Anthony Pompliano

Former Citadel Trader is Now Betting on Retail

🇬🇧 EN🇪🇸 ES
BitcoinMacroTrading
33:23 min youtube 2026 Week 19 🇬🇧 EN

TL;DR

  • Retail Empowerment & Tokenization: Modern platforms like Moomoo US are democratizing finance, allowing retail investors to access sophisticated tools (no-code algo building) and utilize blockchain native tokens for yield and collateral.
  • The Shift in Investor Profile: The modern retail investor is highly educated, often wealthy (25 to 42 years old), favoring strategic buy-and-hold approaches over high-risk trading.
  • AI & Risk Management: AI is augmenting human capabilities by automating market scans and filtering information, while platforms use unique crowd-sourced risk management to combat the primary failure point of human emotion in trading.

Summary

YouTube: https://www.youtube.com/watch?v=TYVG9ijACIo  |  Duration: 33 min

â—† Introduction & Market Evolution

The conversation begins by highlighting the limitations of traditional brokerage accounts, noting that assets cannot always be leveraged for major purchases like a home loan. In contrast, holding blockchain native tokens offers utility by allowing users to earn yield and use them as collateral in smart contracts.

This discussion introduces Neil McDonald, CEO of Moomoo US, who is leading the platform's expansion into the United States market. The focus is on how retail traders are gaining access to sophisticated financial tools involving tokenized stocks, cryptocurrency, and other emerging technologies.

Why Moomoo is growing so fast: Moomoo capitalizes on the rise of the modern retail trader. Historically, retail traders suffered from information asymmetry and limited access to fast market data. The internet democratized this, but complex mechanics remain a challenge.

â–¶ Trading Tools, Failure Points, and Community

The platform provides advanced tools such as no-code algo building and free backtesting across 20 years of data. While Wall Street firms maintain an execution speed advantage, modern retail technology has leveled the playing field.

The primary reason most traders fail is due to human emotion and a lack of risk discipline when trading alone. To combat this, the platform utilizes a unique crowd-sourced risk management community. This global network functions like a virtual trading floor where users share ideas, run trades collectively, and receive input on strategies and exit points—a key differentiator.

★ AI & The Future of Trading

AI is fundamentally changing trading by augmenting human capabilities. It allows traders to automate tedious tasks, such as instantly scanning the entire market for specific technical setups (e.g., double tops) based on a chosen strategy, saving hours of manual searching.

Furthermore, AI cuts through the overwhelming flood of financial information. Users can leverage it to ask complex questions about earnings reports or company filings that would be impossible to research manually in a short time. Essentially, AI provides actionable signals and streamlines intensive research for retail investors.

â–º Stocks vs Crypto & Tokenized Assets

The platform generally attracts users who are long-term investors focused on stocks, with crypto typically allocated only a small portion (around 5 to 10 percent of their portfolio). Users purchase digital assets using fiat currency directly within the account.

Advanced topics include tokenization. A key advantage of blockchain native tokens over traditional stocks is enhanced utility: while a standard stock primarily functions as margin collateral, tokenized assets allow users to earn yield through smart contracts and use them for loans or cash withdrawals.

Critical Insight on Tokenization: The market supports two simultaneous trends—crypto entering regulated financial systems and decentralized platforms operating permissionlessly. These models are not mutually exclusive, requiring companies to integrate new instruments with rigor and discipline.

â—† Options Trading & Retail Behavior

Retail investors have heavily adopted options trading, particularly zero-day options. The platform offers a robust option product featuring an Option Strategy Builder that simplifies complex trades by allowing users to set risk tolerance and tenor before generating strategies. For high volatility Zero DTEs, the system utilizes trailing stops as a critical risk management tool.

The company counters the narrative that retail investors are merely flippers by providing data showing sustained buying interest and massive demand during initial offerings. The platform's development is driven by clients through a suggestion system called Andon.

â–¶ Career Lessons from Wall Street & Fintech Building

The speaker emphasizes that culture was paramount at institutions like Morgan Stanley, stressing excellence, humility, and collaboration. His career path involved pioneering cutting-edge trading technology, starting with index option trading at Morgan Stanley, leading to automated market making and quant algo trading at Citadel, and building the global electronic market making business at JP Morgan.

Building a fintech in a regulated world: As a broker-dealer regulated by FINRA and the SEC, compliance is central. They view this highly regulated space as a useful discipline that brings rigor and transparency. Every new initiative must successfully answer three core questions:

  • Is it right for our clients?
  • Is the timing correct for us?
  • Are we the right people to deliver something different?

★ Evolving Investor Profiles & Risk Management

The profile of the independent investor has changed significantly; they are often wealthy individuals, typically aged 25 to 42, who are highly educated. Their average assets under management exceed that of US competitors, and they generally favor a buy and hold strategy.

Risk Management Comparison: Wall Street firms like Citadel employ completely automated and unemotional risk management systems (e.g., strategies automatically stopped out if they fall below tight limits). The rise of sophisticated pod shops mirrors the increasing intelligence among retail investors, as technology platforms rapidly narrow the knowledge gap.

â–º Biggest Challenges Ahead

⚠️ Operational & Regulatory Risks: The biggest challenges involve keeping up with rapid technological change (especially AI tools) while navigating evolving regulations like the Clarity Act. Operationally, maintaining 24/5 platform uptime is critical. The CEO notes that his risk focus at Moomoo centers on client and reputational safety rather than solely managing book exposure.

📊 Financial Asset Overview

Asset Class Role on Platform Thesis/Usage
Stocks (Traditional) Primary Investment Focus Used for long-term investment and strategic buying of dips.
Cryptocurrency Minor Portfolio Allocation (5-10%) Purchased via fiat currency, often used in conjunction with tokenized assets.
Tokenized Stocks Advanced Utility Asset Allows users to earn yield through smart contracts and use assets as collateral/for loans.

â—† Search for the alpha

The core thesis is a disciplined migration of capital away from pure, high-leverage speculation and toward utility-driven assets within an increasingly regulated financial structure. The guest's thinking centers on leveraging technological advancements—specifically tokenization and AI—to grant sophisticated retail investors institutional rigor while maintaining a cautious, long-term accumulation bias.

  • Maintain a primary focus on stocks for long-term investment, allocating only 5% to 10% of the portfolio toward cryptocurrency.
  • Prioritize assets with enhanced utility (e.g., earning yield through smart contracts) over traditional stock collateral, anticipating widespread tokenization within the next decade.
  • Avoid high-risk speculative trading; while zero-day options are popular among retail, the sophisticated investor profile favors buy and hold strategies and views market drawdowns as investment opportunities.
  • New ventures must pass a rigorous three-part filter: Is it right for our clients? Is the timing correct for us? Are we the right people to deliver something different? (This acts as a strong risk/opportunity gate).
The twist: The guest is implicitly arguing that the knowledge gap between institutional and highly informed retail traders is rapidly closing, not because of sheer capital size, but because of superior technology platforms. This means traditional information asymmetry is becoming obsolete for disciplined investors who utilize advanced tools like AI research augmentation.

â–º Chapter Summaries

Intro (0:00)

The speaker highlights the limitations of traditional brokerage accounts, noting that assets cannot always be leveraged for major purchases like a home loan. In contrast, holding blockchain native tokens offers utility by allowing users to earn yield and use them as collateral in smart contracts. The conversation introduces Neil McDonald, CEO of Moomoo US, who is leading Moomoo's expansion into the United States market. He will explain how retail traders are gaining access to sophisticated financial tools on the platform. The discussion focuses heavily on tokenized stocks, cryptocurrency, and other emerging technologies. Furthermore, Neil McDonald, a former executive from large financial institutions, plans to share institutional approaches with the average retail trader.

Why Moomoo is growing so fast (1:05)

Moomoo is experiencing rapid global growth by capitalizing on the rise of the modern retail trader. The speaker, who previously worked in institutional trading at Citadel, notes that historically, retail traders suffered from significant disadvantages. These included information asymmetry, where institutions had privileged knowledge before it became public, and limited access to fast, cheap market data. The internet and platforms like Robinhood revolutionized this by democratizing information and offering commission-free trading. While everyone now has the same basic information and easy access, complex market mechanics still present challenges for many retail participants. This shift represents a major evolution in how people interact with financial markets.

How trading tools changed everything & why most traders fail (4:38)

The platform provides advanced tools such as no-code algo building and free backtesting across 20 years of data. While major Wall Street firms still hold an advantage in execution speed, modern retail technology has made the playing field much more even. The primary reason most traders fail is due to human emotion and a lack of risk discipline when trading alone. To combat this, the platform utilizes a unique crowd-sourced risk management community. This global network functions like a virtual trading floor where users can share ideas, run trades collectively, and receive input on strategies and exit points. This social component is highlighted as the key differentiator from other retail platforms.

AI & the future of trading (9:28)

AI is fundamentally changing trading by augmenting human capabilities rather than replacing them entirely. It allows traders to automate tedious tasks, such as instantly scanning the entire market for specific technical setups like double tops based on a chosen strategy. This capability saves hours of manual searching and reduces the chance of human error. Furthermore, AI helps cut through today's overwhelming flood of financial information and opinions. Users can leverage AI to ask complex questions about earnings reports or company filings, which would be impossible to research manually in a short time. Essentially, AI provides actionable signals and streamlines the intensive research process for retail investors.

Stocks vs crypto on the platform (12:31)

The platform generally attracts users who are long-term investors focused on stocks, rather than active day traders. For crypto, users typically allocate a small portion, around 5 to 10 percent of their portfolio. Users purchase these digital assets using fiat currency directly within the account, making it appear like a traditional stock transaction on statements. The discussion then moves to advanced topics like tokenization and blockchain native offerings. They highlight Figure's recent SEC approval for a blockchain asset, noting they were uniquely positioned technically to facilitate this offering. On their platform, users buy these assets as US dollar items, which are then converted and minted onto the Open Platform on Figure.

Tokenized stocks explained (14:12)

Tokenization of stocks is projected to become widespread within the next decade. A key advantage of blockchain native tokens over traditional stocks is their enhanced utility. While a standard stock primarily functions as margin collateral, tokenized assets allow users to earn yield through smart contracts and use them for loans or cash withdrawals. The market currently supports two simultaneous trends: crypto entering regulated financial systems and decentralized platforms operating permissionlessly. These models are not mutually exclusive; both are active in the evolving ecosystem. Companies must therefore bring rigor and discipline when integrating these new instruments into trading processes.

Options trading & retail behavior (18:33)

Retail investors have heavily adopted options trading, with zero-day options being particularly popular. The platform offers a robust option product featuring an Option Strategy Builder that simplifies complex trades by allowing users to set risk tolerance and tenor before generating strategies. For high volatility Zero DTEs, the system utilizes trailing stops as a critical risk management tool. Platform development is driven by clients through a suggestion system called Andon, blending user feedback with internal product leadership ideas. Furthermore, the company has successfully advocated for larger retail portions in IPO allocations. They counter the narrative that retail investors are merely flippers by providing data showing sustained buying interest and massive demand during initial offerings.

Career lessons from working on Wall Street (22:28)

The speaker highlights that culture was paramount at Morgan Stanley, emphasizing a spirit of excellence, humility, and collaboration within smaller working groups. He has consistently sought environments that avoid feeling overly corporate while still being highly professional. His career path involved pioneering cutting-edge trading technology, starting with index option trading at Morgan Stanley. This led to co-leading the group for the first electronic exchange formation in 1999, which transitioned him into automated market making and quant algo trading at Citadel. At JP Morgan, he was responsible for building the global electronic market making business. He states that his continuous interest has been in developing advanced trading tools. Ultimately, he finds Moomoo to be his favorite workplace because it operates with a startup feel, smart people, and minimal ego.

Building a fintech in a regulated world (24:32)

Building a fintech in this environment requires managing multiple fronts, including technology development and navigating rapid industry changes like tokenization. As a broker-dealer regulated by FINRA and the SEC, compliance is central to their operations, with much of the US office dedicated to protecting customers and handling AML requirements. They view working within a highly regulated space as a useful discipline that brings rigor and transparency. The company aims to apply this strict standard to new asset classes. Rather than rushing into innovation, they adopt a cautious approach, thinking long and hard about potential ventures. Every new initiative must successfully answer three core questions: Is it right for our clients? Is the timing correct for us? And are we the right people to deliver something different?

How retail investors are evolving (26:16)

The profile of the independent or retail investor has significantly changed; they are often wealthy individuals rather than those with small amounts of capital. These modern investors, typically aged 25 to 42, are highly educated and sophisticated in their approach to markets. Their average assets under management exceed that of US competitors, and they generally favor a buy and hold strategy over high-risk trading like zero DTE options. They demonstrate strategic acumen by buying dips on major stocks and utilizing credit or put spreads when market conditions warrant. Unlike heavily leveraged hedge funds where poor performance is catastrophic, these clients exhibit strong fortitude and view market drawdowns as opportunities for investment.

Risk management on Wall Street vs retail (27:59)

Wall Street firms like Citadel employ completely automated and unemotional risk management systems for their trading pods. Traders must maintain a strong track record, such as a Sharpe ratio above 2.6, but the downside is extremely strict; strategies are automatically stopped out if they fall below tight limits, often just five percent. This structure allows these large firms to profit from the infrastructure while others absorb the risk. The rise of sophisticated pod shops mirrors the increasing intelligence and sophistication among retail investors. Technology platforms and AI are rapidly narrowing the knowledge gap between institutional traders and highly informed retail participants.

Biggest challenges ahead (30:20)

The biggest challenges ahead involve keeping up with rapid technological change, particularly concerning AI tools, while navigating evolving regulations like the Clarity Act. Operationally, the company manages both necessary safe broker-dealer infrastructure and cutting-edge AI development. A significant concern is maintaining 24/5 platform uptime since markets are always running globally. The CEO notes that his risk focus at Moomoo centers on client and reputational safety rather than solely managing book exposure. Furthermore, running global options books requires constant vigilance due to information releases happening outside of standard market hours. He praises the platform's ability to allow users to easily run backtests, calling this a democratization of trading.

Generated with algorithm v1-chunked · model google/gemma-4-e4b · 2026-05-07T11:16:51Z

Transcript

[0:00] If I've got $10,000 in Moomoo, I can't
[0:02] do anything with it. I can pledge it for
[0:03] a margin loan, great, but I can't pledge
[0:05] it for a home loan. I can't take cash
[0:06] out against it. If the stock loan gets
[0:08] tight, I get no yield. If I hold the the
[0:10] blockchain native token, I can enter
[0:13] into a smart contract either on figure
[0:14] or on another platform, earn yield, take
[0:17] cash against it. I can use it as a home
[0:19] loan. You know, it's got utility to me.
[0:21] What's going on, guys? Today we got a
[0:22] great conversation with Neil McDonald.
[0:24] He's the CEO of Moomoo US, and Moomoo is
[0:27] taking over the United States. These
[0:28] guys are on fire.
[0:30] >> And he's here to explain to us exactly
[0:31] what's happening, why so many retail
[0:33] traders now have sophisticated tools,
[0:34] what are they doing on the platform, how
[0:36] is he thinking about tokenized stocks,
[0:38] crypto, and various other new
[0:39] technologies. And then we even get into
[0:41] what he's doing himself on the platform.
[0:43] Neil's very interesting because he used
[0:45] to work at a bunch of very large
[0:46] financial institutions. He was a big dog
[0:48] there. He ran some of the teams. He's
[0:50] going to explain to us what was going on
[0:51] there, how cultures work. But now he's a
[0:53] CEO of a retail trading platform, and
[0:55] he's trying to bring a lot of those
[0:56] types of tools or those types of
[0:57] approaches to the retail trader. That's
[0:59] you, that's me, and that's a lot of
[1:01] people who are listening. Here's my
[1:02] conversation with Neil McDonald.
[1:04] All right, Neil, I thought a good place
[1:05] to start the conversation, Moomoo is
[1:06] taking over the world. I think that
[1:08] people in the United States a couple
[1:09] years ago they had never heard of this
[1:10] thing before. They had heard of, you
[1:12] know, all the other retail brokerage
[1:13] platforms, but you guys burst on the
[1:15] scene. You're taking over the subway.
[1:16] You got a Mets partnership. All this
[1:18] stuff that is marketing. But I looked
[1:20] into the numbers. You guys are massive.
[1:23] Talk a little bit as to why is Moomoo
[1:25] being so successful on a global stage
[1:26] behind this whole retail trader
[1:28] movement? I I think we kind of caught
[1:30] like the the
[1:31] uh it's it's good timing, right? So, the
[1:33] rise of the retail trade everyone talks
[1:35] about. Um
[1:36] so, we've got like Moomoo is a global
[1:38] firm, so we started in Hong Kong. Uh we
[1:40] came to the US about 2019-2020, but the
[1:43] big push in the US has been really the
[1:45] past couple of years. You know, with the
[1:46] subway, with the Mets,
[1:48] uh and just the name recognition. We're
[1:49] we're going old school, but opening a
[1:51] store, back to the old E-Trade days with
[1:53] a coffee shop in it uh in Midtown on
[1:55] 33rd and Broadway uh just to be more
[1:58] visible and you know, have something
[2:00] people can touch and trust and and and
[2:02] everything else. So, I I I got a call 2
[2:05] years ago from I Moomoo was not on my
[2:07] radar. It was kind of I knew all these
[2:09] I've got every other platform.
[2:10] >> No, you did you did the marathon. You
[2:12] you went through pretty much every major
[2:13] amazing finance company. You worked
[2:15] there and ran a very big division there,
[2:17] right? Morgan Stanley, JP Morgan. I
[2:19] mean, you just ran the gamut. Yeah, so I
[2:21] was always a
[2:23] I ran options trading desk and quant
[2:24] trading desk at Citadel. I did all that
[2:26] kind of So, I was always on the other
[2:28] side of the retail trader, right? I was
[2:30] always the guy happy to take retail. I
[2:32] would pay more to people like E*TRADE
[2:34] and TD Why? and those guys.
[2:38] There's four things that retail traders
[2:40] have lacked, right? First was
[2:41] information. The information asymmetry.
[2:43] When I started in late '80s,
[2:46] I was at Goldman's and when Procter &
[2:48] Gamble had their earnings, for example,
[2:50] that some guy would dial it in from
[2:52] Cincinnati to the sales guys. They'd go
[2:54] and speak to institutions.
[2:57] The stock would move. The the All the
[2:59] information would be digested into the
[3:00] stock price. And then, by the time I got
[3:03] it the next day as a retail guy in the
[3:04] Wall Street Journal or the Financial
[3:06] Times in the UK, all the alpha's gone,
[3:09] right? So, there was that huge
[3:10] information asymmetry. That got solved
[3:12] by the internet. And then the second
[3:14] thing was access. So, people like
[3:16] E*TRADE, Robinhood really gave cheap,
[3:19] fast access to to data, to the markets
[3:22] themselves. And then the rise of like
[3:24] free trading. So, Robinhood was
[3:27] revolutionary back in 2013, '14 and
[3:29] that's when
[3:30] Futu Moomoo started in Hong Kong around
[3:32] the same time. Um
[3:34] So, I was saying, it was information
[3:36] they lacked. So, they're always going to
[3:38] be wrong. If you do your Series 7 today,
[3:40] and this is in 2026, they still have a a
[3:43] question and a section on a thing called
[3:46] the odd lot theory. And this is a a real
[3:48] thing. And that is And this is obviously
[3:50] before you could slice dice orders,
[3:52] block trades were institutions. Small
[3:55] trades were retail. That's just how it
[3:57] was before you sliced trades into small
[3:58] algo stuff as an institution.
[4:01] And so, when the volume divided by the
[4:04] number of trades hits a certain level,
[4:06] so it's more retail participation, when
[4:08] that gets high, it's a sell signal.
[4:10] And when it gets low, it's a buy signal.
[4:12] Mhm.
[4:12] >> Right? So, they're always wrong. So, we
[4:15] solved the internet solved the
[4:16] street.com or Yahoo Finance. That's
[4:18] democratized information. All of a
[4:20] sudden
[4:21] I know when the when the Fed changes
[4:23] rates, I know when an earnings report
[4:25] comes out. I can watch the news, I can
[4:26] watch CNBC, I can listen to podcast. So,
[4:29] we all have the same information, but
[4:31] then do you have the access? And now
[4:33] everyone has the access and um
[4:35] commission-free trading, so it's cheap
[4:37] and it's accessible. So, the next step
[4:39] what they didn't have is the tools.
[4:41] Right? So, you've got the access, you've
[4:42] got the information. How do I actually
[4:45] use the access and information to make
[4:46] money?
[4:47] So, the tools-wise, uh if you're looking
[4:49] at our platform, it's it's bonkers. It
[4:51] really is. It's You have on our desktop
[4:54] and our phone what I had at Citadel
[4:56] running a quant trading desk. You've got
[4:58] backtesting. Um
[5:00] It's funny. It's it's New Year's. So,
[5:01] every New Year for the past maybe 10, 15
[5:04] years, I bought the Udemy teach yourself
[5:06] Python course, right?
[5:08] >> Yeah. I've done two lessons and given
[5:09] up. Um on our platform, you don't need
[5:12] that anymore. It's uh
[5:14] no-code algo building. So, just block to
[5:16] block to block. Just if then if then if
[5:18] then. But, here's Here's the crazy
[5:20] thing. I can build an algo
[5:23] and then I can backtest it on 20 years
[5:24] worth of data for free. Wow.
[5:26] >> And it'll give me every entry and exit
[5:28] point I did, every trade, and how your
[5:31] P&L looks over time for what- whatever
[5:33] time period you choose. And then if you
[5:35] like it, you click and you run the algo.
[5:37] That's pretty cool, right?
[5:38] >> That's, you know. So, it's great having,
[5:40] you know, but then again, it's great
[5:41] having great tools, but you have to
[5:42] teach people how to use them.
[5:43] >> Now, as the retail tools increased in
[5:46] efficacy, did the
[5:48] big bad Wall Street firms, the Citadels
[5:50] of the world, etc., their tools
[5:51] obviously have increased as well. So, do
[5:53] you think that they still have an
[5:54] advantage, but maybe it's a little bit
[5:56] more of an even playing field? It's much
[5:58] more even. Their advantage is still
[6:00] maybe in speed. Mhm. Right? So, we're
[6:02] we're pretty quick, but we don't have
[6:03] our bare metal servers, you know, 3
[6:07] cm away from where the matching engine
[6:09] is. Cuz we don't need super super
[6:10] microseconds or speed, but certainly the
[6:14] tools are at a at a par of where it was
[6:16] 5 years ago. I mean, that's pretty
[6:17] crazy, right?
[6:18] >> And then with agentic AI and everything
[6:20] else, it really has leveled it to the
[6:21] point.
[6:22] >> Mhm. Now, when you look at you guys
[6:24] versus many of the other retail trading
[6:25] platforms, what do you think the big
[6:26] differences are? Why have you guys had
[6:28] so much success? Well, so the the first
[6:30] thing I'd say that we lack We've got to
[6:31] go back to that for a second. So, it's a
[6:33] it's a
[6:34] information access tools. And then it's
[6:36] really
[6:38] risk discipline, right? Human beings are
[6:40] generally terrible traders on your own.
[6:42] Mhm. So, when when I sat at Goldman's or
[6:44] JP Morgan, I was in a big trading floor
[6:46] with 500 smart people trading somebody
[6:48] else's money. That's kind of
[6:50] that's an easier thing to do than to be
[6:52] sat at home with your own money trading
[6:55] to try and build a financial future for
[6:57] yourself. It's tough. Mhm. You know,
[6:58] human beings are emotional Mhm. um
[7:02] emotional beings.
[7:04] um
[7:05] FOMO
[7:06] uh
[7:07] risk aversion or the heuristics from the
[7:09] Chicago school, all that's, you know,
[7:11] Taniman Kahneman and Tversky stuff. Uh
[7:14] it's tough to trade cuz even when I
[7:16] trade on my own, so when I've had to
[7:18] leave a company and have a
[7:20] uh 3-month or 6-month garden leave, I've
[7:22] been trading my own money, terrible.
[7:24] Awful. Interesting.
[7:25] >> Cuz I chase stuff and I panic out and
[7:27] cuz it's tough. So, what we have is this
[7:29] 29 million people distributed
[7:33] uh crowd-sourced risk management kind of
[7:36] um
[7:36] desk of people. So, you'll see people
[7:38] when our biggest influx of cash was uh
[7:41] liberation day last year. Really?
[7:43] >> came and they bought the dip. And I'm I
[7:45] was on the Nvidia chat and it's every
[7:47] second someone saying something. But
[7:49] this is someone in Tokyo, in Hong Kong,
[7:50] in Singapore, in Australia, in Canada,
[7:52] or in the US. And it was like, "What do
[7:54] I do here?" And they're like, "No, guess
[7:56] below 100, we're all buying." And it's
[7:58] There's like a It's like having a
[7:59] trading floor of people to speak to. So
[8:01] you don't I always before I trade, I
[8:03] say, "What do you think?" And I'll send
[8:04] my trades out, I'll send my port-
[8:06] portfolio out, I'll send my algos out,
[8:08] and people will take the time to run
[8:11] them themselves and change parameters to
[8:12] say, "Hey, there's an extra 400 basis
[8:14] points if you change this." Interesting.
[8:16] And so this social component is
[8:18] something that most of these other
[8:19] platforms do not have. Explain a little
[8:20] bit more as to how this works. So it
[8:22] It's certain It's a bit like Wikipedia
[8:24] against Encarta, right?
[8:26] Some things are organic and can't be
[8:28] replaced, and some things you can't just
[8:29] throw money at. So we started this back
[8:31] in 2013 just to make it like a a chat
[8:34] room for people to share ideas. One of
[8:36] the
[8:37] one of the main tenants in the firm is
[8:38] to make investing easier, but not alone.
[8:41] Mhm. And that's super important.
[8:44] I know as I said, I'm a terrible trader
[8:45] when it's I'm actually on my own and not
[8:48] talking to other people, not bouncing
[8:49] ideas off people, not I'll I'll panic,
[8:52] I'll do all the all the trader stuff the
[8:54] traders do. Same things I do. Same
[8:56] thing, yeah.
[8:56] >> [laughter]
[8:56] >> So this this community aspect is really,
[8:58] really important. It's I'm on there
[9:00] every single day. I have thousands of
[9:02] people follow me, I follow thousands of
[9:04] people. And I have people I really
[9:05] trust. I'll go, "What what are we doing
[9:07] here? What are we thinking? Is this
[9:09] important? Mhm. I'm thinking about
[9:10] buying these calls." And I'll get I'm
[9:12] waiting till this level before I buy
[9:14] them. You know, what we think.
[9:17] Or you know, I'm saying, "Where's my
[9:18] exit point here?" So if I'm trading
[9:20] options, I'm like, "Where's my exit
[9:21] point?" And they go, "We think it's
[9:22] here." Mhm. So it's It's like being on
[9:24] the trading floor, but this is people
[9:27] around the world, yeah. Now, do you
[9:28] think at some point you'll also be
[9:30] asking the AI? Like it Right now you're
[9:32] talking to humans, do you think that AI
[9:34] will also be fast enough, good enough,
[9:36] etc. to start
[9:37] >> think so,
[9:38] It's interesting, right? Cuz you start
[9:39] to mix AI and humans.
[9:41] >> platform. It does some fun stuff. Some
[9:43] of the Some of the LLM stuff we've got.
[9:45] Like for example, if you like if you're
[9:47] a technical trader, you like
[9:49] double tops or head and shoulders, you
[9:51] just pick one of 26 strategies. You
[9:53] click on it, and in a second it finds
[9:56] every stock in the universe that has the
[9:58] setup and shows where it's drawn.
[10:00] So that's great for entry and exit
[10:02] points. Mhm. So So explain this a little
[10:04] more cuz I think This is like a very
[10:05] fascinating way to think about retail
[10:07] investing is
[10:09] um
[10:10] information and education has
[10:12] drastically increased. Now you got
[10:13] somebody at home who says, "Hey, I like
[10:15] double tops." Okay. I I look I spend
[10:18] hours a day trying to find stocks that
[10:20] are, you know, in this specific
[10:22] formation.
[10:23] Um now they can basically say to the
[10:25] system, "Go find me every double top in
[10:27] the US listed public stock market."
[10:29] >> click it, and it just it goes swoosh,
[10:31] and it's ins- it's instant. And then
[10:33] what? It's just like another click or
[10:34] two to be able to buy? You just buy. And
[10:35] then it's you just click on it, and it
[10:36] say, "What do you want to do here?" Mhm.
[10:38] I mean it's it's You couldn't do that to
[10:40] a human being. Yeah, I mean you're
[10:42] you're basically automating what is uh
[10:44] hours and hours of
[10:46] uh time, but also frankly prone to
[10:49] mistakes. Yeah. Right? I mean, you know,
[10:51] I'm very fascinated
[10:52] >> are really good at like seeing patterns
[10:53] that aren't there. That's what I mean,
[10:54] right? Yeah. You want to You want to You
[10:56] want to buy, you'll find something to
[10:57] tell you that it's right to buy.
[10:59] >> they say technical analysis is just
[11:01] astrology for men, right? You know, you
[11:02] just draw the lines everywhere. Um but I
[11:04] kind of think of it like with doctors,
[11:05] right? Like now AI's doing more and more
[11:07] reading of X-rays, and there's still a
[11:10] doctor involved, but the X-ray AI system
[11:14] is able to pick up things that the
[11:15] doctor may miss or maybe the doctor is
[11:17] just tired or, you know, been a long day
[11:19] or whatever. To me, that's where AI
[11:21] becomes really, really interesting is
[11:23] it's augmenting the human, which sounds
[11:24] like kind of what you guys are doing
[11:25] where you're basically saying that human
[11:27] has an idea, it tells the system to go
[11:29] find a bunch of stuff, and then the
[11:30] human is the oversight and and double
[11:32] checking and saying, "Yes, confirm I
[11:34] want to do this."
[11:35] >> always got the do you want to trade yes
[11:36] or no? There's always a confirmation pop
[11:38] to any kind of
[11:39] trade that's kind of suggested or
[11:41] whatever. Um
[11:42] but it's it's tough cuz it's um
[11:45] you know
[11:46] I came here, I was on the subway, I was
[11:47] still on my phone. I was on Twitter and
[11:49] stuff. I was reading some of your stuff.
[11:51] We're just we're bom- bombarded with
[11:53] information more so now than at any time
[11:55] in history. You're just bombarded with
[11:57] opinions, views, information, data. Um
[12:00] So, what AI does on our platform anyway
[12:02] just cuts through that. It tries to make
[12:04] signals to give you actionable things to
[12:06] do. So, you know, to it will suggest to
[12:08] you, here's the summary from uh from you
[12:11] know, the filings from You can even ask
[12:13] it the earnings report, "What was
[12:14] different in this earnings earnings um
[12:17] announcement than the last one?" And I
[12:20] can't do that. I'm not going to go
[12:20] through every announcement, listen to
[12:22] listen to the earnings call for the last
[12:24] three or four quarters. That's just too
[12:26] much work. But you can do that with AI.
[12:28] So, it just cuts down your research
[12:30] time.
[12:32] You guys have all of the traditional
[12:34] assets, you also have crypto on the
[12:35] platform. So, talk a little bit as to
[12:37] what do you see users actually doing on
[12:39] the platform? Are they mostly equities?
[12:41] Are they more crypto traders? Are they
[12:43] international, domestic? Just like what
[12:45] are some of the patterns? Yeah, so so so
[12:46] our guys are generally the
[12:48] uh stock guys.
[12:50] Uh our our class tends to be like buy
[12:51] and hold and longer term.
[12:54] We have more of those than kind of the
[12:55] in and out active day traders.
[12:58] Uh so, for crypto, we found it's people
[13:00] who want to make it 5 10% of their
[13:01] portfolio. So, they buy through fiat,
[13:03] they they don't have to have a wallet.
[13:05] It it's in their account. They look at
[13:07] their account. And even though it's it's
[13:10] you know, in in digital form, in in
[13:12] their daily statements on their phone,
[13:13] it just looks like a stock. Mhm.
[13:15] >> And they buy it with fiat, we do the
[13:16] conversions, we do all the back end
[13:18] stuff.
[13:18] >> Mhm. And we actually funny if the
[13:20] talking about like digital stuff and
[13:22] tokenization, so the big deal happened
[13:24] in February the the first um
[13:27] SEC blockchain native thing with Mike
[13:30] Cagney at Figure. So, we were the I I
[13:32] I'm an investor in Figure and
[13:34] I'm a big fan of Mike Cagney. So, that
[13:36] was fun to see. I was talking to I was
[13:37] talking to him yesterday. So, we he had
[13:40] there was a tight deadline for the S-1.
[13:41] It ran out on I think Feb 16th. They
[13:44] only got the okay on the the Thursday
[13:46] before. And we were the only broker with
[13:49] the technical ability to make that
[13:52] happen. Interesting.
[13:53] >> So, on our platform, you buy it with So,
[13:55] you just it's a US dollar asset on our
[13:57] platform. On the back end, we convert to
[13:59] WLTS and then we get it minted on open
[14:02] platform on on Figure. So, the only
[14:05] place you can buy it outside of Figure
[14:07] ATS is through Moonbase. Interesting.
[14:10] >> So, so we did that and we think there's
[14:11] going to be many more of those.
[14:12] >> going to say, do you think that over the
[14:14] next 5 or 10 years, like what percentage
[14:16] of the stocks that people are buying on
[14:17] your platform will be tokenized versions
[14:19] versus kind of the traditional
[14:20] electronic use?
[14:21] >> Mike Cagney would say 100%. That's what
[14:23] Mike Cagney would say when you were
[14:24] there. 100%. Um
[14:26] We're just hoping that maybe with
[14:28] things like Open AI and
[14:30] you know, and the
[14:31] the big IPOs coming, that those guys are
[14:33] fairly technically advanced and they
[14:35] would they would make some portion of
[14:36] those blockchain native, you know.
[14:38] >> Yeah. So, for I mean, we we took down a
[14:40] third of the IPO. Mhm. Our clients So, I
[14:43] said I said to my client, "Why did you
[14:44] buy it?" They there was a they wanted to
[14:46] be to buy the first ever SEC registered
[14:49] tokenized security on on the platform.
[14:52] And then also you can earn yield, right?
[14:53] There's no
[14:54] If I've got $10,000 in Nvidia, I can't
[14:56] do anything with it. Right? I can pledge
[14:58] it for a margin loan. Great. But I can't
[15:00] pledge it for a home loan. I can't take
[15:02] cash out against it. If the stock loan
[15:04] gets tight, I get no yield. Mhm. But if
[15:06] I hold the if I hold the um the
[15:09] blockchain native token, I can enter
[15:11] into a smart contract either on Figure
[15:13] or on another platform, earn yield.
[15:16] Um I can take that and
[15:18] take cash against it. I can use it as a
[15:20] home loan. You know, it's got utility to
[15:22] me, that just a stock in a stock um
[15:24] portfolio has very little utility apart
[15:27] from
[15:28] collateral for margin. Today's episode
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[17:43] Mhm. Yeah, it's fascinating to see.
[17:46] Um on one hand you've got crypto assets
[17:48] that are trying to get into the
[17:49] regulated system. On the other hand
[17:51] you've got things like a hyperliquid or
[17:52] something, right, that's trying to
[17:53] basically create uh the like
[17:55] crypto-native decentralized, you know,
[17:57] version. And both are working. Yeah, I
[18:00] think that's the part like to me that's
[18:01] the biggest thing is it's not either or,
[18:02] it's both, it seems like. Yeah, so like
[18:04] on you know, one of the biggest traded
[18:06] uh contracts on hyperliquid was oil. So
[18:08] people like permissionless, and there's
[18:09] going to be a certain sector of the
[18:11] investor base and the client base who
[18:12] always want to do permissionless stuff.
[18:14] And then there's people who want to
[18:15] trade on a platform that's secure,
[18:17] that's uh guaranteed, they can and
[18:19] they're used to using the tools for
[18:20] stocks.
[18:21] Um so what we we didn't rush into crude
[18:23] oil, we took our time. So we wanted to
[18:26] try and um
[18:27] you know, bring some rigor, discipline,
[18:29] transparency to the process, and just
[18:31] make trading crypto just like trading
[18:33] stocks. What about with the options?
[18:34] Like it seems like retail investors
[18:36] have, you know, really flocked to
[18:37] options trading. Um zero-day options now
[18:40] are the most popular option. Um
[18:42] there's, you know, potential pitfalls
[18:44] with so many people trading options, but
[18:45] it does feel like this is a huge part of
[18:48] uh the market.
[18:48] >> Yeah, we we special our option product
[18:50] is probably the strongest product we
[18:52] have, and that's kind of one of our
[18:54] advantages over some of our competition
[18:56] is that some of the tools we have we
[18:57] have So I've been trading options for
[18:59] 35-plus years.
[19:00] You know, the people say AI and tools
[19:02] will take your job. All my knowledge is
[19:05] worth zero right now. All that
[19:07] experience is worth nothing. We have a
[19:09] thing called option strategy builder,
[19:11] where you say, "I'm very bullish,
[19:12] bullish, neutral, bearish, very
[19:14] bearish." You can set a slider for your
[19:16] risk tolerance,
[19:18] um for your um for the tenor you want to
[19:20] go out, and it will just build you the
[19:22] strategy.
[19:23] And show you
[19:24] all the payoffs all in um
[19:27] image format, and then you can just uh
[19:30] slide the strike, slide um
[19:32] whether you want to take more risk or
[19:33] less risk, and it will build the
[19:35] strategy, and you can click trade it
[19:37] straight through the interface.
[19:39] So, it's almost uh obfuscating away some
[19:42] of the technical components of it, and
[19:43] you're more so the user interface is
[19:45] making it much easier to interact with.
[19:46] Cuz you you can just see your payoffs.
[19:48] And then for zero DTEs, as you know,
[19:50] they you know, gamma goes to infinity
[19:51] about 5:00 to 4:00.
[19:53] And so, one thing we have is we have a
[19:55] trailing stop on zero DTEs. Mhm. So, I
[19:58] use that all I never enter into a zero
[20:01] DTE without a trailing stop, especially
[20:03] cuz you want to catch that wizard,
[20:05] right? You want to go it's 10 cents,
[20:06] it's not it's a $1.50, um but then it's
[20:09] a $1.50 and it's 10 cents again. Mhm.
[20:11] So, I use tra- I use our trailing stops.
[20:13] So, I know if it goes up and it's down
[20:14] by 10, I'm out. Yeah. How important is
[20:16] it that you're trading on the platform
[20:17] as well? I I make all the mistakes. So,
[20:19] I'm like, this is what the the you
[20:21] normal average uh trader will do. So, I
[20:24] I use it and you know, we have
[20:25] everything we do is we have this system
[20:27] called Andon. I think it came from
[20:28] Toyota.
[20:30] But um every change we make is driven by
[20:32] clients. So, people make suggestions,
[20:34] I'll make suggestions, that goes when
[20:36] it's a certain level goes straight to
[20:37] our product guys, and then they start
[20:39] So, it's not we it's not like I'm
[20:41] thinking, "This be a great feature."
[20:42] It's when people ask for the features.
[20:44] >> Mhm. Mhm. Yeah, but you as the
[20:48] uh leader of the business, you are like
[20:50] touching the problem. Yeah. Right? Like
[20:51] you're Yeah, yeah. It feels like that
[20:53] would be pretty important.
[20:54] >> Yeah, so I'm I make suggestions, I'm
[20:55] like, "We can do this better. Here's
[20:56] what I'd like to see." And then it goes
[20:58] we to a group of people, we discuss, and
[21:00] then Yeah. But we we actually turn out
[21:03] product really quickly. We've got 4,000
[21:06] We've got 4,000 people
[21:08] globally. 3,000 of them are in product
[21:11] development and um
[21:13] yeah, product and dev.
[21:14] You've made a huge push into these IPO
[21:16] allocations and really advocated for
[21:18] retail investors to get bigger and
[21:19] bigger portions. What have you seen
[21:21] there in that effort? Yeah, I mean we've
[21:22] had most success with with people like
[21:24] Mike Cagney, Mike Belichic cuz they're
[21:26] just disruptive people by nature. And so
[21:28] they look at you know they made their
[21:30] money by looking at a legacy ecosystem
[21:32] saying that doesn't make sense. I can do
[21:34] that better, cheaper, faster.
[21:36] Um
[21:37] so they look at the you know um you go
[21:39] to an investment bank and you have to
[21:41] pay them to tell you your price should
[21:43] be this so they can send it to their
[21:45] institutional um clients. And there's a
[21:47] conflict of interest there or people can
[21:49] see that as a conflict of interest. So
[21:51] we went directly to these guys or we
[21:53] went through uh some of the banks who
[21:54] said, "Listen,
[21:55] um we can show you all the data. Retail
[21:57] is not The idea of the narrative that
[21:59] retail's a flipper is not the case. So
[22:02] we have all the data. If I take uh Fig
[22:04] or Bill Rich for example, we've been net
[22:06] buyers of the stock every week since the
[22:08] IPO." Interesting. So we have more
[22:10] people who hold the stock now than
[22:12] actually we got allocation for. Yeah,
[22:14] I'm a great great for those businesses,
[22:15] right? And we and we get huge amounts of
[22:17] demand. BitGo, uh it was a $200 million
[22:20] deal. I know it's down uh from its its
[22:22] price. But we had like almost $700
[22:24] million of
[22:25] um demand. Wow.
[22:27] Um
[22:28] you've been friends with uh Jordy Visser
[22:30] for a long time. Jordy's a a star of the
[22:32] show. Uh maybe I have to change it to
[22:34] Pomp and Jordy show. Um but
[22:36] >> and Pomp or maybe. Yeah, that's actually
[22:38] yeah, at this point why don't even have
[22:39] my name in it? It's just the Jordy show.
[22:41] Um
[22:42] talk a little bit about the early days
[22:44] of Morgan Stanley in your career and and
[22:46] kind of what you learned there and then
[22:47] also I think Citadel is a pretty
[22:49] interesting place that you know most
[22:51] people with your pedigree and and
[22:53] experience they don't kind of flip over
[22:55] on the other side of the table. And I
[22:56] think it's very fascinating you worked
[22:57] at some of these places that are you
[22:59] know very well respected for a long time
[23:01] for the culture they built, the quality
[23:03] of the people, the tools they built. So,
[23:04] talk a little bit about that. Yeah, I I
[23:06] what I remember about
[23:08] Stanley, JP Morgan Stanley, I think
[23:10] culture was the main thing. There was a
[23:11] culture of excellence of uh being
[23:14] humble, um never thinking you're right
[23:16] all the time, collaboration. So, I I
[23:19] when I joined Goldman's, there was maybe
[23:20] 4,000 people globally when it was still
[23:22] a partnership.
[23:23] >> Mhm. And it felt like you were part of
[23:24] something. That That was really very
[23:26] important to me. And I've been looking
[23:28] to work at places that have had that
[23:29] kind of Mhm. that
[23:31] it doesn't feel too corporate.
[23:33] Obviously, they're large banks, but you
[23:34] know, in within groups of people, you're
[23:36] working with very smart people who are
[23:38] all trying to get to the same point.
[23:39] Mhm. So, uh moomoo is is exactly like
[23:42] that. It feels like a startup. It feels
[23:43] exciting. So, I when I've been at the
[23:46] banks, I've always done the more
[23:47] cutting-edge stuff. So, with Jordy, when
[23:49] I was at Morgan Stanley, uh we were
[23:50] index option traders together. I was
[23:52] doing Europe, he was doing the S&P.
[23:54] And then when the um when the ISE was
[23:57] formed in '99, the first electronic
[24:00] exchange, uh I co-led that group. So, I
[24:03] got into the automated market making,
[24:05] and then that led to the the quant algo
[24:07] trading at Citadel. Uh at JP Morgan, I
[24:09] built globally the electronic market
[24:11] making business. So, the tools to trade
[24:13] have always been something I've been
[24:14] interested in.
[24:15] And then that kind of was natural that
[24:17] comes to like moomoo that feels like a
[24:18] startup. Um
[24:20] a bunch of super smart people all
[24:22] working really hard, uh a lack of egos.
[24:26] It's it's it's the favorite place is I
[24:28] would say it's it's my favorite place to
[24:30] have worked in all of my career. Yeah.
[24:32] Wow. And when you think about
[24:35] uh this business, I think one of the
[24:36] things that's really interesting is
[24:38] you've got a lot of fronts that you've
[24:39] got a uh kind of manage, right? You've
[24:40] obviously got the internal team and the
[24:42] culture and and things that every
[24:43] business has to deal with. You're
[24:45] building technology, so there's all the
[24:47] product and dev work that you got to do.
[24:48] Uh but you're building it in a dynamic
[24:50] environment where, you know, 10 years
[24:52] ago crypto wasn't a thing really uh for
[24:54] a lot of these platforms. Now there's
[24:55] tokenization, prediction markets. I
[24:57] mean, it's just every day there's
[24:58] something new. And then you've also got
[25:00] to deal with regulation on top of that.
[25:01] And so talk about how do you like like
[25:03] what is your normal day look like? How
[25:05] do you handle so much complexity? I
[25:07] think that's a good point. So we're a
[25:09] fintech company, but we're a
[25:10] broker-dealer, right? So it's it's you
[25:12] can't be like a fintech that just throws
[25:13] things against the wall and breaks
[25:15] things and cuz you can't cuz if you
[25:16] break one thing and people can't trade,
[25:18] you're out of business, right? And then
[25:20] you know, we're regulated by FINRA, uh
[25:22] registered with the SEC.
[25:24] Um so we you know, a large part of our
[25:26] US office is compliance, right? So
[25:28] [clears throat] it's protecting the
[25:29] customer, uh
[25:31] AML stuff. So we're
[25:32] we're super tight on that stuff. It's a
[25:34] useful discipline to work within a
[25:36] highly regulated environment. It
[25:38] protects our clients, it protects us.
[25:40] Um and so we're trying to bring that
[25:42] kind of as I said rigor, compliance,
[25:44] transparency, discipline, trying to
[25:46] bring that to new
[25:47] new classes. It's the first time in
[25:48] history I've never know I don't know
[25:50] what next year will look like. It's
[25:51] super exciting. It's exciting, but it's
[25:54] also you got to try to figure it out. So
[25:56] like what how do you figure it out?
[25:57] Yeah, so uh not rushing it not rushing
[26:00] into the next So we we think long and
[26:02] hard. We think why us? Why this? Why
[26:04] now? And so they have those three
[26:06] questions have to be have to be
[26:08] answered. Is it the right thing for our
[26:10] clients? Is it the right timing for us?
[26:12] Are we the right people to do this? Can
[26:13] we deliver something different?
[26:15] >> Mhm. And so when you look at these new
[26:17] technologies that are coming out, uh one
[26:19] of the other things I think is really
[26:19] interesting is like who the
[26:21] quote-unquote retail investor or this
[26:23] like I call them independent investor is
[26:25] has really changed. It used to be you
[26:26] know, somebody with five bucks.
[26:28] These people are wealthy now.
[26:29] >> These people wealthy, Right. And then
[26:31] talk talk a little bit as like who that
[26:32] user is.
[26:33] >> Yeah, I mean it's like 25 to 42. Uh some
[26:36] of the money's come down from their
[26:37] parents. You know, there's that whole
[26:38] waterfall from uh from the boomers. But
[26:41] they're smart. I mean, they're not your
[26:42] average they're not the retail investor
[26:44] of even 10 years ago. Um
[26:46] again, it's about educating yourself. So
[26:49] you know, you can have all the best
[26:50] tools in the world, but if you don't
[26:51] teach people how to use them, they make
[26:53] it makes no sense.
[26:54] >> Mhm. So, our our investors say our
[26:56] average AUM is much higher than our US
[26:59] competition. Um
[27:01] they tend to be buy and hold. They're
[27:02] not they don't they're not going crazy
[27:05] on zero DTEs. They have the tools and we
[27:07] do have a some active traders on the
[27:08] platform. Uh
[27:10] but generally
[27:12] um the
[27:13] I'm always amazed by their fortitude.
[27:15] Right? They And that's part of being in
[27:17] the community stuff, but we have people
[27:18] who bought Nvidia Jan 23 at
[27:22] below 20 bucks. And all they've done is
[27:24] buy dips all the way down. And then when
[27:26] it's a bit extended, they'll sell sell
[27:28] credit spreads. When it's coming off
[27:30] again, they'll sell, you know, um
[27:32] put spreads.
[27:33] So, they're quite sophisticated. They're
[27:35] sophisticated. They they don't panic.
[27:37] You know, that's um
[27:38] you know,
[27:39] I I I kind of make the joke that um
[27:41] my wife's not going to find me from my
[27:43] 401k, right? If I have a bad quarter.
[27:45] But you know, if you if you're in a pool
[27:47] at Millennium or you're over-leveraged
[27:48] hedge fund, you have a bad quarter,
[27:50] you're out. You're down 5% you've lost.
[27:52] Right? So, my um
[27:55] our clients will take drawdowns and see
[27:57] it as opportunity. Talk a little bit
[27:59] more about like take the pods, right?
[28:01] And whether it's Citadel or anywhere
[28:02] else or Millennium.
[28:04] Um
[28:05] I don't think people quite understand
[28:06] the risk limits and how
[28:08] uh kind of unemotional the
[28:10] decision-making there is. So, so talk
[28:11] just a little bit. Well, it's completely
[28:12] automated. So, if you're a PM and you're
[28:14] running a strategy, you have to show
[28:15] your sharp above like 2.6 I think it is
[28:17] for for same Millennium. I don't know I
[28:20] quote is he here, but 2.6 is 10, you
[28:22] know, you have to show a track record.
[28:24] And then they'll give you money,
[28:25] absolutely. And if you do well, you get
[28:27] paid. Mhm. The downside is they start to
[28:29] gate you down to an off three and down
[28:32] five you're out. Mhm.
[28:33] >> just stop you out and you're wiped out.
[28:35] Yeah, so like this year, I don't know,
[28:37] maybe 100 million dollars, once you're
[28:39] down 5%
[28:40] it's over. That's over. Yeah, and it's
[28:42] really a culture of I mean, if you up a
[28:44] you know, if you up 100, then I think
[28:46] they scale it, so but if you down five
[28:48] below average zero, then you definitely
[28:50] are. Yeah. And so it it's interesting
[28:52] because they're doing this across, you
[28:54] know, in some cases hundreds of pods,
[28:56] and it really just becomes this like
[28:57] automated big risk mitigation, you know,
[28:59] and just
[29:00] >> I mean, it's uh it's
[29:02] they're getting paid on the picks and
[29:03] shovels, and other people are taking the
[29:05] risk. Mhm. So, it's a great business
[29:07] model. Mhm. Yeah, it's pretty uh it's
[29:09] pretty interesting.
[29:09] >> Assuming you've got really tight risk
[29:11] limits and that you can liquidate down
[29:12] five. Well, that's the other thing.
[29:14] Yeah. You get into these correlations
[29:15] and, you know,
[29:16] um I I always uh I yearn for the old
[29:19] school like cowboy risk takers.
[29:21] They're they're not working any pod
[29:23] shops, right? Cuz these guys might go
[29:24] down 20% and, you know, make it all back
[29:26] in a single trade. Um but I do think
[29:28] that the rise of the pod shops mirrors
[29:31] the rise of the sophisticated investor,
[29:33] where everyone is becoming much more
[29:35] informed and understand some of the
[29:38] pitfalls of financial markets together.
[29:40] Um and, you know, Twitter X has been a
[29:43] huge part of that, but but it does feel
[29:45] like the pod shops have really hit their
[29:47] stride and become super sophisticated.
[29:49] Retail has as well. Again, it's not
[29:51] saying a retail investor's like a pod
[29:52] shop, but um there just feels like
[29:55] overall the market is getting smarter.
[29:57] Yeah, I'm I'm in again, it's an
[29:58] education process. We've got 2,000
[30:00] videos and stuff on the platform, trying
[30:02] to take people from you know, trading
[30:04] 101 to to using algos, to using uh
[30:08] backtesting environments, to using the
[30:09] tools. The gap between the guy at
[30:11] Millennium and Citadel and the
[30:14] sophisticated retail retail trader has
[30:16] never been narrower, and AI is making
[30:18] that really, really tight. Interesting.
[30:20] What what do you like lay awake at night
[30:22] over? What what what are the challenges?
[30:25] Um
[30:27] other than the Mets not being good.
[30:30] Well, the Mets being seven and 11 at the
[30:31] moment.
[30:32] And they they've got to play one more
[30:33] game in in LA as well. I know. I know.
[30:36] As a Yankees fan, I can, you know, give
[30:38] a little. They're going to be they're
[30:39] going to be seven and 12.
[30:41] They're going to be seven and 12 by this
[30:42] evening.
[30:43] >> [laughter]
[30:43] >> I I won't be watching the late game
[30:45] tonight. Um
[30:46] Uh
[30:47] regulation with the ask on clarity act I
[30:50] really care about. Regulators having to
[30:52] move quicker than I think it makes them
[30:54] comfortable. The The world is changing
[30:56] so quickly.
[30:58] We got lots of issues with the AI stuff
[31:00] and with our tools. Um
[31:03] And it's just can can we keep up? Can we
[31:05] keep giving our guys the tools that they
[31:07] need? Mhm. So we know we we we we most
[31:10] of them when it goes in R&D and product
[31:12] development. And we're just hoping that
[31:14] you know we keep turning out the
[31:15] product.
[31:15] >> like super AI piled and they're all just
[31:17] like running wild with all the models
[31:19] and everything? So we have some like
[31:20] that. We have a whole section that we
[31:22] got Remember we we've got over in a
[31:23] broker dealer. So we need the safe
[31:25] boring infrastructure. Mhm. Um cysex
[31:28] stuff. All the stuff you need. And then
[31:30] we've got the more fun stuff which is
[31:31] the AI. Mhm. Um and and the people
[31:34] coding the fun stuff. But a lot of it is
[31:36] just making sure we're up all the time.
[31:39] Like for for for Take it for the we make
[31:41] markets 24/5 in the we make markets. We
[31:43] give access 24/5 to figure D to the
[31:46] token. Mhm. So that was a big step for
[31:48] us and then so we have we have to be up
[31:50] all the time. So my worry is that at
[31:53] some point something happens and we go
[31:54] down. Do you sleep? I do sleep. Yeah
[31:56] yeah yeah. I sleep a lot more as CEO of
[31:59] Moon Pay than I ever slept at Citadel
[32:00] Jefferies before.
[32:01] >> Why? Cuz I'm not running risk. Oh. I'm
[32:04] running risk. I care about my my clients
[32:05] and reputational risk and they make sure
[32:07] the platform's up.
[32:08] >> Yeah yeah. But not like a book Not like
[32:10] a book, yeah. Yeah yeah. That's
[32:11] interesting though that actually there
[32:13] you felt much more kind of pressure to
[32:16] on the risk side of the the book versus
[32:19] the
[32:19] >> Yeah I mean especially because there's
[32:21] so much more information on weekends
[32:23] now. Mhm. So if I was running a huge
[32:25] global options book and then you know
[32:27] something happens on a Saturday
[32:29] You know we got a guy at the White
[32:30] House. He likes to do stuff on Friday,
[32:32] Saturday, Sunday. [laughter]
[32:33] I mean I I would He's He's suspiciously
[32:35] waits till the market close on Friday
[32:36] and starts firing the information. I
[32:38] would never be not running slides. Yeah.
[32:40] You know, but back then you mentioned
[32:42] Monte Carlo before.
[32:43] We should run those overnight. Mhm. On
[32:45] bare metal servers. Mhm. Right?
[32:47] [clears throat]
[32:48] And the fact on our platform you can
[32:49] click and just run a whole back test is
[32:51] is That's crazy. It's crazy. Yeah, yeah.
[32:54] That's democratization right at its
[32:55] finest. And then you you can share them
[32:57] with people. Yeah. So you see you see in
[32:59] our chat everyday taking video. People
[33:02] just putting their trades up and their
[33:03] wins, their losses. Mhm. And there's a
[33:05] feeling of being part of something, you
[33:06] know, you're in a big trading venue.
[33:09] Yeah. Uh rather than just being in your
[33:10] bedroom or in the kitchen or
[33:12] Yeah, I love it. I love it. All right,
[33:14] well thank you for taking the time to do
[33:15] this. If you guys want the best trading
[33:17] experience go to Moomoo. Go check them
[33:18] out and uh we'll do this again in
[33:20] future. Anthony, thank you.

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