1
00:00:03,120 --> 00:00:12,960
Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. I'm so tired. My

2
00:00:13,039 --> 00:00:16,360
Speaker 1: body battery is twenty one out of one hundred.

3
00:00:16,840 --> 00:00:18,320
Speaker 2: Is this the thing that I should know what it is?

4
00:00:18,680 --> 00:00:20,439
Speaker 1: Well, if you have a garment, you would know what

5
00:00:20,520 --> 00:00:21,400
Speaker 1: yours is, So that.

6
00:00:21,440 --> 00:00:23,159
Speaker 2: Was a yes, I should know what it is. But

7
00:00:23,239 --> 00:00:23,640
Speaker 2: I don't.

8
00:00:23,720 --> 00:00:25,440
Speaker 1: I don't know what's going to happen when I hit

9
00:00:25,560 --> 00:00:28,960
Speaker 1: zero during this podcast, maybe all time.

10
00:00:30,160 --> 00:00:32,600
Speaker 2: Hello and welcome to The Money Stuff Podcast. You're a

11
00:00:32,640 --> 00:00:36,440
Speaker 2: weekly podcast where we talk about stuff related to money.

12
00:00:37,560 --> 00:00:39,520
Speaker 2: I'm Matt Levine and I write The Money Stuff com

13
00:00:39,560 --> 00:00:40,479
Speaker 2: for Bloomberg Opinion.

14
00:00:40,760 --> 00:00:43,159
Speaker 1: And I'm Katie Greifeld, a reporter for Bloomberg News and

15
00:00:43,200 --> 00:00:46,120
Speaker 1: an anchor for Bloomberg Television. Short week this week, can't

16
00:00:46,120 --> 00:00:50,000
Speaker 1: we short week? Short? Tough week? It's not as bad

17
00:00:50,040 --> 00:00:53,320
Speaker 1: when we're all on Fridays. I love those for Davies.

18
00:00:53,920 --> 00:00:55,800
Speaker 1: When you're off on a Monday, it just feels like

19
00:00:55,840 --> 00:00:58,560
Speaker 1: the rest of the week you're just sliding rapidly down

20
00:00:58,600 --> 00:00:59,440
Speaker 1: a mountain.

21
00:00:59,440 --> 00:01:03,040
Speaker 2: And here we have reached the bottom of the nets.

22
00:01:03,120 --> 00:01:04,120
Speaker 1: We're about to crash.

23
00:01:04,640 --> 00:01:07,039
Speaker 2: Yeah, it was what have we scraped.

24
00:01:06,680 --> 00:01:08,800
Speaker 1: Up for Jack Bogel's nightmares?

25
00:01:08,840 --> 00:01:10,959
Speaker 2: Because we have like a synergy where you read about

26
00:01:10,959 --> 00:01:12,200
Speaker 2: a thing and then I wrote about the thing you

27
00:01:12,240 --> 00:01:12,720
Speaker 2: wrote about.

28
00:01:12,920 --> 00:01:15,360
Speaker 1: Yeah. Yeah, I guess the challenge for us is finding

29
00:01:15,400 --> 00:01:17,720
Speaker 1: things to say beyond that. But we're going to tackle

30
00:01:17,760 --> 00:01:19,520
Speaker 1: that in a minute. We're also going to talk about

31
00:01:19,480 --> 00:01:23,200
Speaker 1: taxicabs and New York's all important industry, and then we're

32
00:01:23,240 --> 00:01:26,039
Speaker 1: going to talk about truth, social.

33
00:01:26,760 --> 00:01:31,520
Speaker 2: Social Left for GTF. Jack Bogel's Nightmare.

34
00:01:31,840 --> 00:01:34,840
Speaker 1: Yeah so you know Jack Bogel.

35
00:01:35,120 --> 00:01:35,960
Speaker 2: Yeah, we're buddies.

36
00:01:36,120 --> 00:01:36,360
Speaker 1: Yeah.

37
00:01:36,400 --> 00:01:37,360
Speaker 2: I actually did meet him once.

38
00:01:37,560 --> 00:01:39,240
Speaker 1: Yeah, I wish I had met him. I mean I

39
00:01:39,280 --> 00:01:42,760
Speaker 1: worked closely with Eric Belgunis from Bloomberg Intelligence, who literally

40
00:01:42,760 --> 00:01:46,560
Speaker 1: wrote the book about Bogel and Vanguard, and he sounds

41
00:01:46,600 --> 00:01:49,360
Speaker 1: like he was a real who to interview and talk

42
00:01:49,400 --> 00:01:52,040
Speaker 1: to up until the end. But he founded Vanguard. He's

43
00:01:52,160 --> 00:01:56,440
Speaker 1: the father of the index fund. He hated ETFs, which

44
00:01:56,440 --> 00:01:59,560
Speaker 1: is really funny since they're sort of the offspring of

45
00:01:59,600 --> 00:02:03,720
Speaker 1: index funds. He said that ETFs they only incentivize trading

46
00:02:03,840 --> 00:02:08,680
Speaker 1: among This is a quote fruitcakes, nutcases, and the lunatic fringe.

47
00:02:09,240 --> 00:02:13,239
Speaker 1: And it's funny that in twenty twenty four, some ETFs

48
00:02:13,240 --> 00:02:16,240
Speaker 1: are being designed to do exactly that just incentivized trading

49
00:02:16,280 --> 00:02:18,079
Speaker 1: them on that cohort of traders.

50
00:02:18,360 --> 00:02:20,640
Speaker 2: He's kind of wrong that, like an SB five hundred,

51
00:02:20,680 --> 00:02:24,160
Speaker 2: ETF is a perfectly good buy and hold product that's

52
00:02:24,160 --> 00:02:27,080
Speaker 2: actually slightly better than an index fund because it has

53
00:02:27,160 --> 00:02:29,200
Speaker 2: tax advantages if you are going to buy and hold it.

54
00:02:29,720 --> 00:02:31,560
Speaker 2: But it is also the case that you can put

55
00:02:31,560 --> 00:02:34,560
Speaker 2: lots of things into an ETF wrapper, and some of

56
00:02:34,600 --> 00:02:37,320
Speaker 2: those things are high octane gambling products.

57
00:02:37,400 --> 00:02:39,919
Speaker 1: I feel like I've ETF pilled you over the course

58
00:02:40,160 --> 00:02:42,160
Speaker 1: of this podcast, which is great. It's nice to hear

59
00:02:42,240 --> 00:02:43,639
Speaker 1: like a full throated defense.

60
00:02:44,080 --> 00:02:45,880
Speaker 2: You know. I was for a long time an investor

61
00:02:45,919 --> 00:02:48,520
Speaker 2: in Vanguard index mutual funds.

62
00:02:48,720 --> 00:02:51,359
Speaker 1: And I would imagine then I was like.

63
00:02:52,000 --> 00:02:54,480
Speaker 2: I know enough about the tax advantages of ETFs that

64
00:02:54,480 --> 00:02:57,720
Speaker 2: I'm going to start being an investor in index ETFs.

65
00:02:57,760 --> 00:02:59,480
Speaker 1: I get it, But I don't like day trade them,

66
00:02:59,520 --> 00:03:02,160
Speaker 1: you know. And I mean Jack Bogel he was a

67
00:03:02,200 --> 00:03:05,280
Speaker 1: principaled guy, so he did. He didn't like literally the

68
00:03:05,360 --> 00:03:08,320
Speaker 1: exchange traded portion, like why why do you need that?

69
00:03:08,880 --> 00:03:12,000
Speaker 1: He also famously didn't want any commodity funds or anything

70
00:03:12,040 --> 00:03:15,120
Speaker 1: like that. He was just stock spawns playing fanilla that

71
00:03:15,200 --> 00:03:18,160
Speaker 1: was his whole thing. And now you look at this

72
00:03:18,240 --> 00:03:22,560
Speaker 1: ETF market that we exist in, and the subject of

73
00:03:22,840 --> 00:03:28,280
Speaker 1: my story specifically was these leverage single stock ETFs, leveraged

74
00:03:28,320 --> 00:03:31,480
Speaker 1: and in verse one point two five all the way

75
00:03:31,560 --> 00:03:34,079
Speaker 1: up to three if you include Europe as well. Europe

76
00:03:34,080 --> 00:03:36,920
Speaker 1: has higher leverage than we do. And uh, I've been

77
00:03:36,960 --> 00:03:40,720
Speaker 1: calling them one day only funds because you're not supposed

78
00:03:40,720 --> 00:03:42,880
Speaker 1: to hold them for more than a single day, in

79
00:03:42,880 --> 00:03:45,160
Speaker 1: some cases not more than a couple hours.

80
00:03:45,720 --> 00:03:49,640
Speaker 2: Right, there's a lot there. One thing is that this

81
00:03:49,800 --> 00:03:53,040
Speaker 2: is not a fund, right, You're getting a levered three

82
00:03:53,080 --> 00:03:55,680
Speaker 2: times return on an n video or whatever. Like. It's

83
00:03:55,720 --> 00:04:01,080
Speaker 2: not in any meaningful sense an excentradmoron. It's a retail

84
00:04:01,160 --> 00:04:04,040
Speaker 2: leverage product. Right, It's a way, Yeah, you get three

85
00:04:04,080 --> 00:04:07,480
Speaker 2: times the returns of a stock without borrowing money from

86
00:04:07,480 --> 00:04:08,040
Speaker 2: your broker.

87
00:04:08,240 --> 00:04:11,520
Speaker 1: Yeah, And if you talk to the CEOs of these firms,

88
00:04:11,560 --> 00:04:14,440
Speaker 1: that's exactly what they say. I've interviewed Will Rind of

89
00:04:14,480 --> 00:04:17,680
Speaker 1: Granite Shares for this article, and that's exactly that they're

90
00:04:17,839 --> 00:04:23,520
Speaker 1: offering institutional grade leverage without the expenses of opening a

91
00:04:23,560 --> 00:04:24,800
Speaker 1: traditional margin account.

92
00:04:24,960 --> 00:04:27,160
Speaker 2: Right. I mean, they probably do get better leverage terms

93
00:04:27,320 --> 00:04:30,679
Speaker 2: than every tilvester, but it does come at the cost,

94
00:04:31,440 --> 00:04:33,360
Speaker 2: as as you and I both read about of like

95
00:04:33,760 --> 00:04:38,119
Speaker 2: they rebalance every day. Yes, so if you borrow money

96
00:04:38,120 --> 00:04:40,720
Speaker 2: to buy a stock, you decide when you want to

97
00:04:40,720 --> 00:04:42,400
Speaker 2: close out that position. I mean, unless you get a

98
00:04:42,440 --> 00:04:45,920
Speaker 2: margin call, but like you know, you decide want to

99
00:04:45,920 --> 00:04:48,760
Speaker 2: close that position. And if you take out a fifty

100
00:04:48,800 --> 00:04:50,800
Speaker 2: percent margin Lon and died, you know, twice as much

101
00:04:50,839 --> 00:04:53,120
Speaker 2: stock you have, like two times leverage, you'll get two

102
00:04:53,160 --> 00:04:55,039
Speaker 2: times the return of the stock for whatever period you

103
00:04:55,040 --> 00:04:59,479
Speaker 2: hold it for. With the leveraged ETFs, it doesn't work

104
00:04:59,520 --> 00:05:02,240
Speaker 2: that way. They rebalance every day, so you get two

105
00:05:02,320 --> 00:05:05,160
Speaker 2: times the daily returns or three times the daily returns

106
00:05:05,360 --> 00:05:09,000
Speaker 2: each day. And as you and I both read about,

107
00:05:09,640 --> 00:05:14,480
Speaker 2: that has like sort of arithmetically paradoxical results, where like

108
00:05:14,560 --> 00:05:18,080
Speaker 2: you read about there's a micro strategy. Micro strategies is

109
00:05:18,120 --> 00:05:22,280
Speaker 2: like insanely volatile sort of bitcoin proxy stock, and there's

110
00:05:22,279 --> 00:05:25,680
Speaker 2: a micro strategy three times ETF micro strategy is ut

111
00:05:25,720 --> 00:05:27,200
Speaker 2: like one hundred and ten percent this year, and that

112
00:05:27,279 --> 00:05:30,400
Speaker 2: ETF is down eighty percent, right, yeah, because three times

113
00:05:30,440 --> 00:05:32,800
Speaker 2: one hundred and ten is negative eighty which is not

114
00:05:33,320 --> 00:05:34,360
Speaker 2: normally how things.

115
00:05:34,120 --> 00:05:37,600
Speaker 1: Work and it's so interesting and you know, the math

116
00:05:37,680 --> 00:05:39,440
Speaker 1: is so much better than me. So that's that's the

117
00:05:39,480 --> 00:05:43,000
Speaker 1: micro strategy dynamic, and you're seeing that play out with

118
00:05:43,279 --> 00:05:46,640
Speaker 1: Nvidia and a lot of these single stock funds are

119
00:05:46,680 --> 00:05:49,160
Speaker 1: based on Invidia. That is the most popular stock to

120
00:05:49,240 --> 00:05:52,839
Speaker 1: launch a single stock fund on. Understandably, it's not as bad.

121
00:05:52,960 --> 00:05:55,279
Speaker 1: You're doing negative right, exactly.

122
00:05:55,240 --> 00:05:57,200
Speaker 2: Lower than three times, but it's it's not nicive.

123
00:05:57,240 --> 00:06:00,640
Speaker 1: Yeah, you're doing pretty okay up to this point. We'll see,

124
00:06:00,720 --> 00:06:03,720
Speaker 1: you know what the next few weeks hold for in video,

125
00:06:03,760 --> 00:06:05,560
Speaker 1: but you're doing pretty okay if you're in a leverage

126
00:06:05,640 --> 00:06:06,640
Speaker 1: long and video product.

127
00:06:06,800 --> 00:06:09,480
Speaker 2: Yeah. It's like the math has to do with basically,

128
00:06:09,520 --> 00:06:12,360
Speaker 2: like the comparison between the sort of returns of the

129
00:06:12,400 --> 00:06:14,800
Speaker 2: stock and the volatility of the stock. So Microshata is

130
00:06:14,839 --> 00:06:17,960
Speaker 2: incredibly volatile and is up a lot, but like in

131
00:06:18,080 --> 00:06:21,800
Speaker 2: Vidia is less volatile and is up more, so that

132
00:06:21,839 --> 00:06:24,720
Speaker 2: effect sort of swamps the volatility effect. But basically, like

133
00:06:24,960 --> 00:06:27,520
Speaker 2: the intuition is, you know, if a stock goes up

134
00:06:27,760 --> 00:06:30,800
Speaker 2: ten percent and then down ten percent, you're subtracting the

135
00:06:30,800 --> 00:06:33,640
Speaker 2: losses from a bigger number. So when it goes up

136
00:06:33,640 --> 00:06:35,560
Speaker 2: to ten percent, you have a bigger number, and then

137
00:06:35,600 --> 00:06:38,039
Speaker 2: down ten percent is like ten percent of a bigger

138
00:06:38,120 --> 00:06:40,279
Speaker 2: number than you started with, and vice versa. If it

139
00:06:40,279 --> 00:06:42,560
Speaker 2: goes down ten percent and up ten percent, you're getting

140
00:06:42,600 --> 00:06:46,039
Speaker 2: like ten percent return on a smaller number. When you

141
00:06:46,120 --> 00:06:49,640
Speaker 2: multiply things, that effect gets amplified, and so you're making

142
00:06:49,680 --> 00:06:53,400
Speaker 2: the downswings worse. Yeah, and therefore you can turn the

143
00:06:53,440 --> 00:06:57,520
Speaker 2: long term returns negative even if the unmultiplied returns are positive.

144
00:06:57,680 --> 00:07:00,920
Speaker 1: So not to toot my own horn, sure, but this

145
00:07:01,240 --> 00:07:04,919
Speaker 1: article was much more widely shared than I anticipated it

146
00:07:04,960 --> 00:07:07,440
Speaker 1: to be, partly because you wrote about it in Money Stuff,

147
00:07:07,480 --> 00:07:10,440
Speaker 1: and it feels like the probability of getting your face

148
00:07:10,480 --> 00:07:12,400
Speaker 1: ripped off is what a lot of people focused on.

149
00:07:12,520 --> 00:07:15,960
Speaker 1: But the surprising thing that I found while looking at

150
00:07:15,960 --> 00:07:20,280
Speaker 1: this was actually that these funds are being broadly used

151
00:07:20,320 --> 00:07:24,400
Speaker 1: as intended, which is interesting. There's a really rough Napkin

152
00:07:24,480 --> 00:07:28,120
Speaker 1: math way to take a look at the average daily

153
00:07:28,160 --> 00:07:31,040
Speaker 1: holding period, and again this is very rough, but basically,

154
00:07:31,120 --> 00:07:33,920
Speaker 1: if you divide the average trading volume by the average

155
00:07:33,960 --> 00:07:36,400
Speaker 1: market cap of one of these funds, you should get

156
00:07:36,440 --> 00:07:38,320
Speaker 1: a pretty rough answer there. So if you take a

157
00:07:38,360 --> 00:07:41,680
Speaker 1: look at the largest single stock ETFs, it's also from

158
00:07:41,680 --> 00:07:45,640
Speaker 1: granted shares, it's two times long. On Nvidia, it's almost

159
00:07:45,720 --> 00:07:49,240
Speaker 1: five billion dollars. It takes under three days for the

160
00:07:49,360 --> 00:07:52,920
Speaker 1: entirety of its shares to flip over, which is not bad,

161
00:07:53,000 --> 00:07:53,200
Speaker 1: you know.

162
00:07:53,400 --> 00:07:55,840
Speaker 2: Yeah, they do a good job of warning people. Yeah,

163
00:07:56,320 --> 00:07:59,520
Speaker 2: and probably if you're finding this sort of thing, you

164
00:07:59,560 --> 00:08:03,600
Speaker 2: know what you doing. But that average probably can seal

165
00:08:03,760 --> 00:08:05,680
Speaker 2: some number of people buy it and forget it and

166
00:08:05,720 --> 00:08:07,400
Speaker 2: then end up down eighty percent or whatever.

167
00:08:07,640 --> 00:08:10,480
Speaker 1: Yeah, it's inevitable that someone's having a really painful time

168
00:08:10,520 --> 00:08:11,760
Speaker 1: and maybe doesn't even know.

169
00:08:11,880 --> 00:08:16,720
Speaker 2: Most likely doesn't even right. Yeah, three times Yeah, I

170
00:08:16,760 --> 00:08:20,760
Speaker 2: think that, like they are probably mostly being used for

171
00:08:21,200 --> 00:08:24,320
Speaker 2: speculative day treading by people who know what they're doing. Yeah,

172
00:08:24,400 --> 00:08:28,520
Speaker 2: but that's Jack Buckle's nightmare, right exactly. And also, I mean,

173
00:08:28,560 --> 00:08:31,280
Speaker 2: in addition to my sharing your piece, I don't know

174
00:08:31,320 --> 00:08:33,559
Speaker 2: if you saw you were, Cliff Asma has put out

175
00:08:33,559 --> 00:08:37,079
Speaker 2: this this paper this week. Oh my god, market inefficiency.

176
00:08:37,320 --> 00:08:40,480
Speaker 1: Old man Wining is he is what he called himself.

177
00:08:40,480 --> 00:08:42,720
Speaker 2: He said something like, I'm gonna sound like a grumpy

178
00:08:42,760 --> 00:08:45,160
Speaker 2: old man because he's like sort of known as a

179
00:08:45,160 --> 00:08:48,319
Speaker 2: as a like quantitative value investor and essentially the point

180
00:08:48,360 --> 00:08:49,520
Speaker 2: of the paper is like, it's hard to be a

181
00:08:49,600 --> 00:08:53,360
Speaker 2: quant value investor these days because like value keeps underperforming,

182
00:08:53,880 --> 00:08:56,200
Speaker 2: which he argues is because the markets are inefficient. And

183
00:08:56,280 --> 00:08:59,800
Speaker 2: one reason markets are inefficient is because people are crazy,

184
00:09:00,280 --> 00:09:04,360
Speaker 2: like retail investors are like crazily chasing like speculative eyes.

185
00:09:04,800 --> 00:09:08,200
Speaker 2: And he does cite one day on the ETFs with

186
00:09:08,320 --> 00:09:11,480
Speaker 2: a little parenthetical Grayfield twenty twenty four. I loved that

187
00:09:11,559 --> 00:09:13,719
Speaker 2: footnote saying what fresh hell is this?

188
00:09:14,280 --> 00:09:18,000
Speaker 1: So he tweeted that on Friday, and like three pm

189
00:09:18,040 --> 00:09:21,200
Speaker 1: on a Friday, I am fried. You know, there's nothing left.

190
00:09:21,240 --> 00:09:25,120
Speaker 1: My body battery is negative. I saw that he tweeted that,

191
00:09:25,240 --> 00:09:27,320
Speaker 1: and I was so scared because all he said was

192
00:09:27,640 --> 00:09:29,920
Speaker 1: what fresh hell is this? With no follow up? And

193
00:09:29,960 --> 00:09:32,560
Speaker 1: I was like, is he gonna rip me? Like what's

194
00:09:32,600 --> 00:09:33,920
Speaker 1: going on? But I'm glad that he said it.

195
00:09:34,200 --> 00:09:36,480
Speaker 2: He's mad not at you, yeah, but at the thing

196
00:09:36,520 --> 00:09:37,280
Speaker 2: you read about.

197
00:09:37,120 --> 00:09:40,320
Speaker 1: Hate the game, not the player. One quick fun fact

198
00:09:40,440 --> 00:09:43,800
Speaker 1: on the average holding period, so less than three days

199
00:09:43,880 --> 00:09:47,120
Speaker 1: is really short. Eric Belchunis was telling me that remember

200
00:09:47,160 --> 00:09:51,160
Speaker 1: those vics ETFs that blew up in Valmageddon. Sure, at

201
00:09:51,160 --> 00:09:54,040
Speaker 1: one point one of the biggest ones had an average

202
00:09:54,040 --> 00:09:57,440
Speaker 1: holding period of literally less than one day. The average

203
00:09:57,440 --> 00:10:00,000
Speaker 1: holding period was less than one day, which is amaz

204
00:10:00,600 --> 00:10:02,040
Speaker 1: So people were holding it for like.

205
00:10:02,040 --> 00:10:04,199
Speaker 2: During the blow up or like weeks before the.

206
00:10:04,160 --> 00:10:08,000
Speaker 1: Book going into it when they still existed. Yeah, now

207
00:10:08,040 --> 00:10:09,640
Speaker 1: there arefs.

208
00:10:09,640 --> 00:10:13,600
Speaker 2: Again, that does suggest professional usage, right, yeah, or they're

209
00:10:13,679 --> 00:10:14,480
Speaker 2: crazy day dreading.

210
00:10:14,480 --> 00:10:14,920
Speaker 1: I don't know.

211
00:10:15,080 --> 00:10:16,800
Speaker 2: The one other thing I would have mentioned is yes,

212
00:10:17,080 --> 00:10:19,960
Speaker 2: that the day after I read about this, the trader

213
00:10:20,200 --> 00:10:23,400
Speaker 2: launched a set of products that are like week long yeah,

214
00:10:23,640 --> 00:10:24,800
Speaker 2: month law liberty.

215
00:10:24,840 --> 00:10:28,000
Speaker 1: That was such funny timing. Yes, And funny timing is

216
00:10:28,080 --> 00:10:32,079
Speaker 1: kind of what we're talking about with the dfs, so

217
00:10:32,280 --> 00:10:37,239
Speaker 1: I so they're trying to solve this problem of volatility,

218
00:10:37,280 --> 00:10:39,360
Speaker 1: drag or decay. I know you don't like those terms,

219
00:10:39,400 --> 00:10:40,960
Speaker 1: but that's what they're trying to do with these. I

220
00:10:40,960 --> 00:10:43,320
Speaker 1: actually spoke to the guy behind it. His name is

221
00:10:43,720 --> 00:10:47,679
Speaker 1: Matt Markuwick's and he said that, I know, we were

222
00:10:47,679 --> 00:10:49,760
Speaker 1: just talking about how less than three days is pretty good.

223
00:10:49,840 --> 00:10:52,719
Speaker 1: He was saying, and they have single stock daily ETFs

224
00:10:53,120 --> 00:10:55,840
Speaker 1: that it's clear people are holding these for more than

225
00:10:55,880 --> 00:10:58,959
Speaker 1: one day, which is not using them as intended. So

226
00:10:59,160 --> 00:11:02,000
Speaker 1: he's not happy with that stat So the idea behind

227
00:11:02,000 --> 00:11:04,920
Speaker 1: this with a weekly reset is that you don't have

228
00:11:05,000 --> 00:11:08,840
Speaker 1: to babysit the funds in your position as closely as

229
00:11:08,840 --> 00:11:11,199
Speaker 1: you would have to with a daily reset. But even

230
00:11:11,280 --> 00:11:14,040
Speaker 1: still it does introduce risk, like you have to show

231
00:11:14,040 --> 00:11:16,920
Speaker 1: it at I know, but you have to time when

232
00:11:16,920 --> 00:11:18,680
Speaker 1: you buy it to get the full effect.

233
00:11:18,960 --> 00:11:21,920
Speaker 2: Right. The reason the one day funds work the way

234
00:11:21,960 --> 00:11:23,920
Speaker 2: they do, even though people get mad about it, is

235
00:11:23,960 --> 00:11:28,600
Speaker 2: because they're giving you exactly the same experience every day.

236
00:11:28,600 --> 00:11:31,320
Speaker 2: They're like, you're getting the one three times daily return

237
00:11:31,800 --> 00:11:34,040
Speaker 2: no matter what day you buy it. With a weekly fund,

238
00:11:34,040 --> 00:11:36,079
Speaker 2: if you buy it on a Tuesday, you're getting slightly

239
00:11:36,120 --> 00:11:38,720
Speaker 2: different eybe more or less, you're getting a slightly different

240
00:11:38,720 --> 00:11:41,680
Speaker 2: than the advertised return. But if you then hold it

241
00:11:41,679 --> 00:11:43,720
Speaker 2: for four days, you get something closer to what you expected,

242
00:11:43,760 --> 00:11:47,319
Speaker 2: Whereas if you hold the single day ETF the daily

243
00:11:47,360 --> 00:11:50,800
Speaker 2: rebouance ETF for four days, you get something very different

244
00:11:50,960 --> 00:11:54,640
Speaker 2: than three times the four day return. Yeah, if people

245
00:11:54,679 --> 00:11:56,800
Speaker 2: hold things more than a day, it doesn't necessarily mean

246
00:11:56,800 --> 00:11:59,080
Speaker 2: they're wrong or not using it as intended. It's just

247
00:11:59,120 --> 00:12:01,840
Speaker 2: they are making a series of bets that are like,

248
00:12:01,880 --> 00:12:04,440
Speaker 2: this is going to go up each of these days. Right,

249
00:12:04,920 --> 00:12:07,199
Speaker 2: if it goes up all of the days, then holding

250
00:12:07,240 --> 00:12:11,240
Speaker 2: the daily rebalancing atf is better than holding that's true,

251
00:12:11,360 --> 00:12:13,440
Speaker 2: the weekly. It's just like it has to go up

252
00:12:13,440 --> 00:12:15,400
Speaker 2: every day. Yeah, maybe it will.

253
00:12:16,360 --> 00:12:19,480
Speaker 1: I feel like that's a in some cases generous interpretation

254
00:12:19,640 --> 00:12:21,880
Speaker 1: of holding the daily one for more than one day,

255
00:12:21,880 --> 00:12:23,719
Speaker 1: that you are choosing clearly, in.

256
00:12:23,640 --> 00:12:26,120
Speaker 2: Some cases, gener clearly. In some cases people just buy

257
00:12:26,160 --> 00:12:28,880
Speaker 2: it for a year and forget about it. Probably someone

258
00:12:29,040 --> 00:12:30,120
Speaker 2: is like, at the end of day, yeah, this is

259
00:12:30,120 --> 00:12:31,520
Speaker 2: getting up again tomorrow. I don't know.

260
00:12:47,559 --> 00:12:53,000
Speaker 1: Taxi caves and the American Transit Insurance Company, Boy, are

261
00:12:53,080 --> 00:12:54,040
Speaker 1: they in trouble.

262
00:12:54,720 --> 00:12:57,040
Speaker 2: Yeah. So this is a Bloomberg News article about the

263
00:12:57,120 --> 00:12:59,840
Speaker 2: American Transit Insurance Company, which like apparently insures.

264
00:12:59,600 --> 00:13:01,640
Speaker 1: Most sixty percent uber.

265
00:13:01,480 --> 00:13:04,560
Speaker 2: Drivers, taxi drivers. If you get if you've like get

266
00:13:04,559 --> 00:13:06,640
Speaker 2: in a car in New York, it's probably insured by them.

267
00:13:06,840 --> 00:13:07,320
Speaker 1: Yeah.

268
00:13:07,360 --> 00:13:09,199
Speaker 2: And there's a reason for that, which is that they

269
00:13:09,200 --> 00:13:09,959
Speaker 2: offered cheap.

270
00:13:09,840 --> 00:13:11,000
Speaker 1: Rates, super cheap.

271
00:13:11,080 --> 00:13:13,079
Speaker 2: And there's a reason for that, which is that they

272
00:13:13,080 --> 00:13:15,440
Speaker 2: were under reserving for their risk and now they are

273
00:13:15,480 --> 00:13:16,360
Speaker 2: apparently insolvent.

274
00:13:16,720 --> 00:13:21,440
Speaker 1: So this is amazing because if Bloomberg News has done

275
00:13:21,480 --> 00:13:24,280
Speaker 1: a great job covering this, and I was reading one

276
00:13:24,280 --> 00:13:27,199
Speaker 1: of the pieces out today that Okay, so this company

277
00:13:27,559 --> 00:13:32,240
Speaker 1: was founded in nineteen seventy two, and in nineteen eighty six,

278
00:13:32,640 --> 00:13:36,520
Speaker 1: state regulators were already describing the company as insolvent by

279
00:13:36,559 --> 00:13:39,600
Speaker 1: six million dollars. That is according to a state examination

280
00:13:39,679 --> 00:13:43,640
Speaker 1: report that was obtained by Bloomberg. So they've been insolvent

281
00:13:43,800 --> 00:13:47,000
Speaker 1: for decades. It was six million dollars in nineteen eighty six,

282
00:13:47,160 --> 00:13:50,360
Speaker 1: and I believe in the second quarter it posted more

283
00:13:50,400 --> 00:13:53,920
Speaker 1: than seven hundred million dollars in net losses. That's according

284
00:13:53,960 --> 00:13:56,920
Speaker 1: to a filing with the National Association of Insurance Commissioners.

285
00:13:57,440 --> 00:14:00,199
Speaker 1: It's amazing how long this has been.

286
00:14:00,080 --> 00:14:03,160
Speaker 2: Going on, right, I mean for years people have been

287
00:14:03,160 --> 00:14:06,360
Speaker 2: saying they're charging too little, yeah, and they're underreserving. And

288
00:14:07,240 --> 00:14:10,120
Speaker 2: you know, it's a great illustration of like a lot

289
00:14:10,160 --> 00:14:14,720
Speaker 2: of financial services, it's very easy to win market share

290
00:14:15,320 --> 00:14:19,680
Speaker 2: by being wrong. Yeah. So the classic is like consumer

291
00:14:19,800 --> 00:14:22,800
Speaker 2: like lending. FinTechs will be like, we have this new

292
00:14:22,800 --> 00:14:26,000
Speaker 2: algorithm to like evaluate people's credit. It's better than regular

293
00:14:26,040 --> 00:14:28,680
Speaker 2: credit scores, and we're going to do such a great

294
00:14:28,720 --> 00:14:30,160
Speaker 2: job and make so many loans. And if they make

295
00:14:30,200 --> 00:14:32,640
Speaker 2: so many loans. That just means they're like mispricing on

296
00:14:32,640 --> 00:14:34,680
Speaker 2: the risk and their algorithm is wrong, and then they

297
00:14:34,840 --> 00:14:36,920
Speaker 2: you know, and like the way it works is that

298
00:14:36,960 --> 00:14:40,200
Speaker 2: if you do that, then you get a lot of

299
00:14:40,240 --> 00:14:43,640
Speaker 2: business and book a lot of profits early on, and

300
00:14:43,680 --> 00:14:45,960
Speaker 2: then later you go insolve it window. It's like don't

301
00:14:46,000 --> 00:14:48,720
Speaker 2: get paid back. It is weirder here just because this

302
00:14:48,840 --> 00:14:52,200
Speaker 2: is a decades long process process where like they keep

303
00:14:52,560 --> 00:14:53,720
Speaker 2: apparently under charging.

304
00:14:53,840 --> 00:14:57,120
Speaker 1: Yeah, this is pretty bad. This is according to Bloomberg News,

305
00:14:57,160 --> 00:15:01,280
Speaker 1: reporting again that New York's insurance regulator issued a report

306
00:15:01,360 --> 00:15:04,840
Speaker 1: on Thursday that shows that state regulators under both Governor

307
00:15:04,880 --> 00:15:08,000
Speaker 1: Kathy Hochel and Andrew Cuomo have been aware for at

308
00:15:08,080 --> 00:15:11,400
Speaker 1: least half a decade about just how bad things were.

309
00:15:12,160 --> 00:15:14,880
Speaker 1: So this has just been festering in plain sight.

310
00:15:15,080 --> 00:15:20,200
Speaker 2: For a while, right, But it's like the fix is rates.

311
00:15:20,320 --> 00:15:22,320
Speaker 1: Yeah, and you know, it's hard.

312
00:15:22,080 --> 00:15:24,880
Speaker 2: To politically unpopular to be like we're going to double

313
00:15:24,920 --> 00:15:26,880
Speaker 2: the price of insurance for ubers, which means we're going

314
00:15:26,920 --> 00:15:30,320
Speaker 2: to push out the price of and ubers And I

315
00:15:30,320 --> 00:15:32,960
Speaker 2: don't know, yeah, we sort of hope that like this

316
00:15:32,960 --> 00:15:35,240
Speaker 2: this is the thing, like this model of like under

317
00:15:35,320 --> 00:15:37,240
Speaker 2: charging for insurance through in market share and then like

318
00:15:37,640 --> 00:15:39,720
Speaker 2: getting out of town when the when the when the

319
00:15:39,760 --> 00:15:42,600
Speaker 2: claims come to goodbye. It's like so obvious, right, there's

320
00:15:42,680 --> 00:15:45,440
Speaker 2: lots and lots of insurance companies in history that have

321
00:15:45,640 --> 00:15:47,720
Speaker 2: kind of done this, and the point of insurance regulation

322
00:15:47,840 --> 00:15:52,480
Speaker 2: is just to prevent that. Right. But in a important

323
00:15:52,760 --> 00:15:56,040
Speaker 2: salient industry like New York City taxi cabs, it can

324
00:15:56,080 --> 00:15:57,720
Speaker 2: be hard for the regulators to say, we have to

325
00:15:57,760 --> 00:16:01,000
Speaker 2: double rates because the insurances be underpriced, and so you

326
00:16:01,040 --> 00:16:04,280
Speaker 2: get this weird dynamic where where it's like the short

327
00:16:04,320 --> 00:16:07,200
Speaker 2: term benefit of everyone and to under charge and then

328
00:16:07,240 --> 00:16:09,560
Speaker 2: it's like, you know, you kick the can down the

329
00:16:09,600 --> 00:16:11,800
Speaker 2: road and yeah, there's not enough money to pay claims. Yeah.

330
00:16:11,800 --> 00:16:17,400
Speaker 1: According to Bloomberg Reporting, drivers insured by the American Transit

331
00:16:17,400 --> 00:16:21,320
Speaker 1: Insurance Company typically pay annual premiums of four thousand dollars

332
00:16:21,400 --> 00:16:26,040
Speaker 1: to six thousand dollars, depending on experience, accident claims, different calculations.

333
00:16:26,320 --> 00:16:29,480
Speaker 1: So I mean jacking that up to eight thousand dollars

334
00:16:29,480 --> 00:16:31,680
Speaker 1: a lot, I mean I assume a lot of drivers

335
00:16:31,720 --> 00:16:33,720
Speaker 1: just wouldn't be able to do that.

336
00:16:34,440 --> 00:16:36,560
Speaker 2: I just think about that's a lot higher than my

337
00:16:36,760 --> 00:16:41,400
Speaker 2: current insurance yeah, but I'm not driving yeah the day.

338
00:16:41,720 --> 00:16:47,200
Speaker 1: So what happens now? According to Bloomberg Reporting, I wonder

339
00:16:47,240 --> 00:16:49,120
Speaker 1: how many times I'm going to say that the New

340
00:16:49,200 --> 00:16:55,240
Speaker 1: York regulator has ordered this company to weigh a sale.

341
00:16:55,440 --> 00:16:57,880
Speaker 1: I don't know what happens here. It seems that a

342
00:16:57,880 --> 00:16:59,520
Speaker 1: lot of people are saying a lot of analysts are

343
00:16:59,520 --> 00:17:04,080
Speaker 1: saying that if they can't keep insuring drivers, it's going

344
00:17:04,119 --> 00:17:07,080
Speaker 1: to be massively painful for people moving around New York

345
00:17:07,160 --> 00:17:08,080
Speaker 1: drivers included.

346
00:17:08,320 --> 00:17:10,760
Speaker 2: But because like some drivers will be forced out of

347
00:17:10,760 --> 00:17:12,600
Speaker 2: the market because they won't be able to get insurance. Yeah,

348
00:17:12,640 --> 00:17:15,440
Speaker 2: and then like prices of ubers will go up, Yeah,

349
00:17:15,760 --> 00:17:19,280
Speaker 2: because they've been underpressed for years, that'll go offer.

350
00:17:20,000 --> 00:17:23,480
Speaker 1: It's horrible, and maybe it's gonna happen. You did compare

351
00:17:23,520 --> 00:17:26,480
Speaker 1: this to that working paper that you reference in money

352
00:17:26,480 --> 00:17:30,040
Speaker 1: stuff about when insurres exit. It was a case study

353
00:17:30,040 --> 00:17:32,600
Speaker 1: looking at Florida red.

354
00:17:33,040 --> 00:17:35,720
Speaker 2: It's so good because it's like half of it is.

355
00:17:35,760 --> 00:17:38,840
Speaker 2: This is just this classic insurance story, which which is,

356
00:17:38,920 --> 00:17:43,040
Speaker 2: you know a lot of houses in Florida are risky, right,

357
00:17:43,040 --> 00:17:44,800
Speaker 2: They're like near the beach and there's hur Again.

358
00:17:44,840 --> 00:17:49,280
Speaker 1: I'm well acquainted with Florida real estate. Sure, yeah, I

359
00:17:49,520 --> 00:17:50,720
Speaker 1: leave that one hanging out there.

360
00:17:51,800 --> 00:17:55,600
Speaker 2: And so you know a lot of insurance companies don't

361
00:17:55,640 --> 00:17:57,760
Speaker 2: want to ensure them or would charge very high rates.

362
00:17:58,040 --> 00:18:01,120
Speaker 2: And so there's this like class of wish insurance companies

363
00:18:01,119 --> 00:18:05,040
Speaker 2: in Florida that will ensure you know, houses in risky.

364
00:18:04,800 --> 00:18:07,399
Speaker 1: Areas, vibrant startup ecosystem.

365
00:18:07,040 --> 00:18:10,560
Speaker 2: And they'll do it at like reasonable seeming rates which

366
00:18:10,560 --> 00:18:15,320
Speaker 2: are probably underpriced. And this paper argues that these insurers

367
00:18:15,320 --> 00:18:18,879
Speaker 2: are under capitalized and risky insurance have to be raided

368
00:18:19,040 --> 00:18:22,200
Speaker 2: by ratings agencies. These insurers tend to be rated by

369
00:18:22,280 --> 00:18:24,639
Speaker 2: like new startup ratings agencies.

370
00:18:24,359 --> 00:18:26,040
Speaker 1: Another rant ecosystems.

371
00:18:26,040 --> 00:18:29,440
Speaker 2: It's like slightly different criteria from the regular more traditional

372
00:18:29,520 --> 00:18:32,040
Speaker 2: ratings agencies. And so you have these insurers that are like,

373
00:18:32,040 --> 00:18:34,600
Speaker 2: according to the others of this paper, under capitalized, that

374
00:18:34,760 --> 00:18:37,679
Speaker 2: get good enough ratings to be like sort of in

375
00:18:37,720 --> 00:18:41,359
Speaker 2: good standing with regulators. But so that's like kind of normal.

376
00:18:41,359 --> 00:18:43,320
Speaker 2: And then like you know, some of these insurers go bankrupt.

377
00:18:43,400 --> 00:18:45,960
Speaker 2: When then when a lot of clampshead and it's like wow,

378
00:18:46,000 --> 00:18:49,080
Speaker 2: you know, they're not really providing insurance. The fascinating thing

379
00:18:49,160 --> 00:18:52,919
Speaker 2: is like it's homeowners insurance right. So like New York

380
00:18:52,960 --> 00:18:55,640
Speaker 2: City taxis it's like this politically scient industry. It would

381
00:18:55,640 --> 00:18:57,800
Speaker 2: like be bad for the government if you couldn't ensure

382
00:18:57,800 --> 00:19:00,480
Speaker 2: your home, and so the regulators have an incentive to

383
00:19:00,520 --> 00:19:05,199
Speaker 2: be okay with these companies. But there's another party, which is,

384
00:19:05,560 --> 00:19:08,080
Speaker 2: you know, these homes tend to have mortgages, and the

385
00:19:08,080 --> 00:19:11,600
Speaker 2: mortgage lender doesn't want them to be uninsured or you know,

386
00:19:12,000 --> 00:19:16,400
Speaker 2: have insolvent insurers. And what the authors find is that

387
00:19:16,480 --> 00:19:21,439
Speaker 2: when these insurers ensure the homes, the mortgage lenders are

388
00:19:21,480 --> 00:19:24,359
Speaker 2: more likely to sell their mortgages to Fanny May and

389
00:19:24,359 --> 00:19:29,040
Speaker 2: Freddie Mack, the government backed mortgage you know kind of

390
00:19:29,280 --> 00:19:33,439
Speaker 2: guarantee firms. And the way it works is just like

391
00:19:34,119 --> 00:19:37,920
Speaker 2: there's a market signal that these insurance companies aren't that good,

392
00:19:38,160 --> 00:19:39,920
Speaker 2: and the market signals the banks don't want to hold

393
00:19:39,920 --> 00:19:42,320
Speaker 2: mortgages that are insured by them or where the houses

394
00:19:42,320 --> 00:19:45,040
Speaker 2: are insured by them, But the banks will sell the

395
00:19:45,119 --> 00:19:48,000
Speaker 2: mortgages to Fanny and Freddy, which like are kind of

396
00:19:48,040 --> 00:19:50,840
Speaker 2: like unthinking, like they don't like send a market signal,

397
00:19:50,840 --> 00:19:53,120
Speaker 2: they just like look at the rating and like there's

398
00:19:53,119 --> 00:19:56,320
Speaker 2: a rating from like this arguably you know, bad rating.

399
00:19:56,359 --> 00:19:59,640
Speaker 2: Agency and they say you meet the ratings criteria, said,

400
00:19:59,640 --> 00:20:01,760
Speaker 2: we'll buy the mortgages, and so all of the like

401
00:20:02,560 --> 00:20:05,159
Speaker 2: mortgages and like the risky areas migrate to Fanny and

402
00:20:05,200 --> 00:20:06,640
Speaker 2: Freddy because the market doesn't.

403
00:20:06,400 --> 00:20:08,879
Speaker 1: Want to hold them, similar to houses in Florida. Seems

404
00:20:08,920 --> 00:20:10,920
Speaker 1: like a really shakily built system. There.

405
00:20:11,000 --> 00:20:11,480
Speaker 2: There you go.

406
00:20:11,640 --> 00:20:15,800
Speaker 1: It is interesting. I mean, coming back to the timelines here,

407
00:20:16,320 --> 00:20:18,560
Speaker 1: reading and listening to your summary of this paper, which

408
00:20:18,600 --> 00:20:22,440
Speaker 1: I haven't read, it seems like these insurers are cropping

409
00:20:22,520 --> 00:20:25,960
Speaker 1: up in Florida, whereas again this is in New York

410
00:20:26,080 --> 00:20:30,520
Speaker 1: with the taxi industry. Is just I am just speechless

411
00:20:30,560 --> 00:20:33,879
Speaker 1: that it's been going on for longer than I've been alive.

412
00:20:34,200 --> 00:20:36,920
Speaker 2: Yeah, some of this is like increased the claims in verdicts, right,

413
00:20:36,920 --> 00:20:38,920
Speaker 2: Like yeah, some of it is like all of insurance

414
00:20:39,000 --> 00:20:42,280
Speaker 2: is like estimating risks, right, and like maybe they were

415
00:20:42,920 --> 00:20:45,119
Speaker 2: doing an okay job of estimating risks and then the

416
00:20:45,200 --> 00:20:47,080
Speaker 2: risks changed, but maybe not.

417
00:20:47,880 --> 00:20:49,320
Speaker 1: Well, it'll be fun to follow.

418
00:20:49,680 --> 00:20:51,439
Speaker 2: We'll definitely talk about it next week.

419
00:20:51,680 --> 00:20:54,880
Speaker 1: Yeah, the whole system collapses and I.

420
00:20:54,880 --> 00:20:56,280
Speaker 2: Can't get here because I can't get.

421
00:20:56,160 --> 00:21:09,200
Speaker 1: A newer then we really have to cancel the podcast

422
00:21:11,640 --> 00:21:15,040
Speaker 1: Truth Social DJT, DJT.

423
00:21:15,160 --> 00:21:17,840
Speaker 2: Trump Media and Technology Group, Right for sure, Social, let

424
00:21:17,920 --> 00:21:20,720
Speaker 2: me be formal, Trump and Media and Technology Group is

425
00:21:20,760 --> 00:21:23,520
Speaker 2: the is the name of the company, and DJT is

426
00:21:23,560 --> 00:21:25,119
Speaker 2: the ticker, which is what everyone calls it.

427
00:21:25,240 --> 00:21:29,720
Speaker 1: So true, So this stock is flat at least on

428
00:21:29,760 --> 00:21:32,479
Speaker 1: Thursday on a year to day basis, a one year basis,

429
00:21:32,520 --> 00:21:36,120
Speaker 1: it's down closed to seventy percent since it's market cat

430
00:21:36,119 --> 00:21:40,280
Speaker 1: beaked in early May. It's now worth three point four

431
00:21:40,280 --> 00:21:43,880
Speaker 1: billion dollars. It was almost ten billion dollars. It has

432
00:21:43,920 --> 00:21:46,200
Speaker 1: to be one of the few three billion dollar companies

433
00:21:46,240 --> 00:21:48,560
Speaker 1: that doesn't have a single analyst that covers it. And

434
00:21:48,640 --> 00:21:51,560
Speaker 1: I know why because what are the fundamentals here? But

435
00:21:51,600 --> 00:21:53,560
Speaker 1: I'm still really hoping when I typed an A and

436
00:21:53,680 --> 00:21:56,480
Speaker 1: R on my Bloomberg terminal that something would possible.

437
00:21:56,640 --> 00:21:59,000
Speaker 2: Imagine being an alyss covering this company. Like it's bad

438
00:21:59,040 --> 00:22:01,560
Speaker 2: enough for me writing about it, but like like what

439
00:22:01,600 --> 00:22:02,280
Speaker 2: can you say?

440
00:22:02,480 --> 00:22:02,720
Speaker 1: Yeah?

441
00:22:03,240 --> 00:22:05,840
Speaker 2: Sell and then like Donald Trump will be mad at you, yeah,

442
00:22:05,880 --> 00:22:08,679
Speaker 2: And what's the benefit of that? Like everyone knows that,

443
00:22:08,720 --> 00:22:10,399
Speaker 2: Like there's no fundamentals to this company.

444
00:22:10,480 --> 00:22:13,280
Speaker 1: So you remember when meme stocks were just dawning. I

445
00:22:13,320 --> 00:22:18,360
Speaker 1: guess so came up and AMC. There were real analysts

446
00:22:18,400 --> 00:22:20,760
Speaker 1: who covered those companies, but like.

447
00:22:20,680 --> 00:22:22,720
Speaker 2: Those are like you kind of say stuff about that

448
00:22:22,760 --> 00:22:25,159
Speaker 2: business exactly. You can be like, okay, this this is

449
00:22:25,200 --> 00:22:26,920
Speaker 2: you know, a thousand percent, but.

450
00:22:26,880 --> 00:22:29,480
Speaker 1: A lot of them did end up dropping coverage and.

451
00:22:29,880 --> 00:22:32,160
Speaker 2: Because like like what value do you add?

452
00:22:32,280 --> 00:22:34,840
Speaker 1: Yeah, I remember inviting a couple of them on TV

453
00:22:34,920 --> 00:22:36,800
Speaker 1: and they were like, I Am not going to talk

454
00:22:36,840 --> 00:22:38,360
Speaker 1: about this on time.

455
00:22:38,440 --> 00:22:40,440
Speaker 2: And it's because like, one, what value do you add?

456
00:22:40,440 --> 00:22:43,400
Speaker 2: Because like the dynamics are not things that you can

457
00:22:43,960 --> 00:22:46,600
Speaker 2: inform with your fundamental analysis. But then also people being

458
00:22:46,640 --> 00:22:49,639
Speaker 2: mad at oh yeah right, yeah. It's the same with DJT, right,

459
00:22:49,720 --> 00:22:52,720
Speaker 2: like oh, you could be like, you know, this company

460
00:22:52,800 --> 00:22:54,960
Speaker 2: is like one million dollars of revenue and it's a

461
00:22:55,000 --> 00:22:58,760
Speaker 2: three point five billion dollar market cap sell right, Like okay, one,

462
00:22:58,840 --> 00:23:00,919
Speaker 2: everyone knows that, and then two people get mad at you,

463
00:23:00,960 --> 00:23:02,160
Speaker 2: like what's you why?

464
00:23:02,440 --> 00:23:06,560
Speaker 1: Yeah? Yeah. So it's interesting. It's enormous fall from grace.

465
00:23:06,640 --> 00:23:09,639
Speaker 1: Of course it's approaching the end of the lock up period,

466
00:23:09,680 --> 00:23:14,359
Speaker 1: but also the fundamentals that it did have have been eroded,

467
00:23:15,400 --> 00:23:18,399
Speaker 1: undermined by the fact that Donald Trump is back on

468
00:23:18,640 --> 00:23:20,679
Speaker 1: X Now I don't know what are you not a

469
00:23:20,680 --> 00:23:24,120
Speaker 1: truth social guy? This is shocking.

470
00:23:26,440 --> 00:23:29,320
Speaker 2: Truth social. I agree with you that, like if your

471
00:23:29,480 --> 00:23:32,040
Speaker 2: if your case, if your business case for Trump media

472
00:23:32,240 --> 00:23:37,359
Speaker 2: was like truth social is like the place for tens

473
00:23:37,359 --> 00:23:39,720
Speaker 2: of millions of Donald Trump fans to like get their

474
00:23:39,720 --> 00:23:42,480
Speaker 2: social media, then like the fact that Donald Trump is

475
00:23:42,520 --> 00:23:44,680
Speaker 2: back on X and that X is like clearly the

476
00:23:44,760 --> 00:23:47,520
Speaker 2: right wing social network. Now, yeah, undermines that business case.

477
00:23:47,560 --> 00:23:50,360
Speaker 1: I do have some stats for you. Okay, So Bloomberg's

478
00:23:50,359 --> 00:23:53,879
Speaker 1: Bailey Lipshoals has done such a fantastic job covering pretty

479
00:23:53,960 --> 00:23:58,320
Speaker 1: much everything but including a dj team. So I was

480
00:23:58,359 --> 00:24:02,119
Speaker 1: asking him how many people are actually on truth Social

481
00:24:02,119 --> 00:24:05,879
Speaker 1: and it's really difficult to tell, and DJT truth Social

482
00:24:05,960 --> 00:24:09,040
Speaker 1: will refute these figures. But this is according to aptopia.

483
00:24:09,200 --> 00:24:11,840
Speaker 1: It's been around three hundred and fifty thousand, not above

484
00:24:12,040 --> 00:24:15,960
Speaker 1: one million, over the past year. For context, I think

485
00:24:16,000 --> 00:24:18,720
Speaker 1: Twitter has a few hundred million, and then you compare

486
00:24:18,720 --> 00:24:19,840
Speaker 1: it to Reddit.

487
00:24:20,560 --> 00:24:23,960
Speaker 2: I wouldn't compare that number to the Mummy Stuff subscriber base,

488
00:24:24,000 --> 00:24:25,680
Speaker 2: but I won't because those figures maybe.

489
00:24:26,880 --> 00:24:29,840
Speaker 1: Flex Flex what's your market cap?

490
00:24:29,920 --> 00:24:31,159
Speaker 2: Yeah, it's three five billion.

491
00:24:31,200 --> 00:24:34,159
Speaker 1: That's huge. Wait wait, wait, one more point Reddit ninety

492
00:24:34,160 --> 00:24:37,560
Speaker 1: one million users in the second quarter. Reddit's market cap

493
00:24:38,040 --> 00:24:41,000
Speaker 1: is only three times that of DJT. Reddit is like

494
00:24:41,119 --> 00:24:42,200
Speaker 1: nine point seven billion.

495
00:24:42,359 --> 00:24:44,000
Speaker 2: It's the way. Maybe the case with the stock was

496
00:24:44,040 --> 00:24:45,359
Speaker 2: Donald Trump is going to.

497
00:24:45,280 --> 00:24:47,120
Speaker 1: Start that I could see that as social media.

498
00:24:47,440 --> 00:24:49,760
Speaker 2: I think that's that's over now, right, I mean, no one,

499
00:24:50,119 --> 00:24:53,040
Speaker 2: no one really thinks that now. The case for the stock,

500
00:24:53,440 --> 00:24:54,840
Speaker 2: if I had a case for the stock, it would

501
00:24:54,880 --> 00:24:57,000
Speaker 2: be like it would be a corruption based case, right.

502
00:24:57,040 --> 00:24:59,919
Speaker 2: It would be like Donald Trump lucom president again is

503
00:25:00,359 --> 00:25:03,560
Speaker 2: most obviously large and monetizable asset will be his like

504
00:25:04,040 --> 00:25:10,000
Speaker 2: sixty percent holdings of DJT, and people who want his

505
00:25:10,080 --> 00:25:13,479
Speaker 2: attention and favor will do things to increase the value

506
00:25:13,720 --> 00:25:16,080
Speaker 2: of that stock. I don't know exactly what that is, right,

507
00:25:16,240 --> 00:25:18,919
Speaker 2: Maybe like the Saudi government will buy ten percent of

508
00:25:18,920 --> 00:25:20,760
Speaker 2: the stock at a premium. Right, Maybe someone ever knows

509
00:25:20,760 --> 00:25:24,480
Speaker 2: offered to take over the company. Maybe Elon musklell strike

510
00:25:24,480 --> 00:25:27,080
Speaker 2: a business deal where like you know, there's a lot

511
00:25:27,119 --> 00:25:29,840
Speaker 2: of ways you could imagine the stock going up because

512
00:25:30,119 --> 00:25:33,960
Speaker 2: people want to influence and or send money to Donald Trump.

513
00:25:34,640 --> 00:25:36,560
Speaker 2: That case, I think has been a little undermined by

514
00:25:36,600 --> 00:25:39,080
Speaker 2: the fact that Trump and his sons have been promoting

515
00:25:39,080 --> 00:25:42,280
Speaker 2: a crypto project, right yeah, because it's like like DJT

516
00:25:42,400 --> 00:25:44,359
Speaker 2: is essentially a token of like let's give money to

517
00:25:44,400 --> 00:25:47,040
Speaker 2: Donald Trump. And they're like, wait, we can create those tokens,

518
00:25:47,080 --> 00:25:49,159
Speaker 2: like freely, we can create as many tokens as I.

519
00:25:49,160 --> 00:25:52,680
Speaker 1: Confess something to you. I have been blissfully not following

520
00:25:52,800 --> 00:25:54,959
Speaker 1: that story at all so.

521
00:25:54,440 --> 00:25:57,080
Speaker 2: Closely, but there is there's like and there's not much

522
00:25:57,080 --> 00:25:59,199
Speaker 2: of a story. It's like, yeah, they have teased like

523
00:25:59,280 --> 00:26:05,679
Speaker 2: we're starting this like DeFi Crypto World Liberty project, and

524
00:26:05,720 --> 00:26:06,720
Speaker 2: then the other day they.

525
00:26:06,600 --> 00:26:11,399
Speaker 1: Were act like it was Eric Trump, right, it's.

526
00:26:11,280 --> 00:26:13,320
Speaker 2: Like the Trump sons. But then like some other Trump

527
00:26:13,359 --> 00:26:17,120
Speaker 2: family members were hacked and like we're posting promotions for

528
00:26:17,119 --> 00:26:19,359
Speaker 2: for their crypto project that were actually just like scam

529
00:26:19,359 --> 00:26:21,919
Speaker 2: sites that would take your money. So it's just like

530
00:26:21,960 --> 00:26:24,680
Speaker 2: too perfect. But anyway, the point is like the DJT

531
00:26:24,800 --> 00:26:27,000
Speaker 2: thing is such an amazing proof of concept because you

532
00:26:27,040 --> 00:26:29,000
Speaker 2: have this like minimal business and you attach a three

533
00:26:29,000 --> 00:26:31,480
Speaker 2: billion dollar memestock to it, and like you to do

534
00:26:31,520 --> 00:26:33,439
Speaker 2: that again with like without the minimal business, right, you

535
00:26:33,440 --> 00:26:35,480
Speaker 2: do like some DeFi project and you're like, oh, give

536
00:26:35,560 --> 00:26:37,320
Speaker 2: us money for a DeFi project, and like it gets

537
00:26:37,359 --> 00:26:39,400
Speaker 2: a billion dollar market cap. Yeah, there yet, but it's

538
00:26:39,440 --> 00:26:41,760
Speaker 2: like the more they do that, the less any individual

539
00:26:41,760 --> 00:26:44,480
Speaker 2: project is worth. Right, So I think that undermines DJ

540
00:26:44,600 --> 00:26:47,800
Speaker 2: two too. But then the real problem with DJT, yeah,

541
00:26:47,840 --> 00:26:50,560
Speaker 2: go on is that Donald Trump bounds like sixty.

542
00:26:50,359 --> 00:26:51,760
Speaker 1: Percent of it, for sure, he does.

543
00:26:51,920 --> 00:26:53,920
Speaker 2: Shares are locked up, and the lockup ends like.

544
00:26:53,840 --> 00:26:56,000
Speaker 1: This month, yeah, I September.

545
00:26:57,119 --> 00:26:59,919
Speaker 2: Yeah, And so like it's fascinating to me because what

546
00:27:00,119 --> 00:27:01,320
Speaker 2: he sold it all? Yeah?

547
00:27:01,359 --> 00:27:02,720
Speaker 1: And can he sure?

548
00:27:02,880 --> 00:27:04,520
Speaker 2: I mean in what sense?

549
00:27:04,760 --> 00:27:06,919
Speaker 1: I don't know. There was some in reading the various

550
00:27:07,040 --> 00:27:09,639
Speaker 1: articles that Elliptionals has written about this, it seems like

551
00:27:09,680 --> 00:27:11,919
Speaker 1: there are some complications about whether he'd be able to

552
00:27:11,920 --> 00:27:12,240
Speaker 1: sell it.

553
00:27:12,240 --> 00:27:14,679
Speaker 2: At one fells, you can't if you're an insider of

554
00:27:14,680 --> 00:27:17,439
Speaker 2: a company, you have limit, like legal limits on how

555
00:27:17,480 --> 00:27:20,320
Speaker 2: much you can sell without registering yourselves. But like he

556
00:27:20,359 --> 00:27:25,000
Speaker 2: could conceivably to a registration statement, and the company would

557
00:27:25,000 --> 00:27:27,760
Speaker 2: do a registration statement saying we're selling He's selling two

558
00:27:27,760 --> 00:27:30,680
Speaker 2: billion dollars of stuck, and then like they could try

559
00:27:30,720 --> 00:27:34,919
Speaker 2: to find buyers for it, and they might write like

560
00:27:35,160 --> 00:27:39,879
Speaker 2: they might not as like a not necessarily as that

561
00:27:40,080 --> 00:27:42,280
Speaker 2: on the fundamentals of the company, but as a like

562
00:27:43,920 --> 00:27:46,520
Speaker 2: I would like to give Bendon Donalds from Yeah, you

563
00:27:46,560 --> 00:27:49,320
Speaker 2: see this a lot in crypto, where it's like you

564
00:27:49,359 --> 00:27:53,840
Speaker 2: can do a thing and it can have like nominal

565
00:27:54,119 --> 00:27:57,400
Speaker 2: multi billion dollar market capitalization, but then when you try

566
00:27:57,400 --> 00:28:00,880
Speaker 2: to cash in, the evaluation proof stamp to zero, right,

567
00:28:00,920 --> 00:28:04,520
Speaker 2: like because like the valuation is like trading of a

568
00:28:04,640 --> 00:28:07,879
Speaker 2: like a sort of small like portion of the of

569
00:28:07,920 --> 00:28:11,760
Speaker 2: the market cap, like you own most of it, and

570
00:28:11,840 --> 00:28:14,920
Speaker 2: like your involvement is crucial, and once you sell, everyone

571
00:28:14,960 --> 00:28:16,359
Speaker 2: will say, oh, this thing is going to zero, and

572
00:28:16,359 --> 00:28:18,679
Speaker 2: so like the market cap just poofs and you're not

573
00:28:18,760 --> 00:28:21,040
Speaker 2: able to actually extract the billions of dollars of paper

574
00:28:21,119 --> 00:28:24,560
Speaker 2: value that's like easily imaginable here, right, And like it's

575
00:28:24,600 --> 00:28:26,480
Speaker 2: probably part of why the stock is going down. And

576
00:28:26,560 --> 00:28:29,040
Speaker 2: it's like Trump wants to monetize it. Like that's a

577
00:28:29,080 --> 00:28:31,320
Speaker 2: bad sign for the future of the stock, and so

578
00:28:31,440 --> 00:28:34,080
Speaker 2: like why would you hold going into that? But I'm

579
00:28:34,119 --> 00:28:36,640
Speaker 2: not sure what happened here, Yeah, and other possibilities people

580
00:28:36,720 --> 00:28:38,360
Speaker 2: be like, oh, yeah, we love Donald Trump, we love

581
00:28:39,200 --> 00:28:41,600
Speaker 2: what he's done with the truth social and we're going

582
00:28:41,680 --> 00:28:44,400
Speaker 2: to pay to buy stock from him, right, Maybe not

583
00:28:45,080 --> 00:28:47,560
Speaker 2: you know, it's like seventeen dollars. Now, maybe not seventeen dollars,

584
00:28:47,640 --> 00:28:49,840
Speaker 2: but enough that you could extract hundreds of millions of

585
00:28:49,880 --> 00:28:53,000
Speaker 2: dollars from this company that has a million dollars of revenue.

586
00:28:53,080 --> 00:28:55,360
Speaker 1: Yeah, so we'll see because that period, that lock up

587
00:28:55,400 --> 00:28:56,840
Speaker 1: period is expiring very soon.

588
00:28:57,600 --> 00:28:59,800
Speaker 2: I assume he's not actually going to dump stock and like,

589
00:29:00,240 --> 00:29:02,880
Speaker 2: you know, now mighty borrow against the stock. Like I

590
00:29:02,920 --> 00:29:07,000
Speaker 2: love that outcome because like I love the idea of

591
00:29:07,040 --> 00:29:09,920
Speaker 2: being the margin lender at a bank and having him

592
00:29:09,920 --> 00:29:12,000
Speaker 2: come in and say, I have two billion dollars of

593
00:29:12,080 --> 00:29:14,680
Speaker 2: DJT collateral. How much will you lend me against the

594
00:29:14,800 --> 00:29:16,680
Speaker 2: non recourse what's the right answer?

595
00:29:16,760 --> 00:29:19,400
Speaker 1: Then you literally start rubbing your hands as you say,

596
00:29:19,520 --> 00:29:20,680
Speaker 1: I love this outcome.

597
00:29:20,800 --> 00:29:22,720
Speaker 2: To me if you were like Donald Trump wants to

598
00:29:22,760 --> 00:29:26,240
Speaker 2: borrow against two billion dollars of DJT stock non recourse, Yeah,

599
00:29:26,280 --> 00:29:31,240
Speaker 2: like how much would you give him? Some twenty million dollars?

600
00:29:31,360 --> 00:29:33,240
Speaker 2: But like someone will go higher?

601
00:29:33,280 --> 00:29:37,239
Speaker 1: Someone someone will So there's a lot to keep an

602
00:29:37,240 --> 00:29:41,480
Speaker 1: eyeball on here. You do present two robust, compelling reasons

603
00:29:41,520 --> 00:29:44,360
Speaker 1: to explain why the stock is absolutely pancaked over the

604
00:29:44,440 --> 00:29:45,240
Speaker 1: last two months.

605
00:29:45,480 --> 00:29:47,320
Speaker 2: It hasn't even like pancaked is the wrong word. It's

606
00:29:47,320 --> 00:29:48,640
Speaker 2: a three point five billion dollar market.

607
00:29:49,080 --> 00:29:50,400
Speaker 1: It's seventy.

608
00:29:50,800 --> 00:29:52,880
Speaker 2: It's a stack, so it's like, you know, like people

609
00:29:52,960 --> 00:29:55,120
Speaker 2: put in ten dollars a share, like way back when

610
00:29:55,200 --> 00:29:57,320
Speaker 2: when those back launch, and it's at seventeen. So it's

611
00:29:57,320 --> 00:29:58,960
Speaker 2: like it's a pretty successful spack.

612
00:30:00,320 --> 00:30:03,680
Speaker 1: It was more successful, though it is less successful than

613
00:30:03,720 --> 00:30:07,240
Speaker 1: it was. There's also the argument to be made that

614
00:30:07,640 --> 00:30:11,160
Speaker 1: Donald Trump's clear lead in the polls has eroded since

615
00:30:11,240 --> 00:30:14,400
Speaker 1: Kamala Harris entered the race. Absolutely, and this was like

616
00:30:14,480 --> 00:30:15,000
Speaker 1: a proxy.

617
00:30:15,200 --> 00:30:17,080
Speaker 2: Partly because it was just literally a proxy here, it's

618
00:30:17,080 --> 00:30:19,400
Speaker 2: just literally a token of attention, and then partly because

619
00:30:19,440 --> 00:30:21,520
Speaker 2: if you had a business case for the stock, it

620
00:30:21,600 --> 00:30:25,200
Speaker 2: was it evolved around him being president and somehow value

621
00:30:25,200 --> 00:30:27,280
Speaker 2: according to the company because he's president, and if he's

622
00:30:27,320 --> 00:30:30,680
Speaker 2: not president, if he's not president, maybe has more time

623
00:30:30,880 --> 00:30:33,160
Speaker 2: to focus on his social media company and it will

624
00:30:33,200 --> 00:30:34,240
Speaker 2: become a powerhouse.

625
00:30:34,280 --> 00:30:37,800
Speaker 1: But yeah, it didn't make me think briefly, and this

626
00:30:37,840 --> 00:30:41,280
Speaker 1: is something we've talked about before election contracts and the

627
00:30:41,320 --> 00:30:44,880
Speaker 1: fact that they're illegal. Question Mark can't really do.

628
00:30:44,880 --> 00:30:48,600
Speaker 2: That right, Like if you want to bet on like

629
00:30:49,200 --> 00:30:52,600
Speaker 2: the fluctuating chances of Donald Trump being elected, Like trading

630
00:30:52,760 --> 00:30:54,760
Speaker 2: DJT stock is not the worst way to do it

631
00:30:54,840 --> 00:30:57,600
Speaker 2: because it does seem pretty correlated to his like polls. Yeah,

632
00:30:57,640 --> 00:30:59,480
Speaker 2: it's probably easier to get money down than it isn't

633
00:30:59,520 --> 00:31:01,280
Speaker 2: like the action contrast markets.

634
00:31:01,360 --> 00:31:03,560
Speaker 1: Yeah, so if you want to scratch that itch, this

635
00:31:03,720 --> 00:31:05,160
Speaker 1: is the way that people have been doing.

636
00:31:05,120 --> 00:31:08,120
Speaker 2: It, go on because it doesn't like resolve to one

637
00:31:08,160 --> 00:31:10,240
Speaker 2: hundred dollars if he's elected on zero dollars if he's

638
00:31:10,280 --> 00:31:12,280
Speaker 2: not right, it's like it's not it doesn't really have

639
00:31:12,360 --> 00:31:14,440
Speaker 2: anything to do with but it does.

640
00:31:14,240 --> 00:31:17,280
Speaker 1: Because like a million percent, right, there's some.

641
00:31:17,280 --> 00:31:19,680
Speaker 2: Like business case for if he's president, it's worth a

642
00:31:19,720 --> 00:31:21,200
Speaker 2: lot of money, and if he's not president, it's not

643
00:31:21,200 --> 00:31:24,080
Speaker 2: worth a lot of money. But I think probably the

644
00:31:24,720 --> 00:31:27,160
Speaker 2: moves in the price are exaggerating that business case, and

645
00:31:27,200 --> 00:31:29,840
Speaker 2: it's really mostly like people want some proxy for that,

646
00:31:29,880 --> 00:31:31,480
Speaker 2: and it feels like a good proxy.

647
00:31:31,720 --> 00:31:34,120
Speaker 1: I still wish some analysts covered it. I want to

648
00:31:34,120 --> 00:31:35,640
Speaker 1: interview the loan analysts.

649
00:31:35,640 --> 00:31:37,320
Speaker 2: It would be fun, right, because this is the thing,

650
00:31:37,360 --> 00:31:40,240
Speaker 2: like there should be analysts who cover meme stocks and

651
00:31:40,360 --> 00:31:44,280
Speaker 2: this stock and crypto, and they should just have a

652
00:31:44,320 --> 00:31:46,320
Speaker 2: different method of it out because like, obviously you're not

653
00:31:46,360 --> 00:31:47,680
Speaker 2: going to be like, oh, he looked at orders and

654
00:31:47,680 --> 00:31:49,120
Speaker 2: they're coming in a little light, right, you need a

655
00:31:49,120 --> 00:31:51,920
Speaker 2: different method of analyzing this company. But like, if you're

656
00:31:51,920 --> 00:31:53,720
Speaker 2: good at making calls about what the stock would do,

657
00:31:53,760 --> 00:31:54,800
Speaker 2: that'd be like a value.

658
00:31:54,560 --> 00:31:56,840
Speaker 1: Out of ten read in the room reading sentiment, I

659
00:31:56,880 --> 00:32:01,480
Speaker 1: will say zerolysts track the stock as tracked by Bloomberg.

660
00:32:01,880 --> 00:32:04,160
Speaker 1: So maybe there's someone out there in the world but

661
00:32:04,200 --> 00:32:07,800
Speaker 1: they're not on the Bloomberg terminal system. Someone some of

662
00:32:07,840 --> 00:32:09,880
Speaker 1: the I want to hear from you.

663
00:32:10,120 --> 00:32:10,960
Speaker 2: How's your battery?

664
00:32:11,280 --> 00:32:17,080
Speaker 1: Oh god, it's nineteen This has drained me.

665
00:32:19,240 --> 00:32:21,160
Speaker 2: The electricity of the last.

666
00:32:21,040 --> 00:32:24,680
Speaker 1: Fading before your eyes and yours. I'm going on vacation though,

667
00:32:24,840 --> 00:32:29,000
Speaker 1: really yeah, on vacation. It wasn't enough. I'm going to

668
00:32:29,880 --> 00:32:35,920
Speaker 1: retact it the week after next. Maybe not ma, maybe

669
00:32:35,920 --> 00:32:37,440
Speaker 1: I'll wait a few months there. But anyway, the week

670
00:32:37,480 --> 00:32:39,360
Speaker 1: after next I'm going on vacation, so there won't be

671
00:32:39,960 --> 00:32:41,360
Speaker 1: used a podcast.

672
00:32:41,120 --> 00:32:43,520
Speaker 2: In lieu of a scintillating conversation about the monetary news

673
00:32:43,560 --> 00:32:46,160
Speaker 2: of the week. We're going to can and mail bag.

674
00:32:47,080 --> 00:32:52,000
Speaker 1: Yes, absolutely so send us your best questions. We appreciate

675
00:32:52,040 --> 00:32:54,880
Speaker 1: everyone who's sent questions so far, and we have those

676
00:32:54,920 --> 00:32:58,120
Speaker 1: in the can, but we want to fill thirty minutes.

677
00:32:58,200 --> 00:33:00,560
Speaker 1: Oh my god of answering questions.

678
00:33:00,720 --> 00:33:05,040
Speaker 2: So what kind of questions do we like? Our producer asked,

679
00:33:05,040 --> 00:33:06,360
Speaker 2: and we look fl mixed.

680
00:33:06,440 --> 00:33:07,080
Speaker 1: What do you like?

681
00:33:07,160 --> 00:33:07,680
Speaker 2: Fun question?

682
00:33:07,760 --> 00:33:11,040
Speaker 1: I love talking about myself. No, yes, No one ever

683
00:33:11,160 --> 00:33:12,960
Speaker 1: asks me questions.

684
00:33:13,040 --> 00:33:14,200
Speaker 2: Oh okay, this is the call.

685
00:33:15,960 --> 00:33:17,960
Speaker 1: Please. I love talking about myself.

686
00:33:18,560 --> 00:33:20,400
Speaker 2: Talking about that would be a good episode.

687
00:33:21,000 --> 00:33:23,200
Speaker 1: I like other things too, But what do you like?

688
00:33:23,280 --> 00:33:24,920
Speaker 2: Matt? I like questions about myself.

689
00:33:24,960 --> 00:33:26,000
Speaker 1: We're both needy people.

690
00:33:27,960 --> 00:33:29,360
Speaker 2: It's the point of a podcasts.

691
00:33:29,440 --> 00:33:30,320
Speaker 1: Yeah.

692
00:33:30,760 --> 00:33:33,400
Speaker 2: I also like finance stuff. I don't weird conceptual stuff.

693
00:33:33,520 --> 00:33:35,360
Speaker 2: I love Katie's.

694
00:33:34,920 --> 00:33:38,640
Speaker 1: Horse, horses and cats and reptiles.

695
00:33:38,720 --> 00:33:42,600
Speaker 2: I'm more of a dog guy myself. And that was

696
00:33:42,640 --> 00:33:43,720
Speaker 2: the Money Stuff podcast.

697
00:33:43,880 --> 00:33:45,840
Speaker 1: I'm Matt Livian and I'm Katie Greifeld.

698
00:33:46,040 --> 00:33:48,080
Speaker 2: You can find my work by subscribing to the Money

699
00:33:48,080 --> 00:33:49,960
Speaker 2: Stuff newsletter on Bloomberg.

700
00:33:49,520 --> 00:33:51,840
Speaker 1: Dot com, and you can find me on Bloomberg TV

701
00:33:52,040 --> 00:33:55,680
Speaker 1: every day on Open Interest between nine to eleven am Eastern.

702
00:33:55,800 --> 00:33:57,479
Speaker 2: We'd love to hear from you. You can send an

703
00:33:57,480 --> 00:34:00,640
Speaker 2: email to money Pot at bloomberg dot Net. Ask us

704
00:34:00,640 --> 00:34:02,160
Speaker 2: a question and we might answer it on air.

705
00:34:02,320 --> 00:34:04,440
Speaker 1: You can also subscribe to our show wherever you're listening

706
00:34:04,520 --> 00:34:06,520
Speaker 1: right now and leave us a review. It helps more

707
00:34:06,560 --> 00:34:07,440
Speaker 1: people find the show.

708
00:34:07,600 --> 00:34:10,360
Speaker 2: The Money Stuff Podcast is produced by Anna Maserakus and

709
00:34:10,440 --> 00:34:10,880
Speaker 2: Moses On.

710
00:34:11,320 --> 00:34:13,160
Speaker 1: Our theme music was composed by Blake.

711
00:34:12,960 --> 00:34:16,160
Speaker 2: Maples Friend and Frances Newnham is our executive producer and

712
00:34:16,200 --> 00:34:18,560
Speaker 2: special thanks this week to Cal Brooks and.

713
00:34:18,560 --> 00:34:20,560
Speaker 1: Stage Bauman is Bloomberg's head of Podcasts.

714
00:34:20,680 --> 00:34:23,000
Speaker 2: Thanks for listening to The Money Stuff Podcast. We'll be

715
00:34:23,080 --> 00:34:24,600
Speaker 2: back next week with more stuff