When a new trader joins predicting alpha, the 1st book we recommend they read is called the laws of trading by Augustin LeBron. It's not only an amazing book on trading, it's a phenomenal book on decision making in general, helping you shape the way you think about the world so that you can go out there and actually find good opportunities. In this podcast, I had the pleasure of sitting down with Augustine to have a really candid conversation about what it takes to make it as a trader. This was an awesome conversation. I really enjoyed having it, and I think you're gonna get a ton of value. So with that being said, my name is Sean Ryan, cofounder of predicting alpha and the host of the predicting alpha podcast. Let's hop into the conversation. Cool. Well, thanks for having me, Sean. This is, this is good to to be here, certainly. Brilliant. Yeah. So, you know, I know you asked me to kinda give maybe a little bit of a bio about myself and kinda my career. So, yeah, I did engineering in school, and then I got a job as an engineer. I was designing front end radio chips for cell phones and GPS receivers, that kind of thing. And right around 2006 or something was the the poker boom. Right? The online poker boom, like Chris Moneymaker, all that stuff. And I thought, okay. Well, I'm gonna get into that bit. And and it turned out I was, like, I enjoyed it, and I was, like, I was getting good at it, getting decent at it anyway. And at the same time, the engineering was getting a little bit more, we'll say, boring. It's just design cycles get compressed, and so you get to do less and less interesting stuff. And it's just more cookie cutter kind of stuff. And so I decided, well, this isn't gonna be a great 30 year career for me. I don't want this. And so I decided to look for jobs that were half engineering and half poker, and, of course, that pretty much describes trading really well. And so, I went into my boss's office on January in January like, my January 2008, I said, hey. Look. You know, I'm quitting. I wanna look for a job in finance. And I said, okay. Yep. Too bad. Hate to see you go. Are you sure you wanna do this? Yep. Yep. Great. And so then fast forward, like, mid March, I had found a job. I had gotten an offer from Jane Street, and the world is imploding. We were traveling around, like, Sequoia area and and we heard that Bear Stearns had imploded. And my wife looks at me and she goes, is this is this bad for us? Yeah. Do you still have a job? So, like, I call I called my future boss and I said to her, hey. I I heard Bear Stearns is imploding. Like, is this good? Do I, like do I still have a job here? And she said, yep. Yep. Listen. I can't talk right now. Training's really busy making a ton of money. I can't wait for you to get here. Bye. And that was it. So Nice. I feel like I was okay. So so, yeah, so I worked at Jane Street for a bunch of years, and, left Jane Street 2014, came back to The United States. And, now I do whatever it is that I do now. It's unclear. You know, it's a it's something you you often hear, and I wanna pick your brain on it, is you hear people coming from, like, a physics background or an engineering background, and you also hear tons about poker. And for some reason, it's like poker, physics, and engineering, and and trading are, like, the trifecta of of sort of risk taking variance based Yeah. You know, careers Right. That seem to always coincide. And and why do you think that is? Well, you know, it's just it's the skill set, I think. At least for the kind of trading that I've I've learned to do over the years, it's very informed by math about statistics. And so there's that side of it is being able to think analytically about problems, certainly. But the other side of it is knowing those other non analytical things or being comfortable in those spots where you have to make a decision with incomplete information for lots of money and the results ride on your decision. You can make a good decision and lose. You can make a bad decision and win. And and understanding that at a very emotional level, I think, is important too. 100%. And, you know, I I think that this is the the biggest thing about about trading that it's, like, the real challenge. It is that that decision making component. Right? It's the the name of the game is who can make better decisions over an extended period of time. Right. Exactly. You know, things that I I loved in your book were, you know, that were eye opening to me because they were well worded were things like a the parts about, like, information asymmetry, evaluating decisions. I thought I found all these parts to be, really valuable. And so what I wanted to ask you about is a process for evaluating information when you're dealing with maybe incomplete information or when there's a lot of a lot of noise and maybe very little signal out there. How do you go about actually making a decision in a world like that, specifically trading as well? Yeah. So I think fundamentally, the 1st thing I think it's important to say is that there is no clear answer. Right? There in some strong sense, there cannot be a clear answer. And that's because it is a competitive world. And so there are other people trying to solve this exact same problem as you. And so if there were a very well defined process or procedure that would get you to the right answer, at least good answers, then that would get competed away. Mhmm. And so that's that's the balance. Right? You need to have enough of a process around how you're thinking about problems, what your goals are, how you're arriving at those goals with some of this other stuff. The stuff that that well trained human brains are so good at, which is, this is a weird random thing that I think I have to think about. And, you know, that's experience, that's training, that's having good mentors. Mhmm. You know, 1 of the things I think I tell a lot of retail traders that I talk to is if you're out there trying to figure this out on your own in the sense that you're reading Twitter or whatever, you're just you're not gonna do well probably because it takes that interactive help of somebody who's been there before, who's more senior for you to accelerate your learning process. I think that's really important. I think, you know, obviously, the community that you've built is is an answer to that. Mhmm. I appreciate that. And I I actually 100% agree with you. And maybe maybe I'll ask you a bit more about that because so for me, for example, I I was a little lucky where I had some people in my family who were trading professionally. So Mhmm. It didn't take me too long to be able to sort of say, okay. This is definitely the wrong way to be going, and maybe this is a better path to go as a a generality. Mhmm. But then, you know, for my business partner, for example, and others I've known, being able to learn from someone who is way ahead of where you are Right. And and and, you know, maybe you you know is good at the game that you're trying to be good at. Right? So they're not necessarily you didn't find them because of good marketing or anything like that. They maybe are managing money or, you know, they're they are winning at that game in particular was a absolute game changer. So how can you know, did did you have that in your career? I mean, guess, through Jane Street. Right? Like, I came into to my my life at Jane Street having no trading experience whatsoever. I mean, aside from buying the odd stock on your personal whatever account, basically 0. I knew nothing. And in fact, day 1 walking to the door, I didn't actually really know what I was gonna do. I remember clearly telling my wife, we just moved to New York. We're in temporary housing, and I get up to go to work the 1st day. And and I said to her, look. And I'm pretty sure I don't have a clue what it is I'm gonna be doing today. Because I got I got interviewed kind of partly as developer and partly as a trader, and then I got an offer that said trader, but I wasn't sure what that really meant. And so I walked in day 1. I didn't know where I was what I was gonna do. And so day 1, basically, all I did is I sat next to senior traders, a senior trader in particular, and and it became obvious that my job was to do menial stuff and learn as much as I could about the other stuff as fast as I could. That was my job. Mhmm. And it was awesome. It was a great job. Like, when you're when you're getting paid to learn interesting things, that's about as good as you can do. And so that was my job for for months and months and months. It's just try to learn as fast as you can about this stuff. 100%. And so I guess last thing I'll ask you about about that in particular is, you know, obviously, there's a ton of really good books out there. There's a you know, obviously, this Voltwit and FinTwit space has, you know, some merit, and it's awesome that people share their ideas there. Yeah. Do you think that it's imperative for someone to find someone to learn from? Like, would you say that is, like, a a key component of it, or does it just shorten the learning curve? Yeah. Imperative is far too strong. I'm sure I'm sure there are people out there who are auto did x and they figured it out and they're doing just fine. I'm sure there are people out there like that, but I think for the average person, it just like you said, it shortens the the curve and it makes things significantly easier. It's just gonna go down fewer paths fewer bad paths. A 100%. So when you were at Jane Street, like, you know, I I feel like these huge liquidity providers and market making firms are you know, some people think they're the enemy. Some people have no idea what's going on there. It seems like this sort of vague mysterious thing out there. Mhmm. I I so I I really wanna ask, like, you know, obviously, without giving away too much of the secret sauce, when you're working at a place like that, what is their edge? What is the the edge that a place like this has over the market that makes them this giant? Yeah. So I think I think there are multiple answers to that question based on the level of abstraction at which you're asking the question. Mhmm. Because you can you can ask you can sort of answer the question at a very base level by saying, well, their edge is that they understand prices better

Than the marginal participant in the market. Right? They understand either what prices are good to trade against or where where prices are good to provide because there's order flow or something like that. Right? So at base level, that has to be true. At a higher level, it's certainly true that that on its own is not enough. And in in some sense, Jane Street's biggest edge is that Jane Street isn't bad at very many things. Jane Street is pretty good at almost everything. And it turns out, in order to be good at trading, you need to be good at decent at almost everything. Not just the tradings, not just the systems, the cost structure, back end stuff, relationships. All all of those little things are tiny sources of edge that add up. And because trading is so competitive, you kinda have to be good at all of those things. So that's kinda maybe the the organizational level. Right? Okay. And then I would say there's sort of there's the highest, the meta level, the thing actually that interest me the most, which is fundamentally, Jane Street has an edge because they hire really, really good people. And they put them in a good situation to be able to succeed. And so if you hire really, really good people and you put them in good situations where their interests are aligned, like, you're just gonna be successful in anything. It doesn't matter if it's trading or or selling widgets. Right? Yeah. Okay. I I that makes a lot of sense. And that's really cool actually because it it's it really shows like I I think the 1 that always gets forgotten or sometimes gets forgotten in the retail space is that trading is actually a business. It's a profession. It's a career. And so you have these companies that, like, go out of their way to employ the best in in so many different aspects of the business. It's not just like you've made money trading. Okay. Let's let's hire you. It's like there's all these different components that sort of work together just like any other business out there. Exactly. But as a retail trader, you know, I I don't have the luxury of going out there and hiring a team and, you know, buying the best infrastructure. But I I, you know, I do think there is still edge for the the smaller fish. You know? Maybe it's for different reasons, like playing in a a pond instead of the ocean kinda idea. Right? So what are your thoughts on sources of edge for retail? Right? How can someone, like, retail compete against the Jane Street, or do they go out of their way to stay away from that? What what are your thoughts on edge for retail? Obviously, retail people shouldn't compete against Jane Street on the trades Jane Street is doing. Right? I think that would be a mistake. I think we could probably agree that that would be a mistake. Yeah. And as you said, a lot of the sources of edge that retail have is because of things that aren't worth the bigger players' time to to spend time on because it doesn't scale or because of some other reason. And so 1 of the big sources of edge for retail is really, really deeply understanding a niche either industry or product or something like that. We have this we have this notion, I think, or you see this notion a lot with retail traders that, oh, well, I I need to figure out a couple of little techniques so that I can scalp a couple points on the spoon or or something. Those aren't gonna work. And and I'm gonna maybe get flamed for it, but those don't work. They just don't. Okay? What does work is or what can work maybe is maybe actually, I had I had a Twitter conversation the other day with with a person who's a a turbine engineer. Okay. And and and getting into trading, has been doing trading and stuff like that. And and so what could that person's edge be? Well, they probably understand the world, the the the industry of turbine manufacturing certainly better than me Mhmm. And probably with a bit of effort, better than any Wall Street analyst. Yeah. Right? And so could they trade the, I don't know, 4 or 5 I don't know how many companies there are. 4 or 5 companies, like, maybe the earnings on those or the the options on the earnings on those? Yeah, that that sounds like a plausible source of a small amount of edge for somebody in that spot. It's not sexy. It's not exciting sounding, but that's probably a good source of edge. What what did I thought of like that? Because I actually agree with you. I think specialization by industry or, like, skill sets that you have outside of trading is it's like something unique to you, and that that that tends to be a source of edge. So for example, 1 that I thought of was, let's say, you've had a ton of experience working in software startups, and you kinda have a really strong idea of the turnaround to get certain types of projects done and certain products released. You could maybe take a look at, like, the microcap software space and look at the the timelines and forecasts of development for these companies or, you know, fundraising or something like that. And, you know, maybe you can Figure something out. Figure something out. Right? Exactly. So would you say that you think specialization is more important than having broad generalization as a trader, or do you think there's a balance there? So, yeah, it's the whole t t shaped skill set thing, right, where you need enough of all of these things in order to not get smoked by them, but you definitely need some of those sticks in the tea. Right? Something that where you go deep. So it's a balance for sure. Okay. Okay. And, you know, something that I've in the retail space, it it it's it's always a a battle between the 2 is the idea of, like, systematic strategy strategies versus, like, more, like, discretionary, like, 1 off trades maybe. Yeah. Do you do you think in the in the retail space, the average trader should be focused on trying to build out a a system or or getting good at just, like, evaluating individual situations? Where do you think, like, more edge lies for a a retail trader? Yeah. So so the the fundamental problem you're trying to solve is well, it's actually 2 of them. Right? The reason that these systematic kinds of strategies are attractive is because often they just let lets you, a, trade more frequently. And so getting more data points lets you get that signal to noise ratio up over time. That's 1 thing. And the other thing is if you stay stick to something systematic, you don't fall prey to some set of human biases that we're all that we all fall prey to. So that's the attraction. But, of course, again, getting back to the conversation about having a procedure, there's sort of this like, the efficient frontier of of trades and strategies that are available out there that have been competed away is naturally going to make you have a bit of both. Right? Some amount of systematizations, you get the benefit of the large n and, you know, avoiding biases while still retaining some of that while special sauce that you have that you're gonna try to put it into words or systematize it, but it's gonna it's gonna change over time. It's gonna be particular to you, etcetera. That's probably the efficient frontier of where edge is. Interesting. How do you I'm glad here, Shadi, because I feel like I'm I'm answering your questions with both all the time. Yeah. I know. But I think you're you're doing a fair enough job explaining both sides and, you know, like you said, the the answers aren't always, you know, a 1 or a 0. It's it's sometimes a little more I mean, sometimes they are 1 or 0. That that that's I think those are the the the And then, like, I sometimes it's both. Right. Yeah. So how do you think so this is a this maybe is an interesting conversation. How do you think strategy should change or or, like, more systematic or discretionary or any any of these factors relative to account size? Because, obviously, you know, doing 8% a year on 1000 dollars isn't very exciting. And but, you know, 8% a year on $10,000,000 is, you know, enough to to live quite comfortably. So Right. How do you think strategy should change or or the way someone looks at markets should maybe change or not relative to their account size? Let's say somewhere between, like like, a 10 k account, a $500,000 portfolio, and, let's say, a $5,000,000 portfolio. Right. Right. Yeah. So I think it get pass it gets back to some of the things that I said in the book where being really, really clear eyed and understanding the source of your edge really, really well is what's going to inform your beliefs about the capacity of your strategy. I think that's kind of what we're talking about here is what is the capacity of the strategy? Capacity kind of defining it as how big can I do this trade and if for it to still make money or enough money to be worth doing? Right? Some strategies just have a natural cap on their capacity. Right? There's Want me to explain that a little bit? Yeah. So well, just think about it this way. If I had a strategy that that kind of made a bunch of money or was very profitable, but it only applied to 4 micro cap stocks in Thailand. Right? There's a natural cap on how much money I can deploy on that strategy just because those things don't trade very much. Right? Conversely, if I found a source of edge that involved, you know, trading the S and P 500 a bunch of times a day, that has much more or the S and 500 future, that has more capacity. Right? I can definitely deploy a few million dollars doing that. And and I could go even further. Right? I could I could put on these massive massive macro bets. Yeah. And those have, like, essentially unlimited capacity. You could put billions of dollars to work on on a bet on US interest rates, let's say, like, on a 2 year bet on US interest rates. Right? And so that's just a nature of, that's just the nature of this the strategy that you have. Right? Like, how big can you do it? And so when you're talking about your portfolio size, really what you're talking about is how big can the strategy get before it stops being profitable. Mhmm. Well so but also with that, you know, if you're looking for an edge in the S and P, you're probably not gonna find the edge that gives you, you know, a 100% of your return. Right? Like, it it's very unlikely you'll find something like that because I I think it comes back to the Jane Street conversation where don't you wanna be competing against these guys who are, like have the best teams, the best infrastructure, everything like that. Right. And they tend to be the bigger fish, so they tend to be over there. Yep. Besides you know, so I I guess it makes sense if you have a smaller account to try and look for something with maybe a lower capacity. Yes. Inherently. Yes. Absolutely. You should look for those weird niche

Is in corners. Mhmm. Are you are you able to share any besides, let's say, the obvious of, like, market cap Mhmm. That maybe would have this this smaller capacity? Like, any ideas that you think are worth exploring? Yeah. Foreign countries, certainly, is a thing. Okay. If if, like, if for example, you are I don't know. You're an immigrant to The United States, your family came from, I don't know, Turkey or something. Right? You probably understand Turkey or you could be you could sort of eat more easily get to a point of being able to understand Turkey and Turkish stocks better than somebody else who's random person sitting here in The United States. Of course, you might not understand it as well as somebody who lives in Turkey and lives and breathes it, but you have the advantage of living here and understanding things here. And so there's sort of that that kind of Venn diagram, that intersection. Right? So countries is definitely a thing. Okay. Regulatory regimes, like, are certain things that that, you know, many many funds and and and other entities kind of can't do for regulatory reasons either because they have covenants. So for example, many many places can't trade stocks that are smaller than something like we talked about the market cap or maybe even a certain sector. Right? Interesting. Sports betting, for example. Right? Like, could think of that as as a thing that most legit financial companies don't touch. Some of them do, but most of them don't. Maybe there's edge there. Like tobacco companies, things like that. Well, so the thing about that is that it it that's more of, like, that maybe the ESG thing is another topic. Mhmm. But you should think of those as as like, trades trades kind of don't care about about the sector in that sense. Like, what Yeah. Like, the morality of it. Like, the Right. Exactly. Like, investments do, but trades don't. Got it. Yeah. Okay. Yeah. Yeah. And and, like, you know Oh, and 1 sorry. 1 1 other thing, Sean, novelty. Like, if there's something that's brand brand brand new and just got listed, there's probably not a lot of systems that are trading it systematically at these big places because it takes time to get historical data to build models, blah blah blah. So if you can get in there 1st and just figure it out before everybody else, it's probably a good source of edge. Yeah. Right. Because if it's a new product, let's say, or something like that, then there's, no one's priced it yet. You can maybe come in and and, you know, take your stab at being the 1st to put a fair value on this asset and, maybe make some coin. What what do you think about maybe, like, liquidity? Like, I guess that would be related to, capacity. Like, so do you think it's worth looking at more like illiquid stocks, or would you still wanna have that liquidity as a retail trader, just maybe not the volume? Yeah. So the I mean, they go together. Right? Because it's not like they're they're orthogonal things. Right? Trading volume, liquidity, eyeballs, dollars, like, they they all sort of turn into the same thing in the end. So they're highly correlated with each other. So when we're, like when we're looking at trades as as retail traders and you know, actually, maybe maybe I'll I'll start off by ask asking you this. Since you've left Jane Street, are you still trading your your own book, or are you more so into I know you have your own new company in the hiring space. Are are you doing any trading right now? So up until a few months ago, the answer was no. Okay. Other than very sporadic 1 off trades, you know, my my after I after I left Janestreet, the thought was pretty simple. I can't compete with them. I don't have the cost structure, etcetera, etcetera. The stuff I know how to do that I know that I know how to do, I can't do as a retail person. Mhmm. And so the right thing is to do nothing. Now that said, every once in a while, really, really crazy stuff happens in the market where it's just it's obvious. Right? Like, spring of 2020 was a thing. I don't know if you remember when when oil briefly went negative. Like, oil futures went negative. Like, doesn't take a genius to figure out. You should just get along some oil futures and wait for it to go back to normal. You know? Like, sort of fairly obvious trades like that, I I still would do, but I mostly just didn't do any trading. So that was the story up until a few months ago. Lately, it's been, I've gotten into the crypto space a decent amount. And so, now now we're starting to do a little bit more trading in crypto Mhmm. Growing all the time. So, that's kind of where I'm focusing my trading thoughts on these Are are you are you focused on, like, crypto derivatives or are you more in, like, the just like the delta 1 sort of crypto space? Delta 1 derivatives, certainly, like Yeah. Like, per futures and that sort of thing, cross exchange hours. Trying to look at everything that's fairly sensible that that is adjacent to stuff that I know and trying to learn about stuff that isn't that adjacent to what I know. It is a massive, massive world that is changing all the time. So was it the opportunity in the product that brought about this re re you know, this comeback to the trading space, or was it some sort of maybe change in in the way you viewed things in general, like the questions you would ask when you looked at trades? What sort of drove this this, comeback here? Yeah. Well, part of it was certainly, you know, having the time a little bit to to be able to to devote to it. And and part of it was just, you know, getting to talk to really smart people that that were interested too and and kinda working with them a little bit. That definitely helped as well. So combination of factors. In in a sense, had, like, you know, like, a a restart for your trading here when you when you came back. And the the 1 of the questions I wanted to ask you was if you had to start over again, what would you have maybe done differently, or would you have done things the same way? How would you have changed Or or the way you learned about trading? Sorry. Say sorry. Say that again? Yeah. So 1 of the questions that I wanna ask is if you had to start all over again, right, ground 0 knowledge. What did you what did say? You said from the very beginning, you're saying? Yeah. So if you just had to if you had if you were fresh to the trading field again, you know, obviously, with the experience like, knowing what you know now, if you could if you had to start again, what would you do differently? I would definitely still take the job at Jane Street. That's a no brainer. I might have made some slightly different decisions about what desks to want to move to. And, but fundamentally, I probably would have done fairly similar things. I'm quite certain I would have gotten into crypto significantly earlier than I have. But I think everybody would say that. So, yeah, that's terribly novel. Yeah. I I bet on Tom Brady winning this many Super Bowls and then No. But I yeah. I think there is definitely a, like, a couple of inflection points where there were sort of decisions that I made on, yeah. Well, should I look into this some more and and just kinda made the decision? Well, maybe not right now. And so probably would have gone the other way on those. Yeah. I've got a funny 1 like that. I have a I looked on my old desktop computer the other day, and I have a the original Dogecoin wallet downloaded because I tried to figure it out back in, like, 2016 or something. Right. Right. Never got just gave up on it. Now now I'm sitting there going, go figure. Oh, yeah. What are the odds? Love it. Do you have any you know, 1 thing I'd like I'd like to ask people on this podcast is just about trading stories. Mhmm. Feel like we don't hear enough of, like, you know, any, you know, bad beats or, like, awesome trades. Do you have any trading stories that you you think would be fun or valuable to chat about and and maybe sort of Sure. What went into it? Yeah. So, certainly, the story that comes to mind the most is fairly early on in my career where, you know, I was on I was on the options desk. It was me and somebody else in London, and this is in late 2008. And the we were trading a bunch of products, including some some DAX options. And and the senior person on my desk, he left. He left to do some recruiting stuff for a day. And so my job was just to just to hedge the deltas on the on the on on our book, but mostly just the DAX stuff. And so that's what I did. I like you know, we were long some stuff and so long some options. And so, you know, DAX would tick up and I'd sell some and DAX would tick down and I'd buy some. And it was pretty straightforward. Like, it was pretty no brainer stuff. I did notice that given the amount of vol on the day and that sort of thing, I was trading more than like, more size than I kind of had remembered us trading the last few days. It's just kinda weird. And then, our counterpart in in New York, he comes on the video chat, you know, early. And I was, like, probably 11 or something, 11AM, 11:30 maybe, London time. And and he said, oh, how's it going? Good. Good. So tell me about the trading you've been doing. I kinda talked to him how much I bought, how much I'd sold. And he goes, that's kind of more than I would have expected. Interesting. And that's when it dawned on me at that moment that I had forgotten the multiplier. So the max multiplier, it was 5. And so I was trading 5 times as many contracts as I should have been to be hedging this book. Oh my god. And so, yeah, I wanted to crawl under a rock and die. Yeah. And and everything inside me was screaming, like, try to make up a story, man, for why you did this. But I I don't know if it was, like, it definitely wasn't a deep sense of moral rectitude, but more just I couldn't come up with anything. And so I just said, look, you know, I fucked up the multiplier. Oh, no. And I'm like, oh, man. Okay. Well, let's figure out where what our delta actually is, and then we can talk about it. And I was I was positive I was gonna get fired. I was like, a 100, I'm gonna get fired here. It's it's been a good few months ride, but I did not get fired. We talked

About it, figured out kind of what, you know, what I could have done differently. And and that was a big eye opening experience for me actually to be in that spot. How come? And for the for the firm to to sort of have that mindset about, well, you know, made a mistake, blah blah blah. And so even though even though it was, like, a few $100,000 mistake, it it it was it was I was gonna ask about that because it sounds like you you caught it pretty quick. Right? Maybe, like, an hour later. But Right. You know, I was gonna ask, like, because, obviously, with so much size, it's like, what's the damage there? You know? Yeah. And So in expected value terms, the damage isn't that big because in expected value terms, you're basically just paying fee more fees than you should be. Right? Mhmm. But in actual practice, the deltas did go against me some and so, you know, there's more money than little bit more. Should have been in expected value terms. But So 1 thing you always, you know, is, like, a thought about the industry is that it it's, like, super cutthroat and the mistake like that definitely, you know, fired. What has your experience been with that? Is it as, like, cutthroat as it seems in in terms of, you know, the expectation of performance, or is there, you know Right. Some understanding of a learning curve? Because, for example, you came in with, you know, some of the the base skills that would make you a good trader, but without the tangible trading experience. I'm sure that you know, there were mistakes along the way. And and what's your experience with that been? So I think, yeah, prop trading firms actually, there's a there's a good Twitter thread yesterday. Prop trading firms firms are very heterogeneous. Right? And I feel like there are 2 stable equilibria. Stable equilibrium 1 is is kind of borderline scams, honestly. And I I because your audience is retail traders and, you know, might be interested in something like this, I will tell you. Many, many, many prop trading firms are just outright scams. If they ask for a capital contribution, run away. If they don't pay you a salary, run away. These are scams. Places like those, you don't last very long. Right? Mhmm. Like, you make a mistake, you're gone. Right? So it's a stable equilibrium of hire a bunch of people, fire a bunch of people, and whoever sticks around manages to survive. Great. Cool. There's another stable equilibrium, which is the Jane Street equilibrium, which is spend an ungodly amount of resources trying to identify, attract, interview, hire, and train good people. And so well, if you're doing that, then you can't have the quick trigger on firing them because that would make no sense at all. So that's another stable equilibrium. There there are companies like Jane Street and many others that are like that. And so you need to kinda figure out which 1 of the 2 you wanna be. Yeah. Exactly. It's like it's 1 of those if you've made it in the door at a place like Jane Street, the turnover is probably pretty low. It is extremely low. The hard part's getting in the door. Yep. That's right. Yeah. Once you have your seat, though, it's probably okay. That that I think that's very valuable for people to hear because I feel like some of the some stigmas around this the industry that that hopefully that helps dispel a little bit. Rightfully so. I mean, that's that's the thing about it. And the thing that's actually kinda terrible about it, in fact, is if you're a smart, you know, good person, you're and you don't know much about the industry, you're going to be probably thinking that what you need to do in order to track the attention of a Jane Street or somebody else is to show your trading acumen, you know, trade a bunch, learn a bunch, blah blah blah. And in fact, that does make you attractive to the scam shops. Mhmm. But makes you unattractive to the good places because the good places just see that mostly as stuff they're gonna have to unteach you somehow. Yeah. And so and so it's actually counterproductive a lot of the times to do some of that. So, Augustine, why did you leave the professionals trading space? Right? It sounds like you had a good gig going there. Was it a a good gig. Interest or what what what what changed it? So, I mean, I did have a good gig, and I I can't speak highly enough about about Jane Street, about the people there, you know, people that are still there, people have left. I mean, it was a phenomenally good place to work. Mhmm. In my case, it was kind of a a number of things. Certainly, you know, part of part of being an employee at a proprietary trading firm is that you're expected to not have much of a public persona. That's just part of the deal. Right? Yeah. But I wanted to write this book. Right? And so not because I thought I had anything terribly novel or innovative to say. I'll be honest. Like, it's just because I wanted to see, you know, a, if I could do it, if I could get a publisher to, like, take it and and publish And and, b, just to see if I could do it. And so that's kind of a personal challenge for me. And and so that was part of it. But also look. You know, I tell my kids all the time, people say life is short. Like, no. Life is long. Life is very long. And there's lots and lots of interesting things to do in the world. And I was an engineer for a bunch of years and I was a trader and you know, let's see what else is out there. There's nothing wrong with with seeing what else is out there. And so it wasn't so much a push as maybe a pull of the unknown that that maybe maybe transition. Interesting. That's very cool. And now how long after so you left you left Jane Street, then you wrote the book. Mhmm. And then that that's so funny that you wouldn't have been able to do that as a employee of a a firm. And then was it how long after that did you start your tech recruiting business? Yeah. So it's funny. When I, you know, when I left Jane Street, you know, my my thing was I kinda hung up a shingle as a a technical consultant. You know, mostly Okay. Machine learning stuff. Like, I knew I knew people that had interesting machine learning problems that were really, really hard. And so, you know, I got involved with that for a little bit, and doing some consulting in the machine learning space and, you know, a bit of trading space. But I'm fond of saying that every technical consultant turns into a management consultant whether they want to or not. It's kind of a thing I say a lot. And so companies that that I talked to, they just ended up having a lot of the same problems again and again and again. And and on the hiring space in particular, especially in the last few years, now that's a that's a thing that I feel I have a decent amount of experience with, you know, at Jane Street. I actually added it up. I've conducted on the order of 2,000 technical interviews in my career, which is a lot. And after a few 100, I thought, okay. I'm pretty awesome at this interviewing stuff. And then after a few 100 more, I realized, you know what? This is way harder than I thought it was. And I actually have to get good at it. And Jane Street is a company that I think has phenomenally good hiring practices. And so a lot of stuff that seemed obvious to me that these companies weren't doing, and it's just like, well, look, let me just help you out with some of this stuff. And it worked. Right? They started getting better hires, and I thought, okay. Well, there's a business here, obviously. Now I'm sure coming from your data science quantitative background that some of that worked its way into your your process for hiring. And you and I briefly chatted about this in in a DM prior to setting this up, but what sort of overlaps did you see it or or maybe taking advantage of even between the trading world and the hiring world? Yeah. Yeah. What what are seeing there? So it's funny that so we have a process that we put together, and we're in the process of rebranding it. But but the very, very we call it a playbook. And the very, very 1st play of that playbook is called money ball for nerds. Okay. Which is how do you figure out how much you have to pay your people? That's like a super fundamental thing that you need to figure out. And that is very much informed by my experiences in trading because the whole thing here, especially for startups that can't compete with large, software companies, is figuring out where your edge is, where where the undervalued skill is in the market that you need or undervalued relative to what you need so that you can identify that and then get good value for money and the people you hire. So that's that's a very clear spot where where trading informs decision making about hiring. The other thing is just figuring out what the right KPIs are, what to track, how to figure out whether the process is working, how to iterate, how to get better at it. That's another sort of again, that's sort of instinctive at this point for how to think about things in that way. So do you almost like a do you take so for anyone who's listening that hasn't watched the movie Moneyball, obviously, recommended to go watch it. It's a it's a great movie. Would you say you almost look at the let's say you're consulting with company ABC and they have a team of 20 employees. Do you almost view that as, like, a, like, a sports team and you're trying to like, is that the same sort of lens that you are looking at it through? Without question. Without question. Like, you need some starting pitching. You need some this or that. A lot of what we do with the hiring consulting is obviously consulting an organizational structure. Like, how you should organize teams and who you need and who's missing and how do we figure out how to, you know, fill gaps and that sort of thing. And then I guess, do you do you almost have, like, KPIs for each of these different positions within an organization so that then you can go out and, like, know like like in the movie Moneyball, instead of saying, oh, yeah. He's got a a great swing. It's now, like, he he gets this many bases. Yeah. Yeah. You have that they can go out and then apply to the market? Yeah. No. It's not quite that granular, and the reason is because there's a there's a common failure mode that every technical almost every technical organization starts out, living in, which is overvaluing technical skills. Mhmm. Because that's the easiest thing to test for in an interview. It's just, you know, do you know Python? Do you know whatever? I can evaluate that. But more general thinking abilities, are they smart? Are they you know, do they know how to debug weird stuff? You know, that kind of stuff is harder for technical people to evaluate, and so they don't end up doing it. And so then when people fail, it's not because of the technical skills. It's because of this other stuff. And so in back to the money ball thing, there are a lot of lot of spots where where these sort of more general abilities because companies don't they're not good at evaluating evaluating them and we can help them do

That that that they get super good value by identifying individuals that just have these other abilities. The skill set the skill stuff, they're gonna pick that up. Mhmm. So that's that's kind of 1 of the ways that this manifests itself. It's it's really interesting because you can you can just hearing you talk about this, it's like it's almost like we're talking about trading. You know, it's like it's very, very interesting. And I wanna ask you another question about data here. So we we can talk about this in trading, outside of trading, what what whichever. But, basically, in in the professional space, everybody has access to data. Right? Is it the you know, in the retail space, I would say having access to data is a little rare because looking forward something like a Bloomberg, it's not, you know Yeah. You know, predicting alpha. That's why we exist. But on the other side, everybody has the data. Mhmm. So that can't be the edge. Right? The edge can't be having access to to data points. No. So what do you think it takes? Like, how do you find an edge in data? I feel like, you know, that that's something that's still a a little mysterious to to the retail trader. How do you actually find an edge in data? So there's this within the world of trading, I think a productive model to use is this idea of you have prior beliefs about the market or about things you think are interesting or that you wanna look at. And so you form those into as coherent and cohesive a picture as you can before you look at the data. And so then then you go off and you because that informs how much data you need to look at, what data you need to look at, what it's gonna tell you, etcetera, etcetera. The the 1 of the common failure modes, especially in the retail world is, okay. I'm gonna grab a bunch of data and then I'm just gonna start exploring it. And I'm not saying you shouldn't do that, but it's very, very, very easy to get to the point of, oh, look at this thing that I found. It's like, yeah, you found that because you didn't find 50 other things you tried 1st. Right? It's a very common failure mode. Yeah. And so getting the story that you want to study, tell yourself, etcetera, ready and and really well thought out before you look at data, I think is 1 of the ways that you end up that lets you end up using data right. Right? The end ends up letting you use data productively. So almost like rather than trying to make something fit to the data, right, where maybe it's like, you know, if you took 1000000 technical indicator combos and threw it over the S and P, you'll find something that perfectly predicts it. Like, I remember absolutely do that. You know, there was, like, a Jim Simon's interview where he was saying they had discovered some relationship between, like, corn production cycles in Italy and the S and P returns. And it was, like, a perfect correlation. Yeah. Right. But it but it's obviously not tradable. Yeah. Exactly. So would you almost say it's better to like, almost like a scientific method. Like, start with, like, a hypothesis. Right. Exactly. Right? Like, some sort of idea about the world or, like, you know, this is interesting. Why why does this look the way it is? This was weird. Mhmm. And then try to explore it from from that perspective. Do you think almost Right. Exactly. That's a way to do it? Yeah. And and that's I feel like in the world of trading when you really get into it, that's where a lot of the really interesting decisions come in is the humans well trained humans are good at 1 thing or 1 set of things, and machines are good at another set of things. And thinking deeply about the meta problem of how do you how do you partition the work between what the humans are good at, what the machines are good at so that that interface lines up perfectly, that's a really, really interesting problem. I think that that 1 doesn't go away. And and so going too far in 1 direction, too far in the other direction, you know, we're too far in 1 direction is, oh, I'm just gonna bun like, look at a bunch of data and just do what the data says. That's wrong. And I have a really strong conviction about x. I don't need any data to tell me whether it's right or not. That's also wrong. Right? It's sort of that's the interface is where the interesting stuff happens. So coming back to more more of a, like, a we'll bring it down, like, 1 level to, let's say, talk about somebody who is just starting to explore the world of, you know, statistical modeling and data in applications for trading. Okay. I I feel like 1 of the things that is so tricky is actually being able to say, like, this has edge. Mhmm. Or here's some sort of edge or there this has a inflated risk premium. Mhmm. Because for, you know, for example, overfitting and or, you know, there could be things, for example, that have a strong correlation, but if everybody knows about it, it might not have edge. Sure. Right? So how can do do you know of any, like, good questions we could ask almost as, like, a checks and balance for our decision making that I think it's always imperative to ask when we have an idea. Right. So, again, this gets back to what we said earlier about, you know, if there were a procedure, it wouldn't be very useful. Right? So I feel bad kind of saying that, but I I do want to Yeah. Thanks, man. That helps. No. Like, not gonna lie. Saying it because it makes it sound as though it's just kind of this weird thing. You'll figure it out as you go along, and and it doesn't feel like that from the inside. Mhmm. But I think the the the key thing to really understand is that that's the good stuff. The fact that there isn't a procedure to this, that's what that's what makes this so interesting and difficult and endlessly fascinating to keep doing. Because if there were a procedure, then it would just kinda get boring. Right? You would go off and do something else. Now to sort of answer more concretely, look, nothing prevents you costs are very low. Nothing prevents you from just trying something. Right? Like, if you have edge, then you'll have to figure out whether whether the actual results, are noise or not. But at worst, if you're a noise trader, you're just gonna be paying fees. Right? And so as long as you're kind of within your risk limits, try stuff. Right? Bias towards trying stuff, I would say, is is people coming from a very academic background, from a very mathematical background are biased towards, well, I need to get it perfect before I start trading it. Yeah. No. Just try stuff. No. Okay. I love that. I love that. And, yeah, you know, and may maybe something like what do think about this? I I think, you know, we're almost like reflection is important in a sense of whether you you win or lose. So how do you balance try stuff with, you know, developing good methodology? Mhmm. Right? So underlying try stuff, do you think there's, a a core methodology that people should be considering? Well, before you try stuff, you probably need to have some story to your for yourself for how long am I gonna have to try this before I have a decent idea 1 way or another. And, again, the story you tell yourself, the structure you put around the problem before you looked at data should inform that. And for the kind of trade that I think I'm about to do, I think I need to run it for 3 months before I before I kinda really know whether it's making money or not. Maybe it's 2 weeks. Maybe it's 2 years. Right? And being very clear eyed about that. Because a lot of the time, the answer is gonna come back an awful lot longer than I'd like for for me to have to run it in order to know. And so try not to fool yourself at that point. Right? 100%. So I I guess there's 1 more conversation that I I I'd love to pick your brain about here in particular. And that would be where do I have the question here? It's basically a conversation about risk and your view on risk. I I think, you know, there's there's so many different views on on risk taking and trading that are out there. But I I'm interested in yours because you come from a very, like, edge oriented perspective. Right? Like like, do we have edge or expectancy? So how do you view the the world of risk taking and trading? Right. So anytime you have an edge, there is a risk you're taking in order to, sort of collect that edge. Right? And so a lot of the stuff you think about as a trader, or at least I think about as a trader, is what risks am I being paid to take in the sense that I think that that is a risk that I understand well and that I have identified, you know, a thing that can make me money and which risks am I not paid to take? So the canonical example here is is Warren Buffett. Right? Warren Buffett is famously the Oracle of Omaha. He sits into his, office. He drinks cherry cokes and he buys companies and he makes a bunch of money. Right? Yep. So the risk that he is incredibly good at taking is identifying underpriced companies. Right? So he goes off, he buys some company, and it's it's it's a good trade except that the market crashes and he loses a bunch of money. Right? Yeah. So in the course of buying that company, he took on the the risk that he's supposed to take, which is the is this company better than most companies? But he didn't he wasn't supposed to really be taking the is the world gonna go to crap risk. Right? Mhmm. And so that he took 2 risks with 1 trade. And so, obviously, the the way he should, he could hedge that risk is by selling S and P 500 futures or something. Right? That as long as his company outperforms, then he'd Right. So then, like, he's got that he's more kind of well isolated that risk that that he's really paid being paid to take. And so that's kind of what you're doing as a trader is trying to identify the risks that you're being paid to take and managing the ones that you're not either by hedging or by making sure that you don't though those don't get too big to actually materially affect your future trading, etcetera, etcetera. That's kind of that's the game. Yeah. At least the way I think of it. What do think obviously that makes it hard just to kind of put a fine point on it is it is very easy to fool yourself about what the source of risk is that you're being paid to take. What do you mean? A lot like, a lot of things look like for example, let me talk about this in the book. Like, let's say that you've identified, you know, a company that you think is cheap and you wanna buy it. Right? Did you identify that that

Company is cheap, that the sector is cheap, that everything is cheap right now. Like, it's not obvious which of those it is. And and the story you tell yourself is really important because that informs how you hedge your risks and that sort of thing. Interesting. Yeah. And what what do you what do you think about this saying for for risk taking? In terms of deciding what risks you wanna take, an okay place to start is to look at the risks that other people don't wanna take. Sure. Do you think that that's a decent idea for someone to start at, when trying to explore risks? Sure. Although I would say, yes. But I'll I would say in a liquid market, it's a 2 sided market. And so whatever price something is priced at is the is the kind of the market clearing price for that risk. And so it's more like relative to the marginal participant in the market are like, is my risk profile good or bad for taking 1 side of that risk or the other? So, like, here's a canonical example is, you know, downside puts. Do you wanna be buying them or do you wanna be selling them? Mhmm. Well, it depends on who you are. Yeah. If you're if you are a a pension fund that has incredibly slow money that's gonna be around forever, probably you should be the 1 selling those downside puts. Right? You're selling insurance. You can handle it. People who are who really need that insurance against big down drops, hedge funds or something like that, they should probably be buying it. And so for you, for your personal situation, which 1 kind of matches up more for you? Should you be the 1 selling insurance in that in that situation or should you be buying insurance? And it it's different. Right? Like, I buy car insurance, I buy home insurance. I know I'm paying up for that. Mhmm. But that's fine. Right? Like, that is a risk that I want to eliminate, and so I'm gonna pay up for that service. And then because you pay that premium, there's a business on the other side to provide you that service. Exactly. Right? Like, the insurer insures that, and then they sell out the their insurance to reinsurers like Warren Buffett. And it's fine. Everybody everybody wears the risk that they are placed to wear. Mhmm. So in terms of so that that's a it's funny. I actually wanted to start that conversation talking about, like, like, bet sizing almost, but then we went down to, like, risk exposure lens, which I I'm glad we did because that's a a a really good conversation to have. But in terms of bet sizing, let's go let's go to that for a 2nd. You know, you you'll have a a lot of, sort of the the the 1st things people will will find about risk taking is, like, never bet more than 2% of your account kind of thing or never bet more than 1%. And then maybe the next thing you find is, like, Kelly criterion. Right? And all of sudden, it's like, I think I have a 70% chance of winning and a 1 to 1 risk reward, and all of sudden, I'm betting 40% on my account. You know? What are your thoughts on bet sizing? And how should you know, how have you seen different participants think about it? So maybe how have you seen, like, the Jane Streets think about it, maybe the the smaller hedge funds and then the retail trader and and your thoughts on that? Yeah. So, I mean, certainly, to to speak specifically about about Kelly, Ewan Sinclair in 1 of his books, I can't remember which 1 it is, he talks about this. And he and 1 of the things he talks about that's very, important is there's this incredible asymmetry in the uncertainty you have about your edge in something where if you're like, you think your edge is x. Right? If you're wrong 1 way, then then Kelly is kind of okay. If you're wrong the other way, Kelly is a complete disaster. Yeah. And so fractions of Kelly make a lot more sense than Kelly because of this idea of uncertainty about how much edge you have. You never actually know that it's a 60 40 bet. You just kinda think it is. Right? So that's 1 thing to say. In terms of bet sizing in in institutional situations, there's a lot of different constraints. Right? It's very multivariate thing. Right? Like, you can certainly have a risk that says, no matter what, I'm never gonna bet I'm never gonna have more than 1000000 dollars worth of exposure in a given stock. Right? That's like no matter what else is true, that has to be true. And then you can say something else. Right? Like, no matter what else is true, I don't wanna have more than x dollars worth of downside risk in, I don't know, options of this type. Right? So that's like a different thing. And so and so these are all kind of bounds on how much risk you should put on. Right? And if if you think about those bounds, then whatever size maximizes profitability up to those bounds is probably the bet you should make, if that makes sense. Got it. Got it. And then in the in the retail space though, like, you know so, obviously, the the thing I I I'd start with is I I think the 1st thing is know if you have an edge. Right? You know, if if you don't, then you're you're just choosing how quickly are you gonna bleed out. So, you know, I I we could probably agree on that. Right? Like, that'd probably be the the underlying premise is have an edge. But so something that that I've personally been been struggling with and trying to determine is, know, I I let's say I've I've found a couple things recently that I I thought had really big edge, and then, you know, really being able to scale into that and bet according to what I believe my edge to be. Mhmm. You think that that's what are your thoughts on that? Like, you know, knowing when to bet big versus, like like, choosing that that option? Do think you that there's a time and place to be doing that, like, that exists? Or Yeah. For sure. I think that's fundamentally the nature of trading is most of the time you're doing nothing too very small. And very, very rarely, you're doing enormous size about things that happen that you're terrified about. Right? Yeah. I call them type 1 and type 2 traits. Right? Type 1 traits kinda keep the lights on and make sure that you can buy milk. And those are kind of normal, and and you're probably not gonna size them up very much. Every once in a while, something crazy happens and you're like, this is a screaming, screaming bet, and I have to do this. We don't have to, but, like, I can do this in size. And, yeah, there's some risks here, but it is such a huge edge that that I have to do it incredibly big. Right? That's kind of up to you at that point as a retail trader. I mean, within a within a company, you have you have senior people talking about things with lots of experience, previous situations like this. And so you can kind of collaboratively come to a decision that you can be comfortable with whether you made money or not later. When you're on your own, that's hard, man. That's just that's hard. Well, would you really see stuff like that happen in the institutional space where maybe there's, like, a risk manager overlooking and, you know, you know like, a lot of people would, for example, believe that a lot of the the institutional space is, you know you know, let's get our fee and not lose all this money. You know? Like, there is some view of that in some of the space. How do you see that sort of balancing? Do do you see is that something you've seen in the Yeah. So within the prop trading world, because all the money is internal to the company or almost all the money is internal to the company, then it's the people who come into work every day whose money it is. Mhmm. And so it's a very, very different mindset than a hedge fund where you're you're investing somebody else's money and probably some as well. So that's 1 thing to say. I think that's fair enough. Very fair. And but, yeah, in those spots, like, yeah, it it really is a conversation about, you know, which what best should we put on and and how big should we put them on. And it's our money, so we better get this right. In the hedge fund world, as we all know, there's the there's kind of a principal agent problem. Right? Like, if a if a hedge fund is getting paid 2 and 20, then they're sort of their their optimal amount of risk is higher than the investor's optimal amount of risk because they they're getting paid on a call option, so they need vol. Yeah. There's ways to mitigate that and kind of talk about that. But so there's a bit of that. But I think when you're in the trenches and you're actually making decisions, it really is just about maximizing. What is the what is the thing that what is the most that I should bet here to make the most money that I can in this situation? But it does happen. Like, it it definitely happens. Like, weird stuff happens all the time. If we have time, can tell you maybe 1 more Yeah. I'm I'm I'm good for time. Yeah. So this is this was an options thing where a Dutch metal company was spinning off something. And it was just kind of a weird spin off and we like, the options in in The Netherlands adjust in kind of semi weird way. They're actually very sensible. It's just kind of subtle. Mhmm. And so we were expecting these these new options are gonna list on a certain day and that it would be fairly easy for people to screw it up. And so we're all ready to sort of pay attention to that thing. It turns out that 1 of the important Dutch market makers had screwed up the original, like, the the thing that didn't spin off, the the the metal that stayed. And so and so they were basically putting markets out that made absolutely no sense. And it made such little sense that it actually took us more an embarrassingly long time for me and a couple other people to figure out what they were screwing up. Like, were obviously wrong. Everything indicated they were wrong. We were doing trades against them. But until you know how they're screwing things up, you're not really that comfortable putting 100%. It's like, this is so messed up that I can't even bet. Figured out how they were screwing up and, you know, we got to we managed to put some more size on. But, you know, we left a lot of money on the table that day from being just slow at figuring out what was going on. It's probably, like, 1 of the bigger, should'ves Yeah. In my trade career. I don't think there's anything worse than that besides, like, seeing a huge edge. Like, this is being, like, what is going on here? And then not figuring it out in time, and then, like, all of a sudden it just closes. And you're like, wait a minute. No. This can't be real. That's right. Oh, it turns out it was really, really good. Yeah. How how do I know? Because it's not there anymore. So I wanna ask you about this. And and, you know so I, for example, like, within Breaking Alpha, there's some people who are taking the game really, really seriously and would love to create a, you know, a full professional career out of

Uh-huh. Coming from the retail space and trying to break into the professional space, do you have any, tips or paths that people could follow to get there? You know, maybe they they don't have the the PhD in physics or anything like that, but they've done a lot of self learning. They can code, build their own models. They've maybe even developed a, like, a strategy that, you know Yeah. Generate some alpha. How can someone go from that sort of state where they've learned all this stuff to career? So so I guess a couple questions are why career? Like, if you're if you're doing well and you're making money at this, then then why? Right? Is it because you don't have enough capital? It could be capital. It could be a variance. Right? You know, it could be can't get a mortgage sometimes if you're trading your own capital. It could be a little tricky. You know? Right. So maybe stability would be 1 of them or Mhmm. Learning more. Right. So so part of the part of those answers like, all the stuff you described about about having experience in trading and that sort of thing, like I said, it attracts it, like, it will attract prop trading firms that that you probably don't necessarily wanna be associated with or that will give you capital that you might want, but you're not gonna get that stability that you're looking for. The thing about, as I said, you know, companies like Jane Street and that sort of thing is is the that kind of background just ends up being seen right or wrongly. I kinda making no claim about whether whether it's the right thing or not, as a negative. Mhmm. That's just a fact. The thing I would tell people is if you if you want to if you don't have a math degree from Harvard and and you want to apply to a really good prop trading firm or even a bank or something like that, the thing I always used to look for a thing that I used to look for a lot was, if you're, like, the 3rd best player in the world at some obscure chess variant, I wanna talk to you. Mhmm. Why? Because you you obviously are very good at learning something and getting good at it, and that's, like, an incredibly important skill. And you also did it because you wanted to, because it was interesting to you, because you had that curiosity and desire, not because there was a massive pot of gold at the end of that rainbow. Right? Nobody's printing money being the 3rd best player in the world at some obscure chess variant. You did it because you're just obsessed with it. Right? That's probably an interesting person to talk to provided they have decent amount of background and other stuff. And so I would say, yeah, highlight the stuff that you are It's hard. I'm not saying it's easy, but highlight stuff that you are world class at no matter how obscure. Because the world's a big place and being world class at something, even if it's obscure, probably involves an awful lot of effort and and time and toil and learning how to learn things and blah blah blah. Do do you see the you know, I mean, you know, obviously, experience is from, you know, Jane Street, which is, you know, 1 of 1 of the biggest firms in the world. But in in in What kinda started? Yeah. I guess well, it's it's it made me I'm I'm not saying causation, but, you know, all I'm seeing is you joined, and all of a sudden, it's the biggest firm in the world. So Well, you did. Yeah. I don't know. But for even, you know, smaller shops, things like that, you know, something that I've been in, you know, encouraging some of the members to do is, like, you know, build up some of these fundamental skills. Right? That that you know, it's not just about, oh, I've made money trading. Nobody nobody cares if you made money, but they care maybe a little bit, but not really. It's like, what skills do you have? And I sort of see what you were saying where, you know, if you've come out of, like, you know, school or an engineering background, you have no bad habits, and they can they have their process. Right? They have their way of doing things, and they can mold you into being able to do that rather than having to have you unlearn stuff. That's right. But, you know, if you've done a ton of projects and stuff, you've built a whole bunch of cool dashboards and models and things like that, and then, you know, you maybe get involved in, like, an online space, things like this. Do do these things help? And, like, could these could this manifest into a career in your eyes, or is there, like, some key component that they should be also considering? Like like, sort of, like, the chess variant thing. Right. So that's the thing. Anything that shows that you are incredibly hardworking, that doesn't hurt. Yeah. I've we've definitely talked to people who on paper maybe didn't stack up their resumes didn't stack up to to other people, but you look at their their GitHub repos or something like that, and it's just interesting project after interesting project that they just did. And that that aren't clones of other projects that they just changed 4 lines on their stuff from scratch, weird stuff. People like that are are always good to talk to. Mhmm. Because because that innate curiosity drive, whatever you wanna call it, and we talk about that a lot in the consulting work that we do, is not easy to detect, not easy to evaluate for, but incredibly predictive. We have all the data, incredibly predictive of success almost anywhere, whether it's trading or anything else. Can't teach that. Do you think in the, you know, the 21st century, it's it's necessary to have some sort of coding background to to get a job as a trader these days? Necessary is probably a little bit strong, but close to it. Close to necessary, I would say. And and would you say that's just because the the world's gone a more quantitative direction now? Or Yeah. Or or it's just it's the same reason that that executives have to be able to type now in a way that they didn't in the 19 sixties. Right? It's just there's an efficiency there where if you're a trader and you can't answer your own questions relatively simply, you have to involve somebody else to answer your question. That's just a friction that that doesn't have to be there now. And so it's more like part of the job is being able to answer questions for yourself quickly, grab a bunch of data, massage it, not screw it up, and you build a couple simple tools. Because by the time you explain it to somebody who's good at it and they code it up and then you iterate, whatever. It's totally wasted. Things have changed. Yeah. So I guess this will lead into to my last question for you, which is given the the current state of trading and stuff, what do you think is necessary for somebody to stay ahead of the game? Right? Stay aware of new developments, new trades, etcetera. And and how can you do that as, like, an independent trader? Yeah. So I think I go back to the what we talked about at the top of the hour, which is, you'll find the right community for you. Find a community of people that that are highlighting useful and interesting things that that you can contribute to that that kind of obviously value your input. And that's like, humans are social social creatures, and so that's a nice little flywheel for yourself too. Right? Like, being part of a community and and be getting involved in things that helps you stay there. Right? Just by by force of social pressure if nothing else. So I think that's an important thing. You know, obviously, Twitter FinTwit has some of that for me, certainly. But you can find it in in different places. You know, people you can bounce ideas off of, that's always really, really important. Yeah. Let let me ask you about Twitter quickly. When did you start getting involved in that community? Because I I love everything you share pretty much and, you know, that whole community is great. How'd you find it? How'd you get involved in it? Said it was I mean, it was the book, really. When my when Wiley said they would publish my book, my editor said, by the way, you understand that you're gonna have to sell this book. Like, you personally are gonna have to sell this book. And I was like, well, I thought that was that was your job. Like, I'm gonna write it and you're gonna sell it. Yeah. Nope. Nope. You're the 1 that's selling it. And so I started Twitter account, just started talking about stuff, and and it evolved from there. Now I'm not really selling my book anymore in the sense that I mean, it sells, but it's not like a thing I think Sells itself. I mean, it does doesn't much, but it does a little bit. And so but it's more about just getting getting that conversation with with other people that I think are, you know, sharp and interesting and and learning about new things. That's the value I get out of it, certainly. Yeah. I well, I I gotta say, like, you know, after I read your book, was delighted to find you on on on Twitter. Do you do any Quora or anything like that as well, or is it just strictly Quora for now? Quora. I thought about it, but I don't know. It seems like a big time sink. Yeah. Oh 0, definitely. If you see the it's like every response is a thread. Exactly. So but, I mean, different people have different things. Like, a good friend of mine, Aaron Brown, who's written a bunch of books that that you should I was gonna ask you about them. Read. So he like, he's mister Quora, and he's, like, he's not even on Twitter. So, you know, find find your your community. He's also incredibly prolific on Amazon reviews. And so Oh, really? Yeah. No. Aaron is is an incredibly good and prolific Amazon reviewer. Really? Yeah. He's like the it's like a he's like the Yelp reviewer but for books and products. Yeah. Yeah. Exactly. So, yeah, look look him up on Amazon. There's a there's a lot of gold in his Amazon reviews, actually. That's so funny because I myself and especially my business partner, Jordan, has has spent he's probably read every single thing that Aaron Brown has put out on Quora. So I'll let him know about the the Amazon reviews. I'm sure there's a little bit of alpha in there. So Yeah. And his Bloomberg columns are always great, and and his books, obviously. Brilliant. Augustine, thanks so much for coming on the podcast. Is there is there any last piece of advice or or comment you wanna make to the audience? Any anything you wanna leave them with? No. I mean, the thing the thing that's hard about being a retail person is obviously the stuff we've talked about. Right?

Kind of on your own. You don't have that support structure, etcetera, etcetera. 1 of the things lots lots of retail traders DM me fairly regularly. And the 1st question I invariably ask is is why? Like, why are you doing this? And I don't mean it as a challenge in the sense that you should stop doing it, but that you should be very clear eyed about what you're getting into. And Mhmm. This is literally the most competitive thing you can try to do on earth. There is nothing more competitive than this on the planet. And so what what is it that's attracting you to this? Right? Is it that challenge? Is it or is it something else? Is it in the back of your mind, oh, yeah. I'm gonna figure this out. I'm gonna make a ton of money. What is it? And being very, very self aware and clear eyed about that because there is a huge industry of people, you see them on Twitter, you see everywhere else, who who make it their living to separate well meaning smart people from their money because they're not self aware about why they're doing what they're doing. And so that's the number 1 thing that I think needs to be communicated again and again and again. There's lots of Charlottans to use a Taleb term out there. And the more you can understand yourself and why it is that you're you're undertaking this incredibly difficult thing, finding people who who resonate with with that thing that you've identified, the more protection you're gonna have against the incredibly low signal to noise ratio that you're faced with day to day. Brilliant. I think it's a good note to end off on there. Alright, Sean. This is great. I really enjoyed it. We should do this again soon. 100%.