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He Went From $20K to $70M Using a Strategy Anyone Can Learn Transcript, AI Summary & Key Points

My First Million · Dec 22, 2025 · Entertainment · 01:19:31 · EN

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00:00 You really only need one great trade to be a top 1% investor. The most inherently ground true thing of investing, the most important thing, the thing that matters more than anything else is I don't look at valuation. I don't look at PE. All I look about is there is new information. I've been reading TikTok comments. That's where I get most of my alpha from.

00:22 >> You have Buffett or Munger and who are like reading the Moody's manual cover to cover just company financials and you're like I scrolled the TikTok comments. That year I made like 30 million in one year and it was a wild ride. You will try to beat the market, you'll trade with leverage, you're moving in and out of positions, you're not a buy and hold forever kind of guy.

00:40 Just before the pandemic I had made the worst trade of my life. I lost a third of my portfolio on a single trade. >> Okay, so let's break it down. This is where the biggest mistake I ever made was. [snorts] You break all the rules of investing. You know, all what I normally hear is you should just index, don't try to beat the market, don't take any leverage.

01:11 >> [laughter] >> You know, and so but you do the exact opposite, right? You will try to beat the market, you'll trade with leverage, you're moving in and out of positions, you're not a buy and hold forever kind of guy. According to the internet you've done pretty well. So I've seen some different numbers that have been floated around. Can you set the record straight?

01:27 What is the actual story? Yeah, I I I started with 20,000 in 2007 to try this new methodology which is the way I was investing when I was way way younger that worked for me. I I call it social arb investing today. But what it essentially is is observational investing. You're you're looking for any change that's happening in the world whether it's you know, change in consumer behavior, uh change in culture, change in technology, change in the weather, politics, anything that has the potential to be meaningfully

02:06 impactful to one or more publicly traded companies in either a positive or negative way. So if you can surface that change early and connect the dots back to a company that would benefit or be harmed by that change, that's essentially the entire methodology. Uh it doesn't really incorporate much fundamental analysis. It definitely doesn't incorporate any technical analyses.

02:33 In in in its purest form, you really don't even need to know what the stock is trading at when you open up a position or what it's trading at when you exit. So like ideally you'd be completely blind to stock price, completely blind to everything other than the extent to which other investors were aware of that one thing that you surfaced that you feel would ultimately be impactful to that company and you know, you enter your position at the point of information asymmetry, right?

03:10 When when when you know that thing and very few others do and you exit the position at the point of information parity when other investors start to learn about that thing that you uncovered first. And it's it sounds so simple and it really is. But there are nuances to it and like everything else to do it to be great at it it takes time and a and and a little effort and some regimented processes that you have to go through like is the information that you found actually meaningful?

03:45 Is it a needle mover for that sector or for that company? You know, is the information you found really off radar? Uh or do you institutional and retail investors or already accounting for it? And are there any other things that are happening at that moment of time or within the window of that trade that are equal to more important than that piece of information that you're trading, right?

04:12 So there is a process there. Of course, yes. So and and I want to go through a bunch of examples of it. So you take this idea of observational investing of arbitraging information without being, you know, a guy who grew up on you weren't working on Wall Street, you didn't have an MBA, you didn't have the what what would be like, you know, some 20-year 20 years of experience doing this.

04:38 The story is you take 20 grand, you start doing this type of investing and you run it up. It's it works pretty well for you. It's successful. I don't know the exact numbers but I've seen something like you know, 60 million, 70 million, 80 million is how you've grown that portfolio starting at 20,000. Is that right by the way cuz I mean that sounds in some sense too good to be true.

04:59 Yeah, it it it certainly is does sound too good to be true. It it is accurate. It's I don't know the exact number 70 or 80 million dollars of returns from the 20k. Um but I've been audited over the past 17 years. I'll be re-audited at the end of this year and I'll fall somewhere around 75% annualized returns total portfolio over the 17 or I think it might be 18-year period now since 2000 and 7.

05:31 >> [music] >> Hey, let's take a quick break because the team at HubSpot has put together something pretty cool. You know, in this episode Chris is talking about the way he knows how to make money, identifying these trends, scouting the TikTok comments, making these big leverage bets. That's great for him. It is amazing. Some people will like that. I personally don't know how to make money that way.

05:47 I wouldn't do it. But I've talked before about the way that I know how to make money, about how I build a money making skill, about how to leverage your time and energy and the team at HubSpot actually went through the video where I explained all that and turned it into a free downloadable cheat sheet on my four rules of how to make money. Now, this is not, you know, get rich quick advice.

06:06 It's just core principles, foundational principles about building wealth, things that I wish I knew when I was, you know, just getting started. And so if you want to download it, it's in the description below. It's totally free. You can go get it. Thanks to the folks at HubSpot for doing the research, making this document and making it available to all you guys.

06:19 All right, back to this episode. Okay, so let's break it down. So you you said I started doing this as a kid. You got I felt I went to the type of investing I was doing as a kid. I I I I I I I had read your book Laughing at Wall Street. And you talked about like basically kind of like starting with like, you know, garage sailing and very simple stuff when you were a kid, noticing things, talking to your brother, talking to your dad.

06:41 Hey, could this mean this? And and taking, you know, getting learning lessons with very small bankroll, you know, 100 bucks type of deal. So can you just take us like early days, what was the what where did you kind of have this sort of aha moment that this style of investing can work? Yeah, you know, I I was an entrepreneurial kid. I was really interested in making money before that was a cool thing to do.

07:09 You know, the the new generation now, all these all these kids are traders, they're trading crypto. I mean it's all it's like every kid now is like I was back in the, you know, 80s. And by the way, that makes sense now cuz if you're a kid you're on YouTube, you're on TikTok, you'll you'll see things. But why why did you have that itch? What what made you want to to to get on that hustle?

07:31 What who did you see? I don't I don't know what made me so laser focused on grinding at age 12, 13 but but I will I but the way that I was going about it was not investing. It was arbitraging garage sale and estate sale merchandise. I would take, you know, buses around the city on Thursday and Friday mornings and Saturday mornings before I could drive.

07:56 Sometimes I'd take three or four buses before school to the one estate sale that I had seen in the paper the night before that based on my analyses I thought was most likely to have mispriced merchandise and and the thesis there is that most of these estate sales at the time were run by older women who really had a great knack for pricing silver and pricing other, you know, types of things that they knew about and cared about but they were really really bad at identifying value in male-oriented items like whether it

08:36 was old trains, old watches, a- a- any anything that tended to be male-oriented. >> eBay, right? So you can't just go look up every item quickly and know the know the current like life market price for it. >> Yeah, it was pre- eBay, exactly. So I would show up at 5:30, 6:00 in the morning and the goal is if you pick the right sale and you're first in line and you know exactly what you're looking for, uh you know, you got a good shot at buying something that is mispriced.

09:09 And I I would I did that for years. Um I just happened to go to the same 7-Eleven every morning and get a bottle of Snapple uh lemon flavored iced tea which was like the hot company at the time. It was the hot drink at the time. >> Yeah, Snapple used to be huge. Yeah, and one morning I went to the 7-Eleven and they had like one quarter of the door space dedicated to Snapple.

09:37 They had brought in a couple other brands of iced tea. I don't even recall what it was. Maybe it was Arizona iced tea and a couple others. The clerk told me that that's the way it was going to be from that point forward uh due to this new competition coming in. And sure enough I talked to my older brother. I shared the observation with him. He was a stockbroker.

09:59 Uh I asked him, "Can I make money off of this? This has got to be bad for Snapple, right? I mean, it's such a hot company." Sure enough, a few weeks later they had announced earnings. He taught me how to short Snapple with put options. I did it through his account. I was too young to have a brokerage account. I think I gave him $300, which was most of the money I had at the time from garage saleing.

10:21 And he tripled the money in the course of about a month because Snapple, for the first time in its history, had reported, you know, bad earnings due to inventory building up due to retailers like 7-Eleven giving them less door space. So, it was just something that I had noticed as a kid, and you have to ask yourself like, that's crazy because, you know, professionals on Wall Street, they could have easily have seen the same thing that I saw.

10:54 But, they were so distracted by so many other things, macroeconomics, noise, government, their jobs, just herd mentality that they didn't see something very simple that was right in front of their face. So, you know, if I did that as a, you know, young teenager, that really means something. Now, of course, I didn't realize what I did at the time how special it was because you would never believe that you as a kid are better than, you know, all Wall Street.

11:23 So, I I got really into stocks and investing after that, but I did it in the conventional sense. I read all the books, and I mean all the books, technical trading, fundamental. And I just tried every type of investing method. And, of course, basically nothing worked. So, I was just like everybody else. But, later on in my life, when I was in my 20s and I had a job and I wasn't making as much money as I wanted to make or I felt that I needed to make to have the life that I wanted, I got back into investing, and that was

12:01 really most aggressively in 2007. And I said, you know, why don't I try this kind of observational approach that I did a little bit of as a kid. And I recalled that one approach, and at the time it was similar. What I did as a kid was reflective of what Peter Lynch was doing. Though, Peter Lynch, you know, utilize observational investing as just part of his methodology.

12:27 He also did a lot of fundamental analysis. So, let's break it down. So, there's major schools of thought around investing, right? Number one, passive investing. You know, don't try to beat the market, just be in the index or even worse, mutual fund. And, you know, you go as the American economy goes. All right, that's one school of thought. Then there's, "I think I could do better than indexing."

12:55 And there's technical analysis, which is, you know, some cross between, I don't know, horoscopes and, you know, fantasy football or something. >> [laughter] >> And so, there's a lot of people who believe that they can really see patterns and and and and, you know, signs and math in the charts, and that that the charts will tell you, the technical analysis will tell you where the where the price is going.

13:16 And so, there's a lot of people who try to do that. I've never met anyone smart who's good at that, but it's possible that that is a thing. >> people that are Some people do that. So, okay, so there's [laughter] there's technical trading, there's fundamental analysis, the sort of Buffett style of investing where you're trying to understand the intrinsic value of the business, trying to understand the, you know, the durability and the quantity of the cash flows, and you're trying to use that to to try to understand what

13:42 the business is worth relative to what the market's pricing. A lot of people try to do that, that's sort of seen as like kind of gold standard. What you do is this other school of thought. So, you know, here comes door number three. And door number three, you kind of described it a second ago, but I would my short summary of that is you're looking for significant behavioral change.

14:02 So, the way that either consumers or businesses are changing in some way, whether that's COVID is going to make it where people are not traveling, or it's teenagers are now doing this thing. You gave this example of women who were changing their bra preference from wired push-up bras, and Victoria's Secret is on top, to start noticing a lot of people talking about the word bralettes.

14:27 And now they're wearing bra and here, you know, there's two guys talking about bras. There's now women are wearing bras without a wire or a no bra movement. And hey, that's probably going to affect the number one bra player, Victoria's Secret, who's not even carrying bralettes at the time. So, you're looking for some behavioral change somewhere. >> let's not let's not restrict it to behavioral change.

14:50 Uh, let's say any change. It could be a hail storm, okay, that impacts a positively impacts a publicly traded roofing company. It could be anything that's happening in the world that is change-oriented, that is not well well discovered or known by by the investing community. >> Correct. So, not sort of consensus, not quote-unquote priced in. And so, let's go through a couple of examples.

15:19 So, what are your favorite examples of these that you found in your life? Take me through a couple of your greatest hits. Yeah, I mean, there's like there's maybe north of 80, 80 to 90 I know over the past 18 years. Uh, you know, there've been a handful that didn't work out. We can talk about those, too. But, for the most part, almost every one of them has worked out.

15:42 I know that's really hard to believe. I know it's like exceptionally difficult to believe. The one I just mentioned that popped in my head is actually one of my my favorites. I I would track every spring, I would simply go and track the number of people that were searching for the words of roof damage or roof repair. It's a it's a free data source. Anyone could, you know, leverage Google Trends.

16:09 And what's fascinating about this is when there is a hail storm, people will immediately start Googling roof repair the day after that hail storm hits. Now, at the time, there was a publicly traded company called Beacon Roofing, and they're one of the largest roofing companies in North America. And if the hail season was particularly damaging, that would meaningfully impact their bottom line as a roofing company.

16:33 So, what's fascinating about that is that the Wall Street generally would utilize insurance sector reports that would report on the damage from the hail season as a data point to analyze Beacon Roofing, you know, prior to earnings. But, those reports take a very long time. They're really delayed. They're delayed by like, I don't know, 5, 6 weeks after that that the actual hail storms happen.

17:02 So, I had discovered this real-time data source that would tell me in real time the volume of people searching for roof repair because even if you knew there was a terrible hail storm and you see it on the news, if that hail storm just happened to be over a super populated area as opposed to 2 miles down the road that isn't populated, that's what makes the difference.

17:26 And the only Nobody really knows how many people are impacted by hail, how many roofs are, until they get reflected in the insurance reports. Or, a great measure of that that's maybe slightly less precise, but way more real time is that the volume of people that are searching for roof repair. Now, what's so great about platform like Google Trends is you have, you know, 15 years of historical data.

17:51 So, you can look at every single spring and you could see where the peaks are in the search volumes. So, there was one hail season in particular that the peaks were nearly triple anything I had ever seen before in years past. So, I I went in on a very large, very levered call long position on Beacon Roofing. And yeah, I mean, that would be considered like a greatest hit.

18:21 My understanding is you the same thing you did in the garage sales where you said, "Look, most of these garage and estate sales were run by older women. They knew the price of jewelry really well. You're not going to get too much of a deal there. But, they may not know what their kind of husband or their son's baseball card collection is worth. Specifically, this one 1996 Topps rookie card, Kobe Bryant, you know, whatever."

18:47 So, you you find the value there. My understanding is you you applied the same principle to Wall Street. You said, "Well, most of the guys who are on Wall Street, you got people who work in finance are guys, white guys, live in New York, who are of a certain age, and then you started saying, "Well, instead of I'll use the garage sale principle again.

19:05 If they know a lot about certain types of things, where are their blind spots?" Is that right? Is that how you how you thought about it? So, that's how you identify like the lowest hanging fruit or the highest probability of finding the most opportunity, especially early on, I would say. The vast majority of my big wins were around, you know, changes in consumer behavior and culture that were primarily female-oriented or youth-oriented or to some demographic that wasn't older, white, northeastern, you know,

19:47 geographically located in So, you know, it it it could be something like I talk a lot about the the moment that Jeffree Star, who was a beauty influencer, uh you know, made a single video about this drugstore cosmetics product made by e.l.f. Cosmetics that was just as good as a $60 product. It was called the e.l.f. primer putty. That was That was an old trade now, but that was back when e.l.f.

20:17 was trading at like $7 a share before it blew up to $170 a share, right? But but just be seeing a you single YouTube video and then realizing that, "Wow, it has 10 million views, and this is a company that nobody cares about." And all of a sudden, the most influential, you know, content creator in the world for beauty is saying that it's just as good as one of the best products in the world.

20:44 I went down to I think it was CVS or actually I think it was Walgreens by my apartment, and just stood there all day and and and watched moms coming in with their kids and buying out all the e.l.f. products because all of a sudden, instantaneously, this drugstore brand that was just like at a price point of like eight bucks for any piece of makeup, right, became a cool brand because this one individual said it was.

21:12 And and and so, that was a game-changing moment that I witnessed via watching a YouTube video. And I actually called one of the analysts on Wall Street who was covering e.l.f. Cosmetics because part of my methodology is not just to discover things early, but you have to assess the degree to which other investors might already be aware of that information in order to gain conviction that you that you truly found some information asymmetry in the market.

21:43 So, I called this analyst. I said, "You know, what do you What do you think about the Jeffree Star uh video on on e.l.f.? You know, has that impacted the way that you're analyzing e.l.f. this quarter?" And the analyst said, "Who's Jeffree Star?" And and and that at that moment, I knew everything I needed to know about that trade, right? And and listen, it makes sense.

22:10 These guys are not watching, you know, YouTube videos of beauty influencers, right? But that's all that I do. I I spend People don't believe me, but I spend on average three to four hours a night, late night, uh basically reading through, these days, last 6 7 years, uh uh TikTok comments, right? So, like that's where I get most of my alpha from recently is people's cuz cuz that's just happens to be the place where people express themselves most freely uh across the uh largest number of topics.

22:51 And that'll get you laughed out of the room with with, you know, quote-unquote serious investors, right? Like, you know, you have you have Buffett or Munger and these guys who are like reading the Moody's manual, you know, cover to cover, just company financials. And that's where they're looking for an opportunity. And you're like, "I scrolled the TikTok comments, and that's why I'm compounding 75% a year for 20 years."

23:14 [laughter] >> Well, well, okay, so here's what you have to determine as an investor because we we can't all be, you know, Warren Buffett, right? So, like like, who do you want to compete with? I always say it's really not important for you to be smart, but it's important for you to figure out how to be smart in a totally different way than others. So, do you want to go and compete with the top mathematicians in the world as a as a technical trader?

23:42 Do you want to compete with just droves and droves of, you know, Wharton and Harvard grads who are doing financial analysis? Can you do that analysis a little bit better than them? Yeah, maybe you maybe you can. Maybe you're that type of a person. But let's be honest, most of us, I'll even say 99% of us, probably don't fit into one of those two camps.

24:10 So, how could the rest of us get an edge on Wall Street? How could the 99% figure out a way to outperform others in the market? Like, what could we do that others aren't doing? And you have to think differently. So, you have to look for edge in a place where your competition, and your competition being conventional, institutional, and retail investors are not willing to go.

24:37 And, you know, the one thing about institutional Wall Street is they like correlated data. They they like certainty. They like proof in in in historical correlations. So, the data that I am trading is conversational data because Wall Street primarily uses transactional data. So, they'll use credit card receipts that they spend millions of dollars for, and then they synthesize all this transaction data so that they can kind of figure out what's happening at that company before earnings.

25:16 So, a lot of times when we see stocks move a week or two before earnings, and we're like, "Who's doing that? Like, how do they know?" Right? Like, it's transactional data. Wall Street's been utilizing it for 15 years, more so today than they ever have. So, like, how do we gain an edge on a hedge fund that's spending millions to tens of millions of dollars and has fleets of people analyzing credit card receipts?

25:45 Well, what do you do before you buy something? Uh you talk about buying it. Uh so, you you you there's a billion people out there that are talking about their interest and what they want and what they did and what they plan to do tomorrow every single day. Uh if they see a video about a particular, you know, piece of apparel, uh you'll have 30,000 women commenting whether they plan to also buy that piece of apparel that they just saw the video on, right?

26:18 And and so, what you could actually measure the depth of interest in in infinite number of things even before that's provable through sales, right? And and so, it in my opinion, it's a superior uh way to to discover alpha, a change in the world, although it's imperfect because you have to do a lot of your own interpretation of what you're reading and what that actually means because it's speech.

26:55 And and and it's a lot of times the speech is nuanced, and uh the way that we speak about things is constantly evolving. So, you know, if you're just a regular person that spends a lot of time in the real world uh and and it on social media, uh believe it or not, you're probably well qualified to make that assessment. Yeah. >> [laughter] >> There's uh there's a great story.

27:25 I don't know if you know the story of the trending tab on Twitter. It's actually kind of it's it's an interesting story. So, that the guy I met the guy who who did it. He's running a company. His name is Abdoer. So, my friend Abdoer was basically at the time had a, you know, a group of basically data nerds, machine learning and data nerds, and they were trying to figure out they were trying to do something very meaningful for the world.

27:49 They're like, "We would love to be able to do sentiment analysis." So, trying to figure out how people feel about things. So, do they feel positive about something or negative about something? And um so, he's like, "Oh, Twitter is this huge source of text traffic. So, let me just try to use Twitter to understand sentiment about things." And he was trying to do it, and it wasn't really working very well.

28:05 And one day he's on a train, and he's working on something, and he just sees that like his program he's writing is not spitting out sentiment analysis about things, but it's just spitting out like city names. And he's like, "Why are there like these city names? Or the sorry, country names. Why are these country names just popping up out of the the Why is it being surfaced as signal?"

28:28 And what he realized was that the Olympics was going on, and the and they were basically like, you know, the the opening parade was happening, and each country that was, you know, being shown was getting mentioned a lot. And what he realized was that like, "Oh, if I just paid attention to the delta, so like if nobody's ever talking about, you know, whatever, Zimbabwe, and suddenly, it's not that a lot of people are talking about it, but way more than usual are talking about it, that's got to mean something."

28:55 And so, he created a standalone product that was basically just tell you, "What are people talking about in a abnormal way on Twitter?" And then Twitter ended up buying that and making it the trending product, which was actually like really really important for Twitter to succeed because they were able to differentiate from Facebook and others by being about like real time what's going on in the world.

29:16 How do you figure out what's interesting and new and fresh that's going on in the world? Well, you needed something like that that was reading all the social signals. It sounds like you were kind of manually doing a similar thing when you're like, "Oh, I noticed a lot of people are I've heard you talk about the example of slime. Hey, this slime trend is getting really big.

29:33 Well, how do you make slime? Right? If everyone's doing slime If all the kids are doing slime, well, how do you make slime? You need Elmer's glue. And then you go and you figure out that, "Wow, people haven't really priced in that Elmer's glue Elmer's is about to have, like, you know, a huge quarter or a huge huge earnings call. So, me and my business partner, we actually created a platform called TickerTags in the mid-2010s with Twitter.

29:53 Uh and we had access to the Twitter Decahose, which is a 10% randomized sample of every tweet in real time. And we hand-curated um about 1.5 million word combinations that represented how people were speaking about every product, brand, basically anything that was connected to any publicly traded company or meaningful to any publicly traded company in any way, we had organized into a taxonomy.

30:23 So, every company had like, you know, 300 to 1,000 combinations of words. Like, what would be an example? What do What do you mean by that? So, like, if I'm Nike, what what do I care about? >> So, okay. So, you just mentioned slime, so which is one of my big trades. Newell Brands makes Elmer's Glue, all right? So, Elmer's Glue would be a tag for Newell Brands.

30:47 DIY slime, which is a product that uh utilizes white Elmer's Glue when your kids are playing with slime, that would be a tag. Because to the extent that DIY slime gets more popular, that's something that someone who's invested in Newell Brands might want to know. So, we were actually monitoring in real time the frequency of mentions of those 1.5 million words and benchmarking them against historical norms including seasonality.

31:17 And so, since it was organized in a taxonomy, uh when there was any type of anomaly in speech patterns happening across Twitter that were impacting a subject matter that we had curated to be impactful, potentially impactful to a publicly traded company, our system would flag that. So, that that's a platform that we developed and sold to hedge funds and sell-side banks.

31:44 And so, what that was was basically me taking my methodology of what I had done manually and institutionalizing it for Wall Street. And at the time, people expressed their opinions on Twitter about everything that they were doing in life the way that people currently no longer do on Twitter, but do on you know, play in places like TikTok. Now, you know, Twitter is mostly news-oriented or finance or tech-oriented, right?

32:13 Uh political-oriented. But people are not generally talking about the movie that they watched last night on Twitter, >> Right. right? They're doing that on other Yeah. platforms. But but we sold that company to Jefferies Bank Uh years later. Was that like a successful company, you know, obviously, you know, it's not that it was unsuccessful, but I guess you know, it's all relative.

32:34 So, for example, you know, you're selling the data to hedge funds, are they really receptive to this? Do they believe what you believe? Were they willing to pay? And That's the coolest part of the story. Uh I spent years flying to New York nearly weekly training the top sell-side banks and the I would say, you know, probably five or six of the top 10 hedge funds in the world on how to interpret this observational conversational data and how to attempt to correlate it.

33:06 And they just had very little interest. They had interest in the results, but they couldn't figure out how to build teams around it because hedge funds generally have individuals that are like mathematicians, right? That that that were that they were hiring from the West Coast to develop, you know, algorithms for for for trading like quant traders. And then they have very traditional fundamental analysts who are basically finance heads that would, you know, would crunch numbers and kind of do fundamental analysis.

33:41 They didn't really have, you know, 20-something-year-old females on staff who were really savvy interpreting, you know, conversational data. You know, coming coming off it and and and like, yes, this is a trend, this is not a trend. Uh this is meaningful, it's not meaningful. So, it was a whole you know, Wall Street they they do things kind of in the same way that they've always done things, right?

34:10 And it's really difficult for them to stick their neck out and say, "Hey, you know, we believe this thing matters when there's no historical correlation between the speech pattern of that subject matter and the stock price or the earnings of that company. Because like I said, speech patterns evolve. And that thing that they're talking about could be a new thing that was never meaningful before at that company.

34:39 Sure. That is unfortunate for Wall Street, but it's fortunate for retail investors, right? Because we we now know uh I guess I'm telling you right now that this is still a data set that they're scared of. This is still a methodology that they have a hard time wrapping their head around because they can't really document the degree to which it's it's meaningful for thesis.

35:12 If if you were to have someone come out and say, "Hey, I I I I've been reading TikTok comments and I I I [laughter] believe that this new show at the Sphere in Vegas, Wizard of Oz, people are super hyped on it. And I like read 180 comments of people flying in from Europe next month to see it. And I think this just might be the like the one thing that Sphere has done right and it's going to be a game-changing moment for the company finding product-market fit."

35:41 Sounds oddly specific. >> [laughter] >> Is that actually a trade trade you're you're in right now or no? It was Yeah, so so so that was so Sphere, uh the Wizard of Oz, Uh Sphere was actually one of my largest wins of 2025. And it came from reading comments Uh of Wizard of Oz the first 48 hours that it was out and essentially making a a monstrously big >> Wow.

36:08 Sphere up 114% this year. Well, it was a levered options trade, so it was a lot more than that. A lot of what I do when I have high conviction around Uh a particular thesis that has a especially when they have a very defined window of time when I believe others will will start to acknowledge that that that ground truth. In the case of Sphere, it was people counting seats sales of seats.

36:36 So, you're actually able to go in and see how many seats are available for a show that's a week and or 2 weeks out. And that's exactly what happened. So, over the course of a few weeks, Uh other and it was cool because it was like retail analysts. It wasn't even like Wall Street, but the other people that were trading Sphere were like, "Hey, like, we're seeing a there's a lot of seats.

36:59 We've never seen seats sell out like this before for a show." So, what I had interpreted early user early reviews ultimately came out in seat sales that other retail investors started trading. And then Wall Street eventually picked up on it when the company came out and said that they're adding new shows, Right. Because they're selling out all their shows.

37:27 They're increasing their, you know, profit guidance. And yeah, you with the stock is, you know, more than doubled here over the last few months Uh exclusively almost because of Wizard of Oz. Do you remember when So, the show's called My First Million. Do you remember when you made your first million and you know, what what got you there and how did it feel?

37:46 Yeah, I I I I 100% do. I was Uh working at a company called eRewards in Dallas, Texas Uh with one of my best friends, Patrick. It was like not far past when I started this in 2007 with the $20,000 that I had grown to a few hundred thousand dollars and I said, "This is just absolutely crazy." I said, "I think I'm going to I think I'm going to hit a million dollars here like within the next I don't know, next year or so."

38:14 And it was a few months later I hit a million dollars. And I'll never forget walking into his cubicle and saying, "I did it. I cannot believe my account just hit a million dollars." It absolutely melted my mind. Uh And that happened. And you know, I wrote my book I don't know, 2 years, 3 years later Laughing at Wall Street because there was this tracking service called Covester at the time and Covester was like the first portfolio tracking service.

38:44 I think they had 40,000 accounts in it including mine. And it would monitor, you know, how well you're doing month to month, total portfolio. And it would rank you publicly. And there was a while a moment in time when I was the number one ranked investor on Covester, Uh which is just absolutely wild. And it was during that 3-year period. And that's when I I I I was on a few different business shows like Fox Business talking about it.

39:12 And then I got a book deal to write that book Laughing at Wall Street. And when I wrote Laughing at Wall Street, it was 20,000 to 2 million dollars. It was 100 times your money in 3 years. And at the time, there was a small piece of me that thought, you know, is am I just like part of the long tail statistical anomaly? Right. You flip a coin, flip a coin 100 times, somebody if you get enough people to do it, somebody will land on heads you know 90 times and they'll you'll think they're they're a genius.

39:45 You know No, 100%. I doubted myself more and now I had a really defined methodology and I knew the narrative behind every one of my trades. It was very sensible, right? Like it wasn't like this mystery where I came up with some random formula and it was just trading stocks on its own and maybe it the formula just happened to get lucky. I felt strongly that the nature of observational investing about simply uncovering some piece of meaningful information that others weren't aware of intuitively just makes sense, right?

40:21 Like it's not like this mystical thing that you're like, well that doesn't make any sense. Of course it makes sense. You're just uncovering important information a little bit quicker than other people and you're connecting dots a little bit quicker than other people. So in my head I knew the methodology at its core was really valuable, but I still didn't believe that 3 years was enough.

40:43 So in my head I was like, if I can get to 5 years and keep this track record up, that would be insane. I got to 5 and I was like, okay. Let's see if I can push it to 10. And then I got to 10 years and now here I am, I'm at eight Like I said, I think I'm going on 18 years of average 70, you know, mid-70s uh total portfolio returns and I truly believe I can hit 20.

41:07 So like 20 years So that's the new number in my head. I want to go for 20 years and all I have to do at this point is not mess it up, right? Like But But at the same time it's very hard generating you know, returns that are that high. So let me ask you a couple mechanical questions. Do you take profits every year? Do you reinvest everything? What What are you actually doing with the sort of annual Yeah, cuz you know, you compound at that rate for a long enough time, the number's actually much bigger than 70 million

41:38 that you >> it's almost a billion dollars. So it it So what's in This is where the biggest mistake I ever made was that I'm now resolving for the most part. So just about I've been half of my life is trading public equities through, you know, observational investing, social arb, conversational data, everything we're talking about. The other half of my life has been an entrepreneur and you know, I've had some success as an entrepreneur and like a lot of entrepreneurs that had success, you start investing in other

42:10 entrepreneurs. So I've been an early-stage venture investor for 20 years. I'm actually invested in 160 early-stage companies. And my performance investing in early-stage companies is pretty much average. It You know, I'm on sync with just about any other average VC. I I want to say maybe 10, 11, 12% annualized returns. So I have pulled out almost all of my gains every single year for the past 18 years and have taken that money and invested it in the private market.

42:53 >> [snorts] >> And that has been really unfortunate for obvious reasons. It's unfortunate because the opportunity cost of my capital is so high, but I never even believed in myself that much on the public side that I could continue to do that. So I was never like, oh, well, I'm just going to keep doing 70 some odd percent average returns. That never really seemed feasible.

43:18 It I felt like I needed to make my home runs in the early-stage VC world. And I finally came to terms a few years ago with the fact that that was a really bad decision and it's taken me about 4 years to pull myself out of early stage because when you're in when you're an early-stage investor and that big of an early-stage investor, I mean, I was taking hundreds of meetings with founders annually and it takes a long time to unwind yourself from that ecosystem.

43:49 >> [laughter] >> Yeah. So I don't know who it was, maybe Peter Lynch, he had like a don't don't cut your flowers to water your weeds, right? Like he basically he talked about with with stock individual stocks, right? Don't sell your winners to diversify back into like losers, but I you know, in a way what you were doing was at at a at an overall level if you were performing at 70% in one asset or one strategy and 10 or 11% in the other, but you were taking the profits out, you know, that's a that's a water that's a

44:18 water your weeds sort of scenario. Yeah, and and and by the way, not I love Peter Lynch maybe more than any other investor, but you know, I I don't believe in any preset rule of investing like that. Like my methodology is very clean, you know, I I I you invest when you discover something that other people haven't discovered yet that will be meaningful to a trade and you exit as soon as other people have figured that out.

44:46 And that's it. That that's literally the only thing. And and if that stock goes up 100x or 200x, you don't sell it because it's up 200x. You know, you you sell it when other people find out the information that you're trading. So one of my most controversial trades a a over a year ago was, you know, Palantir and I I went all in unbelievably levered in Palantir at $30 a share and I was very public about it.

45:18 You know, I have a YouTube channel Dumb Money Live and we did a multitude of episodes on Palantir and this really strong thesis that we felt there was this kind of 12-month window where the whole world was going to discover these things about Palantir that were really misunderstood. And I had never gotten so much heat, a lot of it from Palantir investors going, "You're an idiot.

45:42 We've been in this thing since six bucks. You're going to do this at $30 a share? Like what are you talking about?" I'm like, "Well, I I'm not trading the information you were trading at $6. I'm trading something >> of two-line reason you were so bullish on Palantir at that stage? Well, cuz cuz people didn't even understand what they did, all right?

46:01 They didn't understand the the where they would actually sit in the stratosphere of the AI wave that was coming as a beneficiary of it. And Palantir was just starting to scrape the surface of this new product that they had with clients and there was it was unstoppable, right? Like like there was just going We knew there would be this 12-month window when everything that Palantir had been working on for years, they finally had the case studies done with their first set of clients and now they were just going to start to

46:42 steamroll and and add add to clients. So so they were just scratching the surface of their TAM and the market didn't realize that. So what was interesting about Palantir is that they were so overvalued at the time based on fundamentals that people were like, there's no way you could be going in levered on Palantir at $30 a share with its valuation already so out of whack.

47:06 And my response to that was the valuation is irrelevant to me. I don't I don't look at valuation. I don't look at PE. I don't look at anything like that. Um all I look about is there is new information that's about to come online for Palantir that will bring in a whole new group of investors and once people see this information, however they're valuing Palantir today based on the information that exist, this is new information that will be settled into the stock price.

47:40 And that that's exactly what happened. And Palantir went from, you know, 30 to 160, right? Or whatever it went to. So mechanical question. You say, you know, I went really big into this. So I made a huge bet on this. What is that and you're taking leverage which could cut both ways, right? So obviously leverage will increase your gains, but it'll quickly sink your your portfolio if done incorrectly.

48:04 How much are you actually Let's say you have you I think you said something like 70 million dollar portfolio. Let's say you have 70 million dollars and you get a lot of conviction about something. What are you actually betting at a high conviction bet at this stage? Are you Is it Are you putting 1%, 10%, 30%? Like what are you putting out there and then you're leveraging up and then how do you manage that risk of that going south?

48:30 Yeah, and by the way, just to be transparent, it's 70 millionish of returns, right? Of of of gains over that time and you know, those gains were taken and put in into other things like private companies, right? So I'm not managing That's not my public portfolio. >> Let's say that's gains, you got to pay taxes. A lot of your stuff sounds like it might be short-term because it's you got all all almost exclusively And then you're you're reinvesting that into your addiction in startups.

48:54 And so that's that There's a lot of it's going that way. But But percentage-wise, percentage-wise, when you have a high what I I call it just a high conviction idea, I'm usually investing between 5 and 10% of my entire liquid portfolio into that idea via options. So if you're wrong, you just lose 5 to 10% of the portfolio. And you know, a good example of where I did that and was, you know, wrong like I think two or three, maybe three weeks in a row, maybe four weeks in a row and I lost like 30, 40% of my portfolio was

49:35 during COVID during the pandemic when I was kind of tracking the virus coming out of China. I was you know, using Google Translate on a lot of medical reports coming out of China to assess how big of a deal that virus was and it became very clear to me that it was going to be a global pandemic and you know, global pandemics only do one thing to financial markets, right?

50:01 So, I I was essentially taking I think 10% of my portfolio and putting it into puts in the S&P casino stocks, Vegas casino stocks, and airlines every week and the market wasn't moving down. Like the market just wasn't accepting COVID for what it was and I got to a point where it was like 30 to 40% of my portfolio was gone. And I did it again the week after and that week after was the first week the market cracked and it went down 2%.

50:36 And then the next week is where it it really hit and that that was one of the biggest trades of my life and uh over the court I think that year was like a 370% annualized return total portfolio something like that and it was partially because I had shorted the pandemic early on even though it was a little too early and paid off and then 2 days after it bottomed I had selection of I think 14 or 15 companies that should have never gone down at all.

51:11 They should have only gone up as soon as we realized it was going to be a global pandemic and and everybody would be stuck living in their house for you know, working in their house for a year. So, you know, companies ranging from Hewlett-Packard where everybody would want to go buy printers for their house to Peloton because you can't go to the gym, you got to work out at your house now.

51:30 Shopify because you know, you're shopping online Amazon obviously you know, Campers World because one of the things you can do you can still go camping, boat stocks, you know, I bought a company out of Canada that nobody even had ever traded before that owned Schwinn bicycles because you know, Schwinn had a run of the biggest bicycle sales in the history of the company.

51:51 I think that that company went up 8X 8 or 9X over the course of 9 months. So, you know, I had these 14 15 companies. So, I was like these companies should be doubling right now and instead they were all down like 30 40 50% just because the whole market traded down. So, I always knew that I was going to go levered long in these 15 companies, but I didn't want to do it until the market became less erratic and irrational.

52:17 So, once the markets finally started to you know, normalize and come back up, I took all the gains from shorting the travel stocks in the market at large and just put them into levered positions in these 15 companies which was obviously the trade of a lifetime. So, So, that was a that was a huge year. >> the biggest dollar gains you've ever had? I I I don't know by the way.

52:42 I don't watch enough of your content to know how much you talk like do you like do you disclose like how much you make on these things? Do you say like I got a 10 million active portfolio? Like what what do you actually say? I don't know I don't know what you're transparent about. >> and transparent. I think that year I made 30 million in the market.

53:00 So, that was like 30 million in 1 year and it it was it was a wild ride. Didn't it? I think the most interesting part of that narrative was just before the pandemic I had made the worst trade of my life and it was actually a trade that was psychologically damaging >> [laughter] >> like I lost a third of my portfolio on a single trade just months before the pandemic started and the probably the thing I'm most proud of myself of is I was so down and out about that trade that I still found a way when I when I you know,

53:43 had come out with all that conviction on COVID to actually still go all in on my thesis on COVID even though my account was so brutally damaged at the point that if I got another one wrong I mean so it was like I could have gotten that would really have wiped me out. I mean I would have wiped me out, but it it would have been an unbelievable unbelievable damaging implosion for me to have two monster trades in a row go wrong.

54:15 The one that went wrong months earlier was a company QSR. They own Burger King, Popeyes, and Tim Hortons and I was so convicted that the company would have the best earnings quarter in its entire history because two of the three companies they owned both had anomalies on the positive side. Burger King had the Impossible Whopper which was unlike anything the company had ever done before in terms of sales traction and Popeyes had the crispy chicken sandwich which is during this is the chicken wars if you remember.

54:57 >> yeah. Yeah, I I at the time and that chicky crispy chicken sandwich at Popeyes had it would literally sell out in like 2 hours every day. It Popeyes no one had ever talked about Popeyes ever in the history of the company until this crispy chicken sandwich and I was monitoring both of those trends and I was like they're they're both going to report the best quarter in the history of their quarters at Burger King and Popeyes and then you have this third piece which was unfortunately the biggest piece the company Tim

55:31 Hortons and Tim Hortons is just you know, they're they're a Canadian coffee and donut shop, okay? And the company had basically been around forever. It had not been doing awesome, but it was kind of flatlining. They would have to have had a really bad quarter to screw up my trade and it was just happened to be a really difficult company for me to to extract information on through the methods that I use because it was Canadian and people just didn't talk about it that much, right?

56:10 There was nothing happening there. So, it was like I saw zero reason why they should have this anomaly of a bad quarter. Which is exactly what happened. They just happened to have like randomly one of the worst quarters ever which statistically the chance of that happening were so low and it crushed my trade. I I lost all of my money on that trade and it was like a third a full third of my portfolio and the wildest piece about that and this is where there was a lot of self-reflection cuz I take a lot of pride in in

56:43 going in deep and doing really intense comprehensive due diligence where sometimes if I if I have a high conviction trade, I will put you know, 60 plus hours of due diligence into the trade where I like to joke that I'll uncover every piece of contextualized information on the company globally through every social media anyone who's speaking about any of their products.

57:07 I will visit I will sometimes travel if they they're a retailer and visit stores and talk to store owners and clerks. But because there were three things I was having to deal with Burger King, Popeyes, and then Tim Hortons I just assumed Tim Hortons how bad is it going to be? Well, they had the Tim Hortons annual meeting a few weeks before earnings in Florida that I didn't realize they had this meeting.

57:31 But if I did realize that and I had done my homework, I would have been at that in Orlando for that annual meeting not cuz I would have got gotten in, but I would have hung out at the bar and I would have talked to all the franchisee owners because from what I understand there was a revolt at that at that meeting by franchisee owners because the company was doing so many things wrong.

57:54 Their sales were just getting slaughtered due to recent decisions that corporate was pushing on the franchisee owners and it would they were very public about it at that meeting. It was really harsh and if I was just in in the building right at the bar, I would have been well aware of that. So, going back, I learned that you know, you really have to be comprehensive in your research if you're going to take a levered bet on a thesis that you have and you can't you can't be lazy.

58:30 What are the bets you're looking at now? Cuz a lot of these examples are from the past 17 years. Where are you now? On the AI side, you know, two of my favorite AI picks you know, right now one is Bloom Energy. You know, the energy trade is a big one and it's one that's really really really misunderstood I think by most investors. So, Bloom Energy is a company that just has a really different approach to powering data centers, right?

59:01 They're not using big gas turbines. You know, they have a technology that they've worked on for you know, 20 years that is actual you know, DC technology where instead of combusting gas, it's actually a chemical change that creates the energy and they have a really quick timeline to energy for a data center. So, if you have a data center and you could actually get energy through Bloom and get your data >> center and you could actually get energy through Bloom and get your data center up and running 6 to 12 months

59:42 quicker uh than getting on a waitlist for gas turbines and going through all the various approvals. That's that's a really big deal and that's why Bloom Energy has I think they're up like 5 or 6x, right? Over the past 8 or 9 months as people are starting to realize this. But there's still a lot of controversy around the company. So again it's it's somewhat unproven.

01:00:09 They only have a couple big hyperscaler deals and you know ones with Oracle. Uh I think there'll be others that will be announced in the near future. But it's a new technology. So people are still somewhat skeptical of it. And then you have you know news events that that happen like this last week where now we're building data centers, you know, in in space, right?

01:00:32 You know, now that you know, SpaceX is preparing to IPO, all of a sudden we have this narrative pop out of nowhere where oh didn't everybody realize that we're just going to be doing, you know, compute data centers in space now? Like that's oh that's like right on the horizon. Like couple of years, 2 3 years, yeah, we're just doing data centers in space.

01:00:50 Like the this is the noise in the market right now, all right? So like oh we're doing data centers in space. And do we don't even need any down here? Like oh well if you're powering those with solar, you know, why would we want to value an energy company you know, here in the US uh if you're just going to do them in space with solar. So the market is so ADD that it's changing week to week, month to month based on whatever the hype story is and that will, you know, either positively or negatively impact companies in the

01:01:26 space. But for me, I I think uh I think Bloom Energy is definitely one of my favorite AI plays right now because they will be the company that will enable data centers to get up and running I think meaningfully quicker uh over the next 3 to 5 years. And I think that's a company that's just going to see its earnings double basically year over year for the next 3 to 4 very much misunderstood.

01:01:54 They're actually going to be the topic of my next uh Dumb Money Live episode. I'm going to go uh on Bloom Energy. We we spent like a couple months uh doing some doing deep analysis on on the company. Do you publish all your like do you publish your portfolio do you publish your trades somewhere? Um we don't I don't ever publish trades. I I sometimes speak about trades on a really high level.

01:02:17 The last thing we ever is other investors trying to mirror our trades because that's not it's not what we do, right? We don't think it's a healthy behavior. Uh I always tell investors to steal my ideas and run with them. So take the idea. Uh then poke holes in the idea. Do all of your own research, right? Uh and then come back to me and tell me where I was wrong.

01:02:41 Uh but ultimately then go off and make your own trade based on your own, you know, risk reward because we all have different degrees of risk tolerance and we should all have a different take on an idea. So I love sharing ideas. I don't really share trades. I mean I'll be honest with you because um this is not my world of expertise. I'm a founder first and my investing is very um sort of simple.

01:03:12 Uh you know, I basically own a couple of you know, I own some indexes and I own stocks that I understand. I've owned them for a long time, you know, tech companies basically cuz I have grew up in the tech industry since ever since college. And then I my investing outside of that is private angel investing, again tech. And lastly would be, you know, my own private equity where it's businesses that like individual businesses that I can own and and I can affect with with things that I know how to do operationally or

01:03:36 promotionally with this podcast. And so you're interesting to me because on one hand I I think well first of all, you're interesting because the story is great. Like I turned $20,000 into you know, I've made 70 million in gains or something like that. That's an incredible story. I think it's interesting because your approach like it's just the way you describe observational investing actually lines up with a lot of a lot of the great investors do and say, which is that they don't um sort of spreadsheet themselves to

01:04:05 death. They try to understand like surface out the signal from the noise. What is the actual important thing I need to know about this company that I can believe before it is obvious, true, and proven. And you know, the market uh sort of responds to certainty. And if you can handle uncertainty, um you could do quite well. At the same time uh you know, sometimes you say things like, you know, 99% of the other 99% of us can go do this and we have sort of the I think I've heard you say, you know, uh the game is rigged.

01:04:33 Wall Street is rigged, but it's rigged in our favor. And um you know, that part I think seems untrue. Like if if what you've done is true, it's in many ways because you have a a very unique skill set and upbringing and background. >> No. No. No. That's the that's it I I I >> the last thing I would want is people to listen to this and be like, oh okay, cool.

01:04:54 I can just go and trade levered up off of observations and I too will turn $20,000 into $70 million. There's a reason that's not common. That's not a common result. There's a reason you get a book deal. There's a reason people will follow you because it's not a common result everybody everybody does. And I think one of the reasons it's uncommon is not because it can't work.

01:05:12 That's not what I mean. A lot of it is interpretability, right? So interpret interpreting the signals, trying to figure out what is actually important. Is it already priced in? What does this mean? Who does it Who benefits from that? The second order effects of that. That's not like, you know, something incredibly uh you know, simple that the that uh everybody is going to do.

01:05:29 So there's a big difference between anybody can, yes. Everybody can is different. And so like I view it very similar to to startups where you know, an entrepreneur can come on here and they'll say, look, it's not rocket science. I'm not any smarter than you guys. I just did this this this and this. And it's true that any that was in the capacity for anybody to do, but definitely everybody won't.

01:05:49 And uh and definitely everybody should not try because they don't have, you know, either the nature, the disposition, the the risk tolerance to be able to go do it. So I just think you're interesting cuz you're this sort of like puzzle. Normally, if I hear a story like this, it's too good to be true. It violates a lot of the sort of like fundamental wisdom that people have about investing where you want to buy you know, buy a share in a great company and hold it for a long time.

01:06:11 You know, things that I have sort of accepted from, you know, a a certain school of thought around this. So I think you're very interesting because you violate some of those and I think that that works. And it works for you and I think it's very cool. But I hesitate. I hesitate because I think that this is not something that a lot of people could or should do.

01:06:29 So so I couldn't disagree more. Um I do I agree with some of what you're saying in terms of yes, I mean over a long period of time, you know, doing, you know, generating almost $100 million from a, you know, $20,000 Yeah, that it's that's not easy to do, obviously. But I will say this. I think I think the biggest issue is simply bucketing money and having uh risk capital.

01:06:58 So I think the the the number issue preventing someone from doing this is thinking that they have this one bucket of capital for their life savings, for their future kids college, for their retirement. And they think about that money all as one. And this is something that's a little foreign. The concept of being a regular person and observing something and say connecting the dots and saying, you know what?

01:07:30 I'm going to put a levered bet on that because I just found, you know, I just discovered this. you have your money properly bucketed. And the one thing I teach people is you have to have risk capital. I don't care if it's $50 or $50 million. You don't you shouldn't be waiting until you're part of the, you know, ultra wealth class to to to to think that you have risk capital to take risk with.

01:07:52 You need to have risk capital starting with day one. So everybody should have a big money account. I talk about this in Laughing at Wall Street. Everyone should have a big money account. And the big money account is the account that that yes, you get wealthy quickly with. And you do that by taking big swings on things that you really believe in. And the only way that you're going to psychologically do that is if you fund that big account with money that is not being stolen from other areas of your life.

01:08:25 So I I call it you know, there's this whole concept of like frugality or trade-offs where okay, maybe you mow your own lawn, maybe you make your own coffee, maybe you clip coupons. Like people don't want to clip coupons to save a dollar. But if you think about every dollar in your life as it it as potentially being $100, 100x, which is 100% feasible over a long period of time if you invest aggressively with leverage and get a few wins, then you'll clip a dollar coupon because that dollar coupon is clipping a $100

01:09:02 coupon. Okay, you're going to make your own coffee cuz instead of saving $5, you're saving $500 a day, right? So all of sudden you discover all of this money, new found money in your life by making little trade-offs in things all over your life. The difference is every time you make one of those trade-offs and you save $5 for making your own coffee, you take that $5 and you The risk capital bucket.

01:09:29 Yeah, account, bucket, right? Oh, by the way, this is not financial advice, right? It's just like this is how I did I'm just saying like I hope I'm inspiring people cuz I just understand something. I graduated in the bottom 25% of my high school class. The bottom 20 Today, the way college is, I could not even had I would not have gotten into any university in the United States, okay?

01:09:55 Pretty much today in 2025 with with my grades. This is why I love doing the podcast cuz you can get people who make their money in all different ways. We just had John Morgan who's like the guy on the billboards personal injury law. And he's a guy, you know, he's the biggest personal injury lawyer in the world, $2 billion a year. And then he started you know, he started his career working at Disney World as Pluto.

01:10:19 Like he would be in the costume. And then he started because of that formative experience, he took the money from the law firm and started building little like attractions like a fairs and and and places you go and buy tickets like the the Museum of Crime and History, things like that. And he's made a killing doing that. So you have that guy comes on tells about how you make money that way.

01:10:38 Another guy says how you do it this way. So what I love about the podcast is I get to hear these people who come on with completely different blueprints and playbooks that they 100% believe in. And I get to listen and I get to decide. I get to decide for myself. Does that sound like something that's interesting or would suit me? And I hope the listener does the same because I don't agree with a lot of what you said, but I found it all very interesting.

01:11:00 And you know, there's some things you said if like I'll I'll be I'll be totally honest. If you saw if you have like a paid course somewhere, I would be like I can't run this episode because I feel like this guy is selling this dream to people that hey yeah, you just got to just go go get in the TikTok comments, find an observation, lever up, baby, make a trade.

01:11:19 One trade will change your life. And it's like that is a scary principle. I think that is a heretical idea to a lot of people. It's probably why it's very interesting to me to hear it, to talk about it. Why is it Why is it important to you that people really that the average person who's listening, they believe this and they go take action on this cuz you know, like I said, it's not that you're running a fund, right?

01:11:40 So you're not soliciting investors. You're not selling a course like I'll teach you how to do this. Trust me, it works. You're not doing any of those things, which is usually why people really kind of pound the table and say you can do this. Just believe. Just go for it. My my overriding purpose is to inspire every human on Earth to enter the investing class, right?

01:12:00 Because I think it's the only way we'll ever solve the wealth gap. So like there's no way to solve the income gap. The income gap is an exceptionally difficult problem to solve. The wealth gap is a problem that's solvable by bridging more humans into the investor class. And so everything that I do on X, everything that I do on YouTube, every podcast that I do has a single mission to inspire other people to start investing on their own.

01:12:28 And by all means, if that means just throwing money in the S&P in an ETF, awesome. But there's no reason to stop there, right? Like I I know I know that people love the concept of actually hope and having an opportunity to do something truly great in their life cuz so many people when it comes to income are stuck. Their job is not going anywhere, okay?

01:12:55 Like And by the way, I am not a proponent of people quitting their jobs and becoming entrepreneurs and taking all this massive personal risk to start businesses. I think there are very few people that are capable of doing that. And I think that this road map is way more achievable for people. Start making tradeoffs. Come up with a big money account.

01:13:18 Do it through making tradeoffs in your life and frugality. Learn how to use leverage. Learn how to take big risk with other people's money because I call it other people's money cuz it's all comes to tradeoffs. Um in things that you believe in because you can do this. And by the way, there is nothing cooler than when you're just a regular person and you you just make a grand slam in the market, right?

01:13:45 And you you 30x your money. All of a sudden you have financial independence in life. So I don't know many things that are more important because it just it helps solve so many other issues. And so many humans are just depressed because they look at their life and they're like, this is my job. These are my expenses. This is inflation. Holy crap, I'm screwed.

01:14:07 I will never be the person I want to be for me or my family. And I want to inspire people that it doesn't have to be that way. And you also don't need to be taking big risk with your retirement money or any of that stuff. That's why I'm like I'm very clear. If you're going to do this, do it with money that's bucketed, right? For for risk. You know, this isn't just about investing.

01:14:34 Um the same methodology being able to identify change in the world and tailwinds um and trends should apply to career. It should also, you know, like it should apply to entrepreneurs as well cuz like I'm an entrepreneur like I'm about to start another business. Uh and that business is directly tied to the analysis that I'm doing discovering change in the world, right?

01:15:04 So like, you know, we're about to embark on this journey of of abundance. And that's not going to be like we just hit the age of abundance in 5 years and we're not working. Like no, the age of abundance is going to like slowly happen. It's already happening. It's going to It's going to like happen over the course of decades. And it's just it's just lots of tailwinds and trends.

01:15:29 It's like people will be working a little less. People will have a little more free time. People will have more flexibility to dive into the things that they care about, right? Wealth signaling will I think become even bigger in the future than it is today. I There's just so many changes that are massive that are happening in the world that if you're an entrepreneur trying to figure out like where do I spend my time?

01:15:52 Or if you're just someone that is figuring out where's your next career path? Or where if you're a young person, where's my career path? Like you need to be doing more analysis on where the opportunity is because these are some of the biggest decisions of your life. It's not just about trading a stock. Yeah, especially in in Silicon Valley, you see this all the time.

01:16:15 People will take a job and it's like you realize you're investing all of your life force. You're you know, your creative energy. And you're getting these stock options, but you never thought about this like an investor. Like you're just happy you got the job versus you should be looking at the job market the way an investor looks at these companies.

01:16:31 And even if you're not investing capital, you're investing your time, right? So that that applies, you know, totally there. You You said you're launching a new business. What is it? It is related to the jet industry, private jet industry, which I believe will be one of numerous beneficiaries of us kind of entering into this age of abundance with people having, you know, more In In fact, I'll just quickly state that if you want a glimpse into the future, you need to simply look back into our past from the pandemic

01:17:02 because that one year of the pandemic when we actually had an abnormal amount of time as humans. We had never experienced anything like that throughout our lifetime. When we had excess time to actually do what we wanted to do and we also just happened to have excess money because of this wild stimulus that happened during the pandemic. So if you want an example of what the age of abundance is going to look like in terms of the winners and the losers, just look back to that one period of time.

01:17:37 What did we do when we had more time and more money? We dug into our hobbies. We dug into our interest. Um we, you know, we we we kind of did things that now that we're back to this world, right? Like we do a little bit less of, but if we truly get, you know, the industry of intelligence and automation and robotics to help us do the vast majority of work, uh the repetitive work at least that we do today, I think the entire world has an opportunity to become more creative, uh spend more time with their families, with

01:18:19 their friends, doing things that are meaningful. Uh travel certainly I think it is something that we can all count on in the future as becoming a larger industry, not a smaller industry. I am ultra long on the private jet sector even though myself I carry too much guilt to fly private. Uh so like I you'll never see me on a private jet, but I I I'm very bullish on the sector.

01:18:47 >> [laughter] >> That's amazing. Chris, thanks for coming on, man. I appreciate you. And people can go find you. You got your show Dumb Money Live. It's on YouTube. That's where I watch it at least when I when I tune in. Um so thanks for coming on. And by the way, the only place I am personally is X. So @ChrisCamillo at X. But dumbmoney.tv has all the socials. So thanks for having me on. I I appreciate it. Very cool. Well, that's it. That's the pod. >> Woo.

💡 Answer

Observational investing: detect meaningful changes early, connect them to affected public companies, and trade before the information becomes widely recognized. The approach can be learned, but exceptional results require uncommon interpretation, research, risk tolerance, and discipline.

🧠 AI Summary

Chris Camillo built a portfolio from $20,000 starting in 2007 by using observational or social arbitrage investing: identifying emerging changes in consumer behavior, culture, technology, weather, or politics before they are widely recognized, then connecting those changes to affected public companies. The process emphasizes information asymmetry rather than valuation, PE ratios, technical analysis, or long-term buy-and-hold investing. Examples include using Google Trends to track roof-repair searches after hailstorms, monitoring beauty-influencer content for e.l.f. Cosmetics, and reading TikTok comments for early consumer signals. The strategy can produce exceptional returns but requires interpretation, comprehensive research, risk tolerance, and disciplined capital allocation. Risk capital should be separated from retirement and essential funds, and ideas should be independently researched rather than copied.

🔑 Key Points

  • Observational investing identifies meaningful changes in the world before conventional investors recognize or price them in.
  • Positions are entered during information asymmetry and exited when other investors reach information parity.
  • The methodology prioritizes conversational data from social platforms and real-world observations over valuation, PE ratios, technical analysis, and traditional financial data.
  • Important checks include whether the information is meaningful, whether it can move a sector or company, whether it is off-radar, and whether other events could matter more.
  • Camillo started with $20,000 in 2007 and reported approximately 70 or 80 million dollars of returns, with audited annualized total-portfolio returns around 75% over 17 or 18 years.
  • Leverage magnifies both gains and losses; Camillo lost a third of his portfolio on a QSR trade and lost 30% to 40% during several early COVID trades.
  • Risk capital should be separated from life savings, retirement funds, and other essential financial obligations.
  • The same process of identifying changes and tailwinds can be applied to career and entrepreneurial decisions.

✅ Actionable items

  • Monitor consumer behavior, culture, technology, weather, politics, and other changes that could materially affect public companies.
  • Use Google Trends to compare current search activity with historical patterns and seasonality.
  • Read social-media conversations and comments to identify emerging demand before it appears in sales data.
  • Connect an observed trend to the public company that may benefit or be harmed by it.
  • Assess whether the information is meaningful, off-radar, already priced in, or outweighed by other events.
  • Conduct comprehensive due diligence, including visiting stores and speaking with owners or clerks when relevant.
  • Use ideas as starting points, independently research them, identify where the thesis could be wrong, and make decisions according to personal risk tolerance.
  • Create a separate risk-capital or big-money account funded through savings and personal tradeoffs rather than essential funds.
  • Use historical norms, seasonality, and abnormal changes in speech patterns when analyzing social data.

💡 Business ideas

A private-jet-industry business01:54:39

Chris Camillo said he was preparing to start a business related to the private jet industry, based on his view that increasing abundance and free time could expand travel demand.

For
Private-jet industry customers
Solves
Not explicitly described.
Validate by
Not explicitly described.

    🏗️ Business models

    TickerTags conversational-data platform29:49

    A platform that converted manual social-signal analysis into structured, real-time data for financial institutions.

    1. Access a real-time sample of Twitter posts.
    2. Curate word combinations connected to products, brands, and public companies.
    3. Organize the terms into a company-linked taxonomy.
    4. Compare mention frequency with historical norms and seasonality.
    5. Flag abnormal speech patterns potentially relevant to public companies.
    6. Sell the resulting data and analysis to hedge funds and sell-side banks.
    • The platform used Twitter's Decahose, described as a 10% randomized real-time sample of tweets.
    • The taxonomy contained about 1.5 million word combinations.
    • Each company had approximately 300 to 1,000 word combinations.

    💰 Monetization

    Selling conversational-data intelligence 31:41

    TickerTags was sold as a data and analysis platform to hedge funds and sell-side banks.

    • Hedge funds
    • Sell-side banks

    📣 Marketing

    Sales

    • TickerTags was sold to hedge funds and sell-side banks.
    • The platform was later sold to Jefferies Bank.

    Branding

    • The methodology is called social arb investing, observational investing, and conversational-data investing.
    • The investing book mentioned is titled Laughing at Wall Street.

    Distribution

    • Dumb Money Live is distributed on YouTube.
    • Chris Camillo said he uses X and that dumbmoney.tv contains the social links.

    Customer acquisition

    • Chris Camillo spent years traveling to New York and training sell-side banks and major hedge funds on interpreting conversational data.

    🔍 SEO & discoverability

    Strategies

    • Google Trends was used as a free source of real-time and historical search data.

    Other channels

    • TikTok comments
    • YouTube videos
    • Twitter posts

    Content strategy

    • Social-media comments and videos were monitored for emerging product and cultural trends.
    • Abnormal changes in mention frequency were compared against historical norms and seasonality.

    Keyword research

    • Search terms included roof damage and roof repair.

    🧭 Frameworks

    Social arbitrage or observational investing01:29
    1. Observe a change in the world.
    2. Determine whether the change could materially affect a public company.
    3. Assess whether the information is meaningful and off-radar.
    4. Connect the change to a company that could benefit or be harmed.
    5. Enter when information asymmetry exists.
    6. Exit when information parity is reached.
    Conversational-data signal analysis30:09
    1. Collect social-media conversations.
    2. Organize relevant words and phrases by company or product.
    3. Benchmark mention frequency against historical norms and seasonality.
    4. Flag abnormal speech patterns.
    5. Interpret whether the anomaly represents a meaningful trend.
    Risk-capital bucket approach01:06:54
    1. Separate essential financial funds from risk capital.
    2. Fund a dedicated big-money account through savings and personal tradeoffs.
    3. Use the account for high-risk, high-conviction opportunities.

    🧰 Tools & AI usage

    • Google Trends — Track search volume, historical patterns, and seasonality for terms such as roof repair and roof damage.16:06
    • Google Translate — Translate medical reports from China during the early COVID period.49:43
    • Twitter Decahose — Provide a 10% randomized sample of tweets in real time for conversational-data analysis.29:49
    • TikTok — Source conversational data and comments about consumer behavior, products, and culture.21:59

    AI is used for

    • Translating medical reports from China during the early COVID period — Assess the potential scale of the virus and its effect on financial markets.49:43
    • Analyzing social-media and conversational data — Identify abnormal changes in consumer interest and emerging trends.29:49

    📊 Numbers mentioned

    Costs

    • Wall Street firms were described as spending millions to tens of millions of dollars analyzing credit-card receipts.

    Growth

    • $20,000 grew to $2 million in 3 years.
    • Camillo reported approximately 70 or 80 million dollars of returns from $20,000.
    • Reported annualized total-portfolio returns were around 75% over 17 or 18 years.
    • A bicycle company associated with Schwinn was described as rising 8X or 9X over 9 months.
    • One annual return was described as approximately 370%.

    Pricing

    • The e.l.f. product was described as costing about $8.
    • The competing product was described as costing $60.

    Revenue

    • $30 million made in the market in one year.
    • $2 billion a year attributed to John Morgan's personal-injury law business.

    Traffic

    • About 10 million views for the Jeffree Star video referenced.
    • About 1.5 million curated word combinations in TickerTags.

    ⚖️ Advantages, risks & lessons

    Advantages

    • Uses free or accessible observational and conversational data.
    • Can identify trends before conventional transactional data and institutional research.
    • Allows investors to compete in areas where conventional investors may lack context.
    • Can be applied to investing, careers, and entrepreneurship.

    Risks

    • Leverage can rapidly damage a portfolio.
    • Social signals require subjective interpretation and may be nuanced or misleading.
    • A thesis can fail because an important business segment is overlooked.
    • Historical correlations may not exist for new trends.
    • The strategy requires substantial time, research, and risk tolerance.
    • Exceptional returns are uncommon and should not be assumed to be repeatable.
    • Using essential savings, retirement money, or other required funds for leveraged trades can create severe financial harm.

    Lessons

    • A meaningful information edge can matter more than conventional valuation analysis.
    • Being different from conventional investors can create an edge, but the signal must still be interpreted correctly.
    • Comprehensive diligence is essential when using leverage.
    • Do not sell a position merely because it has risen; exit when the information behind the thesis becomes widely recognized.
    • Independent research is preferable to blindly copying another investor's trades.
    • Small savings can be redirected into risk capital, but only when essential financial needs remain protected.

    💬 Quotes

    You really only need one great trade to be a top 1% investor.

    Expresses the central emphasis on finding a single highly successful opportunity.00:00

    You invest when you discover something that other people haven't discovered yet that will be meaningful to a trade and you exit as soon as other people have figured that out.

    Provides the clearest concise definition of the investing methodology.44:18

    You have to think differently.

    Summarizes the need to seek an edge outside conventional institutional and retail approaches.24:27

    Everybody can is different.

    Distinguishes the learnability of the method from the rarity of achieving exceptional results.01:05:36

    📈 Investment analysis

    mixed

    Assets

    Beacon Roofing bullish
    stock

    A large hail season and increased roof-repair searches were used as a bullish signal.

    e.l.f. Cosmetics bullish
    stock

    A beauty influencer's video and observed product demand were used as bullish signals.

    Sphere bullish
    stock

    Early Wizard of Oz reviews and subsequent seat sales supported a bullish trade.

    Palantir bullish
    stock

    The thesis focused on market recognition of Palantir's AI position, new products, client case studies, and total addressable market.

    Bloom Energy bullish but speculative
    stock

    The company was presented as an AI-related energy play with a faster data-center power timeline, but its technology was described as new and somewhat unproven.

    S&P bearish during early COVID positioning
    index

    Put options were used during the early pandemic thesis.

    Private jet sector bullish
    sector

    The sector was described as a future beneficiary of increasing abundance, free time, and travel demand.

    Price references

    AssetPriceTypeTimeframeContext
    e.l.f. Cosmetics USD $7 to $170 historical price range The stock was described as trading at about $7 a share before rising to $170 a share. 19:52
    Sphere 114% increase 2025 The host referenced Sphere as up 114% that year; the trade used leveraged options. 36:08
    Palantir USD $30 to $160 historical price range The stock was described as rising from $30 to $160, with the speaker also saying 'or whatever it went to.' 47:43
    Bloom Energy 5 or 6x increase past 8 or 9 months The company was described as having increased approximately five- or sixfold. 58:54

    Predictions

    • bullish Bloom Energy — Bloom Energy will enable data centers to become operational meaningfully faster over the next 3 to 5 years. (next 3 to 5 years)
      Its technology could provide energy 6 to 12 months faster than waiting for gas turbines and related approvals.
      01:00:45
    • bullish Bloom Energy — Bloom Energy's earnings will double year over year for the next 3 to 4 years. (next 3 to 4 years)
      The company was described as misunderstood and positioned to benefit from data-center power demand.
      01:01:07
    • bullish Private jet sector — Travel and the private jet sector will become larger industries as people gain more time and resources. (future)
      Automation and robotics may reduce repetitive work and increase time for travel and other interests.
      01:58:38

    Actions noted

    • Allocate through options High-conviction ideas @ 5% to 10% of the entire liquid portfolio
      The position is described as appropriate only for a high-conviction idea and risk capital.
      48:48
    • Enter when the information is known by few investors and exit when other investors learn it. Positions based on information asymmetry
      Exit based on information parity rather than a preset percentage gain.
      04:16
    • Separate risk capital into a dedicated big-money account. Risk capital
      Do not use retirement money or funds needed for essential life obligations.
      01:07:01

    Market factors

    • Information asymmetry — Creates an opportunity when a meaningful change is known by relatively few investors. 03:01
    • Social-media conversation and comments — Can reveal consumer interest before sales data confirms demand. 26:06
    • Wall Street's reliance on transactional and historically correlated data — May leave conversational data underused and create an edge for investors willing to interpret it. 24:23
    • Market hype and rapidly changing narratives — Can cause companies to be positively or negatively affected by new stories from week to week. 01:00:08
    • COVID-19 pandemic — Created sharp market dislocations and different effects across travel, home-work, e-commerce, fitness, camping, and bicycle companies. 49:38

    👤 People & companies

    Chris Camillo

    Investor and entrepreneur associated with observational investing, social arbitrage, TickerTags, and Dumb Money Live.

    01:29
    Warren Buffett

    Investor referenced as an example of a traditional fundamental-investing approach.

    21:44
    Charlie Munger

    Investor referenced alongside Buffett as someone focused on company financials.

    21:44
    Peter Lynch

    Investor whose observational investing approach was cited as an influence, alongside fundamental analysis.

    12:18
    Jeffree Star

    Beauty influencer whose video about an e.l.f. Cosmetics product became a trading signal.

    19:38
    Abdoer

    Data and machine-learning entrepreneur associated with the development of Twitter's trending product.

    27:36
    Patrick

    Chris Camillo's friend and coworker at eRewards in Dallas, Texas.

    37:30
    John Morgan

    Personal injury lawyer referenced as an example of a different path to building wealth.

    01:00:05
    HubSpot

    Sponsored the downloadable cheat sheet about four rules for making money.

    05:32
    Snapple

    Beverage company used in an early observational trade based on reduced retail shelf space.

    09:09
    Beacon Roofing

    Roofing company connected to hail-damage search trends.

    16:20
    Victoria's Secret

    Bra company cited as potentially vulnerable to changing consumer preferences for bralettes and no-wire bras.

    14:14
    e.l.f. Cosmetics

    Cosmetics company whose product gained attention after a Jeffree Star video.

    19:38
    Twitter

    Social platform used for conversational-data analysis and later associated with the trending product.

    28:00
    Newell Brands

    Company associated with Elmer's Glue and a trade based on the popularity of DIY slime.

    30:38
    Jefferies Bank

    Bank that acquired TickerTags.

    32:24
    Sphere

    Entertainment venue and company linked to a trade based on early reactions and seat sales for Wizard of Oz.

    35:48
    Palantir

    Company traded on the expected market recognition of its AI-related products and client case studies.

    45:24
    Oracle

    Hyperscaler mentioned as having a deal with Bloom Energy.

    58:02
    Bloom Energy

    Energy company developing technology intended to power data centers more quickly than gas-turbine alternatives.

    58:42
    QSR QSR

    Company owning Burger King, Popeyes, and Tim Hortons; a trade lost a third of the portfolio after a weak Tim Hortons quarter.

    54:28
    Burger King

    QSR-owned restaurant brand associated with the Impossible Whopper.

    54:38
    Popeyes

    QSR-owned restaurant brand associated with the crispy chicken sandwich.

    54:38
    Tim Hortons

    QSR-owned Canadian coffee and donut chain whose weak quarter damaged the QSR trade.

    55:18
    Hewlett-Packard

    Company cited as a potential pandemic beneficiary because people would buy home printers.

    51:10
    Peloton

    Company cited as a potential pandemic beneficiary because gyms were inaccessible.

    51:28
    Shopify

    Company cited as a potential pandemic beneficiary because of increased online shopping.

    51:32
    Amazon

    Company cited as a pandemic beneficiary of online shopping.

    51:34
    Camping World

    Company cited as a potential pandemic beneficiary because camping remained possible.

    51:36
    SpaceX

    Company mentioned in connection with a reported potential IPO and the narrative around data centers in space.

    01:00:34
    eRewards

    Company where Chris Camillo worked in Dallas, Texas.

    37:30
    Disney World

    Employer referenced in an example about John Morgan's early career.

    01:00:17

    🔗 Links mentioned