1 00:00:00,160 --> 00:00:02,320 Speaker 1: But knowledge to work and grow your business with c 2 00:00:02,520 --> 00:00:06,680 Speaker 1: i T. From transportation to healthcare to manufacturing. C i 3 00:00:06,760 --> 00:00:10,520 Speaker 1: T offers commercial lending, leasing, and treasury management services for 4 00:00:10,600 --> 00:00:13,480 Speaker 1: small and middle market businesses. Learn more at c i 5 00:00:13,560 --> 00:00:27,200 Speaker 1: T dot com put Knowledge to Work. Hello and welcome 6 00:00:27,240 --> 00:00:30,880 Speaker 1: to another episode of the Odd Lots podcast. I'm Joe 7 00:00:30,920 --> 00:00:34,400 Speaker 1: Wisental and I'm Tracy Halloway. So, Tracy, I don't think 8 00:00:34,400 --> 00:00:38,280 Speaker 1: I've ever asked you this, but do you like the Beatles? Uh? 9 00:00:38,800 --> 00:00:43,040 Speaker 1: I feel like there's only one way to answer that question, right, 10 00:00:43,200 --> 00:00:45,320 Speaker 1: Like you would be worried if someone said that they 11 00:00:45,360 --> 00:00:49,600 Speaker 1: didn't like the Beatles. I have met people who say 12 00:00:49,640 --> 00:00:52,560 Speaker 1: they think the Beatles are bad, but every single one 13 00:00:52,560 --> 00:00:55,320 Speaker 1: of them is one is either a troll or a 14 00:00:55,360 --> 00:00:57,760 Speaker 1: mindless contrarian. And I don't like those kind of people. 15 00:00:58,480 --> 00:01:01,160 Speaker 1: What do you think about the Beatles? I actually think 16 00:01:01,160 --> 00:01:04,080 Speaker 1: the Beatles are underrated, and it's sort of I have this. 17 00:01:04,360 --> 00:01:06,600 Speaker 1: I have this belief that the best things in life, 18 00:01:06,840 --> 00:01:10,039 Speaker 1: like in any category, are always underrated, Like I think 19 00:01:10,080 --> 00:01:14,440 Speaker 1: Michael Jordan and Muhammad Ali are underrated, for example. But 20 00:01:14,600 --> 00:01:17,000 Speaker 1: that's the way that that that we could That's a 21 00:01:17,080 --> 00:01:20,840 Speaker 1: topic for probably another episode. But the topic for this 22 00:01:20,920 --> 00:01:25,480 Speaker 1: episode is, um, the Beatles or music in general or 23 00:01:25,640 --> 00:01:27,640 Speaker 1: you know, what are we going to be discussing it 24 00:01:27,920 --> 00:01:31,920 Speaker 1: kind of is the Beatles? Did you know that you 25 00:01:31,959 --> 00:01:34,720 Speaker 1: know if you look at the history of the stock market, 26 00:01:35,200 --> 00:01:38,240 Speaker 1: that certain peaks and troughs in the market actually line 27 00:01:38,280 --> 00:01:41,479 Speaker 1: up with Beatles songs. Uh? You know, I have at 28 00:01:41,520 --> 00:01:45,000 Speaker 1: one time or another scene that chart, and I've always 29 00:01:45,040 --> 00:01:48,320 Speaker 1: been very intrigued by it. But of course, I guess 30 00:01:48,360 --> 00:01:49,880 Speaker 1: when you see a chart like that, the thing that 31 00:01:49,920 --> 00:01:55,200 Speaker 1: springs to mind is correlation versus causation, right, right, yes, exactly. 32 00:01:55,240 --> 00:01:57,840 Speaker 1: But you know, there are people who think that we 33 00:01:57,880 --> 00:02:01,080 Speaker 1: can look at things like what kind of songs are 34 00:02:01,120 --> 00:02:04,520 Speaker 1: popular at any given time, or what kind of fashions 35 00:02:04,640 --> 00:02:07,200 Speaker 1: or what kind of other cultural things are going on, 36 00:02:07,880 --> 00:02:11,480 Speaker 1: and then use that to tell us something about societal mood, 37 00:02:11,960 --> 00:02:15,280 Speaker 1: and then use that information to make calls on the market. 38 00:02:15,760 --> 00:02:18,079 Speaker 1: I mean that sounds really fascinating to me, and I 39 00:02:18,639 --> 00:02:21,800 Speaker 1: can see how you could use pop culture to gauge 40 00:02:21,840 --> 00:02:25,680 Speaker 1: maybe optimism and the strength of the economy. But again, 41 00:02:25,680 --> 00:02:28,200 Speaker 1: like I suppose, the big issue is whether or not 42 00:02:28,400 --> 00:02:31,080 Speaker 1: you get into a chicken and egg situation, right like, 43 00:02:31,240 --> 00:02:34,440 Speaker 1: is the mood following on from the economy or is 44 00:02:34,480 --> 00:02:39,840 Speaker 1: the economy driving the mood. It's fascinating. I mean the 45 00:02:39,919 --> 00:02:44,040 Speaker 1: third possibility is that there's no connection at all and 46 00:02:44,160 --> 00:02:47,360 Speaker 1: people are just drawing random lines on charge. But anyway, 47 00:02:47,400 --> 00:02:51,959 Speaker 1: I'm still intrigued. And there's this guy, Robert Prector, who 48 00:02:52,000 --> 00:02:57,040 Speaker 1: founded something called the Socioomics Institute that examines this in depth, 49 00:02:57,120 --> 00:03:02,760 Speaker 1: this connection between cultural mood day and UH and the market. 50 00:03:03,040 --> 00:03:07,160 Speaker 1: And we are going to be talking to someone who 51 00:03:07,160 --> 00:03:11,360 Speaker 1: works at the Sociogonomics Institute to really dive into these 52 00:03:11,360 --> 00:03:15,119 Speaker 1: connections UH. And we're gonna listen to some Beatles songs, right, 53 00:03:15,400 --> 00:03:17,760 Speaker 1: and that's really what we're doing here. We're gonna listen 54 00:03:17,760 --> 00:03:20,160 Speaker 1: to some Beatles songs and talk about some charts. So 55 00:03:20,200 --> 00:03:34,480 Speaker 1: it should sort of a dream episode. I'm excited. Matt Lampard, 56 00:03:34,480 --> 00:03:36,600 Speaker 1: thank you very much for joining us today. That's a 57 00:03:36,640 --> 00:03:40,480 Speaker 1: pleasure to be here. So Matt, first of all, just 58 00:03:40,520 --> 00:03:44,720 Speaker 1: tell us what is the Sociogomics Institute, what do you do, 59 00:03:45,400 --> 00:03:49,440 Speaker 1: who founded it, and what do you study At the institute. 60 00:03:49,480 --> 00:03:53,680 Speaker 1: We study the relationship between social mood and social events. 61 00:03:54,280 --> 00:03:57,520 Speaker 1: When we tend to think about mood and events. The 62 00:03:57,720 --> 00:04:00,800 Speaker 1: common perception out there is that events shape our mood. 63 00:04:01,000 --> 00:04:04,520 Speaker 1: So we'll read things in the newspaper, like a new 64 00:04:04,600 --> 00:04:07,800 Speaker 1: jobs report came out and that made consumers more optimistic, 65 00:04:07,960 --> 00:04:11,480 Speaker 1: or a politician gives a rousing, encouraging address and perhaps 66 00:04:11,520 --> 00:04:15,560 Speaker 1: that will lift investor confidence. What we do in sociomics 67 00:04:15,720 --> 00:04:18,880 Speaker 1: is we look at that relationship the other way around. 68 00:04:19,080 --> 00:04:22,039 Speaker 1: So instead of starting with the events, we start with 69 00:04:22,040 --> 00:04:24,960 Speaker 1: the mood and we look at how social mood shapes 70 00:04:25,120 --> 00:04:28,840 Speaker 1: the tenor and character of social events, because those events 71 00:04:28,960 --> 00:04:31,600 Speaker 1: have to come from somewhere, and they come from people, 72 00:04:32,160 --> 00:04:34,800 Speaker 1: people who have feelings. So we find that if you 73 00:04:34,839 --> 00:04:36,520 Speaker 1: look at how people are feeling, then you've got a 74 00:04:36,600 --> 00:04:41,680 Speaker 1: leg up on anticipating their actions. And this whole perspective 75 00:04:42,040 --> 00:04:46,200 Speaker 1: came about through a market analyst named Robert Prector. He 76 00:04:46,480 --> 00:04:48,839 Speaker 1: was a Wall Street guy, worked at Meryl Lynch for 77 00:04:48,880 --> 00:04:52,840 Speaker 1: many years as a technical market analyst, and he was successful, 78 00:04:52,880 --> 00:04:56,960 Speaker 1: and he he decided he would start his own firm, 79 00:04:57,080 --> 00:05:01,560 Speaker 1: and the emphasis of the firm started being fairly market focused. 80 00:05:01,560 --> 00:05:04,159 Speaker 1: But as he went on in his career, he realized 81 00:05:04,200 --> 00:05:06,960 Speaker 1: there were all these interesting connections between what was going 82 00:05:07,000 --> 00:05:09,080 Speaker 1: on in the stock market, and what was going on 83 00:05:09,240 --> 00:05:14,640 Speaker 1: in popular culture with music, movies, politics, all sorts of stuff. 84 00:05:15,160 --> 00:05:18,840 Speaker 1: And he started to cultivate a theory that linked those 85 00:05:18,839 --> 00:05:21,039 Speaker 1: two things together. And his proposal was that was a 86 00:05:21,120 --> 00:05:24,800 Speaker 1: common social psychology, a common social mood that was driving 87 00:05:25,920 --> 00:05:29,000 Speaker 1: activity in all of these different domains. So when investors 88 00:05:29,000 --> 00:05:31,960 Speaker 1: were feeling more optimistic, they were inclined a bit of 89 00:05:32,160 --> 00:05:35,200 Speaker 1: stock prices, But when voters were inclined to feel optimistic, 90 00:05:35,200 --> 00:05:38,240 Speaker 1: they were inclined to reelect incumbents. And when teenagers were 91 00:05:38,240 --> 00:05:41,040 Speaker 1: feeling optimistic, they listened to happy, upbeat pop music, and 92 00:05:41,080 --> 00:05:44,479 Speaker 1: then the opposite when that mood turned negative. So, Matt 93 00:05:44,600 --> 00:05:48,400 Speaker 1: tell us, how do you actually go about gauging um 94 00:05:48,480 --> 00:05:51,320 Speaker 1: the public mood? You mentioned pop culture there, but I 95 00:05:51,320 --> 00:05:55,960 Speaker 1: imagine there's some wiggle room for interpretation, right, we look 96 00:05:56,000 --> 00:05:59,159 Speaker 1: at all sorts of indicators. Prector argues that the stock 97 00:05:59,200 --> 00:06:01,839 Speaker 1: market is really the best indicator of social mood because 98 00:06:01,839 --> 00:06:05,440 Speaker 1: not only is it the area where people can express 99 00:06:05,480 --> 00:06:08,440 Speaker 1: their levels of optimism and pessimism, but they can do 100 00:06:08,480 --> 00:06:10,919 Speaker 1: it quite quickly. It just takes a few moments to 101 00:06:11,080 --> 00:06:13,320 Speaker 1: trade a stock, a few clicks of amounts, or a 102 00:06:13,320 --> 00:06:16,200 Speaker 1: call to a broker, and we've got stock data going 103 00:06:16,240 --> 00:06:18,760 Speaker 1: back hundreds of years, so we can back test the 104 00:06:18,760 --> 00:06:21,040 Speaker 1: theory and we can also track mood in real time. 105 00:06:21,320 --> 00:06:23,839 Speaker 1: But we definitely look at a number of other indicators 106 00:06:23,839 --> 00:06:26,880 Speaker 1: as well. There's survey data out there on consumer confidence, 107 00:06:26,920 --> 00:06:31,159 Speaker 1: economic confidence. We look at, as you've mentioned, pop culture indicators, 108 00:06:31,160 --> 00:06:33,880 Speaker 1: what music is popular, what movies are popular. But we 109 00:06:33,960 --> 00:06:36,720 Speaker 1: really find that the stock market is the best indicator 110 00:06:36,720 --> 00:06:40,200 Speaker 1: of mood, and we use some of these other indicators 111 00:06:40,240 --> 00:06:43,200 Speaker 1: to confirm or deny the message of the stock market 112 00:06:43,240 --> 00:06:47,840 Speaker 1: seems to be giving us. Now, in the intro, we 113 00:06:47,960 --> 00:06:52,679 Speaker 1: mentioned the Beatles, and there's this chart that I've seen 114 00:06:52,839 --> 00:06:56,720 Speaker 1: floating around the Internet for a long time titled Major 115 00:06:56,839 --> 00:07:00,920 Speaker 1: Events in the Beatles Career Tracks Social Mood, and it's 116 00:07:00,920 --> 00:07:04,040 Speaker 1: a chart from of the DOWD Jones from nineteen fifty 117 00:07:04,160 --> 00:07:09,400 Speaker 1: six to nineteen seventy and at various times in uh 118 00:07:09,600 --> 00:07:13,840 Speaker 1: these fourteen years, it's annotated with key events in the 119 00:07:13,920 --> 00:07:17,720 Speaker 1: history of the Beatles. So, for example, there's a market 120 00:07:18,160 --> 00:07:22,280 Speaker 1: market peak right around when Rubber Soul came out. It 121 00:07:22,400 --> 00:07:26,600 Speaker 1: spent six weeks at number one. What's the connection there? 122 00:07:26,600 --> 00:07:29,240 Speaker 1: So then the market immediately dropped. So let's let's put 123 00:07:29,280 --> 00:07:32,720 Speaker 1: this social mood theory into practice. Tell us something about 124 00:07:32,800 --> 00:07:35,840 Speaker 1: what was on rubber soul, and then tell us what 125 00:07:35,880 --> 00:07:38,800 Speaker 1: it how it might have indicated a top in the market. 126 00:07:39,800 --> 00:07:42,080 Speaker 1: The study that you're talking about is one that Robert 127 00:07:42,120 --> 00:07:45,160 Speaker 1: Pructor did. It was a case study of the Beatles 128 00:07:45,160 --> 00:07:48,760 Speaker 1: where he tracked their career and found it they were 129 00:07:48,800 --> 00:07:52,400 Speaker 1: a group that that aligned quite well with the with 130 00:07:52,480 --> 00:07:55,960 Speaker 1: the trends in the market. And if you look at 131 00:07:55,960 --> 00:07:58,680 Speaker 1: their history, look at the Beatlemania period basically goes from 132 00:07:58,720 --> 00:08:01,400 Speaker 1: nineteen sixty two to ninete in sixties six, This is 133 00:08:01,920 --> 00:08:05,360 Speaker 1: when they were performing in front of stadiums with screaming fans. 134 00:08:05,400 --> 00:08:08,800 Speaker 1: The whole Beatlemania phenomenon was going on. And what happened, 135 00:08:08,800 --> 00:08:12,280 Speaker 1: Like you said, in nineteen sixty six, this phenomenon tops out. 136 00:08:12,320 --> 00:08:15,600 Speaker 1: It's the top of the market right around the same time. 137 00:08:15,960 --> 00:08:18,880 Speaker 1: And practice argument is that what's happening here is that 138 00:08:19,520 --> 00:08:22,360 Speaker 1: social mood is becoming incredibly optimistic here in the mid 139 00:08:22,440 --> 00:08:26,480 Speaker 1: sixties and investors are expressing that optimism by bidding stock 140 00:08:26,520 --> 00:08:30,280 Speaker 1: market prices stock prices higher and higher, and teenagers are 141 00:08:30,280 --> 00:08:32,720 Speaker 1: expressing it by going out and screaming and buying Beatles 142 00:08:32,760 --> 00:08:36,560 Speaker 1: records and singing along and this sort of thing. And 143 00:08:36,840 --> 00:08:39,960 Speaker 1: after that top in the market in nineteen sixties six, 144 00:08:40,320 --> 00:08:43,120 Speaker 1: what we see is a change in social mood, a 145 00:08:43,280 --> 00:08:46,360 Speaker 1: change in the psychology, and with that change in psychology 146 00:08:46,640 --> 00:08:50,839 Speaker 1: came a change in behavior. So the Beatles decide that 147 00:08:50,880 --> 00:08:54,720 Speaker 1: they're going to stop live touring. They're gonna stay active 148 00:08:54,760 --> 00:08:57,480 Speaker 1: in the studio, but they retire from doing the live shows. 149 00:08:57,520 --> 00:09:01,040 Speaker 1: There's internal tumult within the group. There was even death threats, 150 00:09:01,080 --> 00:09:04,080 Speaker 1: this sort of thing. The market eventually rallies, they get 151 00:09:04,080 --> 00:09:07,000 Speaker 1: more active in the studio. They decide that they're gonna 152 00:09:07,040 --> 00:09:09,960 Speaker 1: record and put out another album. But the bear market 153 00:09:10,000 --> 00:09:13,720 Speaker 1: was already in play here. And in April of nineteen seventies, 154 00:09:13,720 --> 00:09:16,720 Speaker 1: that bear market really started to unfold. Paul announced that 155 00:09:16,760 --> 00:09:19,160 Speaker 1: he was leaving the group, and then the band released 156 00:09:19,160 --> 00:09:22,320 Speaker 1: their last studio album early the following month, within days 157 00:09:22,320 --> 00:09:24,320 Speaker 1: of the Kent State shooting. It's also the month of 158 00:09:24,360 --> 00:09:26,280 Speaker 1: a of a low in the market. So we see 159 00:09:26,360 --> 00:09:30,280 Speaker 1: this change in psychology showing up throughout the social experience. 160 00:09:30,320 --> 00:09:31,880 Speaker 1: That's showing up in the market, it showing up in 161 00:09:31,880 --> 00:09:34,680 Speaker 1: the music, and it's showing up in the character of 162 00:09:35,240 --> 00:09:38,680 Speaker 1: political and social events as well. But here's what I 163 00:09:38,720 --> 00:09:41,680 Speaker 1: don't get about the specific example. So if you say 164 00:09:41,679 --> 00:09:44,520 Speaker 1: that the peak of Beatlemania coincided with the top of 165 00:09:44,520 --> 00:09:47,679 Speaker 1: the stock market stock market and a lot of teenagers 166 00:09:47,679 --> 00:09:50,319 Speaker 1: were really excited about this new rock group and they 167 00:09:50,320 --> 00:09:52,520 Speaker 1: were singing along, I mean there were a lot of 168 00:09:52,559 --> 00:09:56,360 Speaker 1: people around who didn't like the Beatles and who saw 169 00:09:56,360 --> 00:09:59,520 Speaker 1: it as like a sign of the deterioration of the 170 00:09:59,600 --> 00:10:03,560 Speaker 1: old world order um that they were familiar with. So 171 00:10:03,600 --> 00:10:06,120 Speaker 1: how do you kind of I mean, how do you gauge, 172 00:10:06,160 --> 00:10:09,880 Speaker 1: like who likes what and which is more important for 173 00:10:09,960 --> 00:10:14,000 Speaker 1: overall mood. We really look at what's popular. The Beatles 174 00:10:14,000 --> 00:10:17,200 Speaker 1: are one of the most popular music acts in the 175 00:10:17,240 --> 00:10:19,640 Speaker 1: history of the planet. And sure, of course there's always 176 00:10:19,640 --> 00:10:22,240 Speaker 1: a mix, right there are people who who like certain 177 00:10:22,280 --> 00:10:24,560 Speaker 1: things and people who don't like other things. But they're 178 00:10:24,559 --> 00:10:28,679 Speaker 1: definitely a certainly a very very popular group. But it's 179 00:10:28,720 --> 00:10:31,040 Speaker 1: important to keep in mind too that of course there's 180 00:10:31,080 --> 00:10:36,040 Speaker 1: a mix of opinions, beliefs, actions, uh feelings in society 181 00:10:36,080 --> 00:10:38,480 Speaker 1: at all times. Social moods always in flux, and within 182 00:10:38,520 --> 00:10:40,800 Speaker 1: that flux, there's always a mix going on. But the 183 00:10:41,240 --> 00:10:43,600 Speaker 1: question we look at. What we look at is what's 184 00:10:43,640 --> 00:10:50,640 Speaker 1: the quantity and intensity of positive expressions relative to negative expressions. 185 00:10:50,640 --> 00:10:54,600 Speaker 1: So things are never uniformly positive, they're never uniformly negative. 186 00:10:54,600 --> 00:10:57,680 Speaker 1: There's always a mix, but sometimes the balance is shifted 187 00:10:57,720 --> 00:11:00,360 Speaker 1: far more towards the positive side or far more towards 188 00:11:00,360 --> 00:11:03,319 Speaker 1: the negative side. And that's really where you can get 189 00:11:03,320 --> 00:11:05,520 Speaker 1: a better idea of what's going on in the mood 190 00:11:05,600 --> 00:11:08,560 Speaker 1: trend continuing on the Beatles, and then we could sort 191 00:11:08,559 --> 00:11:11,439 Speaker 1: of move off it. I noticed in the late sixties 192 00:11:11,559 --> 00:11:14,480 Speaker 1: that the White Album was released, That's one of my 193 00:11:14,640 --> 00:11:18,360 Speaker 1: favorite albums, and that sort of that was a key 194 00:11:18,440 --> 00:11:21,760 Speaker 1: peak in the market well, and there was also a 195 00:11:21,880 --> 00:11:24,440 Speaker 1: change in the tone of the music around the around 196 00:11:24,480 --> 00:11:28,440 Speaker 1: this time as well. They started becoming more introspective, the 197 00:11:28,480 --> 00:11:32,520 Speaker 1: songwriting became more complex, And one of practice observations is 198 00:11:32,559 --> 00:11:36,679 Speaker 1: that in negative mood periods, one of the manifestations that 199 00:11:36,720 --> 00:11:39,160 Speaker 1: we see, at least in the music world is uh, 200 00:11:39,320 --> 00:11:42,880 Speaker 1: not only a harder edged sound to it, but also 201 00:11:43,720 --> 00:11:47,640 Speaker 1: more sophisticated lyrics, more sophisticated songwriting. And as the Beatles 202 00:11:47,960 --> 00:11:50,760 Speaker 1: grew war on, is there a song that you think 203 00:11:51,040 --> 00:11:54,439 Speaker 1: from that period that really sort of captures this new 204 00:11:54,640 --> 00:12:00,079 Speaker 1: style of introspective, slightly darker songwriting of the Beatles. It 205 00:12:00,480 --> 00:12:03,280 Speaker 1: one could listen to that would have foreshadowed the coming 206 00:12:03,320 --> 00:12:05,959 Speaker 1: sell off in the market appears right after that the 207 00:12:06,040 --> 00:12:09,440 Speaker 1: dow was it around one thousand fell as uh got 208 00:12:09,440 --> 00:12:12,680 Speaker 1: around six hundred, so fairly significant sell off in the 209 00:12:12,760 --> 00:12:15,360 Speaker 1: TAO over the next couple of years. Is there a 210 00:12:15,440 --> 00:12:18,160 Speaker 1: song or something that sort of you think really encapsulates 211 00:12:18,160 --> 00:12:21,440 Speaker 1: this mood change. Well, there's definitely a change in the 212 00:12:21,520 --> 00:12:23,040 Speaker 1: in the tone of the music. For example, if you 213 00:12:23,080 --> 00:12:26,560 Speaker 1: look at the Beatles early stuff, it's energetic, they're singing 214 00:12:26,559 --> 00:12:34,679 Speaker 1: you know, she loves you, Yeah, yeah, yeah, and then 215 00:12:34,720 --> 00:12:37,040 Speaker 1: by the end they're singing, Hey Jude, and it's you know, 216 00:12:37,080 --> 00:12:43,199 Speaker 1: it's it's slower, it's dorker, Hey, don't make it bad. 217 00:12:46,520 --> 00:12:48,840 Speaker 1: But really, what we're doing here is what we're trying 218 00:12:48,880 --> 00:12:51,760 Speaker 1: to look at, is this change in psychology that's going on. 219 00:12:51,840 --> 00:12:54,440 Speaker 1: And we're not necessarily using the Beatles as a cell 220 00:12:54,520 --> 00:12:56,920 Speaker 1: signal or a by signal or something like that. We're 221 00:12:56,920 --> 00:12:59,560 Speaker 1: really just trying to say this psychology is showing up 222 00:12:59,600 --> 00:13:02,839 Speaker 1: and a lot of different areas of social expression in music. 223 00:13:03,200 --> 00:13:05,520 Speaker 1: Music is one of those. And now let's take a 224 00:13:05,559 --> 00:13:08,320 Speaker 1: break for a word from our sponsor. But first we 225 00:13:08,360 --> 00:13:10,160 Speaker 1: want to take a moment to let you know about 226 00:13:10,160 --> 00:13:13,680 Speaker 1: something new from Bloomberg. It's really cool. 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We were just talking about the Beatles 249 00:14:36,360 --> 00:14:39,800 Speaker 1: and whether or not you can sort of trace social 250 00:14:39,880 --> 00:14:42,440 Speaker 1: mood through the ups and downs of the Beatles career 251 00:14:42,760 --> 00:14:47,480 Speaker 1: and whether that has an impact on wider markets. Uh So, Matt, 252 00:14:47,920 --> 00:14:52,000 Speaker 1: I wanted to fast forward about forty years. Let's go 253 00:14:52,800 --> 00:14:55,360 Speaker 1: straight to now. When you look at the social mood 254 00:14:55,560 --> 00:14:58,880 Speaker 1: at the moment, what do you see and what particular 255 00:14:59,200 --> 00:15:01,880 Speaker 1: things are you looking at to gauge it? Right? So 256 00:15:02,040 --> 00:15:04,840 Speaker 1: mood right now? Is is is that a really interesting juncture. 257 00:15:04,920 --> 00:15:08,120 Speaker 1: So we've got in the US, you've got the markets 258 00:15:08,200 --> 00:15:11,720 Speaker 1: near all time highs. There's been all sorts of things 259 00:15:11,720 --> 00:15:14,160 Speaker 1: written about how how calm the markets are and how 260 00:15:14,240 --> 00:15:16,280 Speaker 1: voll I mean, we've heard this one a million times 261 00:15:16,320 --> 00:15:19,520 Speaker 1: over the past a month or so. Uh So, you've 262 00:15:19,520 --> 00:15:23,000 Speaker 1: got this this complacency that's going on at least in 263 00:15:23,040 --> 00:15:24,960 Speaker 1: the US. But if you turn around and you look 264 00:15:25,040 --> 00:15:27,360 Speaker 1: elsewhere in the globe, let's say you go over to Europe, 265 00:15:27,360 --> 00:15:30,240 Speaker 1: what you see is a pretty different picture. The Eurostocks 266 00:15:30,240 --> 00:15:33,360 Speaker 1: fifty index topped in two thousand and on that basis, 267 00:15:33,440 --> 00:15:36,520 Speaker 1: the eurostocks has been in a bear market ever since. Now, 268 00:15:36,600 --> 00:15:39,440 Speaker 1: some national indexes have rallied to new all time highs, 269 00:15:39,640 --> 00:15:42,920 Speaker 1: or if not, have rallied strongly within that trend of late. 270 00:15:43,240 --> 00:15:45,120 Speaker 1: But you look at the tenor of character and actions 271 00:15:45,120 --> 00:15:48,440 Speaker 1: in Europe and they're so different. You've got all kinds 272 00:15:48,440 --> 00:15:52,120 Speaker 1: of political fracturing going on within the EU, You've got 273 00:15:52,200 --> 00:15:54,440 Speaker 1: breakdowns in tension. I mean, this was supposed to be 274 00:15:54,600 --> 00:15:57,280 Speaker 1: a glorious alliance of all these countries that have fought 275 00:15:57,560 --> 00:15:59,480 Speaker 1: for thousands of years with each other, and now that 276 00:15:59,560 --> 00:16:01,760 Speaker 1: they tried get together in form a a union, well, 277 00:16:01,800 --> 00:16:06,080 Speaker 1: that's a manifestation in itself of of of a large 278 00:16:06,080 --> 00:16:09,200 Speaker 1: degree positive mood trend. And as that moods turned negative, 279 00:16:09,200 --> 00:16:13,160 Speaker 1: we've seen the social manifestations of that turn negative as well. 280 00:16:13,640 --> 00:16:15,600 Speaker 1: And we've gotten a flavor of that in the US. 281 00:16:15,680 --> 00:16:19,640 Speaker 1: Certainly there's there's all kinds of polarization to it, but certainly, uh, 282 00:16:19,720 --> 00:16:22,120 Speaker 1: not quite at the level of Europe just yet. When 283 00:16:22,120 --> 00:16:25,440 Speaker 1: you look at cultural things in the US, is there 284 00:16:25,480 --> 00:16:31,040 Speaker 1: anything equivalent that you're tracking, uh sort of musically film 285 00:16:31,160 --> 00:16:35,640 Speaker 1: stuff artistically that sort of might give you a sense 286 00:16:35,880 --> 00:16:38,840 Speaker 1: of where the mood is in the US. Are signs 287 00:16:38,880 --> 00:16:40,760 Speaker 1: that it may be turning in one direction or another. 288 00:16:41,480 --> 00:16:43,960 Speaker 1: One of the things that practice looked at in the 289 00:16:44,000 --> 00:16:48,600 Speaker 1: movie space in particular is is trends and Disney movies 290 00:16:48,720 --> 00:16:52,920 Speaker 1: versus trends and horror movies. So the heyday of Disney 291 00:16:52,960 --> 00:16:56,240 Speaker 1: in the mid nineteen sixties, uh, where they released some 292 00:16:56,280 --> 00:16:58,880 Speaker 1: of their classic films, and of course it's started with 293 00:16:59,200 --> 00:17:02,000 Speaker 1: White Well, but were then uh, you know this is 294 00:17:02,040 --> 00:17:04,680 Speaker 1: this is a great positive mood stuff, upbeat, family fair. 295 00:17:04,960 --> 00:17:07,879 Speaker 1: There's a Disney renaissance in the late eighties and the 296 00:17:07,960 --> 00:17:10,840 Speaker 1: nineties where again they just had hit after hit after hit, 297 00:17:11,560 --> 00:17:15,200 Speaker 1: and then that got interrupted. In the early two thousands, 298 00:17:15,280 --> 00:17:18,600 Speaker 1: horror movies came back in vogue. You had the saw films, 299 00:17:18,720 --> 00:17:21,520 Speaker 1: the torture movies, and these films were a call back 300 00:17:21,600 --> 00:17:23,480 Speaker 1: to films that were popular in the bear market of 301 00:17:23,520 --> 00:17:27,240 Speaker 1: the sixties and seventies, the Texas Chainsaw Massacre, and then 302 00:17:27,280 --> 00:17:31,600 Speaker 1: just just genuinely scary films like The Exorcist, which themselves 303 00:17:31,680 --> 00:17:34,119 Speaker 1: were called backs to films that are popular in in 304 00:17:34,160 --> 00:17:38,639 Speaker 1: the early nineteen thirties during the depression. Dracula, Frankenstein, this 305 00:17:38,720 --> 00:17:44,159 Speaker 1: sort of thing. So right now, we we've seen another 306 00:17:44,280 --> 00:17:47,800 Speaker 1: hit from Disney. They had frozen fairly recently in the 307 00:17:47,840 --> 00:17:50,440 Speaker 1: past few years. But then, but then, of course, the 308 00:17:50,960 --> 00:17:53,040 Speaker 1: Beauty and the Beast remake was a huge hit. They 309 00:17:53,040 --> 00:17:54,879 Speaker 1: had a Cinderella remake, there was a huge hit. The 310 00:17:54,960 --> 00:17:57,840 Speaker 1: Jungle Book remake was a huge hit. So those movies 311 00:17:57,840 --> 00:17:59,960 Speaker 1: are still popular, and we think that the social mood 312 00:18:00,000 --> 00:18:01,439 Speaker 1: has a lot to do with that. But if you're 313 00:18:01,440 --> 00:18:04,119 Speaker 1: a horror movie fan, just hold your breath. It's okay. 314 00:18:04,520 --> 00:18:07,240 Speaker 1: When mood turns negative. There should be some more groundbreaking 315 00:18:07,240 --> 00:18:09,960 Speaker 1: horror stuff on the way for you. I mean you 316 00:18:09,960 --> 00:18:13,960 Speaker 1: you're mentioning Disney movies. Um, the comeback of Disney right now. 317 00:18:14,480 --> 00:18:18,040 Speaker 1: You mentioned earlier that the stock market was probably the 318 00:18:18,080 --> 00:18:21,040 Speaker 1: best expression of current mood. So if you look at 319 00:18:21,080 --> 00:18:24,520 Speaker 1: the US market, which seems to be reaching new highs 320 00:18:24,760 --> 00:18:29,160 Speaker 1: um every week, now, how do you square that with 321 00:18:29,200 --> 00:18:32,360 Speaker 1: what's been going on in politics? Because when we look 322 00:18:32,359 --> 00:18:35,240 Speaker 1: at the US elections, UM and a lot of the 323 00:18:35,280 --> 00:18:39,159 Speaker 1: sort of populist political issues happening right now, it seems 324 00:18:39,160 --> 00:18:40,840 Speaker 1: like there is a lot of anger out there, and 325 00:18:40,920 --> 00:18:43,520 Speaker 1: there is a lot of uncertainty. There's definitely a lot 326 00:18:43,560 --> 00:18:46,320 Speaker 1: of political polarization going on in the US. And in fact, 327 00:18:46,359 --> 00:18:49,240 Speaker 1: my colleague here at the Institute, Robert Fulsome, did a 328 00:18:49,280 --> 00:18:52,639 Speaker 1: study called y Trump Why Now. It came out in 329 00:18:53,400 --> 00:18:57,600 Speaker 1: March of during the primaries, and one of the interesting 330 00:18:57,640 --> 00:19:01,359 Speaker 1: things about the primaries is that the candidates on the 331 00:19:01,359 --> 00:19:04,520 Speaker 1: Republican side, at least initially didn't take Trump very seriously. 332 00:19:04,640 --> 00:19:07,639 Speaker 1: Jeb Bush spent all kinds of money attacking the other 333 00:19:08,240 --> 00:19:10,920 Speaker 1: challengers and basically figured here this Trump guile peter out 334 00:19:10,920 --> 00:19:15,560 Speaker 1: on his own. But Robert looked at the market and 335 00:19:15,800 --> 00:19:19,040 Speaker 1: reached a different conclusion. Now, what we like to do 336 00:19:19,160 --> 00:19:20,679 Speaker 1: with the market is we like to look at at 337 00:19:20,680 --> 00:19:23,000 Speaker 1: a nominal terms. We also like to look at it 338 00:19:23,119 --> 00:19:25,399 Speaker 1: in real money terms. And if you look at the 339 00:19:25,400 --> 00:19:27,679 Speaker 1: market in real terms, that you find is that the 340 00:19:27,720 --> 00:19:31,560 Speaker 1: all time high in the US was and we've been 341 00:19:31,600 --> 00:19:34,720 Speaker 1: in a large degree bear market ever since. Now since 342 00:19:35,520 --> 00:19:38,520 Speaker 1: index has been rallying, we think it's a bear market rally. 343 00:19:38,600 --> 00:19:40,240 Speaker 1: But once you start to see, okay, well, we've got 344 00:19:40,240 --> 00:19:42,439 Speaker 1: nominal markets at all time high as you've got the 345 00:19:42,480 --> 00:19:44,800 Speaker 1: market in real terms, in this bear market rally, it 346 00:19:44,880 --> 00:19:46,879 Speaker 1: makes sense that you'd still see a little bit more 347 00:19:46,920 --> 00:19:49,840 Speaker 1: of a mix, and the polarization that we saw in 348 00:19:49,880 --> 00:19:53,840 Speaker 1: the in the election certainly makes sense in that context. 349 00:19:53,920 --> 00:19:56,679 Speaker 1: And we think that if we see the nominal indexes 350 00:19:56,920 --> 00:20:00,280 Speaker 1: joining the real money indexes on the downside, that's when 351 00:20:01,160 --> 00:20:06,120 Speaker 1: what seems like intense polarization now will get even more. So. Yeah, 352 00:20:06,160 --> 00:20:08,719 Speaker 1: it sort of reminds me of one of my favorite charts, 353 00:20:09,200 --> 00:20:12,080 Speaker 1: which is just the the Dow Jones divided by the 354 00:20:12,119 --> 00:20:16,000 Speaker 1: price of gold, because it's sort of to me, is 355 00:20:16,040 --> 00:20:19,440 Speaker 1: like a measure of like, you know, stocks are, there's 356 00:20:19,520 --> 00:20:23,840 Speaker 1: a sort of investment in human capital, cooperation, society progressing, 357 00:20:24,200 --> 00:20:26,919 Speaker 1: and gold is a rock or a metal or something 358 00:20:26,960 --> 00:20:29,600 Speaker 1: that has no real productive value. And what you see 359 00:20:29,720 --> 00:20:33,400 Speaker 1: is sort of as you say, in two thousand, that 360 00:20:33,560 --> 00:20:36,639 Speaker 1: ratio hit incredible heights and we're still not anywhere in 361 00:20:36,720 --> 00:20:39,480 Speaker 1: that declined as you said through two thousand eleven was 362 00:20:39,520 --> 00:20:42,600 Speaker 1: when that ratio hit it's low, and we're still not 363 00:20:42,760 --> 00:20:46,919 Speaker 1: anywhere near the old highs in terms of uh, you know, 364 00:20:47,320 --> 00:20:50,919 Speaker 1: that ratio signaling at least you know, relative to about 365 00:20:51,160 --> 00:20:53,440 Speaker 1: you know, fifteen or twenty years ago. People are still 366 00:20:53,440 --> 00:20:57,080 Speaker 1: really into rocks relative to humans. That's right. It's interesting 367 00:20:57,080 --> 00:20:59,760 Speaker 1: to look at markets priced and gold. We we like 368 00:20:59,840 --> 00:21:01,760 Speaker 1: to look at Dow Gold for sure. In my colleague 369 00:21:01,760 --> 00:21:03,640 Speaker 1: Allen Hall has just been doing some work recently where 370 00:21:03,640 --> 00:21:07,280 Speaker 1: he's looking at lots of other national stock indexes priced 371 00:21:07,800 --> 00:21:11,320 Speaker 1: in gold. And what you find when you do that 372 00:21:11,440 --> 00:21:15,399 Speaker 1: is that the rally in the U S sinceleven is 373 00:21:15,840 --> 00:21:18,159 Speaker 1: one of the longer rallies when you look at these 374 00:21:18,200 --> 00:21:22,080 Speaker 1: gold denominated indexes globally, a market like Russia has seen 375 00:21:22,200 --> 00:21:25,280 Speaker 1: its nominally in real money indexes falling in tandem since 376 00:21:25,320 --> 00:21:27,840 Speaker 1: about two thousand eight. And when you look at the 377 00:21:27,840 --> 00:21:31,320 Speaker 1: social manifestations that are going on in Russia, suddenly it 378 00:21:31,440 --> 00:21:33,399 Speaker 1: starts to make a little bit more sense. I mean, 379 00:21:33,440 --> 00:21:37,080 Speaker 1: back in two thousand seven, Russia was the darling of 380 00:21:37,080 --> 00:21:41,120 Speaker 1: of of investors. Vladimir Putin was Times Man of the Year. 381 00:21:41,240 --> 00:21:44,520 Speaker 1: They were part of this assortment of brick countries along 382 00:21:44,560 --> 00:21:47,560 Speaker 1: with Brazil, Indya and China, where there was allegedly huge 383 00:21:47,560 --> 00:21:53,240 Speaker 1: investment opportunities out there. And in that environment, Alan said, look, 384 00:21:53,240 --> 00:21:57,840 Speaker 1: there's so much optimism surrounding Russia right now. This is 385 00:21:58,000 --> 00:22:01,479 Speaker 1: very likely going to be a peak in the Russian markets, 386 00:22:01,480 --> 00:22:04,320 Speaker 1: and use the Elliot wave model to to verify that analysis, 387 00:22:04,359 --> 00:22:07,080 Speaker 1: and said, folks, we've got a major bear market coming 388 00:22:07,520 --> 00:22:10,760 Speaker 1: in Russian. When we see that that change in psychology 389 00:22:10,760 --> 00:22:13,520 Speaker 1: manifest in the market, that's when it's definitely time to 390 00:22:13,520 --> 00:22:17,640 Speaker 1: be on the lookout for a military resurgence from from 391 00:22:17,640 --> 00:22:20,359 Speaker 1: that country. And after the market declined, there was the 392 00:22:20,400 --> 00:22:24,639 Speaker 1: invasion of Ukraine and and we've seen just just this 393 00:22:24,760 --> 00:22:28,639 Speaker 1: resurgence and militarism coming coming from Russian And once you 394 00:22:28,720 --> 00:22:31,000 Speaker 1: understand the psychology over there in the context of this 395 00:22:31,520 --> 00:22:34,000 Speaker 1: long term negative mood trend, it starts to make make 396 00:22:34,040 --> 00:22:36,960 Speaker 1: a lot more sense. Matt. That kind of reminds me. 397 00:22:37,040 --> 00:22:40,600 Speaker 1: I wanted to ask how much um analysis you do 398 00:22:40,840 --> 00:22:45,000 Speaker 1: on non US, non European countries and how you actually 399 00:22:45,160 --> 00:22:48,840 Speaker 1: do that analysis, Like would you gauge social mood in 400 00:22:49,320 --> 00:22:52,600 Speaker 1: an emerging market like India or Vietnam And how does 401 00:22:52,840 --> 00:22:56,399 Speaker 1: gathering that information differ from doing it in a developed market. 402 00:22:57,240 --> 00:23:00,560 Speaker 1: Sure well, with the wave of globalization that that took 403 00:23:00,600 --> 00:23:03,040 Speaker 1: hold from the eighties and nineties and into the early 404 00:23:03,080 --> 00:23:07,399 Speaker 1: two thousand, we've got market index is just just about 405 00:23:07,440 --> 00:23:10,800 Speaker 1: all over the world, and we have analysts who cover 406 00:23:10,880 --> 00:23:13,679 Speaker 1: those markets and also look at them through a socionomic 407 00:23:13,800 --> 00:23:17,360 Speaker 1: lens to look at the cultural manifestations in those countries. 408 00:23:17,400 --> 00:23:20,199 Speaker 1: My colleague Mark Galaschowski does a lot of work in 409 00:23:20,359 --> 00:23:23,600 Speaker 1: Asia and the Middle East, looking at India, Pakistan and 410 00:23:23,640 --> 00:23:26,919 Speaker 1: then China, Japan. This sort of thing, and the method 411 00:23:27,000 --> 00:23:29,479 Speaker 1: is is similar to what we do in the U 412 00:23:29,640 --> 00:23:33,000 Speaker 1: S where you take the stock index in the local country, 413 00:23:33,160 --> 00:23:35,000 Speaker 1: use that as an indicator of mood, and then you 414 00:23:35,440 --> 00:23:37,800 Speaker 1: use it as a as a benchmark to forecast and 415 00:23:37,840 --> 00:23:42,240 Speaker 1: contextualize social events that are going on over there. Uh. 416 00:23:42,400 --> 00:23:44,720 Speaker 1: Now we have to wrap up soon. But I think 417 00:23:44,840 --> 00:23:48,080 Speaker 1: you know. The part that sort of I'm still struggling 418 00:23:48,119 --> 00:23:52,600 Speaker 1: with is you know, and I'm sure you've heard this 419 00:23:53,080 --> 00:23:56,439 Speaker 1: people questioned this before, which is that you know, you 420 00:23:56,480 --> 00:23:58,960 Speaker 1: can see a market move, you can see a move 421 00:23:59,160 --> 00:24:01,679 Speaker 1: in the stock mark it and then go back and 422 00:24:01,800 --> 00:24:05,719 Speaker 1: construct an argument for why the mood was good. So 423 00:24:05,840 --> 00:24:08,760 Speaker 1: we say, okay, uh, the stock market has been doing 424 00:24:08,840 --> 00:24:11,040 Speaker 1: really well for the last several years. And look at 425 00:24:11,080 --> 00:24:13,439 Speaker 1: Disney movies. There are a lot more Disney movies than 426 00:24:13,480 --> 00:24:15,840 Speaker 1: there were horror movies, and so this is a sign 427 00:24:15,920 --> 00:24:19,200 Speaker 1: that people are optimistic or you're saying, uh, the US 428 00:24:19,240 --> 00:24:22,200 Speaker 1: elected Trump and you're like, but we're you know, we're 429 00:24:22,240 --> 00:24:25,119 Speaker 1: still kind of in a long term bear market in 430 00:24:25,200 --> 00:24:27,760 Speaker 1: real terms, what do you say to people who say 431 00:24:27,800 --> 00:24:32,840 Speaker 1: that this kind of analysis is essentially retrospective fitting of 432 00:24:32,920 --> 00:24:36,720 Speaker 1: events to markets and that you can sort of ex 433 00:24:36,800 --> 00:24:41,560 Speaker 1: post facto come up with any uh, any mood characterization 434 00:24:41,640 --> 00:24:45,119 Speaker 1: that you'd like to get it to work. Well, I 435 00:24:45,160 --> 00:24:48,720 Speaker 1: think having some objective criteria for your analysis goes a 436 00:24:48,760 --> 00:24:51,400 Speaker 1: long way in doing that. But the other the other 437 00:24:51,480 --> 00:24:53,840 Speaker 1: thing that we do is we issue real time forecasts 438 00:24:53,880 --> 00:24:55,960 Speaker 1: all the time. We've got a monthly publication called the 439 00:24:56,000 --> 00:24:59,320 Speaker 1: Socioonomists where every month we're issuing real time forecast and 440 00:24:59,359 --> 00:25:02,600 Speaker 1: analysis of what's happening right now and looking ahead into 441 00:25:02,640 --> 00:25:04,919 Speaker 1: the future. So I think you you just do your 442 00:25:04,920 --> 00:25:06,920 Speaker 1: best to forecast in real time, and then when you 443 00:25:06,960 --> 00:25:08,399 Speaker 1: look at the past, you just try to be as 444 00:25:08,400 --> 00:25:10,960 Speaker 1: objective as you can, lay down some parameters and see 445 00:25:10,960 --> 00:25:14,879 Speaker 1: where the where the data. Thank you, Matt Lampert of 446 00:25:14,920 --> 00:25:19,760 Speaker 1: the Sociogomics Institute. Really appreciate you coming on fascinating work 447 00:25:19,840 --> 00:25:33,120 Speaker 1: that you do. Thank you so much. So, Tracy, are 448 00:25:33,160 --> 00:25:37,560 Speaker 1: you going to start scanning the weekly billboard charts and 449 00:25:37,920 --> 00:25:41,639 Speaker 1: box office receipts to gain some insight on where the 450 00:25:41,680 --> 00:25:45,040 Speaker 1: market's going. I was kind of thinking, like, if if 451 00:25:45,080 --> 00:25:47,960 Speaker 1: you think that the Beatles were a good way of 452 00:25:48,160 --> 00:25:51,200 Speaker 1: gauging social mood because they were something around which a 453 00:25:51,280 --> 00:25:55,480 Speaker 1: large proportion of people coalesced, what would be the equivalent today? 454 00:25:55,680 --> 00:25:59,199 Speaker 1: And the only thing I could think of, um was 455 00:25:59,240 --> 00:26:04,359 Speaker 1: either Taylor Swift or maybe One Direction or Beyonce. I 456 00:26:04,400 --> 00:26:08,600 Speaker 1: don't know, well I would say, yeah, I was gonna say, 457 00:26:08,640 --> 00:26:13,080 Speaker 1: Taylor Swift and Beyonce are probably the only two musicians 458 00:26:13,119 --> 00:26:19,359 Speaker 1: today that have the sort of like megapower, mega influence, 459 00:26:19,560 --> 00:26:21,479 Speaker 1: mega fan base that might be able to tell you 460 00:26:21,560 --> 00:26:25,960 Speaker 1: anything about where the market's going. So maybe that's a 461 00:26:26,000 --> 00:26:28,960 Speaker 1: good a good reason to listen to both of them 462 00:26:28,960 --> 00:26:33,280 Speaker 1: more closely and see how their songwriting styles evolved. Right, 463 00:26:33,320 --> 00:26:35,520 Speaker 1: It is interesting. I think Taylor Swift like sort of 464 00:26:35,600 --> 00:26:40,040 Speaker 1: switched from h from country to pop fairly around the 465 00:26:41,080 --> 00:26:44,400 Speaker 1: time the market rebounded, So maybe there is something there. Yeah, 466 00:26:44,440 --> 00:26:47,200 Speaker 1: but here's the thing I mean, I was kind of 467 00:26:47,359 --> 00:26:51,680 Speaker 1: talking about it with the Beatles, but like, does everyone 468 00:26:51,840 --> 00:26:55,440 Speaker 1: love Taylor swift know, like, is it a pretty big movement? 469 00:26:55,560 --> 00:26:57,879 Speaker 1: I just I just don't know how much signal you 470 00:26:57,920 --> 00:27:01,159 Speaker 1: can actually get UM from Taylor's it. No, And I 471 00:27:01,200 --> 00:27:04,400 Speaker 1: thought that was a really good question in general, that yeah, 472 00:27:04,440 --> 00:27:07,239 Speaker 1: sure the Beatles are popular, but other people probably at 473 00:27:07,240 --> 00:27:09,600 Speaker 1: the time, So it is the you know, the collapse 474 00:27:09,640 --> 00:27:12,000 Speaker 1: of Western civilization that the kids were listening to rock 475 00:27:12,040 --> 00:27:15,520 Speaker 1: and roll. So I think it's intriguing stuff. I love 476 00:27:15,600 --> 00:27:19,359 Speaker 1: looking at their charts. They fascinate me. Um, I'm not 477 00:27:19,600 --> 00:27:23,520 Speaker 1: sure I would, you know, necessarily commit my life savings 478 00:27:23,520 --> 00:27:26,920 Speaker 1: to strategies based on it. But you know, look, I 479 00:27:27,000 --> 00:27:29,520 Speaker 1: mean I consider myself an open minded person, so I 480 00:27:29,520 --> 00:27:32,360 Speaker 1: won't dismiss it entirely. Look, I think most people would 481 00:27:32,400 --> 00:27:35,280 Speaker 1: say the more data that you can get, UM, the 482 00:27:35,480 --> 00:27:39,479 Speaker 1: more informed you are as an investor. So there, I 483 00:27:39,520 --> 00:27:42,320 Speaker 1: feel like there is something there with social mood. Absolutely, 484 00:27:42,359 --> 00:27:45,520 Speaker 1: And you know, one of our previous guests on the show, UM, 485 00:27:45,520 --> 00:27:49,359 Speaker 1: Peter Atwater from Financial Insights UH is also very into it, 486 00:27:49,400 --> 00:27:52,080 Speaker 1: and he does it very well. And if you think 487 00:27:52,119 --> 00:27:55,320 Speaker 1: about the economy and the fact that a large portion 488 00:27:55,359 --> 00:27:58,920 Speaker 1: of the economy is driven by people's confidence and their 489 00:27:59,080 --> 00:28:03,360 Speaker 1: belief in their ability to invest. Then there is an 490 00:28:03,359 --> 00:28:05,960 Speaker 1: obvious link. I just find it difficult to kind of 491 00:28:06,560 --> 00:28:09,680 Speaker 1: tease it out because ultimately you're dealing with human behavior 492 00:28:09,920 --> 00:28:13,240 Speaker 1: and emotions and it can be tricky. Still, it's a 493 00:28:13,280 --> 00:28:16,120 Speaker 1: good excuse to listen to more music. Yeah, okay, let's 494 00:28:16,160 --> 00:28:19,240 Speaker 1: go do that. All right, sounds good. This has been 495 00:28:19,280 --> 00:28:22,600 Speaker 1: another episode of the Odd LODs podcast. I'm Joseph Why 496 00:28:22,640 --> 00:28:24,439 Speaker 1: Isn't There? You can follow me on Twitter at the 497 00:28:24,480 --> 00:28:28,440 Speaker 1: Stalwart and I'm Tracy Alloway. I'm on Twitter at Tracy Alloway. 498 00:28:28,440 --> 00:28:44,360 Speaker 1: Thanks for listening. Put knowledge to work and grow your 499 00:28:44,360 --> 00:28:48,920 Speaker 1: business with c i T from transportation to healthcare to manufacturing. 500 00:28:49,120 --> 00:28:52,520 Speaker 1: C i T offers commercial lending, leasing, and treasury management 501 00:28:52,560 --> 00:28:55,920 Speaker 1: services for small and middle market businesses. Learn more at 502 00:28:55,920 --> 00:28:58,400 Speaker 1: c i T dot com. Put Knowledge to Work