Edwin Dorsey’s Playbook: Betting on Yourself in Financial Media

Edwin Dorsey started The Bear Cave in his college dorm in February 2020. Within 6 weeks of putting up a paywall, he was at $100K ARR. He’s never worked for anyone else.

This conversation details the brute force hustle that got his first readers, building StockPromotionTracker as a non-technical founder, and where he sees prediction markets going.

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Listen on Spotify here.

The Early Days of The Bear Cave

0:00

Bryan Wagman: So, wanted to start with something that I think is really cool, actually, about your journey, which is the… I guess the… the DMs that you sent and the emails that you sent to get things off the ground in those first days when you were just getting things rolling with the Bear Cave. So, can you… can you tell that story?

0:21

Edwin Dorsey: Yeah, absolutely, Bryan. So, when I was a senior in college, I started the newsletter, The Bear Cave, mainly as a way to get attention and hopefully get hired by a hedge fund. And so, I started writing this newsletter in my dorm room in February 2020, right before the pandemic hits. The pandemic hits, everybody goes home, I graduate a quarter early, so I got all the time in the world to work on this newsletter, and hopefully make it into a thing that people start reading. And it’s always tough to get your first thousand readers. I tweeted about it, and it got some traction, and I had a few Twitter followers at the time, but I really wanted people to read it.

So, I went through every single person who was following me on Twitter, I don’t know how many, maybe it was 10,000 people, and individually DM’d every single one that had DMs open. I literally spent 3 days just DMing people, saying, will you please read my newsletter? And my eyes were hurting, and that’s one way in which I got a few readers to sign up for the Bear Cave early on. Another thing is that I looked at every single college student investment club, and I cold-emailed every college investment club, asking them to check out my newsletter. I just went out to the world and found every potential reader and emailed them to say, sign up for more emails. And luckily, it was the pandemic, and people were really open to finding stuff to read, so that’s how I got the initial ball rolling. And what I found with newsletters is once you have the initial readership of a few thousand people in the right audience, then as long as you produce good content, it kind of grows on its own. So there was a lot of hustle to get those early readers, but now it’s just… the momentum takes it.

2:06

Bryan Wagman: What were those 3 days like? Like, did you have a certain routine to kind of get through it? Like, were you, you know, surviving off coffee? Just, like, paint the picture for us.

2:17

Edwin Dorsey: So I don’t do coffee, lucky. I try to avoid that. I was living with my… in my parents’ house at the time, just graduated, and I’d go down to a table, and it… it’s terrible, it’s not fun just to repeatedly cold email people. The first thing I do is you want to test out various prompts. I had a lot of experience cold emailing people when I was a college student. I sent so many cold emails just trying to meet and network and learn, so I think I drafted 2 or 3 different versions of a DM I could send people to sign up for the newsletter. I tested, I iterated. And I was also testing different times. I’ve long been a believer the best time to ask anybody for a favor or reach out to them to get their attention is in the afternoons. In the mornings, people are busy, and you got your work to get through, and in the evenings, you’re gonna go to bed, and you’re socializing, but in the afternoons, you just had lunch, you’re in a good mood, it’s a lull in the day. So I was testing various different prompts at various different times to send DMs, and I think I concluded, like, I found the prompt that worked best. It’s always just good to keep it short and directly ask what you want, which is them to sign up for the newsletter, and I found that the afternoons were good, so I’d block out 4 or 5 hours, and, you know, say, just get through this many, just get through this many, just get through this many, and then by the time I did, you know, roughly 10,000, I didn’t have anybody else to DM. And it was nice, too, because if people don’t like the message, they’ll just ignore it, and they won’t sign up, but if people do like it, they’ll give you some positive encouragement, so it was cool to get a lot of DMs back, saying, oh, this is so cool, I’ll definitely check it out, I’ll tell a few people. I think the traditional advice with venture capitalists is you do things that don’t scale in the early days to get customers and readers, and this is one example of that.

Brute Force Networking

4:11

Bryan Wagman: Yeah. That’s… that’s sort of what I wanted to ask you about, because I think that’s exactly what it is. Like, it’s… it’s not scalable, and even beyond that, I feel like most people, when they think of just the… the idea of DMing 10,000 people or something like that, like, it seems almost like… not possible, or just, like, something most people wouldn’t really consider. I’m curious, in the past, had you had other examples of taking this sort of, like, brute force type approach to life?

4:38

Edwin Dorsey: Yeah, oh, absolutely. I love that question. That’s one thing I did really good, especially when I was young. I think when you’re a college student in particular, you’ve got this innocence about you, which means people are way more likely to help you than they are, you know, once you graduate from college or you become a full adult in your late 20s and early 30s. So, as a college student with my college email, I… when I was in New York for a few months, I looked at every single Stanford alum at the big financial firms that I admired, and I just pulled their emails from our alumni database and cold email. I think I was averaging 100 cold emails a week. 10% response rate, 5 would lead to meetings. I would not be surprised if I have cold emailed more Stanford grads in finance than anybody to ever be an undergrad. And this is how you get the foot in the door. And the other thing is, it’s great to network when you don’t need anything. So if you don’t need an internship, or you don’t have, like, a clear ask, you’re genuinely just going to learn, and maybe present, and try to… show your skills a little, and just understand the industry better.

So, that was a big brute force approach. There’s one story I like to tell of a particular hedge fund in San Francisco, and I cold email, like, everyone told me you gotta meet with them. And I cold email, I cold email, I cold email, no one’s responding. They didn’t say no, just no responses. So, I decided, as a freshman, let me just go there and see if they’ll meet with me. So I took the train up, I go to this big, fancy building, I go up to the desk with the guard, you know, guarding people from going to the elevators, and he says, do you have an appointment? And I say, no, but I want to present to them my ideas, and maybe they’ll give me an internship, and he’s like, he says, you can’t come up without an appointment. I said, please, just let them say no to me, I just want to go up, and they say, you can’t go up without an appointment. Perfectly fine, and I said, okay, I’ll sit in this lobby and see if… if someone calls down to get me, you know, then they can… I’ll be let up. So I go, I sit down in the lobby, and I start LinkedIn DMing everybody at the hedge fund, saying, look, I’m a freshman in college, I’m in your lobby right now, will you please meet with me? I want to share stock ideas. In hindsight, it’s a little weird, but… in the moment, I had this confidence, and eventually one of them said yes, and they called down, and the guard, the front desk agent, was just amazed that I got let up, and I met with them, and I think they became subscribers to my newsletter four years down the road, and it was just a funny story. So, it’s really important to take a lot of initiative, and once you get older, you can’t randomly show up places, and, you know, cold outreach doesn’t work as well, but I think especially when you’re young, it goes a long way.

7:28

Bryan Wagman: Yeah, that was gonna be my next question. Now that you’re more established, do you find you have to use these sorts of tactics somewhat less? Or, like, when was the last time you can think of sort of doing something along these lines?

7:41

Edwin Dorsey: So, I would never now go show up somewhere randomly, it’s disrespectful and odd. You know, I might… I probably wouldn’t just cold email somebody to say, hey, I just want to talk, unless I feel like I can bring something to the table, because I don’t want people just to donate their time for maybe no reason, unless it’s a special circumstance, but I do cold email a lot of people to get featured on my Idea Brunch newsletter. The thing is, if somebody says no, like, then I’ll take them off my reach-out list. I won’t continue to persist, but I do cold email a lot, but I also believe in just respecting people if they say no, and they’re not interested. You know, I’ll have some people I really admire who I just, every 6 months, I’ll reach out to them, and, you know, until they tell me they’re not interested, I’ll email them every 6 months, because I think they’re great. And, you know, some people do, you know, after 2 years of pestering them every 6 months, hey, can you come on my interview series? They do go on. So, that’s another example. But I’ve found that as you get maybe a little older and more established, it’s better just to demonstrate the value you can provide, do interesting things online, and then let people come to you. And that’s the best way to do it, and that’s kind of been my approach, is try to build cool tools and share them online, write interesting things in your newsletter, and then if people come to you, that can be your new network.

Starting Over & AI Integration

9:01

Bryan Wagman: And if you were just getting started out today, what would you do differently, both in terms of, I guess, the the product and the value add to the client in terms of, like, what you would think about trying to provide, as well as how you would think about distributing it.

9:18

Edwin Dorsey: In terms of, like, if I was starting the newsletter now, what would I do differently with the Bear Cave? The number one thing is you want to be very fluent in AI and using AI tools. I use ChatGPT a lot. I kind of wonder if I was doing the newsletter now, how many AI-related screens can I do to… and make that integrate to the Bear Cave’s content? So, every month or so now, I have ChatGPT Deep Research give me a list of all recent IPOs and SPAC mergers that have high levels of consumer complaints. If I was starting the newsletter now, I’d probably, you know, make 5 or 6 of these different screens that are running all the time, and have AI researching it, and then, you know, here’s some AI-generated ideas, quick spark notes on each one, and the unique filters we’re using to come up with them, so that’s one big thing. I’m not sure I would do anything terribly different. I think I know the newsletter game pretty well, and I think I was really lucky with the pandemic thing timing.

Maybe one thing I did wrong is I think pricing it between $500 to $1,000 a year, that’s a no-man’s land for pricing. I was originally at $340, $34 a month or $340 a year, then I raised it to $44 a month or $440 a year, while grandfathering in existing subscribers at the lower rate, and then I raised it again to $640 a year. I think that last price increase going above $500, it’s a psychological hump where you either charge over $1,000 or under $500. That’s a no-man’s land, and that’s maybe one thing I wouldn’t have done.

Daily Routines & Walking

10:56

Bryan Wagman: Yeah. One thing that stood out as I was doing some research for this podcast was, you have a big walking habit, it sounds like, and also your work, just, I guess, patterns seem to fluctuate a lot. Like, some weeks it can be super intense, and then some it’s more relaxed. So, like, what’s a… what’s a typical day, I guess, like, for Edwin Dorsey during a calmer period? And then, same question for maybe a more intense period?

11:25

Edwin Dorsey: I have a very atypical life and very atypical day-to-day schedules. For me, some of my day is dictated by the weather here in Miami. If the weather’s nice, I’m gonna go for a really long walk, and maybe go to the beach and listen to a podcast or stuff that’s relevant for work. I might, you know, have 3 tickers I’m interested in, I’ll find 10 hours worth of podcasts from CEO executives and industry participants talking about these companies. Just go for a long listen to the podcast, and I’ll listen to one CEO, and I’ll say, you know, he seems reasonably okay. Maybe don’t write on that company. I’ll listen to another one and say, this guy is so bad. Now, this is gonna be a focus, and I’ll try to, you know, piece together a mosaic. So that might be one thing, if the weather’s good.

If the weather’s not so good, you know, I spend a lot of time now on prediction markets, which we may talk to later, so I do a lot of research on those things. I might be just writing the newsletter, because I’m on a schedule. We’re first and third Thursday of the month. I publish these Bear Cave Deep Dives. I have a Bear Cave Deep Dive due this Thursday, so tomorrow and Wednesday, it’s gonna be full-on 12 hours plus in my apartment, just writing the newsletter, doing research on them. That’s really intense. But if it’s a week where I don’t have a Bear Cave due, I’ll probably be spending more time on prediction markets, more time going for walks and listening to podcasts, and more time just, you know, doing soft research on various ideas to try to narrow down which company I want to write on.

Career Path & Betting on Yourself

13:00

Bryan Wagman: Yeah, for sure, and definitely going to get more into those prediction markets later. They were pretty new for me, so I have tons of questions. One other thing I’m really curious to hear how you think about both now, but as well as in the past, and how you sort of found yourself in this situation, is just, you know. Obviously, given your background and your aptitude in this field, you know, you certainly could have pursued a role working on the buy side, or eventually starting your own hedge fund, or something like that. And so now you are certainly still an investor, which I did want to… it was another part of this question I wanted to ask was just sort of, what do you do in terms of… for your own investments, but also you’re kind of running a media company as well, so I’m just curious how you think about your career path, if you will, and why you chose to go the way that you did.

13:53

Edwin Dorsey: Yeah, so, originally, I was interning at a fund all four years of college. I wanted to work for that fund after I graduated, and they said no, because they were kind of in the process of winding down. So I couldn’t work there, and I wanted to get hired at another fund, so I started the newsletter as a way to get hired. So I originally did want to go the hedge fund route, although I really care about culture, and I maybe don’t love typical finance culture. I want to do things that I feel are societally valuable and useful. So, I wanted to maybe work at a really, like, small shop with a good culture that has some, you know, element of short selling for the benefit, or talking to reporters, or highlighting misinformation to others.

So I started the newsletter, and it just became commercially successful in its own right. I think within 6 weeks, it was 100K ARR. I remember I talked to one fund that was kind of interested in me, and I mentioned how much I was making, and I said I would expect it to be, like, matched or double, and they’re like, we don’t pay first-year analysts that much. I’m like, well, then why were we having the conversation, you know? So it became successful. I think there’s a saying, which is, once you work for yourself, it’s tough to work for someone else, and I’ve never worked for somebody else, and I think I would find it really tough. I like having my own schedule, I like working whatever hours I like. I like being able to do whatever I want to do. So that makes me hesitant to join a traditional firm. And I like betting on myself. I think these… there’s chances to make really big newsletters. Doomberg does over 3… I think over $4 million a year now in ARR, and it’s like, well, that’s a huge thing. If I can get to that level, I can build my own tools. I think prediction markets are gonna be an absolutely huge space, so if I have a second act, I could really see it being in tools for prediction markets, or making my own funds and investments to trade on prediction markets, so that’s an area I see a lot of potential, too.

15:58

Bryan Wagman: Yep. In terms of, I guess the, you know, you mentioned AI earlier, and just how that has, you know, become a more significant part of your work. Could you detail just sort of what that journey has been like, and I guess… when did you start to integrate it into your process? How do you feel like it’s come along in terms of the capabilities and how prevalent it is throughout your work, and just where you’re at with it today?

16:28

Edwin Dorsey: So, I mean, it starts by just using ChatGPT a year or two ago and asking it a bunch of questions. Then I use it for maybe more screening. Now, if I’m researching a company, I find myself going to ChatGPT research and just asking a ton of questions to learn, learn, learn. Sometimes it’s surfacing useful insights. Sometimes it struggles with things. Like, it’s really bad at analyzing Glassdoor reviews, which is an area I care about. So, part of it is just company-specific research, asking questions. Part of it is idea generation, asking it to highlight, you know, look at 100 recent IPOs, and give me the five that have high levels of consumer complaints, and then I’ll briefly look at those five, and two will be interesting to me. So, that is idea generation, company-specific research, and then there’s these unique cases. I know we’re going to talk about Stock Promotion Tracker. That uses a ton of AI, where I have a dedicated email inbox that’s receiving all these stock promotion campaigns, and an AI agent reads it all and summarizes it and gives me the data. So, that’s kind of a unique case where I’m using AI to, you know, to try to digest huge amounts of information that otherwise would be too burdensome for me to deal with.

17:44

Bryan Wagman: Yep. You said something earlier when detailing, sort of, your story of starting the newsletter that I thought was interesting, about betting on yourself. And, like, when you were talking to that fund, and you’re like, hey, this is what I’m making off the newsletter, if you can’t match or double this, it doesn’t really make sense. And I think that’s really interesting, because I think a lot of people, especially when they’re younger, get caught up in this mindset of almost just, like, “I’m just happy to be here,” or something like that. And, like, you know, they want to, you know, a lot of people say, oh, don’t worry about how much money you’re making, just focus on the learning experience. And I’m curious to hear your impression of, you know, sort of that career advice, and sort of… how you navigated the… I guess there, you know, because obviously, from your perspective at that point was, oh, well, I guess maybe I won’t have as much mentorship as I did if I went and joined a fund, or, you know, maybe my resume won’t look as nice, but like you said, you bet on yourself, which I think is really impressive, and I’m just curious to hear more about, sort of, your mindset around that.

18:57

Edwin Dorsey: Yeah, so I think, in general, when it comes to giving advice or professional advice, good advice needs to be very personalized. Very little advice or good advice is one size fits all. So what works for me might not work for someone else. What works for someone else might not work for me. I think one universal thing you hear among people who try to start businesses when they’re young is it’s a lot easier to take risks when you’re young. If you graduate from college, and you spend a year trying to build a newsletter business, and it goes nowhere, employers might look at that slightly negatively, but I don’t think anybody would hold it against you to a strong degree. I do think if you’re 30, you know, you have a lot more obligations, you might have a wife and kid, it’s a huge financial risk. If you leave your job, can you go back and join at an equivalent salary and without losing status and prestige? And, you know, it’s not a guarantee. So it becomes way… it just continuously becomes tougher and tougher to take risks as you get older, partly because you have more obligations, partly because you’re giving up more.

But that’s not true when you’re young. So, I think it is true that you need to, if you want to take risks, take risks when you’re young, and I do believe in testing things out in ways that it’s easy to fail. So, not everything I’ve done, you know, has turned out great. I’ve had many side projects that went nowhere, but never have I lost a ton of time or money over a side project which failed. For example, I tried to create a job board for finance jobs. I thought there could be a, you know, universal job board for hedge funds to post internships. And I really tried to promote it, I DM’d everybody, I promoted it in my newsletter, but I could see after 2 months of trying really hard, there was no traction there. So I just shut it down, it cost maybe $1,000, 2 months of focus. No harm. And so, I think I see, you know, with some people, they say, well, do I quit my job or not to start this thing? And I say, well, why not try to test it on a small level? If you’re going to start a newsletter business, try getting active on Twitter and see if you can build a following. Because trust me, if you can’t get people interested in you on Twitter, you’re not going to be able to get them to give you their email. And then, why don’t you start a free newsletter and see if people will give you their email first, because if you can’t grow a free newsletter, there’s no way you’re going to grow a paid newsletter.

To me, the two kind of things I think about are, one, take risks, tremendous risks when you’re young, and two, set things up in a way so you can experiment. So if the experiments go poorly, you can just shut it down easily and try something else. I have had so many things that just, you know, don’t go the way I planned for some reason, but it’s never cost me big time.

Stock Promotion Tracker

21:46

Bryan Wagman: Yeah, absolutely. That’s, that’s good stuff. Wanted to pivot to the promotional tracker tool. So maybe first, if you could just kind of give us an overview, maybe from more of, like, a narrative story perspective, of just your experience tracking stock promotion over time, and just how that idea became to… like, how you came to think, hey, this can be something I can actually productize.

22:13

Edwin Dorsey: So, I didn’t have a ton of experience tracking stock promotions. IPhawk, a guy on Twitter who has a newsletter, you know, would track them. It used to be stock promotions and companies engaging in paid stock promotion were really micro-cap, sub-$100 million companies. Over time, especially as we’ve seen a huge influx of retail investors, we’ve seen a lot more stock promotion, a lot of companies engaging in stock promotion, getting a lot bigger. Stock promotion has moved to new forms of media, like Discord, Reddit, and YouTube. So, it’s kind of become more complex, more institutionalized, bigger dollar amounts, bigger companies. Which makes me think, oh, I can write about some of these companies in the Bear Cave. And so I first kind of got interested in stock promotion by wanting to know what companies would be interesting for short sellers to highlight in the Bear Cave.

Now, in terms of productizing things, I did not originally set out to build a tool that would track stock promotions. I was looking at myself and thinking, I got a good newsletter in the Bear Cave. I got a good newsletter in Sunday’s Idea Brunch. I’m getting this cash in, I have extra money to now spend on new projects. What do I want to do? I want to build tools that are useful for me and useful for others. The first tool I built was FOIA Search.com, which is still up, that lets people search the SEC’s FOIA logs to track potential signs of undisclosed investigations. It’s a really useful tool. I thought it was the best thing in the world. I thought every hedge fund is going to sign up for the paid features to track their portfolio holdings and get alerts, and I think… it got, like, 50,000 visitors, 50,000 people have used it, and maybe 5 have signed up for a paid feature. They’re, like, $50 a month. It was just not… not enough people care, not enough people want to pay for it, it just… for whatever reason, it wasn’t commercially viable, even though I thought it would be, and it’s a useful tool. I made a few other tools, like Comment Letter Tracker, that makes it easy to track SEC comment letters, and a few other minor things, a website so people could highlight text messages sent by stock scammers overseas. So, StopNowZack China Fraud is another website. But none of those were commercially viable, so I decided to just do this stock promotion tracker mainly as a way for myself to track these things. I have an engineer I work with who I pay to help me build these websites who’s excellent. And we were building this, and we quickly realized it’s incredibly complex. He’s working on it 20 hours a week, I’m talking to him 2 hours a week. And we eventually made it into a useful tool for me to find stock promotions, and then for other people to find stock promotions. And then, you know, I’ve been able to charge $1,000 a year for it or so. There’s 20 paying customers now, and I see a big pathway to grow it, or sell it, even.

25:09

Bryan Wagman: What was your process like for finding and beginning to work with that engineer?

25:13

Edwin Dorsey: Well, originally, somebody cold emailed me a long time ago, and I was working with him. He was great, but he didn’t have necessarily the skill sets for what I wanted for something else, so he recommended me my new guy. And then, you know, I think I reached out to, like, 5 people, and this guy on someone else’s recommendation, and he was really excellent. I was just like, might as well work with him. So, I didn’t use any of the traditional… it was just a friend of a friend, which is how I think a lot of these things start.

25:48

Bryan Wagman: Yeah, and to the extent you’re open to speaking about it, would you be able to share anything about, just in terms of the, I guess, tech stack that’s going on behind the scenes for the promotion tracker tool?

26:02

Edwin Dorsey: To be honest, I don’t have no clue. So, like, I mean, I know we use AI tools, and I’m spending, like, $1,000 a month on AI to read through the email. I could explain in a more basic, crude form how it all works. I don’t know necessarily all the tech tools. Despite… I am the least technically savvy person to ever come out of Stanford. I don’t know how to code, I don’t know, like, all these fancy things. I’m good at my research, I’m good at intuition with corporate misconduct, I’m not good with tech stacks. What I can tell you is, you know, we made a list that’s ever-growing of places engaged in stock promotion, and these firms shut down, they sprout up, there’s a lot of YouTube channels. I mean, it’s really more complex than you think. It’s not, like, a universal thing. The SEC doesn’t have good data on it at all, so we kind of initially made this list, and it started with just tracking websites that would put out promotional content. And, you know, you scrape the website every day and upload that data. And we have a scraper and an AI agent that reads it and looks for the data and puts it in.

Then, it changes to be a little more technically complex, where we have a dedicated email inbox that signs up for all the email campaigns, because most of it is done over email, and then we’re scraping that. And then we find 50 or so YouTube channels that engage in stock promotion, and then we put them in, and we build a scraper for that, and it’s complicated with YouTube, because most of these places, they don’t disclose the payments in their YouTube description, they’ll have you click on a link that takes you to the information… so now we have a thing that checks every single link in the YouTube videos from these 50 channels to see if they’re disclosing payment, and sometimes they’ll say, “we may or may not be getting paid.” And I’m like, well, that’s not the law, but I mean… now what do we do? So there’s a million different edge cases, and so much complexity goes into it, which also creates our moat. It’s not as simple as just going to Edgar and seeing, give me a list of all companies paying for stock promotion, but now we’ve got this database that kind of works autonomously, whether it’s checking company blogs, checking our dedicated email inbox, checking all these YouTube channels, a few other sources. We might want to expand to Reddit and text messages and Discords, but right now, I’m confident in saying we have the best database for tracking paid stock promotion in our public markets. I don’t think many hedge funds are aware of it. I don’t think I’ve done a great job promoting it. I think it could be huge. I could see it integrating with a lot of other service providers. I want Seeking Alpha to have a stock promotion tracker risk score, like an API connected to us where we can warn about companies. Benzinga, all these other platforms. That would be a really useful service that doesn’t really exist. But right now, it’s just, you know, we need to be the best source of data on stock promotions, and that’s how we do it.

29:01

Bryan Wagman: Yeah, and maybe you could expand on that a little bit, like, just from a hedge fund’s perspective, like, just what exactly is the value add, and how would you see them potentially integrating it into their process? Or I don’t know if you’ve actually had any conversations with existing customers so far about how they’re using it.

29:17

Edwin Dorsey: So, I think there’s a dual purpose to StockPromotionTracker.com. One can be idea generation. I’m looking for companies to short. Show me which ones are spending tons of money on stock promotion campaigns, and are moving up. So we have a lot of filters for that. We can show you companies that have only recently started paying for stock promotion. We can show you companies that have spent over a million dollars paying for stock promotion. We can let you filter by market cap, because people generally don’t care about sub-$100 million companies. We make it easy for you to find companies that have over a $100 million market cap that have multiple paid stock promotion campaigns in the last 3 months that are listed on a major exchange. You can’t get that list really anywhere else other than our tool, and so that can serve as a really good source of idea generation. I know it serves as a source of idea generation for me in highlighting things in the Bear Cave. It’s unique, it’s differentiated, it’s repeatable, and it’s… these aren’t necessarily companies with no volume, but they’re also not $20 billion companies that everybody’s looking at. It’s really in this $100 million to billion dollar market cap sweet spot.

So that’s one area. I think the second area is diligence. If you invest in a lot of small cap companies, and people who invest in small caps tend to invest in a lot of small caps, it’s not necessarily easy to see: are these companies credible, or are they being overly promotional? Are they paying for stock promotion? Are they paying for stock promotion egregiously, or are they only paying once or twice in the last 2 years? Our tool makes it so easy. 5 seconds, just type in the ticker, and you can see if it’s paid for stock promotion in the past. So it can just be if… you don’t short at all, but you invest in a lot of small-cap companies, 1 out of 10 in your portfolio might be paying for stock promotion, 1 out of 20 might be egregiously doing so, and it’s a sign that maybe you don’t invest, or you at least apply more diligence. And based on the data we have, it seems like companies that do a lot of stock promotion really underperform. And now we’re building more tooling where you can kind of see, like, you know, they kind of go in waves. So does it have one wave where it promotes, issues stock, and collapses, and then another wave? So we’re really trying to do a lot with the data, but right now, it’s just… if you want to track stock promotion campaigns, StockPromotionTracker.com is the place to do it.

31:43

Bryan Wagman: Makes sense. And from a Bear Cave business model perspective, do you feel like your vision for the future, like, is part of this intentional to try to shift more to, like, a software-type business model, as opposed to something that requires you to keep putting in your time regularly?

31:59

Edwin Dorsey: Yeah, I think, you know, Bear Cave, I love it, and I used to say, I’m gonna do it forever, and it’s just my career now. I still love it, I think it serves a societal purpose. If you look at the way people get really wealthy, it’s through building businesses, and if you look at an advantage of the Bear Cave is I don’t just… I can monetize through subscriptions, but I’ve got a great distribution channel to promote other products. I mean, a big thing people struggle with is you can build great products and you don’t have distribution. I have great distribution. It’s almost lazy and foolish if I don’t try to build great products to take advantage of the distribution and trust I have with readers. So, it’s, to me, a natural kind of extension. I do see, you know, newsletter authors, the best might be earning millions a year, but if you really execute, you can build a company that could sell for tens of millions a year, or work autonomously. So, I love experimenting, I love trying new things. So that’s kind of just, you know, I got extra time, I got extra energy, let’s see where this goes. And that’s kind of how I think about it. I’m also incredibly bullish on prediction markets, so we’ll see. I can see myself, honestly, in the future, trying to drop everything to just exclusively focus on prediction markets.

Prediction Markets

33:19

Bryan Wagman: That’s so cool. Let’s get into that. And I want to thank you for putting them on my radar, too, because, like, literally before, you know, a few days ago, I had hardly looked into them at all, and then just, like, binged a bunch of podcasts and stuff like that this weekend. Yeah, like, what an interesting space, but I guess to kick things off, like, how did you first get involved here?

33:43

Edwin Dorsey: So, I first heard about prediction markets when I was a freshman in college. There was an ad for PredictIt, which was a kind of an academic experiment where you could bet up to $850 on political markets. Who will be the next president? Who will be the next governor of a state? What will be the margin of victory? Things like that. And it was really small, it was illiquid, you could only bet $850 into a single contract. It operated under a no-action letter from the CFTC, in which the CFTC is kind of saying, look, as long as you operate under these parameters, we’ll let you continue with your experiment. And I lost money on the first election, it kind of died down.

But then, the second election, in 2020, with Trump-Hillary, then it really started to sprout up, and I just quickly realized there’s a lot of easy ways to make money. You know, there was a monthly market for, “will Hillary Clinton get indicted?” and it’s just, it was a very low chance, and every month it starts at 8%. I’m like, this doesn’t make any sense. It’s a free $50, just max shorting it. There is so many… the numbers would add up in a multi-contract market. “Who will win the Republican nomination?” You just look at all the players, it adds up to 140. So you just short everyone, and you’ve locked in a guarantee. There’s so many inefficiencies, partly because there’s inefficiencies in these new markets, partly because of the $850 limit meant smart money couldn’t come in and correct it. So, I got… and I did really well the second time around with prediction markets, just spotting really obvious inefficiencies, where you could make tens of thousands of dollars in total, but you couldn’t make millions, because there wasn’t liquidity there, and there’s all these limits.

So, that kind of got me interested, but again, the election happens, and it dies down. And now the third time is different with Kalshi. There’s Kalshi and Polymarket. I never touched Polymarket, partly because the… the legality of it for U.S. people is unclear, but I did do… I started depositing on Kalshi for the newest election, and I was betting on it. I think I did fine on the election, but I just see all these other markets where I just start trying to trade and get edges. There’s Spotify markets, and I do well, I do poorly, but I spent kind of a year learning it, and, you know, starting 6 months ago, I really just became consistently profitable at it. I think I got edges, and… now I’m just spending a ton of time on it. I see a path that… I follow prediction market people who earn millions a year. I was like, why can’t that be me? I think there’s gonna be a big market for newsletters for prediction market traders, but also tools to help them do research better. There’s this whole new ecosystem in finance that I’m incredibly bullish on, that the exchanges exist, but the infrastructure around the exchanges don’t. So, I can make money as a participant, and I can make money as an information and infrastructure provider, and I see that as just a huge, enormous opportunity. And I can make money in the Bear Cave highlighting the companies that are gonna be hurt by prediction markets.

36:55

Bryan Wagman: Yeah, this is, maybe, maybe a broader question, but definitely want to get into the prediction element of it after, but in terms of… if you’re open to sharing this, in terms of how you think about investing your own money, like, whether it’s, I want to invest in stocks, or I want to invest in, you know, the Bear Cave, or invest in paying an engineer to build me some tools. Or, you know, prediction markets, like you said. Like, what percentage of your, kind of, portfolio or net worth would you say you’ve been allocating to prediction markets, and how has that trended over time?

37:30

Edwin Dorsey: You know, so prediction markets are liquidity constrained. If I could put all my money in prediction, I think I get higher returns there than I do in stocks. It also is a little scary because, I mean, I trust Kalshi, I believe the money is safe there, but I don’t feel as safe as in my Schwab or Robinhood or anything else. So, basically, I’ve just taken my… and also, because I’m good at what I do on there, it kind of grows naturally. I don’t need to deposit more, I have enough to take advantage of the trade. I historically have invested a lot just in stocks, large cap tech, some random small caps, not too active. I’ve shorted one or two things in my PA or an ETF, but really don’t try to do that, just because it could conflict with the newsletter. There’s not a ton of ways I can invest in the Bear Cave, per se. You know, I could spend money on advertising, but my small experiments there yielded poor results. To me, the number one thing to invest in is always trying to build new tools. So, spending money on an engineer or people to help me, that is always going to be good money, even if it fails, because you get information. So that’s priority number one. I have enough money in the markets, Kalshi, so I don’t need to put more money in. So, just keep money in stocks, be fully invested at all times, don’t use leverage, but don’t not be fully invested when you’re young, I think that would be foolish. But now it’s less, let’s say, financial resources and more, where do I spend my time? Because, Bryan, I don’t know if I look tired to you, but I work from morning till night, you know? I got no free time, ever. Other than to come chat with you. So, it’s more of a time commitment. Where am I prioritizing my time? And I think increasingly… increasingly it’s gonna get to prediction markets.

39:19

Bryan Wagman: Yeah, and so what, you know, you mentioned that it’s sort of been a journey for you of just developing that skill set and getting to the point of being consistently profitable. For someone who knows very little about prediction markets and doesn’t know what a good prediction market investor or trader looks like, or what the different kinds can look like. Can you help me just kind of understand what your journey has been like to this sort of place that you feel like you’re at now of consistent profitability?

39:49

Edwin Dorsey: So, for all prediction market traders, first, you don’t need to trade prediction markets. The best way to get wealthy is to do well at your job, consistently do well, save a little, invest in the S&P 500. That is great advice for 98% of people. You can ignore everything else. You just do that, you will do well in the long run. And if you want to experiment with prediction markets, take 500 bucks and experiment, that’s great. Number one thing with prediction markets is you always want to start small. These markets always have sharp players, even if they seem inefficient. You always are going to do poorly in the first few months. Even if you get beginner’s luck, it is… you should treat your early stages as learning. Even when I start to trade new markets, I just tell myself, I’m gonna lose a few thousand dollars to learn how they work. I’m never gonna make an absurdly big bet because I’m so confident if I’ve only traded a market for the second time. It’s… there’s so many nuances, and “rules cucked,” is what they like to say, and just weird situations that you do not make money early on. You know, you keep it very, very small.

I think another thing that’s really important is to do your own research. I kind of find with the Bear Cave, I am an information service provider, where I’m getting information, I’m servicing it, I’m digesting it, I’m interpreting it, but a lot of times, I’m going direct to the source. I’m using FOIA to get consumer complaints. I’m not relying on other people’s analysis, or at least I try not to. With prediction markets, if you want to be good, you need to think independently and get information from the source. And, you know, I think there’s a big issue where media, mainstream media, can influence prices a lot. But if you just read the media and trade off that, you are the dumb money. The smart money realizes the flaws of media and how they tend to exaggerate and be systemically wrong. One kind of great example is there’s a market for, “will the Ayatollah lose power in Iran?” Will they lose power this month? Will they lose power by March 31st? Will they lose power by the end of the year? And if you read U.S. media, it’s, you know, “Iran is doomed, Trump’s gonna bomb them, they’re done.” And the average person says, oh, let me bet on this guy losing power. Go to Polymarket, look at the market for it, and I… I kid you not, you look at the biggest no-holders, people betting on the Ayatollah staying in power, every single one has millions in lifetime profit, and every single yes holder who’s betting on the Ayatollah losing power has lost a ton of money.

It is never… you can never see a more clear smart money versus dumb money dynamic. This media likes to exaggerate, the reality is you don’t lose power unless you have military defections, and that’s not the case. Iran’s a nuclear-armed power, so you might hit them, but I don’t think you’re gonna topple them. And if regimes tend to lose power, like, even in fast revolutions, with few exceptions, it takes weeks or months of leading up to it. It does not happen, you know, by the end of this month. So there’s… start small, think independently, realize the biases caused by media, follow smart traders, and eventually, I think you’ll start getting a repeatable process that works for you.

43:35

Bryan Wagman: What’s your process for identifying and following smart traders?

43:39

Edwin Dorsey: Well, it’s easy, there’s leaderboards. So, I go to the Kalshi leaderboard, and I turn on alerts for every one of the people who are on the leaderboard. I look at, you know, there’s a trader, Domer is his name, I think he’s fantastic. I follow his Polymarket bets. I follow a few traders that I think are smart and listen to their podcasts and livestream interviews. So, it’s really, you know, that’s why I love prediction markets. In media, there’s so many talking heads. How do you know who’s credible? How do you know who actually knows what they’re talking about? It’s just credentialed—oh, this guy went to Yale, this guy comes with this—but with prediction markets, it’s pretty clear. Your track record speaks for yourself. And so, prediction markets are going to be really good at surfacing new talent and really good at also calling out the fakers of the world. I bet you there’s a lot of people in media who get tons of followers and are seen as really credible who could not outperform on the prediction markets. And then there’s people who will kill it on prediction markets who have no following. So I like prediction markets because… for so many reasons, one of which is they highlight true talent and people who are really good at predicting the future, versus people who are not. And maybe one final thing is, on prediction markets, the one incentive is being right. With traditional media, the incentive can be driving clicks, it can be driving subscriptions, it can be being right, but it can also be playing to a base or playing to biases. With prediction markets, one incentive: be right.

45:24

Bryan Wagman: Yeah. When I was preparing for this, Domer was one of the people that I read through some of his stuff, and I saw on his Twitter account that his pinned tweet—some of his recommended resources are, like, Chapter 8 of The Intelligent Investor, and Superforecasters—and I’m like, as I started to read through this prediction market stuff, I started to think, well, geez, all of these sort of ways of thinking about the world and trying to be data-driven that I’ve learned and tried to apply in investing may even apply better to at least certain markets and prediction markets, it seems like.

46:01

Edwin Dorsey: Yeah, I… you know, you want to play with less sophisticated people. So, if you’re trading mega caps, maybe it goes well. I’m not saying you can’t make money trading, but you’re going against really smart money. You go to small caps, well, you’re still going against some smart people there. You go to prediction markets… you know, I saw one quote from somebody I thought was smart: “You always want to be trading in markets where liquidity is an issue for you.” Because if you’re not, then you’re playing against smarter people than you need to play against. And you go to prediction markets, and you can easily find these niches where you can develop repeatable approaches and start printing money. Markets have gotten more efficient over time, but trust me, there aren’t that many really sharp, you know, traditional finance institutions playing on prediction markets. It is a lot easier to develop a repeatable edge than you think.

46:59

Bryan Wagman: What does your portfolio look like in terms of time horizons and sizes of bets? Because I was thinking about getting into this, you know, if I just want to throw, like, $100 at it or something, I’m thinking, like, okay, I want enough trials that I’m going to be able to learn from this, and I want them to be done in a short enough time that hopefully I can… which is part of the thing that’s so hard about investing, is sometimes the feedback loops. You don’t know if you’re right or wrong about an investment for a couple years down the road. So, when I’m thinking about prediction markets, I’m like, well, I can kind of… I can maybe intentionally shorten the feedback loop. I’m curious how you think about portfolio construction, if that’s even the correct term for prediction markets.

47:44

Edwin Dorsey: I mean, for me, I do things that are expiring generally within an hour, a day, a week, or a month. I don’t want to lock up my capital for a year or two years. Because then, even if I double it over 2 years, I could have… I could get much higher returns just getting a repeatable process in short-term markets. So, the way I think you can make most money is especially with small amounts of money, it’s just repeatable things, and there’s a lot of things for that. For example, there are markets on Rotten Tomatoes scores, trying to predict that, and you start to learn things over time. Rotten Tomatoes scores tend to fall over time, because the people who review it earliest are most excited to see it. The people who review it later are less excited to see it.

Without even the movie being released, how can you predict it? Well, how much is the studio investing in marketing? That’s a good proxy for how good they think it’ll be. When do they embargo reviews? Traditionally, if a studio says to film critics, “you can release your reviews a week in advance,” they know it’s gonna be good and build hype. But if the studio says you cannot release reviews until the movie is in theaters, then that’s a sign they think the movie’s gonna be bad. So there’s all these kind of proxies for how, you know, a Rotten Tomatoes score will be. And once you figure these things out and get to model it, if you’re playing in these markets that repeat every week, you can start kind of printing money. And I think there is a societally useful component to this, where it isn’t just aimless gambling. In Rotten Tomatoes, knowing if a movie is projected to be good or bad is really useful. So I see prediction markets as being a way to kind of digest the world’s information into societally useful ways to help people make better decisions.

49:50

Bryan Wagman: I’m imagining the sell-side firm of the future that has sector specialists focusing on Rotten Tomatoes scores.

49:58

Edwin Dorsey: Yeah, I think these markets are too small a niche, and there’s really sharp people. Your track record is everything, and they’re repeated. With finance, it’s like… I don’t know, you can kind of get lucky in the short term, you can underperform, but you’ll say it’s because you took less risks on a risk-adjusted basis. Everybody outperforms risk-adjusted, it seems like. But with prediction markets, it’s a lot clearer, it’s a lot cleaner. I think it’s a great way to digest the world’s information.

50:36

Bryan Wagman: What are… what are some of those other somewhat shorter-term markets?

50:41

Edwin Dorsey: You know, I think everybody can figure things out for themselves on prediction markets. I don’t want to steer people too much, but you know, there’s weather, there’s Rotten Tomatoes, you gotta experiment on your own. But that’s where I would be playing around if… don’t put all your money in prediction markets. S&P 500 is a lot, but don’t think “I’m gonna make money trading stocks or options.” Think, “I’m gonna make money trading prediction markets.” I think that’s where a lot of low-hanging fruit lies. And the other benefit of prediction markets is you have an enormous number of casual bettors coming through these distribution points, like Coinbase and Robinhood or whatever, who don’t know what they’re doing. So you’re not necessarily playing against the Citadels, you’re playing against just average Joes who are doing it for fun.

51:27

Bryan Wagman: And… so you’ve written on the Bear Cave about how these prediction markets are certainly a new form of competition, I guess, for the wallet dollars of people who are gambling. They’ve had some responses lately that I’m curious to hear your thoughts on, just in terms of, like, I think they had maybe their own predictions app now, and then the, what was it, Railbird acquisition? So, curious to hear your thoughts on the moves that DraftKings has made in response.

52:02

Edwin Dorsey: I think… they’re terrible. I mean, I am in Florida, where things are somewhat restricted, but I look at a lot of reviews, and I mean, everybody just hates these apps. You can’t… it’s very one-sided. It’s just like a sportsbook, still. The whole idea of prediction markets is it’s kind of peer-to-peer. I can’t go on DraftKings Predicts and start giving limit orders to give to somebody else. There’s big liquidity constraints. It’s just like a worse version of a sportsbook. I think in DraftKings’ minds, they’re just gonna call it DraftKings Predict and launch it in new markets where there isn’t legalized gambling as a way to kind of take share. But they haven’t really bought on with the prediction market model. They aren’t allowing new people to come in and participate and be counterparties to the casual bettors. They still want to own that relationship. So I… as far as I’m concerned, it’s a huge and massive miss with both DraftKings and FanDuel. I’m fairly in tune with the prediction market space; I don’t think anybody’s investing any time in trading on those platforms. They realize it’s just a way to scam casual bettors.

Future Content & YouTube

53:22

Bryan Wagman: Gotcha. Another thing I read in one of your interviews—I forget which one—but you had mentioned in passing that you were a fan of, like, MrBeast, for example, and I think there was one more YouTuber who I’m blanking on who had maybe done, like, a daycare investigation or something? Nick Shirley? Yeah, yeah, so I’m just curious to hear more of your thoughts around YouTube, and if you were to do something there someday, what that might look like.

53:50

Edwin Dorsey: I think YouTube and video is the dominant form of content. If I could see myself making a ton of money on prediction markets and just focusing on YouTube investigations. I see Nick Shirley’s video, and I admire it, I admire the impact it had, and I look at it, and I watch it, and I can think, these are 20 things I would have done differently. But I think, like, I can do that. Why am I not doing that? Why am I not getting out there? I have too many projects I’m working on. But I think video is a lot of fun. One thing that kind of frustrates me is you look at so much of these YouTubers, and, you know, it’s… I like just showing the evidence and letting people draw their own conclusions, where I think too much of media now, both creator-led and mainstream, is just telling people what to think. Well, I want to be, like, more of a neutral tone of voice, just an information provider. Let me surface the information for you in a very respectful way towards all parties. No name-calling, no calling for… just very respectful, neutral tone of voice, and let people draw their own opinions. That’s kind of what I try to do with Bear Cave.

And I think there’s a huge market for just information surfacing and letting people think for themselves. So I could see, as I’ve gotten older, my career path options have exploded, rather than narrowed. So I could see myself doing YouTube eventually. I could see myself just really focusing on prediction markets. I could see myself doing Bear Cave and traditional finance tools. I have no clue what the future has in store.

55:48

Bryan Wagman: Yeah, time will tell. This is… it’s been awesome, Edwin. Thanks so much for your time, and is there anything else that you want to let the listeners know?

55:57

Edwin Dorsey: No, Bryan, I really appreciate this interview, and I hope it’s useful for people, and maybe we’ll do it again in two years and see how things have changed.

56:06

Bryan Wagman: Awesome. Sounds good. Well, thank you so much, Edwin.

56:08

Edwin Dorsey: Thank you, Bryan.

56:09

Bryan Wagman: Alright, I’ll see ya.

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P.S. Unrelated -- I’m spending time learning about the hedge fund headhunting and talent placement world, and trying to understand if there is an opportunity to serve any of the involved parties. If you work in recruiting, have placed candidates at funds, or are a fund/analyst who’s worked with headhunters, I’d love to hear about your experience. You can message me, email me at stockthoughts81@gmail.com, or book a 20m call here.