sudden there's volatility either to the upside or 524 00:27:54,000 --> 00:27:57,480 Speaker 1: the downside. That seems to be uh, completely related to, 525 00:27:58,000 --> 00:28:01,000 Speaker 1: you know, the options gammaging and that sort of thing. 526 00:28:01,160 --> 00:28:03,280 Speaker 1: Have you looked into that at all? And and and is, 527 00:28:03,480 --> 00:28:07,680 Speaker 1: you know, not selling Jerry Seinfeld, but what's the deal 528 00:28:07,720 --> 00:28:12,480 Speaker 1: with that? You know, it's it's amazing and it really 529 00:28:12,520 --> 00:28:15,679 Speaker 1: seemed to kind of pick up after, you know, after 530 00:28:15,720 --> 00:28:18,840 Speaker 1: the lockdown, Um, that all of a sudden there's just 531 00:28:18,880 --> 00:28:22,960 Speaker 1: a huge amount of interest in options and meme stocks. 532 00:28:23,000 --> 00:28:25,879 Speaker 1: And Yeah, we have seen that. There are situations where, 533 00:28:26,280 --> 00:28:27,919 Speaker 1: you know, the tailor is wagging the dog and some 534 00:28:28,240 --> 00:28:32,720 Speaker 1: and some names and that option activity has just exploded. Um, 535 00:28:32,760 --> 00:28:35,719 Speaker 1: you know, personally, I use the best indicator I use 536 00:28:35,880 --> 00:28:38,840 Speaker 1: is what my, you know, teenage kids friends are asking me. 537 00:28:39,240 --> 00:28:41,320 Speaker 1: and Um, you know, a few years ago it was 538 00:28:41,360 --> 00:28:44,200 Speaker 1: crypto and then now they're all interested in options. You know, 539 00:28:44,240 --> 00:28:46,120 Speaker 1: they don't want trade stocks, they want to trade bonds. 540 00:28:46,120 --> 00:28:49,680 Speaker 1: They're going right to options right Um, and it's like, okay, 541 00:28:49,680 --> 00:28:53,880 Speaker 1: there's limited downside. I lose the premium, but there's no 542 00:28:53,960 --> 00:28:56,320 Speaker 1: question that like all of a sudden, you know, the 543 00:28:57,240 --> 00:29:00,840 Speaker 1: retail interest has just, you know, sky rocketing. Options I 544 00:29:00,880 --> 00:29:03,120 Speaker 1: think it's. I think it's coming down a little bit now, 545 00:29:03,640 --> 00:29:06,440 Speaker 1: but it's just, you know, there's this you know, it's 546 00:29:06,480 --> 00:29:09,520 Speaker 1: the it's the greater fuel theory. Right, I'm I'm I'm 547 00:29:09,520 --> 00:29:12,040 Speaker 1: buying something because I just expect to sell it in 548 00:29:12,080 --> 00:29:14,240 Speaker 1: a few days at a higher price. But there's no 549 00:29:14,320 --> 00:29:17,160 Speaker 1: particular you know, it's I'm just doing that because markets 550 00:29:17,160 --> 00:29:20,720 Speaker 1: are going up and you know, you know that's great 551 00:29:20,760 --> 00:29:22,520 Speaker 1: as long as it works, but as soon as it 552 00:29:22,600 --> 00:29:25,360 Speaker 1: stops working, all the people that have been drawn into 553 00:29:25,360 --> 00:29:28,400 Speaker 1: that change their view. Yeah, is it's sort of a 554 00:29:28,400 --> 00:29:31,920 Speaker 1: dead end street to try to try to uh, find 555 00:29:31,960 --> 00:29:34,360 Speaker 1: patterns there and trade off of them. You know, to 556 00:29:34,440 --> 00:29:36,400 Speaker 1: the fundamental sort of went out in the long run. 557 00:29:37,000 --> 00:29:39,880 Speaker 1: Um Metal. Look, fundamentals went out in the long run, 558 00:29:39,960 --> 00:29:42,320 Speaker 1: but there's no question that there's hurting right. There's no 559 00:29:42,440 --> 00:29:45,160 Speaker 1: question that when you know, some of these trends become 560 00:29:45,240 --> 00:29:48,000 Speaker 1: established in certain names, they're going to start. They're they're 561 00:29:48,000 --> 00:29:50,600 Speaker 1: gonna get there. It's not gonna play out overnight. They 562 00:29:50,640 --> 00:29:53,960 Speaker 1: can it can go on from like weeks to months. Um. 563 00:29:54,080 --> 00:29:56,440 Speaker 1: Our view is that we tend to focus on longer 564 00:29:56,560 --> 00:29:59,400 Speaker 1: term trends and we try to stay away we don't 565 00:29:59,400 --> 00:30:01,320 Speaker 1: want to be, you know, we don't want to be 566 00:30:01,400 --> 00:30:03,840 Speaker 1: the you know, the snail in front of the steam roller. 567 00:30:04,000 --> 00:30:06,480 Speaker 1: So like if we see, you know, a huge wave 568 00:30:06,560 --> 00:30:09,000 Speaker 1: of retail interest coming a lot of time, we just 569 00:30:09,040 --> 00:30:11,280 Speaker 1: want to we want to be patient and avoid that 570 00:30:11,680 --> 00:30:13,600 Speaker 1: and let that lay out a little bit, because then 571 00:30:13,600 --> 00:30:15,880 Speaker 1: we think there's a better opportunity for the types of 572 00:30:16,000 --> 00:30:18,880 Speaker 1: information that we process, which tends to be a little 573 00:30:18,880 --> 00:30:22,959 Speaker 1: bit more longer horizon in terms of our holdings. And George, 574 00:30:22,960 --> 00:30:25,400 Speaker 1: we talked about Tina and Tia, but I'm wondering what 575 00:30:25,520 --> 00:30:27,960 Speaker 1: you would recommend to somebody who would like to be 576 00:30:28,000 --> 00:30:32,600 Speaker 1: sitting in cash right now. Uh, you know, in all honesty, 577 00:30:32,680 --> 00:30:36,840 Speaker 1: cash is not a bad place right now. Um, you know, obviously, uh, 578 00:30:36,880 --> 00:30:40,440 Speaker 1: it's costing you something in terms of inflation. Um, you know, 579 00:30:40,520 --> 00:30:44,840 Speaker 1: there are some us uh I bonds that that give 580 00:30:44,880 --> 00:30:47,400 Speaker 1: you some reasonable inflation protection, but there's a lot of 581 00:30:48,000 --> 00:30:50,720 Speaker 1: there's limits on how much you can buy of those. Um, 582 00:30:50,880 --> 00:30:52,680 Speaker 1: cash is not a bad place to be in the 583 00:30:52,720 --> 00:30:55,600 Speaker 1: short term, I mean inflation. It hurts you over long 584 00:30:55,640 --> 00:30:58,880 Speaker 1: periods of time. It's less relevant over short periods of time. 585 00:30:58,960 --> 00:31:04,520 Speaker 1: But Um, okay, I've got a decent allocation to cash because, Um, 586 00:31:04,520 --> 00:31:08,240 Speaker 1: you know, it's it's part of the providing downside protection. Well, 587 00:31:08,280 --> 00:31:13,320 Speaker 1: George's fascinating stuff there. It's great to get your perspective. Um, 588 00:31:13,440 --> 00:31:15,680 Speaker 1: we won't let you leave, though, until we get to 589 00:31:16,320 --> 00:31:19,280 Speaker 1: our little gimmick tradition here on the show, which is 590 00:31:19,320 --> 00:31:23,280 Speaker 1: the craziest things we've seen in markets this week. UH, 591 00:31:23,400 --> 00:31:26,920 Speaker 1: Bill Donna, you know you started off on this podcast 592 00:31:27,000 --> 00:31:29,080 Speaker 1: before you were a co host. Remember, your title was 593 00:31:29,160 --> 00:31:34,160 Speaker 1: chief crazy things correspondent. Yeah, it was really good stuff. 594 00:31:34,400 --> 00:31:36,320 Speaker 1: I think we're gonna have to replace you with this guy, 595 00:31:36,640 --> 00:31:41,640 Speaker 1: twiggy Sunday, from twitter. I assume that's assumed. That's his 596 00:31:41,680 --> 00:31:44,360 Speaker 1: real name, real name? Definitely? Yeah, that definitely his real name. 597 00:31:44,400 --> 00:31:46,640 Speaker 1: He's hit me with a bunch of crazy things this week, 598 00:31:46,720 --> 00:31:49,560 Speaker 1: so I'm gonna I'm relying solely on him for mine. 599 00:31:49,600 --> 00:31:51,680 Speaker 1: But let's start with you. And what's The craziest thing 600 00:31:51,920 --> 00:31:54,480 Speaker 1: you've seen in markets? This one probably a lot of 601 00:31:54,480 --> 00:31:56,440 Speaker 1: people already know about. So if you spend any time 602 00:31:56,480 --> 00:32:00,240 Speaker 1: on twitter, you probably saw this story. But the beyond meat, 603 00:32:01,200 --> 00:32:06,160 Speaker 1: the CEO, sorry, their chief operating office beyond, Do you 604 00:32:06,200 --> 00:32:09,480 Speaker 1: know this story? Wait, that wasn't like beyond meat, him, Iberico, 605 00:32:09,600 --> 00:32:12,680 Speaker 1: him that you brought me. Was it you got? You 606 00:32:12,800 --> 00:32:16,480 Speaker 1: got real hamp but beyond meat suspended its chief operating 607 00:32:16,520 --> 00:32:21,800 Speaker 1: officer after he bit a man's nose. Why you didn't 608 00:32:21,840 --> 00:32:24,960 Speaker 1: hear of this? I did, but I thought I dreamed it. 609 00:32:25,000 --> 00:32:27,840 Speaker 1: That really happened. No, this really happened. It's just so ironic. 610 00:32:27,920 --> 00:32:32,680 Speaker 1: It's a it's a non Meat Company. He bit somebody's nose, 611 00:32:33,720 --> 00:32:37,120 Speaker 1: someone in the nose. Yep, he's been suspended and it's 612 00:32:37,160 --> 00:32:41,120 Speaker 1: just I mean, I love thinking about like these meat alternatives, 613 00:32:41,160 --> 00:32:44,240 Speaker 1: as you know, but shares of beyond meat, I checked before, 614 00:32:44,240 --> 00:32:48,000 Speaker 1: the podcasts are down seventies this year and I think 615 00:32:48,040 --> 00:32:52,160 Speaker 1: partly it's because those alternatives are much more expensive, like 616 00:32:52,240 --> 00:32:56,160 Speaker 1: buying for fake meat patties is much more expensive than 617 00:32:56,360 --> 00:32:59,640 Speaker 1: buying buying for hamburger patties. So and having a guy 618 00:32:59,680 --> 00:33:01,960 Speaker 1: go to I'm biting people in the nose, one would 619 00:33:02,000 --> 00:33:03,960 Speaker 1: assume I'm no quad George, but I would assume that's 620 00:33:03,960 --> 00:33:08,520 Speaker 1: not good for a stock person in general. That's pretty good. Well, 621 00:33:08,600 --> 00:33:11,760 Speaker 1: how's the nose? How's The continently? So this was in 622 00:33:11,800 --> 00:33:15,640 Speaker 1: the stories. Apparently he literally actually bit off a piece 623 00:33:15,680 --> 00:33:19,640 Speaker 1: of the nose. Come on, there was some at least 624 00:33:19,720 --> 00:33:23,320 Speaker 1: some damage. Oh my gosh, that is that is truly 625 00:33:23,320 --> 00:33:25,480 Speaker 1: a crazy thing. How about you, George? You see anything 626 00:33:25,520 --> 00:33:29,440 Speaker 1: crazy in markets recently? You know they's been all of 627 00:33:29,480 --> 00:33:32,920 Speaker 1: these Um, you know, depreciating assets, with cars and boats 628 00:33:32,920 --> 00:33:35,239 Speaker 1: in particular, there's a period of time that you know 629 00:33:35,960 --> 00:33:38,440 Speaker 1: there was such a short demand, short supply, that you 630 00:33:38,440 --> 00:33:41,000 Speaker 1: know you could take an old bunker that you know 631 00:33:41,320 --> 00:33:43,600 Speaker 1: it was probably worth nothing and sell it more than 632 00:33:43,600 --> 00:33:46,200 Speaker 1: you paid for it, even adjusting for inflation. So you 633 00:33:46,240 --> 00:33:49,400 Speaker 1: know there were we had a few old cars around and, Um, 634 00:33:49,440 --> 00:33:52,000 Speaker 1: you know, during this time I sold one or two 635 00:33:52,040 --> 00:33:55,160 Speaker 1: of them in a matter of days. That amazing. Um. Yeah, 636 00:33:55,320 --> 00:33:59,320 Speaker 1: so maybe it's probably not the situation now, but I've 637 00:33:59,320 --> 00:34:01,320 Speaker 1: heard it's the same ingod boats. You know that there's 638 00:34:01,360 --> 00:34:04,760 Speaker 1: such short supply of boats and demand has held up 639 00:34:04,880 --> 00:34:06,960 Speaker 1: very well that people have been able to sell boats, 640 00:34:07,000 --> 00:34:11,360 Speaker 1: which the ultimates appreciating asset, for for a profit. I know, 641 00:34:11,480 --> 00:34:13,200 Speaker 1: I was gonna say what's what's the old joke that 642 00:34:13,360 --> 00:34:15,560 Speaker 1: the happiest days of a voter's life is the day 643 00:34:15,600 --> 00:34:17,359 Speaker 1: they buy the boat, that the day they sell it? 644 00:34:17,560 --> 00:34:21,920 Speaker 1: I guess. Well, here's twiggies tweets to me, which offer 645 00:34:22,000 --> 00:34:25,160 Speaker 1: us a great opportunity to play our little game. Show 646 00:34:25,200 --> 00:34:32,239 Speaker 1: the prices precise here. Okay, Vildana, the most followed influencer 647 00:34:32,440 --> 00:34:38,719 Speaker 1: on Tiktok is a guy named Kabi Lane him me, 648 00:34:38,800 --> 00:34:41,439 Speaker 1: neither I. Uh. My kids make fun of me because 649 00:34:41,440 --> 00:34:43,560 Speaker 1: I watched the reels on instagram and they say those 650 00:34:43,560 --> 00:34:46,360 Speaker 1: are all just Tiktok's that are like three, three weeks old. 651 00:34:46,800 --> 00:34:50,640 Speaker 1: So that's where I'm at on the TIKTOK. Yeah, yeah, 652 00:34:50,840 --> 00:34:52,439 Speaker 1: so I'll probably get to this guy in a few, 653 00:34:52,600 --> 00:34:56,160 Speaker 1: few weeks. He'll be a hundred and forty nine, almost 654 00:34:56,160 --> 00:34:59,200 Speaker 1: a hundred and fifty million tiktok followers for this guy. 655 00:35:00,040 --> 00:35:04,920 Speaker 1: So he gets some sponsored posts to put something on Tiktok. 656 00:35:05,040 --> 00:35:10,200 Speaker 1: So try to think what the highest payment he's gotten 657 00:35:10,239 --> 00:35:13,640 Speaker 1: for a single post. Okay, so that's on one side. 658 00:35:13,680 --> 00:35:17,920 Speaker 1: On the other side, twiggy sent me the golf bag 659 00:35:18,400 --> 00:35:19,800 Speaker 1: and that's sorry. By the way, it was courtesy of 660 00:35:19,840 --> 00:35:22,719 Speaker 1: Fortune magazine. They have an interesting profile on this guy 661 00:35:22,760 --> 00:35:25,400 Speaker 1: from tiktok. The other ones from Golf Digest. It was 662 00:35:25,440 --> 00:35:29,080 Speaker 1: the bag that tiger used, his golf bag in the 663 00:35:29,120 --> 00:35:32,640 Speaker 1: two thousand and five season, which was a good season 664 00:35:32,640 --> 00:35:35,600 Speaker 1: for him. I think he won the British open and 665 00:35:35,640 --> 00:35:38,880 Speaker 1: he won the masters. He was aged nine. So the 666 00:35:38,960 --> 00:35:41,640 Speaker 1: question is, and George, I hate to inform you, but 667 00:35:41,680 --> 00:35:46,040 Speaker 1: you're now contestant on the prices precise as well. And 668 00:35:46,080 --> 00:35:48,040 Speaker 1: I ask you both. which do you think it was 669 00:35:48,080 --> 00:35:51,640 Speaker 1: more valuable? One Post from this guy on Tiktok were 670 00:35:51,960 --> 00:35:55,879 Speaker 1: tiger woods, two thousand and five golf bag, and give 671 00:35:55,920 --> 00:35:58,880 Speaker 1: me a number that you associate with the higher one. Well, 672 00:35:58,920 --> 00:36:01,560 Speaker 1: I think the Kardashians something like two hundred or two 673 00:36:01,600 --> 00:36:05,960 Speaker 1: hundred fifty thousand pro post sometimes, I think. So I'M 674 00:36:06,000 --> 00:36:09,680 Speaker 1: gonna go with one fifty for for the guy and 675 00:36:09,760 --> 00:36:12,880 Speaker 1: that the bag is worth more. Now remember this is 676 00:36:13,080 --> 00:36:15,160 Speaker 1: this is the most he's ever been paid for a post. 677 00:36:15,160 --> 00:36:19,200 Speaker 1: So that the top tick of this guy's influence your career. 678 00:36:19,239 --> 00:36:22,520 Speaker 1: You'RE gonna go with not. Not, not like his average. Yeah, 679 00:36:22,520 --> 00:36:28,040 Speaker 1: we don't know his mean. Okay, I think that you're 680 00:36:28,080 --> 00:36:30,839 Speaker 1: telling me that it's more than that. I'll go. I'll 681 00:36:30,840 --> 00:36:35,680 Speaker 1: go with you think the bag is worth so then 682 00:36:35,719 --> 00:36:38,319 Speaker 1: the then that makes a bag worth less, I think. 683 00:36:38,520 --> 00:36:40,600 Speaker 1: Do you think the bags worth less, George? What do 684 00:36:40,600 --> 00:36:42,920 Speaker 1: you think what's what's more valuable? One Post from this 685 00:36:43,000 --> 00:36:46,160 Speaker 1: guy or Tiger's two thousand and five golf bag? You 686 00:36:46,200 --> 00:36:47,879 Speaker 1: know there there's a lot, there's a lot of people 687 00:36:47,880 --> 00:36:50,280 Speaker 1: that are obsessed with golf. When you get you get 688 00:36:50,280 --> 00:36:54,600 Speaker 1: that there's only one bag from tiger right from that year. 689 00:36:54,840 --> 00:36:59,280 Speaker 1: So I'm going with that. Is more expensive, more expensive items. 690 00:36:59,800 --> 00:37:01,600 Speaker 1: I would have gone with the golf bag as well, 691 00:37:02,400 --> 00:37:05,680 Speaker 1: especially you never know, maybe there's some some free teas 692 00:37:05,760 --> 00:37:10,080 Speaker 1: and balls in there somewhere, little tiny pencils. But this guy. 693 00:37:10,320 --> 00:37:13,920 Speaker 1: Top payment for this guy's Tiktok was seven D and 694 00:37:13,960 --> 00:37:17,640 Speaker 1: fifty thousand dollars for one post, for one single post, 695 00:37:17,880 --> 00:37:21,600 Speaker 1: so more than the Kardashians. Yeah, I don't get it. 696 00:37:22,000 --> 00:37:28,760 Speaker 1: That's like a mansion. Um. Tiger's bag thousand, which seems 697 00:37:28,760 --> 00:37:30,120 Speaker 1: s low to me. George, I don't know. I would 698 00:37:30,160 --> 00:37:32,120 Speaker 1: have thought real assets right. I would have thought the 699 00:37:32,160 --> 00:37:35,720 Speaker 1: real asset would have won. But, George, such a treat 700 00:37:35,760 --> 00:37:37,799 Speaker 1: to catch up with you and hear your insights. We 701 00:37:37,800 --> 00:37:40,680 Speaker 1: we really appreciate it, uh and we hope somebody will 702 00:37:40,719 --> 00:37:43,319 Speaker 1: come back and do it again. Look for George on 703 00:37:43,360 --> 00:37:45,799 Speaker 1: Tiktok and we're on Youtube now, by the way, the 704 00:37:45,840 --> 00:37:48,680 Speaker 1: podcast is now on Youtube, so look for us there 705 00:37:48,680 --> 00:37:51,200 Speaker 1: if you uh can't find us on all the other places. 706 00:37:51,200 --> 00:37:55,120 Speaker 1: I've also the track of everywhere. There's a lot of places. Yeah, yeah, 707 00:37:55,200 --> 00:37:57,760 Speaker 1: but if you tube's your thing, maybe some people prefer Youtube. 708 00:37:57,760 --> 00:38:08,920 Speaker 1: I don't know already. Thanks George. Thank George. What goes up. 709 00:38:08,960 --> 00:38:10,839 Speaker 1: We'll be back next week, and so then you can 710 00:38:10,840 --> 00:38:13,719 Speaker 1: find us on the Bloomberg terminal website and APP or 711 00:38:13,760 --> 00:38:16,560 Speaker 1: wherever you get your podcasts. We love it if you 712 00:38:16,600 --> 00:38:18,600 Speaker 1: took the time to rate and review the show on 713 00:38:18,680 --> 00:38:21,920 Speaker 1: apple podcasts so more listeners can find us. And you 714 00:38:21,960 --> 00:38:25,560 Speaker 1: can find us on twitter. Follow me at Reag anonymous bill. 715 00:38:25,600 --> 00:38:29,080 Speaker 1: Donna Hirich is at Bildonna Hirich. You can also follow 716 00:38:29,120 --> 00:38:33,719 Speaker 1: Bloomberg podcasts at podcasts. What goes up is produced by 717 00:38:33,760 --> 00:38:36,440 Speaker 1: Stacy Wang. Thanks for listening. See you next time.