1
00:00:02,520 --> 00:00:09,080
Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Matt, We're talking about

2
00:00:09,080 --> 00:00:11,840
Speaker 1: it a little earlier that prediction market call She is

3
00:00:11,880 --> 00:00:17,000
Speaker 1: partnering with Elon Musk's XAI to bring rock to prediction markets.

4
00:00:17,040 --> 00:00:19,320
Speaker 1: According to a post by x AI, we're going to

5
00:00:19,360 --> 00:00:22,119
Speaker 1: bring in call She CEO Trek Montsur to talk a

6
00:00:22,160 --> 00:00:26,880
Speaker 1: little bit more about this change you're seeing in prediction markets. Tara,

7
00:00:26,920 --> 00:00:29,520
Speaker 1: good to see again. I'm wondering what AI is going

8
00:00:29,600 --> 00:00:33,239
Speaker 1: to do to prediction markets moving forward, particularly because you've

9
00:00:33,280 --> 00:00:36,320
Speaker 1: seen them taken off so much since the election and

10
00:00:36,360 --> 00:00:36,840
Speaker 1: then some.

11
00:00:39,200 --> 00:00:42,000
Speaker 2: Yeah, well thanks for having me. Really excited to be here. Well,

12
00:00:42,040 --> 00:00:43,839
Speaker 2: I think it is one of the things that may

13
00:00:43,840 --> 00:00:45,440
Speaker 2: be the only thing that's going fast on the prediction

14
00:00:45,520 --> 00:00:49,760
Speaker 2: markets today. So you know, we're obviously incorporated my ways.

15
00:00:49,840 --> 00:00:54,480
Speaker 2: As you see, we've done two, i would say, two

16
00:00:54,480 --> 00:00:57,760
Speaker 2: of the leading commercials that were sort of AI first

17
00:00:57,800 --> 00:00:59,760
Speaker 2: commercials over the last few months. You may have seen

18
00:01:00,160 --> 00:01:02,840
Speaker 2: or two of them, and I have seen sort of

19
00:01:02,840 --> 00:01:05,520
Speaker 2: an explosion of the use of AI cross marketing after

20
00:01:05,520 --> 00:01:09,840
Speaker 2: the Surffirt Calchhieri commercial. So we're very excited about, you know,

21
00:01:09,880 --> 00:01:12,319
Speaker 2: the use of the technology, what it could be into

22
00:01:14,360 --> 00:01:16,120
Speaker 2: marketing teams and how it could make sort of teams

23
00:01:16,120 --> 00:01:19,360
Speaker 2: more efficient across the board. Obviously, the prediction markets AI

24
00:01:19,400 --> 00:01:21,440
Speaker 2: intersects could be very interesting going forward in the future.

25
00:01:21,880 --> 00:01:26,360
Speaker 1: Prediction markets have certainly been interesting for retail investors who

26
00:01:26,400 --> 00:01:30,320
Speaker 1: are looking to put their money based on where their

27
00:01:30,440 --> 00:01:33,160
Speaker 1: expectations are. But I'm also hearing more and more from

28
00:01:33,160 --> 00:01:35,200
Speaker 1: Wall Street as well. A little bit earlier in the year,

29
00:01:35,200 --> 00:01:37,959
Speaker 1: as talking to Boaz Weinstein, who has been using prediction

30
00:01:38,040 --> 00:01:40,280
Speaker 1: markets to inform some of the ways he's thinking about

31
00:01:40,319 --> 00:01:44,000
Speaker 1: putting trades on. How much are you talking to institutional investors,

32
00:01:44,280 --> 00:01:48,040
Speaker 1: hedge funds and other large investors in terms of how

33
00:01:48,040 --> 00:01:50,880
Speaker 1: they're using your platform and maybe even putting much larger

34
00:01:50,920 --> 00:01:51,680
Speaker 1: dollars to work.

35
00:01:53,080 --> 00:01:56,480
Speaker 2: You know, it's funny because when I tell people about

36
00:01:56,520 --> 00:01:58,560
Speaker 2: the story of Caush, you know, the genesis of Calshi

37
00:01:58,640 --> 00:02:01,760
Speaker 2: is I was spent out my golden sacks. And at

38
00:02:01,760 --> 00:02:04,200
Speaker 2: the time, it was twenty sixteen that summer, and at

39
00:02:04,240 --> 00:02:06,040
Speaker 2: the time, most of the men that was coming from

40
00:02:06,040 --> 00:02:10,880
Speaker 2: institutional investors was actually, can we put a trade on

41
00:02:10,919 --> 00:02:13,400
Speaker 2: Brexit or hedge against Brexit, or can we take a

42
00:02:13,400 --> 00:02:16,400
Speaker 2: position on Trump or hedge against Trump? So it was

43
00:02:16,480 --> 00:02:18,680
Speaker 2: very simple, like it's Tritians like retail. They think in

44
00:02:18,720 --> 00:02:21,320
Speaker 2: normal human terms, like what will happen in the future,

45
00:02:21,320 --> 00:02:23,000
Speaker 2: and let me figure out how to make money off

46
00:02:23,040 --> 00:02:25,120
Speaker 2: of it or trade on it. But the problem is,

47
00:02:25,120 --> 00:02:26,400
Speaker 2: like you know, for example, we told people like you

48
00:02:26,400 --> 00:02:28,440
Speaker 2: should shore the SMP if Trump wins, and then you know,

49
00:02:28,480 --> 00:02:30,640
Speaker 2: they were right about Trump winning, but then the SMP rally,

50
00:02:30,639 --> 00:02:33,320
Speaker 2: so they lost money. So that was the idea when

51
00:02:33,360 --> 00:02:36,320
Speaker 2: we really created prediction markets six years ago. So we

52
00:02:36,360 --> 00:02:40,680
Speaker 2: started coming in twenty eighteen, and when we came up

53
00:02:40,720 --> 00:02:43,440
Speaker 2: with the idea, it was basically this idea of like, well,

54
00:02:43,800 --> 00:02:46,519
Speaker 2: there's a financial market for all these different things except

55
00:02:46,560 --> 00:02:48,160
Speaker 2: for the one thing that people care most about, which

56
00:02:48,160 --> 00:02:50,800
Speaker 2: is questions about the future. So how about we build

57
00:02:50,840 --> 00:02:53,680
Speaker 2: that financial market for them to take direct exposure to

58
00:02:53,720 --> 00:02:56,520
Speaker 2: all these different questions. And our approach has always been

59
00:02:56,600 --> 00:02:59,640
Speaker 2: like the most important thing to do first is to

60
00:02:59,720 --> 00:03:02,000
Speaker 2: legal lice friction market. So that so Calshi. What we

61
00:03:02,040 --> 00:03:05,080
Speaker 2: did is we created the category, then we legalize it

62
00:03:05,120 --> 00:03:07,240
Speaker 2: first and foremost, and you know, there's a long history

63
00:03:07,240 --> 00:03:09,720
Speaker 2: that we had with the government to you know, going

64
00:03:09,760 --> 00:03:12,000
Speaker 2: through the process for years and then soothing government to

65
00:03:12,040 --> 00:03:16,000
Speaker 2: open the asset class ope wide open, which has finally

66
00:03:16,120 --> 00:03:18,239
Speaker 2: enabled us to achieve division of being able to attract

67
00:03:18,240 --> 00:03:21,400
Speaker 2: institutions and for people to think discredibly and seriously, and

68
00:03:21,440 --> 00:03:23,399
Speaker 2: we're very very excited about that. We're seeing a ton

69
00:03:23,400 --> 00:03:24,560
Speaker 2: of demand going forward.

70
00:03:25,120 --> 00:03:29,160
Speaker 3: How do you pick trek the things that people can

71
00:03:29,200 --> 00:03:33,200
Speaker 3: bet on? You've had contracts on, well, the Pope obviously

72
00:03:33,360 --> 00:03:37,440
Speaker 3: was was an important one, but recently you've had I

73
00:03:37,440 --> 00:03:41,360
Speaker 3: guess a market in whether or not the CEO of

74
00:03:41,440 --> 00:03:46,240
Speaker 3: Astronomer would resign after the Coldplay kiss cam incident, Like

75
00:03:46,280 --> 00:03:48,880
Speaker 3: how do you find these things and choose to put

76
00:03:48,920 --> 00:03:49,320
Speaker 3: them up?

77
00:03:50,480 --> 00:03:52,760
Speaker 2: Well, you know, the interesting thing, the way I think

78
00:03:52,800 --> 00:03:55,400
Speaker 2: about it is, you know, prediction markets are a financial

79
00:03:55,400 --> 00:03:57,520
Speaker 2: market for any questions about the future, right, And if

80
00:03:57,560 --> 00:04:00,720
Speaker 2: you think about it that way, you just have to

81
00:04:00,800 --> 00:04:03,280
Speaker 2: figure out, like, what are the most pressing, interesting, important

82
00:04:03,360 --> 00:04:06,680
Speaker 2: questions about the future that we have today, this week,

83
00:04:06,760 --> 00:04:09,200
Speaker 2: this month, And that's really kind of how we generate

84
00:04:09,240 --> 00:04:12,600
Speaker 2: these questions. So, you know, on that day, obviously the

85
00:04:12,680 --> 00:04:16,599
Speaker 2: Astronomer's CEO went absolutely viral, and the number one question

86
00:04:16,720 --> 00:04:20,160
Speaker 2: that people were asking on social was is he going

87
00:04:20,160 --> 00:04:21,760
Speaker 2: to stick around? Or is he going to get fired,

88
00:04:22,640 --> 00:04:24,719
Speaker 2: and so we sprinted and we listed it, and that

89
00:04:24,800 --> 00:04:27,520
Speaker 2: market was absolutely explosive. We've seen something like fifty million

90
00:04:27,520 --> 00:04:30,240
Speaker 2: impressions on that market and a lot of people made

91
00:04:30,240 --> 00:04:33,240
Speaker 2: a lot of money, you know, trading and forecasting whether

92
00:04:33,279 --> 00:04:35,640
Speaker 2: he was going to get ousted and this is important

93
00:04:35,640 --> 00:04:37,520
Speaker 2: for washing or like whether he was going to stick

94
00:04:37,520 --> 00:04:41,200
Speaker 2: around or be gone. That's you know, going to have

95
00:04:41,200 --> 00:04:42,960
Speaker 2: a huge impact on the valuation of the company, and

96
00:04:43,000 --> 00:04:44,760
Speaker 2: a lot of people are positioned in that company. So

97
00:04:45,800 --> 00:04:47,760
Speaker 2: it really is about what our customers want, what our

98
00:04:47,800 --> 00:04:50,360
Speaker 2: users are suggesting, and what's viral and trending on any

99
00:04:50,360 --> 00:04:50,800
Speaker 2: given week.

100
00:04:51,000 --> 00:04:54,480
Speaker 3: What are some of the most surprising, big volume bets

101
00:04:54,520 --> 00:04:57,560
Speaker 3: that you've seen, Trek. I mean, it's such a wide

102
00:04:57,720 --> 00:05:02,440
Speaker 3: range of issues, right, tell us about the volumes of

103
00:05:02,480 --> 00:05:04,520
Speaker 3: some of these things, like how much were people betting

104
00:05:04,560 --> 00:05:08,080
Speaker 3: on the astronomer CEO's resignation, and what are some of

105
00:05:08,080 --> 00:05:10,239
Speaker 3: the ones that have surprised you.

106
00:05:10,240 --> 00:05:14,040
Speaker 2: You know, it's funny because you know the history sort

107
00:05:14,080 --> 00:05:16,640
Speaker 2: of We won the lawsuit in October and then we

108
00:05:16,720 --> 00:05:18,400
Speaker 2: launched the election market. So it was the first time

109
00:05:18,440 --> 00:05:21,440
Speaker 2: that prediction markets were fully legalized in the US, including elections,

110
00:05:21,440 --> 00:05:23,720
Speaker 2: and then you know, you may remember our numbers completely

111
00:05:23,720 --> 00:05:27,719
Speaker 2: skyrocketed during the election month, right so October November we

112
00:05:27,720 --> 00:05:29,200
Speaker 2: were number one on the app store, we had five

113
00:05:29,279 --> 00:05:31,920
Speaker 2: hundred million unique side visitors. We're pretty much kind of

114
00:05:31,960 --> 00:05:33,920
Speaker 2: the largest website on the planet. For a few hours

115
00:05:33,960 --> 00:05:36,800
Speaker 2: on election night, and then people have the questions like

116
00:05:36,880 --> 00:05:38,880
Speaker 2: is this done? You know, is this going to kind

117
00:05:38,880 --> 00:05:42,440
Speaker 2: of go away after the election, And you know, we're

118
00:05:42,440 --> 00:05:45,000
Speaker 2: extremely proud to announced that this June actually last month,

119
00:05:45,160 --> 00:05:49,480
Speaker 2: we had more volume than the election month. And so

120
00:05:49,520 --> 00:05:51,800
Speaker 2: I think something CALC did something here, which is, you know,

121
00:05:51,839 --> 00:05:54,000
Speaker 2: after we've legalized and opened the space, but then we've

122
00:05:54,000 --> 00:05:56,279
Speaker 2: also taken it mainstream where the average Americans have the

123
00:05:56,279 --> 00:05:58,520
Speaker 2: Calci app in their hand and they're trading on things

124
00:05:58,560 --> 00:06:01,039
Speaker 2: and debating with their friends. Now there's a shift in

125
00:06:01,080 --> 00:06:04,720
Speaker 2: mentality and shift in behavior that we've enacted with the

126
00:06:04,760 --> 00:06:07,280
Speaker 2: American people where now every time they see a headline,

127
00:06:07,320 --> 00:06:09,200
Speaker 2: they see the news, they want to take action on it.

128
00:06:09,240 --> 00:06:11,440
Speaker 2: They want to get informed about the market and see

129
00:06:11,480 --> 00:06:12,960
Speaker 2: what's happening, the same way they did with the election.

130
00:06:13,080 --> 00:06:14,440
Speaker 2: And so we see across the board. You know, I

131
00:06:14,520 --> 00:06:17,279
Speaker 2: mentioned the Pope, the astronomer's CEO is a very interesting market.

132
00:06:17,360 --> 00:06:19,719
Speaker 2: Whether TikTok is going to get banned, that saga is

133
00:06:19,760 --> 00:06:25,600
Speaker 2: not done. Sports has been an extremely fast growing category

134
00:06:25,640 --> 00:06:28,359
Speaker 2: on Calshi. We're actually the fastest growing thing that happened

135
00:06:28,400 --> 00:06:30,320
Speaker 2: to sport in a decade.

136
00:06:31,480 --> 00:06:33,719
Speaker 1: At the same time, you're watching a lot of other

137
00:06:33,760 --> 00:06:37,160
Speaker 1: companies get really interested in the space and other contenders

138
00:06:37,240 --> 00:06:39,880
Speaker 1: able to get a little bigger. You see polymarket for example,

139
00:06:40,120 --> 00:06:43,520
Speaker 1: the Department of Justice ending their probe, them striking the

140
00:06:43,520 --> 00:06:46,640
Speaker 1: deal to buy a derivative exchange in clearinghouse in the

141
00:06:46,760 --> 00:06:51,279
Speaker 1: US market, Robinhood looking at prediction contracts as well. What

142
00:06:51,320 --> 00:06:54,000
Speaker 1: does this mean for you to see that much more competition?

143
00:06:54,480 --> 00:06:56,640
Speaker 1: Does it make you want to bring on more investors,

144
00:06:56,680 --> 00:06:59,679
Speaker 1: do acquisitions on your own, or even sell a company

145
00:06:59,680 --> 00:07:00,400
Speaker 1: at some point?

146
00:07:03,040 --> 00:07:06,599
Speaker 2: Well, it's actually very simple, right, Like you know, whenever

147
00:07:06,600 --> 00:07:08,599
Speaker 2: you see it, this is not not utilian industry. Like

148
00:07:08,680 --> 00:07:10,520
Speaker 2: we've had an incredible amount of success. If you look

149
00:07:10,520 --> 00:07:12,920
Speaker 2: at our volumes, if you look at our revenue trajectory,

150
00:07:12,960 --> 00:07:14,960
Speaker 2: if you look at our customer base on how it's grown,

151
00:07:15,000 --> 00:07:18,560
Speaker 2: it's super normal for competition to basically want to follow,

152
00:07:19,120 --> 00:07:21,720
Speaker 2: you know, and we're excited about that competition. That's amazing.

153
00:07:21,760 --> 00:07:23,680
Speaker 2: It's a validation of the business model, it's a validation

154
00:07:23,680 --> 00:07:25,080
Speaker 2: of the market is going to be very large and

155
00:07:25,120 --> 00:07:27,920
Speaker 2: it's growing, and we have you know, we're squarely in

156
00:07:27,920 --> 00:07:30,960
Speaker 2: the lead position with a very very strong headstart because

157
00:07:31,040 --> 00:07:34,240
Speaker 2: of our unwaivering commitment to build it legally, build it

158
00:07:34,360 --> 00:07:36,480
Speaker 2: credibly in the US, and now a lot of people

159
00:07:36,520 --> 00:07:38,200
Speaker 2: sort of are, you know, trying to replicate the setup

160
00:07:38,240 --> 00:07:39,880
Speaker 2: and do the same exact things that we've done over

161
00:07:39,920 --> 00:07:42,280
Speaker 2: the last few years. So we're super excited about that,

162
00:07:42,360 --> 00:07:46,120
Speaker 2: and we see the marketplace going exponentially over the next

163
00:07:46,120 --> 00:07:47,480
Speaker 2: few years, and we're going to keep being in the

164
00:07:47,520 --> 00:07:48,040
Speaker 2: lead position.

165
00:07:48,120 --> 00:07:49,800
Speaker 1: Turk, what are the odds that you go public?

166
00:07:51,200 --> 00:07:56,240
Speaker 2: I beg, Yeah, you know, I can't bet or trade

167
00:07:56,240 --> 00:07:58,280
Speaker 2: on prediction markets because I run one, but you know

168
00:08:00,080 --> 00:08:02,040
Speaker 2: I like that side of the trade, is what I'll say.

169
00:08:02,840 --> 00:08:06,040
Speaker 3: All Right, Trek, great having you on the program. Please

170
00:08:06,080 --> 00:08:07,880
Speaker 3: come in and sit at the desk with us next

171
00:08:07,920 --> 00:08:10,720
Speaker 3: time you're in New York City. CEO of Klshi there,

172
00:08:10,840 --> 00:08:12,280
Speaker 3: Tarek Mansour