1
00:00:05,920 --> 00:00:09,000
Speaker 1: Welcome to Trillians. I'm Joel Webber and I'm Eric Baltierness.

2
00:00:10,960 --> 00:00:13,200
Speaker 1: We talk a lot about how hyper competitive of a

3
00:00:13,320 --> 00:00:16,360
Speaker 1: landscape et f s are. You know, it's dominated by

4
00:00:16,400 --> 00:00:19,680
Speaker 1: behemoths and those are the issuers and some of the

5
00:00:19,840 --> 00:00:21,439
Speaker 1: older E t f s who have been around a

6
00:00:21,440 --> 00:00:24,840
Speaker 1: long time collected a lot of assets. This episode, we're

7
00:00:24,840 --> 00:00:28,560
Speaker 1: gonna spend more time talking about maybe some indie rock, right,

8
00:00:29,080 --> 00:00:33,559
Speaker 1: so let's talk about what you call rising stars. Right,

9
00:00:33,600 --> 00:00:35,519
Speaker 1: So when you think about the E t F landscape,

10
00:00:35,560 --> 00:00:41,080
Speaker 1: there's products of them have less than fifty million dollars,

11
00:00:41,400 --> 00:00:44,200
Speaker 1: so I would consider that oblivion. So we're talking most

12
00:00:44,240 --> 00:00:47,559
Speaker 1: ETFs live in oblivion literally, so it's tough to get

13
00:00:47,600 --> 00:00:49,560
Speaker 1: out of there, including a lot of the fancy tickers

14
00:00:49,560 --> 00:00:52,680
Speaker 1: that we talk about. Absolutely. Now there's a firm middle

15
00:00:52,760 --> 00:00:57,720
Speaker 1: class which has about of the products. Although there's lower

16
00:00:57,720 --> 00:00:59,960
Speaker 1: middle class and upper middle class. There's a different degree.

17
00:01:00,040 --> 00:01:03,920
Speaker 1: So between one million and a billion, to me, is

18
00:01:03,920 --> 00:01:06,200
Speaker 1: this sort of middle class, and then beyond a billion

19
00:01:06,400 --> 00:01:09,319
Speaker 1: is sort of you're home free. You're now rich. Your

20
00:01:09,400 --> 00:01:13,320
Speaker 1: upper upper class. That's seventeen percent of the product suburbs.

21
00:01:13,360 --> 00:01:18,800
Speaker 1: That's right, So oblivion or middle class. Sevent are upper class.

22
00:01:19,240 --> 00:01:22,759
Speaker 1: So to go from oblivion to middle class is hard enough,

23
00:01:22,800 --> 00:01:24,720
Speaker 1: but then to like go all the way into the

24
00:01:24,800 --> 00:01:28,120
Speaker 1: upper class, it's it's like a swimming up stream. Ye.

25
00:01:28,400 --> 00:01:30,080
Speaker 1: You know, I think this is actually happens to be

26
00:01:30,120 --> 00:01:33,320
Speaker 1: a pretty decent week to bring in a little music metaphor,

27
00:01:33,440 --> 00:01:36,200
Speaker 1: because you know, Spotify is in the background, having just

28
00:01:36,240 --> 00:01:38,920
Speaker 1: had its sort of a non I p O I

29
00:01:39,040 --> 00:01:42,000
Speaker 1: p O, right, and you actually just watched the documentary

30
00:01:42,000 --> 00:01:43,640
Speaker 1: that you think kind of helps frame all of this

31
00:01:43,720 --> 00:01:46,640
Speaker 1: as well. Yeah, you know, I love my music metaphors,

32
00:01:46,680 --> 00:01:48,920
Speaker 1: and this one's really good. This is about a radio station.

33
00:01:49,040 --> 00:01:51,520
Speaker 1: It's on showtime. I think the name of the documentary

34
00:01:51,600 --> 00:01:53,960
Speaker 1: is called Dare to Be Different New Wave, and it

35
00:01:54,040 --> 00:01:57,120
Speaker 1: was basically w L I R in Long Island changed

36
00:01:57,160 --> 00:02:00,520
Speaker 1: Format two from classic rock, which is all anybody was

37
00:02:00,560 --> 00:02:03,120
Speaker 1: playing right stair Way to Heaven like all day every day,

38
00:02:03,160 --> 00:02:06,120
Speaker 1: and in eight two they switched formats completely to new wave,

39
00:02:06,840 --> 00:02:09,480
Speaker 1: so they're you know, they were playing stuff like YouTube, Duran, Duran,

40
00:02:09,600 --> 00:02:14,600
Speaker 1: Depeche Mode, Beastie Boys. This was all became eighties, right,

41
00:02:14,840 --> 00:02:17,359
Speaker 1: that was the main stream eventually, And to me, that

42
00:02:17,440 --> 00:02:21,000
Speaker 1: format change is essentially consistent with what E. T F

43
00:02:21,120 --> 00:02:24,200
Speaker 1: to me are a format change, right, they are completely

44
00:02:24,240 --> 00:02:27,160
Speaker 1: new wave, and that this radio station had something interesting

45
00:02:27,200 --> 00:02:29,760
Speaker 1: called the Screamer of the Week. And what that was

46
00:02:29,840 --> 00:02:32,359
Speaker 1: They played like a few songs that they just got

47
00:02:32,360 --> 00:02:34,200
Speaker 1: in that were new and the and the people would

48
00:02:34,240 --> 00:02:36,400
Speaker 1: call in and vote for their favorite one, and whichever

49
00:02:36,480 --> 00:02:38,640
Speaker 1: one one they played in heavy rotation the next week.

50
00:02:39,080 --> 00:02:40,880
Speaker 1: So if you look at a list of their Screamers

51
00:02:40,880 --> 00:02:43,240
Speaker 1: of the week, this is like early eighties. They've got

52
00:02:43,280 --> 00:02:46,120
Speaker 1: stuff on here, People or People by Depeche Mode, Pretty

53
00:02:46,120 --> 00:02:49,000
Speaker 1: Persuasion by R. E. M. New Year's Day by YouTube.

54
00:02:49,520 --> 00:02:52,440
Speaker 1: So they had a lot of songs that eventually became classics,

55
00:02:52,440 --> 00:02:54,600
Speaker 1: but they also had some duds in their songs that

56
00:02:54,639 --> 00:02:57,080
Speaker 1: you never heard of, like only You by the Flying Pickets,

57
00:02:57,080 --> 00:02:59,880
Speaker 1: Connecticut by Hillary. So the Screamer of the Week was

58
00:03:00,240 --> 00:03:03,440
Speaker 1: necessarily a definite classic, but it was them trying to

59
00:03:03,480 --> 00:03:07,160
Speaker 1: sort of identify as early as possible a song that

60
00:03:07,800 --> 00:03:09,960
Speaker 1: a breakthrough exactly. And that's what I try to do

61
00:03:10,000 --> 00:03:12,600
Speaker 1: with my rising stars research when I do it on occasion.

62
00:03:12,680 --> 00:03:15,679
Speaker 1: So back to the indie rock thing sort of things

63
00:03:14,880 --> 00:03:17,000
Speaker 1: are the rocks maybe they make it maybe they don't.

64
00:03:18,200 --> 00:03:21,560
Speaker 1: This week on Trillions the Rising Stars of the E

65
00:03:21,680 --> 00:03:25,880
Speaker 1: t F World, we also have a guest Carolina Wilson,

66
00:03:26,040 --> 00:03:29,280
Speaker 1: who's a reporter with Bloomberg News. She also has a

67
00:03:29,400 --> 00:03:33,120
Speaker 1: daily column called E t F Watch, so she's almost

68
00:03:33,120 --> 00:03:35,800
Speaker 1: the perfect person to join us and talk about some

69
00:03:35,840 --> 00:03:39,160
Speaker 1: of the ones to watch right now. Carolina, Welcome to

70
00:03:39,200 --> 00:03:42,520
Speaker 1: the show. You weren't born in the eighties. It's not

71
00:03:43,160 --> 00:03:46,640
Speaker 1: when were you born in the year that fascinates me.

72
00:03:46,800 --> 00:03:49,680
Speaker 1: First of all, she doesn't know anything about this radio

73
00:03:49,720 --> 00:03:52,280
Speaker 1: station that you just talked about. Yeah, and like, to you,

74
00:03:52,280 --> 00:03:54,440
Speaker 1: you two is probably this sort of like old man

75
00:03:54,720 --> 00:03:58,840
Speaker 1: classic rock band, right right, like my dad's rock. But

76
00:03:58,960 --> 00:04:01,640
Speaker 1: in two, I'm telling you they were new wave, and

77
00:04:02,000 --> 00:04:03,560
Speaker 1: there is an equivalent to E t F. A lot

78
00:04:03,600 --> 00:04:05,640
Speaker 1: of millennials that's all they know is E t F.

79
00:04:05,680 --> 00:04:08,080
Speaker 1: They don't even know mutual funds anymore, and so there's

80
00:04:08,080 --> 00:04:11,040
Speaker 1: definitely a consistency there. But yeah, what is new wave

81
00:04:11,080 --> 00:04:13,480
Speaker 1: in current today is is going to seem like old

82
00:04:13,480 --> 00:04:16,880
Speaker 1: Fogy tomorrow? Do you remember the cassette? Oh the the act.

83
00:04:17,080 --> 00:04:18,640
Speaker 1: I was like, oh my god, they're gonna start asking

84
00:04:18,640 --> 00:04:20,800
Speaker 1: me about bands now that I don't know. Yes, I

85
00:04:20,800 --> 00:04:24,760
Speaker 1: know what a cassette is. I did, I did? Do you?

86
00:04:24,760 --> 00:04:28,000
Speaker 1: How do you listen to music now Spotify? Yeah? Me too?

87
00:04:28,040 --> 00:04:30,640
Speaker 1: You How about you? Are? I listened to through on

88
00:04:30,720 --> 00:04:33,120
Speaker 1: Sirius in my car and then I still use iTunes

89
00:04:33,760 --> 00:04:36,440
Speaker 1: old school. Yeah, I like to own it. My dad

90
00:04:36,600 --> 00:04:39,320
Speaker 1: is too year old. I am. I'm okay with the

91
00:04:39,320 --> 00:04:43,520
Speaker 1: world's changing. Eric, uh so, so Carolina, Um, we're gonna

92
00:04:43,520 --> 00:04:48,920
Speaker 1: have Eric present his rising Star system and then we're

93
00:04:48,920 --> 00:04:52,480
Speaker 1: going to critique a little bit. But let's look backwards, right, Eric,

94
00:04:52,720 --> 00:04:56,159
Speaker 1: So you use this and you you look backwards at

95
00:04:56,440 --> 00:04:58,680
Speaker 1: you know, ten years ago to see if you could

96
00:04:58,680 --> 00:05:02,799
Speaker 1: have identified ones from history that did break through. What

97
00:05:02,800 --> 00:05:06,400
Speaker 1: what tickers and e t f s popped? So in

98
00:05:06,560 --> 00:05:10,440
Speaker 1: June that's about what eighteen months ago, I looked at

99
00:05:10,440 --> 00:05:12,480
Speaker 1: the fastest growing e t F Here's how we do it.

100
00:05:12,760 --> 00:05:15,080
Speaker 1: We basically look for a minimum masset level. In the

101
00:05:15,120 --> 00:05:18,040
Speaker 1: case in June, I looked at one million minimum. Right,

102
00:05:18,360 --> 00:05:20,480
Speaker 1: you have to have something going on to start, if

103
00:05:20,480 --> 00:05:23,240
Speaker 1: you Yeah, if you look at an ETF that goes

104
00:05:23,279 --> 00:05:26,040
Speaker 1: from one million to ten, that's a thousand percent growth rate.

105
00:05:26,040 --> 00:05:28,680
Speaker 1: But that doesn't really You're right, so we look at

106
00:05:28,839 --> 00:05:31,280
Speaker 1: a decent base of a hundred million back then and

107
00:05:31,320 --> 00:05:34,160
Speaker 1: we saw which one's doubled assets A. So they grew

108
00:05:34,200 --> 00:05:38,560
Speaker 1: by a hundred percent and broke through the billion dollar mark. Um.

109
00:05:38,800 --> 00:05:42,080
Speaker 1: So there were five eighteen months ago that that fit

110
00:05:42,160 --> 00:05:45,320
Speaker 1: that threshold. Um, they were a mixed bag. If you

111
00:05:45,320 --> 00:05:47,640
Speaker 1: want to where are they now? And we'll look to today,

112
00:05:47,680 --> 00:05:52,560
Speaker 1: there was so that's a whole another thing. Yeah. So

113
00:05:52,640 --> 00:05:54,680
Speaker 1: one of them was the I Shares Edge ms C

114
00:05:54,760 --> 00:05:57,760
Speaker 1: I us a momentum ETF ticker m t u M.

115
00:05:57,800 --> 00:05:59,680
Speaker 1: At the time it had broken through to one point

116
00:05:59,760 --> 00:06:02,840
Speaker 1: three billions, so it made my list. Today it has

117
00:06:02,880 --> 00:06:07,039
Speaker 1: seven point four billion dollars. It returned in the eighteen

118
00:06:07,040 --> 00:06:11,040
Speaker 1: months since identified it smash hit. This was like my

119
00:06:11,279 --> 00:06:14,000
Speaker 1: you know, identifying that band before they break and all

120
00:06:14,000 --> 00:06:16,360
Speaker 1: the all the radio does now is play it. That's right.

121
00:06:16,480 --> 00:06:20,920
Speaker 1: So it's on every Spotify list. And Carolina she's probably

122
00:06:20,920 --> 00:06:23,440
Speaker 1: written about mt u M because the flows are always

123
00:06:23,520 --> 00:06:26,360
Speaker 1: making her radar. Yeah. Absolutely, But I feel like with

124
00:06:26,440 --> 00:06:28,960
Speaker 1: these we have, don't we have the same issue we

125
00:06:29,000 --> 00:06:31,560
Speaker 1: have with other single factor funds where they're cyclical, right,

126
00:06:31,560 --> 00:06:33,800
Speaker 1: so we see money pouring into them, but I think

127
00:06:33,839 --> 00:06:37,240
Speaker 1: on On Monday, m t U M fell three the

128
00:06:37,279 --> 00:06:40,760
Speaker 1: SMP filed two. We have analysts saying that the momentum

129
00:06:40,800 --> 00:06:43,200
Speaker 1: trade is over. Yes, this has grown a lot, but

130
00:06:43,760 --> 00:06:46,840
Speaker 1: because it's such a huge tech trade count, won't we

131
00:06:46,880 --> 00:06:49,880
Speaker 1: see investors yank money from this? Right? So the momentum etia,

132
00:06:50,000 --> 00:06:52,920
Speaker 1: for those who don't know, is basically it's following the heat.

133
00:06:52,960 --> 00:06:54,960
Speaker 1: It's looking for stocks that are doing well, and it

134
00:06:55,040 --> 00:06:58,400
Speaker 1: just sort of tries to copy what's done well. And

135
00:06:58,440 --> 00:07:00,280
Speaker 1: then it also has a screen for volatility, so it's

136
00:07:00,320 --> 00:07:02,920
Speaker 1: not too volatile. But long story short, it's performance chasing.

137
00:07:03,400 --> 00:07:06,080
Speaker 1: Right now, it's heavy tech, and it's it's gonna get hurt.

138
00:07:06,200 --> 00:07:08,360
Speaker 1: But if tech starts to go down, it's gonna try

139
00:07:08,400 --> 00:07:11,000
Speaker 1: to like sell the tech and latch onto what's doing well.

140
00:07:11,000 --> 00:07:14,119
Speaker 1: Maybe it's utilities, who knows, Yeah, that's all it does.

141
00:07:14,640 --> 00:07:16,840
Speaker 1: So it could have a rebound. But even if it

142
00:07:16,880 --> 00:07:19,720
Speaker 1: does struggle a lot of times, when assets enter an

143
00:07:19,720 --> 00:07:21,320
Speaker 1: e t F and it gets the seven eight billion,

144
00:07:21,640 --> 00:07:23,160
Speaker 1: even if it has a rough year, it's not gonna

145
00:07:23,160 --> 00:07:25,600
Speaker 1: lose all the assets. It might lose two three billion,

146
00:07:25,680 --> 00:07:28,160
Speaker 1: but it's it's it is now a legit and it's

147
00:07:28,200 --> 00:07:30,480
Speaker 1: the biggest momentum ETF, so it is the go to

148
00:07:30,640 --> 00:07:34,400
Speaker 1: for the momentum trade. So this one popped. One that

149
00:07:34,560 --> 00:07:36,640
Speaker 1: was a dud basically was f x U, which is

150
00:07:36,680 --> 00:07:40,680
Speaker 1: the first trust Utilities alphabex Um. This is utility stocks,

151
00:07:40,680 --> 00:07:43,760
Speaker 1: but it has an overlay of growth value screens. The

152
00:07:43,840 --> 00:07:45,720
Speaker 1: reason it made my list and I learned from this

153
00:07:45,840 --> 00:07:47,760
Speaker 1: is that it was used in a fund of funds

154
00:07:48,080 --> 00:07:50,120
Speaker 1: and once that fund of funds kicked it out, it

155
00:07:50,240 --> 00:07:53,600
Speaker 1: lost it. It's almost like it had like one gigantic investor,

156
00:07:54,320 --> 00:07:57,280
Speaker 1: and so it's shrunk to two hundred million from having

157
00:07:57,280 --> 00:07:59,960
Speaker 1: one point seven billion. So it's and it's only up

158
00:08:01,560 --> 00:08:04,920
Speaker 1: absolutely and there's a couple in the middle, like Jeffrey Gunlock,

159
00:08:05,000 --> 00:08:06,640
Speaker 1: the famous bond manager, has an e t F t

160
00:08:06,760 --> 00:08:09,160
Speaker 1: O t L the double line total return. That one

161
00:08:09,200 --> 00:08:11,080
Speaker 1: is up to three point four billion. That's a billion

162
00:08:11,080 --> 00:08:12,880
Speaker 1: more than when we identified it. It had a three

163
00:08:12,920 --> 00:08:15,240
Speaker 1: percent return. Pretty good. And then another one that I

164
00:08:15,320 --> 00:08:17,160
Speaker 1: was a pretty big hit was Noble. This is the

165
00:08:17,240 --> 00:08:21,320
Speaker 1: pro Shares SMP dividant aristocrats. It looks for companies that

166
00:08:21,320 --> 00:08:25,120
Speaker 1: have increased their dividends for twenty five straight years. It

167
00:08:25,240 --> 00:08:28,800
Speaker 1: is a rigid screen. How's Noble done in oh, b L,

168
00:08:29,000 --> 00:08:31,640
Speaker 1: how's that done? Pretty well? It was up eighteen months

169
00:08:31,640 --> 00:08:33,680
Speaker 1: since we looked at it. It's not three point four billion,

170
00:08:33,720 --> 00:08:36,600
Speaker 1: that's about double from when we identified it. So to me,

171
00:08:36,720 --> 00:08:40,840
Speaker 1: Noble was a legit hit from this list, even with

172
00:08:40,880 --> 00:08:44,840
Speaker 1: its really strict requirements. Yeah, and Noble is like, look,

173
00:08:44,920 --> 00:08:47,880
Speaker 1: everyone loves dividend paying stocks, even if you're not going

174
00:08:47,880 --> 00:08:49,600
Speaker 1: there for yield, because this thing doesn't yield a lot

175
00:08:49,640 --> 00:08:52,480
Speaker 1: because when you're that rigid, the stocks are going to

176
00:08:52,679 --> 00:08:56,120
Speaker 1: be low yielding. But people just love dividend paying stocks.

177
00:08:56,800 --> 00:08:59,720
Speaker 1: Envelope of cash from your grandmother. And it's also sturdy,

178
00:08:59,800 --> 00:09:02,800
Speaker 1: st already company. So Noble was probably very much in

179
00:09:02,800 --> 00:09:07,600
Speaker 1: a lot of like retirement accounts people who are conservative. Um,

180
00:09:07,679 --> 00:09:10,840
Speaker 1: and it it spawned a few copycats. So you know

181
00:09:10,920 --> 00:09:15,959
Speaker 1: you mentioned your class system earlier, Eric, because there's different

182
00:09:16,200 --> 00:09:19,800
Speaker 1: kind of thresholds that ets can kind of climb through. Right,

183
00:09:20,520 --> 00:09:22,680
Speaker 1: So when you think about what these ones that you

184
00:09:22,720 --> 00:09:26,520
Speaker 1: identified eighteen months ago, I've done where where? How far

185
00:09:26,559 --> 00:09:28,320
Speaker 1: did they get and how far could they go? Still?

186
00:09:28,800 --> 00:09:31,280
Speaker 1: So all of them over a billion? So I identified

187
00:09:31,360 --> 00:09:34,160
Speaker 1: them when they were sort of middle class into the

188
00:09:34,200 --> 00:09:37,400
Speaker 1: elite one billion. They cracked the top. Yeah, they're they're like,

189
00:09:37,440 --> 00:09:41,360
Speaker 1: they're rich. Basically they they except for f XU, which

190
00:09:41,400 --> 00:09:44,640
Speaker 1: actually backslid, but the other ones are now firmly in

191
00:09:44,679 --> 00:09:48,760
Speaker 1: this sort of elite category. All right, So we looked backward, Eric,

192
00:09:48,800 --> 00:09:52,640
Speaker 1: you've also refined the system because of that. So let's

193
00:09:52,679 --> 00:09:57,079
Speaker 1: talk about right now some current screamers that you've identified. Yeah,

194
00:09:57,120 --> 00:09:58,640
Speaker 1: I feel like the when I did in the past,

195
00:09:58,679 --> 00:10:00,680
Speaker 1: I got some more brand name is, like, you know,

196
00:10:00,760 --> 00:10:03,680
Speaker 1: Jeffrey Gunlock and Spider and I Shares. So I tweaked

197
00:10:03,679 --> 00:10:05,840
Speaker 1: it a little bit to try to get more indie

198
00:10:06,440 --> 00:10:08,480
Speaker 1: e t s in there, a little more theme ets,

199
00:10:08,559 --> 00:10:11,640
Speaker 1: because when you use a hundred million base, you tend

200
00:10:11,679 --> 00:10:13,040
Speaker 1: to screen out some of those. So I went to

201
00:10:13,040 --> 00:10:16,000
Speaker 1: a thirty million dollar base, and I just looked at

202
00:10:16,160 --> 00:10:19,880
Speaker 1: which one's had the biggest percentage jump in assets, but

203
00:10:20,160 --> 00:10:22,600
Speaker 1: I looked at flows. So in other words, who had

204
00:10:22,600 --> 00:10:26,200
Speaker 1: the biggest organic growth of the thirty million dollar base,

205
00:10:26,480 --> 00:10:29,400
Speaker 1: sorted by the percentage growth over the top five over

206
00:10:29,440 --> 00:10:34,400
Speaker 1: a year, so the past twelve months. And so we'll

207
00:10:34,440 --> 00:10:36,440
Speaker 1: start with the top. The one that just to me

208
00:10:36,720 --> 00:10:40,280
Speaker 1: was on top by a mile was Bots the Global

209
00:10:40,440 --> 00:10:43,880
Speaker 1: x Robotics and Artificial Intelligence ETF. It had thirty million

210
00:10:43,920 --> 00:10:46,800
Speaker 1: dollars a year ago. It's taken in two point three

211
00:10:46,880 --> 00:10:51,120
Speaker 1: billion dollars since then. That's a seven thousand eight increase

212
00:10:51,160 --> 00:10:53,360
Speaker 1: of organic growth in one e t F. I don't

213
00:10:53,600 --> 00:10:56,960
Speaker 1: that's literally going from oblivion to like firmly in the

214
00:10:57,000 --> 00:10:59,720
Speaker 1: elites in one year. It's that you'd never see that.

215
00:10:59,760 --> 00:11:03,560
Speaker 1: What is it do? So? Bots basically tracks companies that

216
00:11:03,600 --> 00:11:07,800
Speaker 1: are designing UH machines and robotics things for the military,

217
00:11:07,880 --> 00:11:12,000
Speaker 1: the household. It's basically tech and industrials, and it's companies

218
00:11:12,040 --> 00:11:15,920
Speaker 1: really focused on robotics and artificial intelligence. Carolina, had you

219
00:11:15,960 --> 00:11:18,760
Speaker 1: known about this one? Had this been on your list? Yeah? Absolutely?

220
00:11:18,800 --> 00:11:20,920
Speaker 1: And I think that it's it's hard to talk about

221
00:11:20,960 --> 00:11:26,520
Speaker 1: bots without mentioning it's like arch enemy Robo. Yeah, I

222
00:11:26,559 --> 00:11:33,040
Speaker 1: like that. Okay, Bots launched in September. Robo also following

223
00:11:33,120 --> 00:11:37,560
Speaker 1: this robotics and automation theme, launched in October. But since

224
00:11:37,640 --> 00:11:41,920
Speaker 1: Bots launched, it's basically outperformed Robo. You know, we're talking

225
00:11:41,920 --> 00:11:44,560
Speaker 1: about Bots being up about sixty one per cent since

226
00:11:44,559 --> 00:11:49,280
Speaker 1: it launched in September versus robos fifty three percent gain

227
00:11:49,440 --> 00:11:52,880
Speaker 1: in that same time frame. Um, it's funny because I

228
00:11:52,880 --> 00:11:58,119
Speaker 1: think less diversification has paid off. Here Bots holds thirty companies.

229
00:11:58,280 --> 00:12:02,080
Speaker 1: Robo I think is closer to what was it, ninety holdings.

230
00:12:02,480 --> 00:12:05,040
Speaker 1: But then you have a significant concentration risk, right, and

231
00:12:05,080 --> 00:12:07,640
Speaker 1: maybe this is where one of the cons one of

232
00:12:07,640 --> 00:12:11,600
Speaker 1: those conpoints come in for Bots. Yeah. Bots his market

233
00:12:11,600 --> 00:12:13,920
Speaker 1: cap weighted, as you know that that makes you have

234
00:12:14,040 --> 00:12:17,720
Speaker 1: more large cap exposure. Typically Robo is equal weighted in

235
00:12:17,800 --> 00:12:21,640
Speaker 1: two tiers, and uh, as Carolina said, it's a lot

236
00:12:21,679 --> 00:12:25,760
Speaker 1: more diversified. Bots had a few large caps that took off,

237
00:12:25,800 --> 00:12:28,840
Speaker 1: so it outperformed Robot. And you keep to go from

238
00:12:28,840 --> 00:12:32,280
Speaker 1: oblivion to the elite, It's usually always going to be

239
00:12:32,360 --> 00:12:34,560
Speaker 1: some kind of what I call a shiny object moment

240
00:12:34,559 --> 00:12:37,920
Speaker 1: where the performance is so outrageous people cannot ignore it.

241
00:12:38,240 --> 00:12:40,040
Speaker 1: They go after it like a shiny object and a

242
00:12:40,040 --> 00:12:44,920
Speaker 1: little child. Right. And so this thing was up at

243
00:12:44,920 --> 00:12:46,400
Speaker 1: one point over the past year. It's come down a

244
00:12:46,400 --> 00:12:49,480
Speaker 1: bit in the recent sell off, but it crushed Robo.

245
00:12:49,800 --> 00:12:53,160
Speaker 1: It's like Terminator too. This was like Robert Patrick, you know,

246
00:12:53,559 --> 00:12:55,880
Speaker 1: in the middle of the movie, just like a object

247
00:12:55,880 --> 00:13:00,360
Speaker 1: for you. Yeah, exactly well done, man, I like that, say, welcome,

248
00:13:00,400 --> 00:13:04,199
Speaker 1: there we go, we're cooking with and the fee right,

249
00:13:04,280 --> 00:13:10,000
Speaker 1: so robot charges basis points. Bots is at st so

250
00:13:10,120 --> 00:13:12,760
Speaker 1: bots are significantly cheaper the other thing bots has and

251
00:13:12,800 --> 00:13:15,920
Speaker 1: this is rare for me too. Product right robo existed

252
00:13:16,000 --> 00:13:18,040
Speaker 1: bots said, Hey, I like that. Let me come out

253
00:13:18,080 --> 00:13:20,920
Speaker 1: with one. This is global X. It's more liquid now

254
00:13:20,960 --> 00:13:24,080
Speaker 1: it's about double the trading volume. So I'm sure robot

255
00:13:24,160 --> 00:13:26,520
Speaker 1: is not thrilled about bots coming into play. But this

256
00:13:26,559 --> 00:13:28,560
Speaker 1: is how brutal the et F landscape is. You can

257
00:13:28,559 --> 00:13:31,760
Speaker 1: come out of the product that's very similar and just um,

258
00:13:31,800 --> 00:13:34,400
Speaker 1: you know, make you eat into that other person's market

259
00:13:34,640 --> 00:13:38,920
Speaker 1: specific rit man, every robot gets to find another robot. Okay,

260
00:13:38,920 --> 00:13:41,840
Speaker 1: so this is shiny object, but how are people going

261
00:13:41,880 --> 00:13:43,600
Speaker 1: to use it in their portfolio? When it comes to

262
00:13:43,640 --> 00:13:46,120
Speaker 1: theme ETFs, I highly recommend looking at two things. The

263
00:13:46,240 --> 00:13:49,920
Speaker 1: overlap with big indexes, like how much original exposure you getting.

264
00:13:49,960 --> 00:13:52,800
Speaker 1: So bots only has about one percent overlap with the

265
00:13:52,840 --> 00:13:55,600
Speaker 1: SMP five hundred in the MSCI world, So it's definitely

266
00:13:55,679 --> 00:13:58,560
Speaker 1: capturing a lot of unique companies. Now, granted it's got

267
00:13:58,920 --> 00:14:02,000
Speaker 1: paying companies and small HAPs and whatnot. But it's pretty original.

268
00:14:02,800 --> 00:14:05,000
Speaker 1: So I would say that given it that it does

269
00:14:05,040 --> 00:14:07,959
Speaker 1: have little overlap, which we call high active share, it

270
00:14:07,960 --> 00:14:10,280
Speaker 1: should be used like hot sauce. You know. It should

271
00:14:10,280 --> 00:14:12,640
Speaker 1: be something on the edge of a portfolio that you

272
00:14:12,720 --> 00:14:15,360
Speaker 1: just believe in, but you're gonna you know, it's got

273
00:14:15,400 --> 00:14:18,760
Speaker 1: what's more volatile than those indexes, so it could underperform

274
00:14:18,800 --> 00:14:22,520
Speaker 1: by more than the index. So essentially it's something to

275
00:14:22,520 --> 00:14:25,800
Speaker 1: be used in small proportions, likely um and something that

276
00:14:25,840 --> 00:14:28,320
Speaker 1: you have to maybe really believe in the story because

277
00:14:28,320 --> 00:14:31,200
Speaker 1: you're probably gonna experience some pretty nasty sell offs here

278
00:14:31,200 --> 00:14:42,240
Speaker 1: and there. Okay, next Rising Star. The next one is

279
00:14:42,240 --> 00:14:45,040
Speaker 1: the Arc web X point oh e t F, another

280
00:14:45,080 --> 00:14:48,000
Speaker 1: futuristic sounding et F with the ticker r k W.

281
00:14:48,680 --> 00:14:50,800
Speaker 1: It had twenty one million dollars a year ago. It's

282
00:14:50,840 --> 00:14:54,800
Speaker 1: taken in four hundred and three million since then. That's increase.

283
00:14:54,880 --> 00:14:57,640
Speaker 1: And this one just went won an award, right, No,

284
00:14:58,040 --> 00:15:00,360
Speaker 1: So the one that won an award was a r

285
00:15:00,440 --> 00:15:03,000
Speaker 1: k K a sister e t F called Arc Innovation.

286
00:15:03,480 --> 00:15:06,200
Speaker 1: So this is a fun family that is managed by

287
00:15:06,480 --> 00:15:10,480
Speaker 1: a woman named Cathy Wood, and they are all active

288
00:15:10,840 --> 00:15:13,240
Speaker 1: and all really a lot of the products are looking

289
00:15:13,280 --> 00:15:17,800
Speaker 1: at like futuristic themes like innovation, the human genome, three

290
00:15:17,880 --> 00:15:22,520
Speaker 1: D printing, industrial innovation. So they try to see themselves

291
00:15:22,600 --> 00:15:26,280
Speaker 1: as a the closest thing to a venture capitalist, that

292
00:15:26,360 --> 00:15:28,640
Speaker 1: is an active manager. That's interesting, right, and and that's

293
00:15:28,760 --> 00:15:32,320
Speaker 1: a place that active can actually play, right. So arc

294
00:15:32,760 --> 00:15:34,760
Speaker 1: A r k W this this e t F is

295
00:15:34,840 --> 00:15:39,040
Speaker 1: up a hundred and fift since launching in the past year,

296
00:15:39,400 --> 00:15:41,440
Speaker 1: and even six percent year to date. It's been a

297
00:15:41,520 --> 00:15:44,720
Speaker 1: rough year for internet type stocks, but it's still outperforming

298
00:15:45,160 --> 00:15:49,080
Speaker 1: and it's been rewarded. If you can not just beat

299
00:15:49,120 --> 00:15:52,000
Speaker 1: the SMP by a couple percentage points, but if you

300
00:15:52,040 --> 00:15:55,080
Speaker 1: can crush it into oblivion, stomp on it and do

301
00:15:55,120 --> 00:15:58,320
Speaker 1: a touchdown dance on its head, you will get assets.

302
00:15:58,680 --> 00:16:00,360
Speaker 1: And that is the name of the game these days.

303
00:16:00,400 --> 00:16:02,280
Speaker 1: I don't it's either all the money is going to

304
00:16:02,360 --> 00:16:05,520
Speaker 1: cheap beta or these shiny objects that just basically run

305
00:16:05,600 --> 00:16:09,080
Speaker 1: circles around the market. So currently, tell me about what

306
00:16:09,240 --> 00:16:13,480
Speaker 1: this one does. Well, So Eric mentioned futuristic themes, it's

307
00:16:13,480 --> 00:16:16,480
Speaker 1: definitely capitalizing on that. But I think another way to

308
00:16:16,520 --> 00:16:19,800
Speaker 1: say that is that it's it's using these giant buzzwords

309
00:16:19,920 --> 00:16:23,960
Speaker 1: right now. Right, So internet of things, cloud, computing, digital currencies.

310
00:16:24,000 --> 00:16:25,880
Speaker 1: I think r W was one of the first U

311
00:16:25,960 --> 00:16:29,120
Speaker 1: s ETFs to have indirect exposure to bitcoin because it

312
00:16:29,280 --> 00:16:31,160
Speaker 1: held I think it's largest holding at one point was

313
00:16:31,240 --> 00:16:34,640
Speaker 1: g BTC, which was this um private vehicle, but this

314
00:16:34,800 --> 00:16:39,040
Speaker 1: Bitcoin trust and r K it's sister fund that you

315
00:16:39,120 --> 00:16:41,200
Speaker 1: had mentioned earlier also held it. But I think that

316
00:16:41,480 --> 00:16:44,720
Speaker 1: it's using some of those things to its advantage, right, Yeah,

317
00:16:44,720 --> 00:16:46,360
Speaker 1: And I think if you look at the holdings, let's

318
00:16:46,360 --> 00:16:49,680
Speaker 1: just look at some of the stocks and here Amazon, Tesla, Twitter,

319
00:16:50,200 --> 00:16:53,800
Speaker 1: basically fang Fund. Yeah, it's it. There's but it's still

320
00:16:53,880 --> 00:16:57,280
Speaker 1: not that much overlap with the SMP. It's got only

321
00:16:58,040 --> 00:17:00,800
Speaker 1: overlap with that or the tech ETF. And it's interesting.

322
00:17:00,880 --> 00:17:02,920
Speaker 1: We had Kathy Wood on this the E t F

323
00:17:02,960 --> 00:17:05,760
Speaker 1: TV show I do, and we asked her about, hey,

324
00:17:05,800 --> 00:17:09,040
Speaker 1: aren't these high octane stocks just gonna like just crash

325
00:17:09,080 --> 00:17:12,280
Speaker 1: and the performance will suffer. She said something that you know,

326
00:17:12,440 --> 00:17:16,119
Speaker 1: was very noteworthy, which is she considers this portfolio deep value.

327
00:17:16,280 --> 00:17:19,520
Speaker 1: She considers Amazon deep value. She just says, you have

328
00:17:19,560 --> 00:17:21,480
Speaker 1: to think about it ten twenty years down the road,

329
00:17:21,560 --> 00:17:25,360
Speaker 1: and she just Amazon in particular. She's very bullish on

330
00:17:25,400 --> 00:17:28,600
Speaker 1: that stock more than the other Fang stocks and thinks

331
00:17:28,640 --> 00:17:30,960
Speaker 1: that that company is just um, you know, going to

332
00:17:31,080 --> 00:17:35,040
Speaker 1: really change the game and multiple ways. So I think,

333
00:17:35,680 --> 00:17:37,679
Speaker 1: you know, you make a strong sales case here, but

334
00:17:37,720 --> 00:17:39,680
Speaker 1: you have to have the performance to back it up.

335
00:17:39,920 --> 00:17:43,760
Speaker 1: And then for now she does, and then uh, it's look,

336
00:17:43,840 --> 00:17:48,479
Speaker 1: the PE ratio is so high it's negative. It's like

337
00:17:48,920 --> 00:17:51,200
Speaker 1: it's like gone to kill screen because it's got companies

338
00:17:51,200 --> 00:17:53,960
Speaker 1: with negative earnings, and so it's it's just, look, this

339
00:17:54,000 --> 00:17:57,879
Speaker 1: is very volatile, high high price to earnings ratio. You're

340
00:17:57,920 --> 00:18:01,240
Speaker 1: paying a lot for the stocks basically, and it's costly

341
00:18:01,280 --> 00:18:04,679
Speaker 1: at seventy five basis points. Okay, so the next rising

342
00:18:04,720 --> 00:18:08,480
Speaker 1: star I like. I like this one because it's somewhat expected, right,

343
00:18:09,000 --> 00:18:13,560
Speaker 1: and it looks outside the US because it's the emerging

344
00:18:13,640 --> 00:18:17,280
Speaker 1: market Internet. Yes, e m q Q went from thirty

345
00:18:17,280 --> 00:18:20,119
Speaker 1: four million dollars this time last year and it's taken

346
00:18:20,119 --> 00:18:22,640
Speaker 1: in four hundred and four million, and that's a one

347
00:18:22,640 --> 00:18:26,720
Speaker 1: tho increase in organic flows. I have a great story here.

348
00:18:27,200 --> 00:18:30,719
Speaker 1: So I interviewed UM in May almost a year ago.

349
00:18:30,800 --> 00:18:33,280
Speaker 1: Kevin Carter, he's the founder of the fund. Here in

350
00:18:33,320 --> 00:18:36,320
Speaker 1: the Bloomberg office, we sat on one of these red booths. Uh,

351
00:18:36,359 --> 00:18:39,520
Speaker 1: mostly because his fund was up like a whopping. It

352
00:18:39,560 --> 00:18:41,720
Speaker 1: was tiny. I had to like beg my editors to

353
00:18:41,800 --> 00:18:44,080
Speaker 1: let me write about this tiny, tiny, forty eight million

354
00:18:44,160 --> 00:18:47,000
Speaker 1: dollar fund. And the headline that came out of that

355
00:18:47,000 --> 00:18:51,560
Speaker 1: story was Chinese tech investments spur huge returns for pint

356
00:18:51,680 --> 00:18:54,879
Speaker 1: sized fund. And I spoke to him maybe five or

357
00:18:54,880 --> 00:18:56,920
Speaker 1: six months later. I think he called me. He was like,

358
00:18:57,040 --> 00:19:00,080
Speaker 1: they had over four hundred million in assets, and he

359
00:19:00,160 --> 00:19:01,919
Speaker 1: was like, remember when you called my e t F

360
00:19:01,960 --> 00:19:05,760
Speaker 1: a pine sized fund. Listen these issues given like, no,

361
00:19:05,840 --> 00:19:09,360
Speaker 1: it's my editor. Yeah, you forget, like especially this one.

362
00:19:09,400 --> 00:19:11,640
Speaker 1: This is just one guy and an idea. So he's

363
00:19:11,640 --> 00:19:14,600
Speaker 1: out there and so he really gets takes the media

364
00:19:14,880 --> 00:19:17,840
Speaker 1: coverage seriously and that that one idea that he had though,

365
00:19:17,960 --> 00:19:21,119
Speaker 1: was he wanted more China exposure because he looked at

366
00:19:21,160 --> 00:19:24,080
Speaker 1: emerging market e t f s and realized that he

367
00:19:24,119 --> 00:19:26,800
Speaker 1: couldn't get as much China as you wanted, and so

368
00:19:26,960 --> 00:19:29,160
Speaker 1: e m q Q became the vehicle to do that. Right.

369
00:19:29,200 --> 00:19:31,880
Speaker 1: It's funny because Eric he coined this perfectly. He said

370
00:19:31,920 --> 00:19:34,959
Speaker 1: that this fund had a triple dose of China. I

371
00:19:35,000 --> 00:19:38,840
Speaker 1: think it holds over sixty of its geographic allocation to

372
00:19:39,080 --> 00:19:41,879
Speaker 1: Chinese companies. You compare that to e M, the colossal

373
00:19:41,920 --> 00:19:45,200
Speaker 1: I Shares Emerging Markets fund that has like so that's

374
00:19:45,200 --> 00:19:47,520
Speaker 1: where that triple dose comes in. But yeah, it's a

375
00:19:47,560 --> 00:19:52,640
Speaker 1: super targeted Chinese Internet uh play and hugely popular, and

376
00:19:52,760 --> 00:19:55,480
Speaker 1: yes it's six China. But let's just take a bigger,

377
00:19:55,480 --> 00:19:57,800
Speaker 1: broader step back. The emerging markets e t f s

378
00:19:57,840 --> 00:20:00,280
Speaker 1: like e M and vw O that people use, they

379
00:20:00,320 --> 00:20:04,000
Speaker 1: only have about seven, eight, maybe ten percent tech. The

380
00:20:04,119 --> 00:20:07,320
Speaker 1: SMP is like what tech, So you could argue that

381
00:20:07,359 --> 00:20:10,959
Speaker 1: the big emerging markets in indices are underweight tech. This

382
00:20:11,000 --> 00:20:12,840
Speaker 1: is a case of an e t F that just saw,

383
00:20:13,000 --> 00:20:14,959
Speaker 1: and this is how a lot of ETF innovation happens.

384
00:20:15,240 --> 00:20:17,639
Speaker 1: It sees a flaw in one of the big guys,

385
00:20:18,119 --> 00:20:20,760
Speaker 1: and it basically comes out and tries to fill that gap.

386
00:20:21,280 --> 00:20:23,199
Speaker 1: And this I think was the complaint of hey, my

387
00:20:23,240 --> 00:20:26,399
Speaker 1: emerging markets e t F isn't really capturing this like

388
00:20:27,000 --> 00:20:30,119
Speaker 1: juggernaut tech movement in the emerging markets, and so this

389
00:20:30,160 --> 00:20:32,639
Speaker 1: one comes out and fills a void. Going back to

390
00:20:32,680 --> 00:20:34,760
Speaker 1: the music analogy, Eric, at one point you said, this

391
00:20:34,840 --> 00:20:38,399
Speaker 1: is a mash up it's combining two hugely popular trends

392
00:20:38,480 --> 00:20:42,679
Speaker 1: into one fund. Okay, so we got one more current

393
00:20:42,840 --> 00:20:45,240
Speaker 1: rising star that you've identified. What is that? The Crane

394
00:20:45,240 --> 00:20:47,800
Speaker 1: Shares Bill Serrah ms C I China A share e

395
00:20:47,880 --> 00:20:50,320
Speaker 1: t F k B A went from thirty five million

396
00:20:50,440 --> 00:20:52,399
Speaker 1: in this time last year and it's taken two hundred

397
00:20:52,480 --> 00:20:55,760
Speaker 1: and eighty million since then. And that's a lot for

398
00:20:55,800 --> 00:20:58,320
Speaker 1: a single country. And it's just part of a single country.

399
00:20:58,359 --> 00:21:00,600
Speaker 1: It's just the A shares of China. But what this

400
00:21:00,640 --> 00:21:03,000
Speaker 1: one does that a lot of people like it's It's

401
00:21:03,040 --> 00:21:05,000
Speaker 1: performance has only been four percent, so unlike the other

402
00:21:05,000 --> 00:21:07,800
Speaker 1: ones which have had that shiny object moment, this one

403
00:21:07,840 --> 00:21:11,040
Speaker 1: has something really interesting, which is that China a share

404
00:21:11,080 --> 00:21:14,080
Speaker 1: market has largely been out of out of sight because

405
00:21:14,119 --> 00:21:16,800
Speaker 1: it's only available to mainly investors. China's opening up their

406
00:21:16,840 --> 00:21:20,119
Speaker 1: markets and so now big indexes like the MSc Emerging

407
00:21:20,200 --> 00:21:24,000
Speaker 1: Markets are going to accept China shares years. This a

408
00:21:24,119 --> 00:21:27,239
Speaker 1: t F holds all the stocks that will ultimately make

409
00:21:27,320 --> 00:21:29,240
Speaker 1: it into the MSc Emerging Markets. So a lot of

410
00:21:29,240 --> 00:21:32,920
Speaker 1: people buy it thinking, wow, there's two trillion benchmark to

411
00:21:32,920 --> 00:21:35,800
Speaker 1: the Emerging Markets index. If I hold this. A lot

412
00:21:35,880 --> 00:21:37,520
Speaker 1: of these all that money is going to have to

413
00:21:37,640 --> 00:21:40,720
Speaker 1: buy a shares just to keep up with the index. Therefore,

414
00:21:40,720 --> 00:21:42,840
Speaker 1: there'll be bid orders coming in for the next five years.

415
00:21:42,920 --> 00:21:45,320
Speaker 1: I'll just sit tight here for five or ten years

416
00:21:45,400 --> 00:21:47,200
Speaker 1: and hold the stocks that they're going to need later.

417
00:21:47,560 --> 00:21:50,800
Speaker 1: It seems like a crystal ball, but there's no there's

418
00:21:50,800 --> 00:21:53,000
Speaker 1: no sure thing or free lunch. But that is why

419
00:21:53,080 --> 00:21:54,719
Speaker 1: the money is going to something that's only up four

420
00:21:54,760 --> 00:21:57,240
Speaker 1: percent this year. They're they're planting their steak in the

421
00:21:57,320 --> 00:21:59,360
Speaker 1: ground and hoping that the money sort of comes over

422
00:21:59,720 --> 00:22:01,919
Speaker 1: because as those stocks are going to be owned more

423
00:22:01,920 --> 00:22:05,400
Speaker 1: and more by foreign investors soon. Okay, so we've talked

424
00:22:05,400 --> 00:22:08,840
Speaker 1: about some hits that have had breakthrough moments, some ones

425
00:22:08,920 --> 00:22:11,440
Speaker 1: that are on the radio right now. Let's go ahead

426
00:22:11,440 --> 00:22:16,159
Speaker 1: and like look forward program Carolina's Spotify playlist for for

427
00:22:16,359 --> 00:22:20,040
Speaker 1: a year from now. What are the future screamers. One

428
00:22:20,200 --> 00:22:23,800
Speaker 1: is pave the Global X Infrastructure et F. If if

429
00:22:23,880 --> 00:22:27,080
Speaker 1: the infrastructure plans get done at some point, we're talking

430
00:22:27,119 --> 00:22:29,720
Speaker 1: a couple of trillion dollars in spenditures. This e t

431
00:22:29,960 --> 00:22:33,160
Speaker 1: F is all US companies, and we know Trump likes

432
00:22:33,200 --> 00:22:38,040
Speaker 1: the higher US. It's also specifically shaved out utilities to

433
00:22:38,160 --> 00:22:39,960
Speaker 1: a degree where it doesn't have as much rate risk,

434
00:22:40,080 --> 00:22:42,320
Speaker 1: right because those are sensitive to interest rates. So if

435
00:22:42,440 --> 00:22:45,720
Speaker 1: rates rise in infrastructure spending happens, this one's kind of

436
00:22:45,800 --> 00:22:47,960
Speaker 1: built for that, for that long haul. So I could

437
00:22:48,000 --> 00:22:51,240
Speaker 1: see this one, you know, sort of getting some traction

438
00:22:51,400 --> 00:22:54,720
Speaker 1: if the infrastructure plan goes through. Pave. Okay, that's good, Carolina.

439
00:22:54,720 --> 00:22:57,359
Speaker 1: What's your top pick? I like k Web. I mean

440
00:22:57,680 --> 00:23:00,240
Speaker 1: this is actually another Crane shares fund, so some learned

441
00:23:00,280 --> 00:23:02,520
Speaker 1: to the one that we had just talked about. But

442
00:23:02,640 --> 00:23:06,399
Speaker 1: it's very similar in exposure to e m q Q,

443
00:23:07,160 --> 00:23:09,760
Speaker 1: except that I think it's an even more pure play

444
00:23:09,880 --> 00:23:14,200
Speaker 1: China Internet uh fund. It has almost of its exposure

445
00:23:14,240 --> 00:23:20,560
Speaker 1: to China to internet companies. It's cheaper also than e

446
00:23:20,760 --> 00:23:23,359
Speaker 1: m q Q is at seventy two basis points versus

447
00:23:23,440 --> 00:23:25,399
Speaker 1: e m q q is eight six basis points. So

448
00:23:25,480 --> 00:23:28,280
Speaker 1: I just think it's a more targeted, pure play China

449
00:23:28,359 --> 00:23:33,240
Speaker 1: Internet exposure fund if that's what you're looking for. Laying

450
00:23:33,280 --> 00:23:37,760
Speaker 1: down the tracks on this Spotify playlist, paved, k Web, Eric,

451
00:23:37,880 --> 00:23:41,560
Speaker 1: what's track three on your future Screamer playlist? Okay, the

452
00:23:41,680 --> 00:23:44,840
Speaker 1: Granite Shares has to commodity E T F S BAR,

453
00:23:45,359 --> 00:23:47,520
Speaker 1: which is just like g l D. It's it's gold,

454
00:23:47,960 --> 00:23:50,200
Speaker 1: but it charges twenty basis points, so it's like a

455
00:23:50,520 --> 00:23:53,879
Speaker 1: It's basically they van guarded the commodity space and they

456
00:23:53,920 --> 00:23:55,200
Speaker 1: came out with the E t F that's half the

457
00:23:55,240 --> 00:23:57,639
Speaker 1: cost of g l D. And then the other one

458
00:23:57,760 --> 00:23:59,680
Speaker 1: is also Commodity c O m B, which is a

459
00:24:00,000 --> 00:24:02,960
Speaker 1: sort of all commodities in one giant basket, and that

460
00:24:03,119 --> 00:24:05,560
Speaker 1: only charges twenty five basis points. Here's why I think

461
00:24:05,600 --> 00:24:08,800
Speaker 1: these could hit. Commodities at some point are going to

462
00:24:08,840 --> 00:24:10,920
Speaker 1: outperform the other as a classes. It could be this year.

463
00:24:10,960 --> 00:24:13,440
Speaker 1: It's looking like it could be. And if and when

464
00:24:13,520 --> 00:24:15,720
Speaker 1: that happens and the money you know, comes over and

465
00:24:15,800 --> 00:24:18,200
Speaker 1: buys up commodities because stocks and bonds aren't doing well,

466
00:24:18,920 --> 00:24:21,600
Speaker 1: these are going to be in good positions. Because yes,

467
00:24:22,040 --> 00:24:24,040
Speaker 1: so they came in last year when no one won

468
00:24:24,080 --> 00:24:28,480
Speaker 1: of commodities and they vanguarded the category. Currently, they came

469
00:24:28,520 --> 00:24:31,040
Speaker 1: in two to three times cheaper than anyone else. Et

470
00:24:31,160 --> 00:24:33,320
Speaker 1: F Securities also has a couple of cheap But if

471
00:24:33,359 --> 00:24:34,920
Speaker 1: and when there's this flood of money, I see the

472
00:24:34,960 --> 00:24:38,119
Speaker 1: advisor crowd choosing the cheaper ones because they love nothing

473
00:24:38,200 --> 00:24:40,359
Speaker 1: more than the cheapest product. So I look out for

474
00:24:40,440 --> 00:24:44,600
Speaker 1: granite shares to maybe make some headway into the commodity category.

475
00:24:45,280 --> 00:24:48,480
Speaker 1: Commodities on this playlist, Carolina, what's your next track? I

476
00:24:48,600 --> 00:24:51,960
Speaker 1: like a fund the takers jets US Global Jet CTF,

477
00:24:52,240 --> 00:24:58,080
Speaker 1: so it holds US and international passenger airlines, aircraft manufacturers, airports,

478
00:24:58,200 --> 00:25:04,320
Speaker 1: terminal services companies. It launched in April, so a few

479
00:25:04,400 --> 00:25:07,359
Speaker 1: years ago, and it just crossed the hundred million dollar

480
00:25:07,440 --> 00:25:09,960
Speaker 1: asset line there and I think it's it's interesting because

481
00:25:09,960 --> 00:25:12,720
Speaker 1: it is almost like this little smart beta play on

482
00:25:12,800 --> 00:25:17,840
Speaker 1: a specific industry. It's outperformed the broader airline index by

483
00:25:18,000 --> 00:25:20,440
Speaker 1: almost eight percent. That's really boosted by the funds holding

484
00:25:20,840 --> 00:25:23,719
Speaker 1: of Boeing, which is interesting to this week in light

485
00:25:23,800 --> 00:25:27,439
Speaker 1: of the China tariffs news. It's interesting. You know, jets,

486
00:25:28,040 --> 00:25:30,000
Speaker 1: we talked about a weedo We had that ticker competition.

487
00:25:30,600 --> 00:25:33,920
Speaker 1: Jets is a great ticker, But the E t F

488
00:25:34,000 --> 00:25:36,280
Speaker 1: that preceded it, that lived and died and is currently

489
00:25:36,359 --> 00:25:39,200
Speaker 1: the graveyard f a A was the Airline et F.

490
00:25:39,359 --> 00:25:41,119
Speaker 1: This is a rare case where an E t F

491
00:25:41,240 --> 00:25:45,919
Speaker 1: comes out tracking airlines. It fails, but then someone else says, actually,

492
00:25:46,040 --> 00:25:48,240
Speaker 1: we can make this work, and they launched one despite

493
00:25:48,280 --> 00:25:50,080
Speaker 1: the failure of the first one. Well, jets is a

494
00:25:50,119 --> 00:25:52,760
Speaker 1: way better ticker than a government agency. To cale, you

495
00:25:52,840 --> 00:25:55,720
Speaker 1: got bounced in the first round for picking Tan in

496
00:25:55,880 --> 00:25:59,280
Speaker 1: our Ticker Madness episode, do you, in hindsight wish you

497
00:25:59,280 --> 00:26:02,399
Speaker 1: would have picked Jet? No. I stand by my my

498
00:26:02,640 --> 00:26:07,520
Speaker 1: Tan designation. Alright, Eric, next track on your Rising Star playlist.

499
00:26:07,640 --> 00:26:10,960
Speaker 1: Mj X The Alternative Harvest e t F. Which alternative

500
00:26:10,960 --> 00:26:13,240
Speaker 1: harvest is like code word for pot. It's kind of

501
00:26:13,280 --> 00:26:16,560
Speaker 1: what marijuna. Yeah, that's what you and your buddies called

502
00:26:16,600 --> 00:26:18,480
Speaker 1: it in college when you were trying to you know,

503
00:26:19,160 --> 00:26:23,000
Speaker 1: the down low. Anyway, m j X. The reason I

504
00:26:23,080 --> 00:26:25,840
Speaker 1: think it's already got four hundred million, But this is

505
00:26:25,920 --> 00:26:29,600
Speaker 1: just a hot area that could just explode. This could

506
00:26:29,600 --> 00:26:34,160
Speaker 1: create shiny object if and when it's getting legalized. Well

507
00:26:34,480 --> 00:26:37,119
Speaker 1: now it is what Jeff Sessions is on this. But

508
00:26:37,880 --> 00:26:40,880
Speaker 1: you know, over time, if if pot ultimately just gets

509
00:26:41,000 --> 00:26:44,399
Speaker 1: legalized in all these places, especially recreationally, I mean, I

510
00:26:44,480 --> 00:26:46,600
Speaker 1: don't really see how money doesn't come into this and

511
00:26:46,880 --> 00:26:49,560
Speaker 1: it become a big deal. Right now, it's struggled with performance,

512
00:26:49,600 --> 00:26:52,000
Speaker 1: but four million out of the gate isn't bad. It's

513
00:26:52,000 --> 00:26:54,840
Speaker 1: gonna track pot stocks and this is where you want

514
00:26:54,880 --> 00:26:56,920
Speaker 1: an e t F. And I've had people ask me

515
00:26:57,000 --> 00:26:58,639
Speaker 1: for pot e TF for a while because no one

516
00:26:58,680 --> 00:27:00,560
Speaker 1: wants to pick a pot stock because they could go,

517
00:27:00,680 --> 00:27:03,200
Speaker 1: you know, to blow up potentials high. So you have

518
00:27:03,320 --> 00:27:06,119
Speaker 1: a diversified basket of pot stocks. They're all sort of

519
00:27:06,600 --> 00:27:08,320
Speaker 1: young up and comers trying to make it in this

520
00:27:08,440 --> 00:27:11,160
Speaker 1: new industry, and this one captures it. And I could

521
00:27:11,160 --> 00:27:14,120
Speaker 1: see this being um big in the future, if, if,

522
00:27:14,200 --> 00:27:17,480
Speaker 1: and when pot does ultimately become legal. So maybe that's

523
00:27:17,480 --> 00:27:21,359
Speaker 1: a long term play. Kelly, that your last track? What

524
00:27:21,480 --> 00:27:23,119
Speaker 1: do you? What do you put when you back when

525
00:27:23,160 --> 00:27:25,960
Speaker 1: we made cassettes, we would try and end that cassette

526
00:27:26,000 --> 00:27:28,320
Speaker 1: with a really great song. So I'm gonna give you

527
00:27:28,320 --> 00:27:32,639
Speaker 1: a ticker that I would have swapped mind ticker good setup.

528
00:27:32,720 --> 00:27:37,000
Speaker 1: Alright's LIT, which is the Global x Lithium and Battery

529
00:27:37,040 --> 00:27:39,119
Speaker 1: Technology t F. It's a bit older it launched in

530
00:27:39,800 --> 00:27:43,560
Speaker 1: but it's nearing a billion dollars in assets. Um I

531
00:27:43,600 --> 00:27:47,200
Speaker 1: don't know. I mean, like we see global lithium miners

532
00:27:47,240 --> 00:27:51,760
Speaker 1: and battery producers their their stocks soaring. Obviously there's rising

533
00:27:51,800 --> 00:27:54,800
Speaker 1: demand for lithium because of electric vehicle makers like Tesla.

534
00:27:55,000 --> 00:27:57,840
Speaker 1: I think it's gonna continue to be a good go

535
00:27:58,040 --> 00:28:01,000
Speaker 1: to et F. I mean has that kind of commodity angle,

536
00:28:01,080 --> 00:28:04,680
Speaker 1: it has that futuristic Tesla electric vehicle angle. It's a

537
00:28:04,760 --> 00:28:08,400
Speaker 1: it's a good it's very specific, very specific. Okay, that's interesting.

538
00:28:08,400 --> 00:28:10,159
Speaker 1: I would I would flip the cassette over to keep

539
00:28:10,200 --> 00:28:13,159
Speaker 1: listening to her. I think, but we've come to the end. Eric,

540
00:28:13,240 --> 00:28:15,159
Speaker 1: Do you have a closing thought that you want to

541
00:28:15,240 --> 00:28:18,200
Speaker 1: talk about with these rising stars? Yeah, you know, just

542
00:28:18,320 --> 00:28:20,880
Speaker 1: because they've gotten assets in the past and we're trying

543
00:28:20,920 --> 00:28:24,040
Speaker 1: to identify swells before they become waves. It doesn't necessarily

544
00:28:24,119 --> 00:28:26,680
Speaker 1: the performance is always a question mark, and we have

545
00:28:26,800 --> 00:28:29,920
Speaker 1: to make that clear. Uh. And so I think typically

546
00:28:30,200 --> 00:28:32,520
Speaker 1: the performance will get an investor's attention, but the question

547
00:28:32,600 --> 00:28:35,719
Speaker 1: is do you really like the story because that you're

548
00:28:35,760 --> 00:28:38,160
Speaker 1: gonna have to like the story because the performance is

549
00:28:38,200 --> 00:28:40,480
Speaker 1: going to come and go. So I think that's where

550
00:28:40,680 --> 00:28:43,760
Speaker 1: a bots gets a lot of help. And lithium is

551
00:28:43,800 --> 00:28:48,280
Speaker 1: because people see the performance but they're like, actually, no,

552
00:28:48,360 --> 00:28:50,680
Speaker 1: wonder it's out performing. I've heard a lot about electric cars.

553
00:28:50,720 --> 00:28:52,960
Speaker 1: I've heard about a lot of robots. They buy into

554
00:28:53,000 --> 00:28:55,240
Speaker 1: the story, and that's key because you're going to have

555
00:28:55,400 --> 00:28:57,840
Speaker 1: to hang in there because these kind of some of

556
00:28:57,920 --> 00:29:00,400
Speaker 1: these themes are difficult to do. But also really I

557
00:29:00,520 --> 00:29:03,800
Speaker 1: think for investors out there, a lot of people now

558
00:29:03,960 --> 00:29:07,000
Speaker 1: are changing their portfolios as they kick out active mutual funds.

559
00:29:07,280 --> 00:29:10,120
Speaker 1: They're going real cheap core with real like you know,

560
00:29:10,560 --> 00:29:14,280
Speaker 1: boring plain vanilla type e t F or index funds

561
00:29:14,280 --> 00:29:17,600
Speaker 1: in the core keeping costs almost two nil. Then they're

562
00:29:17,640 --> 00:29:19,800
Speaker 1: on the outside, they're playing with some hot sauce, and

563
00:29:19,840 --> 00:29:21,240
Speaker 1: these are kind of I think some of the ones

564
00:29:21,320 --> 00:29:25,440
Speaker 1: that you decorate the portfolio within small sauce, the new

565
00:29:25,520 --> 00:29:29,920
Speaker 1: hot sauce. I'm not. I don't like hot sauce, butet

566
00:29:29,960 --> 00:29:32,200
Speaker 1: you drop it all the time. I do because that

567
00:29:32,440 --> 00:29:35,120
Speaker 1: that's I can only equate this too. Or you know,

568
00:29:35,200 --> 00:29:37,840
Speaker 1: putting garlic on a dish, it's like something it's used

569
00:29:37,840 --> 00:29:44,520
Speaker 1: in minor proportions to accent the DISHU truffle. It's a

570
00:29:44,600 --> 00:29:47,160
Speaker 1: good one, all right, Carolina, thank you so much for

571
00:29:47,240 --> 00:29:57,120
Speaker 1: joining us. Eric Balcinas, thank you, thank you. Okay, thanks

572
00:29:57,120 --> 00:29:59,840
Speaker 1: for listening. Trillion Until next time, you can find us

573
00:29:59,880 --> 00:30:03,760
Speaker 1: on Bloomberg terminal Bloomberg dot Com, Apple Podcasts, and a

574
00:30:03,840 --> 00:30:06,400
Speaker 1: bunch of other places I haven't heard about yet. We'd

575
00:30:06,440 --> 00:30:09,120
Speaker 1: love to hear from you. We're on Twitter, I'm at

576
00:30:09,240 --> 00:30:12,960
Speaker 1: Joel Webber Show, He's at Eric Balcunas, and you can

577
00:30:13,000 --> 00:30:19,360
Speaker 1: find Carolina Wilson at Caro E. Wilson. Trillions is produced

578
00:30:19,560 --> 00:30:23,240
Speaker 1: by Magnus Hendrickson. Francesco Levi is the head of Bloomberg

579
00:30:23,280 --> 00:30:24,440
Speaker 1: podcast Bye