Welcome to Better System Trader, the podcast to help systematic traders of all levels improve their trading. We'll give you loads of expert tips and practical advice on system design and validation, money management, trading psychology, and many other topics. Whether you're just starting out or a savvy systematic trader, we're here to help you improve your trading and find more success. This is Better System Trader with your host, Andrew Swanscott. Hi there. Welcome to Better System Trader. Glad you could join us for this fine episode where we're going to be talking about something incredibly fundamental to traders. It's something that we have to do all the time as traders, and it can have such a huge impact on our trading performance. In fact, it doesn't just impact trading. It can impact all aspects of our lives. So what is it? Any ideas? Well, it's decision making. Now don't need to explain the importance of decision making. It is pretty obvious. And I'm sure we've all made good and bad decisions over time and had to live with the consequences. But as traders, what can we do to improve our decision making? Well, in this podcast episode, we're joined by special guest, Augustine LeBron. Augustine began his career as a trader and researcher at 1 of the world's largest money making firms, Jane Street Capital. And over the years, he's traded many different kinds of securities and has created, developed, and implemented successful trading strategies. Now in my chat with Augustine today, you're going to discover the laws traders need to apply to make better decisions. Augustine will also explain to us why we're never really happy with the trades we make and what to do about it. We'll also talk about identifying personal edge and leveraging that in the markets. Why traders need to integrate storytelling into their processes. We'll talk about the dangers of traders mistaking the map for the territory, how to approach a model when it's breaking down, plus a whole lot more. So how about I make the decision now to stop talking, and let's get right into my chat with Augustine. Hey, Augustine. Welcome to the show. It's really great to have you here today. Hi, Andrew. Thanks for having me. So how about we just get started with a little bit of background on yourself 1st just so so that people can get to understand you a little bit better. So do you wanna share a little bit of background on yourself here? Sure. So, well, I grew up in Canada and I did in university, I did electrical and computer engineering. And then I got a job as an engineer making chips for cell phones and that sort of thing. And around 2008, I got a bit bored of that and decided to find a new job. And I was actually playing a lot of online poker back when that was a profitable thing to do and and legal in this country. And so I was looking for something that kind of combined poker and engineering, and that's trading pretty much. And, you know, trading is the most competitive endeavor on earth as I'm sure you know. And I'm a pretty competitive person, so that seemed like a natural fit. So so yeah. So I started applying to a bunch of jobs and eventually found 1 at at a prop trading firm called Jane Street Capital. I was a quant trader and researcher there. And like I said, I started in 2008 just as the world was imploding, which was quite a baptism by fire in some sense. But over time, I've been I've traded just about everything, options, commodities, equities, futures, you name it. Yeah. And and working at Jane Street was great because, I mean, I got to learn from some incredibly sharp people. And eventually, I got to the point where I was doing some of the teaching too. So you mentioned there that you were doing some quant trading and also that you you had an engineering background. So was that I mean, those 2 kind of sound like they they fit together quite well. Was that intentional or did you just kind of happen to somehow end up doing that particular tried top of trade? It it was definitely intentional in the sense that, you know, I think of engineering as fundamentally making good decisions, design decisions when faced with uncertainty. Like, you can't nail down every detail in an engineering design. You have to sort of use your judgment. And the combining of judgment and quantitative skills, I think, in engineering and trading, it's basically the same skill set. Yeah. Well, it's interesting that you mentioned decisions there because you've just released a book or you're just about to release a book called The Laws of Trading, a Trader's Guide to Better Decision Making for Everyone. I think it's it's being published by Wiley Trading. Mhmm. What made you decide to write the book? Why did you think that that this type of book should be written? So I part of it is I think the trading books that are out there, at least the ones that are popular, I think fall into 2 broad categories. 1 of them is kind of storytelling books like Liar's Poker where you talk about crazy times and crazy behavior. Or the other kind which claims to teach you profitable trades. And at least in my experience, they rarely if ever do. And so I tried to write the book that I would have liked to read when I was starting out. Yeah. So who do you think is the ideal person as far as audience for this book? Well, certainly, anyone who's starting or thinking about starting a career in trading will probably find it useful, because I think there's a general lack of good useful information about how professionals think about trading, especially professionals who aren't trying to sell you something at some level. And I think there's also a lack of good useful information on decision making more broadly. Obviously, there's academic studies and that sort of thing, but sort of in the day to day decision making that we all do, I think the things that traders learn to think about end up being very useful for thinking about all sorts of other things in addition to trading. Yeah. I think we're going to dig into that point a little bit more later in our chat. But I just want to ask you. So I I found the title of the book quite interesting. You called it the laws of trading. Why did you use the word laws there and not some other type of of word? Why why are they laws? Sure. So when I was teaching new traders, I just kind of had these little laws of trading as a useful mental shorthand. Like, maybe you should think about this. You know, maybe you should think about law number 1, law number 2. And the broke the book grew out of that. But the laws aren't mine. I mean, they're they're timeless in the sense that you'll find versions of them sprinkled around the literature across the centuries. Yeah. I mean, William Shakespeare sure knew the laws of trading. Why do you say that? Well, I mean, if you think about I don't know. Like, Macbeth, is very much the idea of motivation. Like, why are you doing the things you're doing? You know, like, Merchant of Venice. Like, what is your personal edge in life? You know? Like, these sorts of things. Like, the laws of trading are fairly universal, and and I'm just trying to sort of put them together in a maybe a a modern kind of feel. Yeah. Yeah. Yeah. I wanna ask you about motivation in a minute, but just 1 final question about it sounded like you were suggesting that some of these laws came about or you recognize some of these laws from your own personal experience when you were trading and you were teaching others trading. Can you give us a little bit of insight into how that happened? Were there any particular experiences or things like that that you made that really reinforced these laws for you personally? Yeah. So I think well, let's just take 1 law as an example. So law number 2 is you're never happy with the trades you did. And this is sort of this fundamental idea of adverse selection. Like, if you if you did a good trade, then retrospectively, you probably should have done it bigger or more of it. And if you did a bad trade, then you shouldn't have done it at all. And so being a trader and thinking about acting in competitive markets is this sort of fundamental thing that you're basically just gonna be a little bit unhappy, best case, about every decision you make. And that's something that you learn very quickly. Right? Like, you try not to be results oriented about the trades you do. You try to think about your process, but it kind of leaks back in. Right? Like, you know, you do some good trade and you think, oh, yeah. That was a good process. I did it for the right reasons and it worked out great. And then the back of your mind, you think, well, if it happens again, maybe I should do it bigger. Right? And and then vice versa. Right? Like, you did a bad trade. Like, maybe your process was fine and and you just you know, you got unlucky because there's a lot of randomness in the world. And certainly in the world of trading, you know, you start thinking possibly about the wrong things. Yeah. Now, you just touched on motivation, a minute ago. Why do you think motivation matters in the trading arena? Oh, so I think if you don't know yourself and what motivates you in trading, then, you know, because it's a competitive environment, you're going to be exploited by people who know you better than you know yourself. And it's definitely true, especially for, we'll say, amateur traders that there are a lot of people out there trading who claim to be trading for the money. But when you dig down, you discover it's something else, like boredom or risk seeking or something else. I mean, just go look at the online ads for trading platforms and and retirement things. They're certainly not marketing to your rational self usually. No. So do you think then are there particular types of motivation that actually can be dangerous for people to have or can really impact that the the the types of results that they achieve? It's yeah. I think it infects your your thought process at some level. And this goes back to the idea of really understanding yourself. Like, what is it that wakes you up in the morning

Gets you to work every day. Like, what is the thing that draws you there? And, you know, it can be many things. Obviously, like, when you're actually doing trades, probably you should be thinking about what is the thing that maximizes risk adjusted, expected value, whatever you wanna call it. But you should also think about what are the kinds of trades that I should be doing given my mental, emotional kind of mindset. 1 particular type of motivation is, I guess, on the intellectual side. And Mhmm. You know, I know for myself, I've got a little bit of this, and I know a lot of other traders who do as well. They they see trading as a game or as a puzzle that that needs to be worked out, and you're matching your mind against other great minds. And, you know, I think this is a a really big, type of motivation for a lot of traders. Are there any benefits or dangers for using or having this type of motivation for trading? Yeah. It's a great question, I think. Because there's certainly a lot of value in having a strong intellectual curiosity in trading. In fact, it's super important. Right? Because these things are hard. The things we're trying to do are really hard. But the danger comes in when you start doing things to show someone, usually yourself actually, how smart you are. Right? Like, you sort of think about things in a way. Like, what is the thing that's going to maximize the evidence that I am a smart person or that I'm thinking about things the right way. And so you start privileging a feeling or a state of mind over what should be the important thing, which is making money. And the thing is, certainly it's true that there are a lot of ways of making money that don't require a ton of intellectual horsepower. Mhmm. They're simple, boring, but you have to get all the details right. And it's not intellectually stimulating, but they work. Yeah. I think as well you see a lot of especially on the retail trading side, you see a lot of, you know, very what's the word? Like, professional people like engineers, doctors, you know, psychologists, those type of people getting involved in the market purely for this intellectual stimulation. But as you mentioned there, there can be some real dangers for for this and we need to, I guess, kinda look out for that. Mhmm. Yeah. Okay. Well, I just wanna talk about edges a little bit. 1st, how about we start with a very basic question? How do you define what a good edge is? So the way I think about it, a true edge, a good edge is something that you know and can do that the marginal participant in the market doesn't and can't. That's like your personal special sauce. And a good edge is obviously 1 that's reliable and robust and that won't disappear all of a sudden. And importantly, it's 1 that you're justifiably confident actually makes money. Right? Mhmm. So it it comes down to what is it that you know and what is it that you can do that the marginal person doesn't or can't. Right. Okay. So when you say that they can't do do that, what do you what do you mean? Are you talking about the actual application, the execution, or what types of things? Yeah. Yeah. It could be anything. Certainly, very prosaically, professionals have access to cost structures that are not available to to amateurs. And so there's a set of trades that they can do just by virtue of, you know, their margin costs or their trading costs or what have you that that amateurs can't get to. Right? So that's a very sort of very straightforward can do thing. And then when you think about what is it that you're good at. Right? Like, if if you're good at sort of collecting data, analyzing it, that sort of thing, then that's a thing that you are good at that you can do that maybe the marginal participant can't or isn't as good at. Mhmm. So, yeah, it it depends on your personal situation. Yeah. So we well, you're touching on personal edge there. And I think 1 of the points that actually stood out to me in the book was this idea of personal edge. And I think there's something I probably haven't thought about directly or the way that you explained it in the book, but I think a lot of people probably do it indirectly. Can you explain a little bit more about what this concept of personal edges? Mhmm. Yeah. So again, it's this idea of what you know and can do. And so the 1st step is really understanding very deeply your competitive advantage. What are you good at? And in particular, what are you good at compared to the market you're trading in? I mean, maybe you're really good at understanding financial statements or digging into the operation of companies. I mean, I'm certainly not good at that, but Warren Buffett is. Right? Like, that's his personal edge. And so figure out, like, at the margin, what is the thing that you're good at? And then look for edges that relate to that skill. But what about if you're, like, if you're just starting out or perhaps you think you found your personal edge, but you're not getting the results that you're looking for? How do you go about identifying what your personal edge is? And if you're not performing so well, how do you kind of fine tune that or look elsewhere? Is there like a process that people can follow to do that? I think it's more of an exploratory thing. Right? Like, you try some things and they may or may not work, but you quickly go back to sort of studying what it is that you did, what was your process in in the decisions you ended up making. And I think an analogy from poker is really good. Like, you can learn to play poker by just playing, like, learning the rules and just playing a lot of hands and then you're going to get better. But if you study your hand histories and really dig in and if especially if you have somebody who's better than you who can point out some ideas and things, then that feedback process is incredibly valuable and that accelerates your training. And I think getting back to training, I think part of the value of what you're doing here is it engages people with ideas from other places. And that, again, that accelerates the feedback process. Yeah. I think feedback is especially important in that type of process and and when we're assessing our trading results because it's, you know, something that people perhaps maybe don't look at too much or they just look at the p and l at the end of the day and and that's it. But as you mentioned, you can really dig deeper into some of those things and and come up with some really interesting insights. And part of that is at some level developing the discipline to write down or at least note what you were thinking at the time of the decision. It's very easy as humans to go back and sort of, oh, yeah. I must have been thinking about this. That's probably why I made this decision. And retrospectively convince yourself of something that probably wasn't the case. Yeah. And so, yeah. That's a big 1 certainly for people starting out. Yep. Yep. Now in your book, you have a quote that says, if you can't explain your edge in 5 minutes, you don't have a very good 1. Now I think we've probably all heard something like this in the past, but I'd like to ask you why I mean, surely, like, there's other factors as well that can go into that, like profit and loss, the longevity of a strategy, the risk adjusted return. And there's all these other factors that could determine if an edge is actually a good 1. What do you think the the explanation or the story behind it actually defines if an edge is good? Yeah. I think this is a great question because it gets at the core of we'll say that there's, you know, a a range of opinions on the subject, and I think I'm kind of pretty far on 1 end of the spectrum. The reason that I think you can't really rely on p and l's or, you know, any statistics of your p and l's and that sort of thing is because these things are noisy. And there's a very good reason why these things are noisy. Namely, that when you're dealing in a competitive environment, it is very unlikely I mean, it certainly it's been my experience. I haven't seen it. It's very unlikely to imagine a trade that is so incredibly profitable that just by looking at the p and l's alone, it's clear that this is a profitable trade. Like, all real trades have some performance that is along the lines of, well, I'm fairly sure this makes money, but I'm not positive. Right? So you need something else. You need an explanation. You need a a story. Something that combines both the data that you have and also sort of the thing that human brains are really good at. Yeah. I think the the the challenge of of putting a story to something is that, you know, it it, introduces our personal biases or it can introduce our personal biases. And even if we're using data, we can always twist data to, you know, support a story we wanna see. So how do you match that with actually coming up with a a story or explanation that could possibly be accurate? Yeah. I I totally agree. That is that is the crux of the difficulty of doing this job well is that, you know, if you're thinking about stories, because stories also help you guide your exploration in terms of what what is the next thing that I should be thinking about, then you can always fool yourself. And I spent a long time in the book talking about all the ways that well, I don't know about all the ways, but certainly a lot of the ways that you can fool yourself. And what are the structural and sort of housekeeping y sorts of things that you can do in order to mitigate those risks. Yeah. But as I said, I'm nonetheless a believer in the necessity of stories. Again, because markets are so competitive, I find it, at least in my experience, difficult to imagine a trade that is so profitable that it's clearly profitable just by looking at the p and l and nothing else. Like, you're going to need something else.

Yes. Yeah. Okay. And and the thing is, the other thing, Andrew, I just wanted to sort of add to that a little bit. Like, the thing is you're always going to have at least a human decision to make at some point. And so, like, you can imagine somebody running a completely black box strategy that just okay. Well, it says it makes money. I'm gonna turn it on. Well, how do you know when to turn it on and turn it off? Like, you are imposing some some of your own story in that decision making process. And so it's in some sense, I think it's safer to sort of get good at the storytelling part so that you can integrate that into your process as opposed to making it, like, an out of band sort of thing. There was another comment that that kinda stood out to me in your book, which I think links quite nicely into this fooling yourself statement you may you just made. And that is mistaking the map for the territory, which I thought was quite an an interesting concept. Can you explain a little bit about what what that statement means? Sure. It's you know, you're building models about the world fundamentally. Mental models, actual computer models, it doesn't really matter. And models and there's a famous quote by George Box, all models are wrong, but some are useful. And I think it can be seductive when you have a really good model or 1 that you spent a lot of time working on to just sort of use that as your proxy for how the real world actually works. And my favorite story about this, it comes from the 2008 crisis where David Vineer, was the CFO of Goldman at the time, he has a quote where he said, we were seeing things that were 25 standard deviation moves several days in a row. Now if you know anything about stats, you know that that's impossible. I mean, it's likelier that you win the lottery dozens dozens of times in a row than what he said. But he had so fallen in love with his statistical model, his map, that he didn't even consider the possibility that the model itself might be broken. Mhmm. So yeah. I mean, if you start seeing things that are patently impossible or that are crazy, then it's probably that your mental model or actual model is wrong. You need to rethink your assumptions. Yeah. So that's actually a really good example that you give there from Goldman Sachs that, you know, they've got a lot of smart guys, academics, and those type of people working there. And even they can be sucked into this this illusion, I guess. So it can obviously be a very real danger that perhaps traders aren't even aware of. Yeah. How can we look out for this type of thing when we're not even aware that we're potentially doing it? So I think maybe I'm sounding like a broken record, but I think it goes back to having a good story for what your edge is. Mhmm. Because I think if you have a good reliable comprehensible story, then, you know, when the story starts to make like, when the when the trade start to not make money, then you can go back to your story and sort of examine the assumptions of your story, not from a necessarily a mathematical or statistical point of view, but more just from a horse sense point of view if nothing else. Like, I claim that this trade makes money for reasons x, y, and z. Well, are those reasons still operational? You know, if I'm doing some arbitrage trade between 2 markets, like, if this if this trade stops making money, like, well, maybe the arbitrage is broken for some reason and I'm not aware of it. Right? Yeah. Having a story is a is a very good way to test your assumptions when things start to go crazy. Yep. And then when things do start to go crazy or perhaps models start breaking, how do you determine what's causing the degradation or what what's the source of the decay? Yeah. So that's something I cover in some detail in the book. And I think it a lot of it has to do with, as I said, the source of your edge, but also the nature of the degradations. Right? Like, if, you know, if it was a sudden thing versus a gradual thing, you know, if it's a sudden thing, then, well, maybe something about the world changed overnight. I mean, it's certainly possible for that to happen. We've seen that many times before. If it's a gradual thing, well, I mean, it could be that you just need to refit your model's parameters or something like that. The world changes in these nice gradual ways. Or or maybe you're outcompeted by somebody, you know. And then that question is a pretty subtle 1, to be honest. And I don't think there are any great universal truths to be had here. I think experience is the greatest teacher here. Have I seen this sort of thing before? What should I be on the lookout for? Yeah. Yeah. So if you do notice, you know, a gradual degradation over time, do you do you need to understand why? Do you need to readjust the story? Or do you think it doesn't really matter just as long as you can recognize that it's happening? Well, I mean, if there's something you can do about it, then that would be great. Right? Like, you know, if if if the trade that you're doing requires some kind of model that has some parameters and you can go back and sort of grab some new data and refit them to to more recent, more relevant data, then obviously that you should do that. And that's probably kind of the standard way of proceeding. Right? Like, if if you've seen this before, if you've been running some trade for a while and and you see that it's degrading and then you sort of refit some models and it's back to basically normal, then then that's probably par for the course. But it's certainly true that, you know, all trades eventually degrade. Right? Like, if there is no trade that that exists that's been running uninterrupted with no adaptation to it for 40, 50 years. Right? Yeah. But now what about is it possible to identify potential failures when actually building a model? So, like, getting it way earlier than when it actually starts to decay, but trying to identify possible issues before you even go live with the thing. Sure. I mean, certainly, as we all know, like, back testing strategies is an important thing. You should you should probably do that. You should have good data husbandry and not use all of your data to train a model. You should probably lease them out and test it. Right? Like, knows about this and and has been knowing about it for for decades. But I think there's very little substitute for, okay. Well, let's just try it and see what happens. I mean, I can't tell you the number of times that I've built a model and, you know, tried to run a trade and everything to my to all appearances seemed like it would work. And then you actually start running it and then you realize, oh, wait a 2nd. Like, this is not at all what I expected. And you start digging and you realize there's 1000000 things that you didn't know. And you wouldn't have known them until you started trying. And so there's a very real balance to strike between getting it all right and putting all of your ducks in a row, but also just trying stuff. Like, at the margin, there's very little cost to trying a small trade. Right? Yeah. And as you mentioned earlier, the feedback from that experience can really be helpful in perhaps taking you down a different path and creating a new story and all that kind of thing and uncovering new models and edges that perhaps you would never have thought of. Exactly. Yep. Now another quote so I'm ping pulling out quite a few quotes from your book today. Another 1 that I really love is is about adaptation. And I guess it's kind of obvious why we need to adapt, but the quote was, if you're not getting better, you're getting worse. And I absolutely love this. I'm a big fan of, you know, self improvement and also, you know, trying to make your training better, and I think it's a a constant cycle. But can you give us a little bit of your own personal insights into why this matters? Sure. So the analogy that I draw in the book on on in the chapter on adaptation is between the trading world and just biological evolution. I think that the analogies are very, very strong. The world is a very competitive place and financial markets more so than just about anywhere else. And the thing is markets are fundamentally these enormous distributed information processing machines. And so any profitable trade is like a flashing, hey. Look at me sign to anybody who's willing to look at market data. Right? And so people are always on the lookout for new edges and to improve the ones they have. And so if you keep doing the same thing, you'll just find yourself falling behind. And so, yeah, as you said, getting better is very much the name of the game. Yeah. And I suppose with an institutional background, you see a lot of the resources that go into finding these edges. They hire very smart people. They got unlimited budgets for IT infrastructure. And as a retail trader, you know, we've got to do our best and you keep trying. And as you've mentioned, if you don't do that, you're actually going backwards. That's right. Yeah. I mean, it's it's pretty awe inspiring to see sort of the machinery that is deployed in these markets. But even so, right, like, the world is a very complex interesting place. And if you can find something, some small parochial little thing that, you know, you figured out that nobody else has, you know, I'm confident that those things exist. I mean, traditionally, and hold investors, like, the fifties, sixties, and seventies could trade even medium cap companies profitably because they sort of understood the fundamentals better than everybody else, and then people got better. But even today, I would say there's plenty of micro cap stocks that, you know, a retail buy and hold investor who really understands financial statements, which again is not me. You know? Like, those spots are places where big institutions, you know, it's not worth your time to dig into each 1 of those. Right? There are little corners. You just have to look for them. Yep. Now I just wanna ask you 1 final question now before we start wrapping up for today. And that is the myth of the 0 sum trade. I love this part actually of the book because we've all heard about the, you know, trading is a 0 sum market. But you've you've got

Little myth buster there for us. So do you mind explaining a little bit about that? Because I thought that was that was super cool to think about the way Sure. You've explained it. Well, I mean, I think the best example I can give is honestly, it it ends up being a plug for my former employer, but I think it's it's important. Jane Street Capital is a big ETF market maker, and 1 of the big ETFs that they they make markets in is EEM. So this is a US listed ETF that invests in emerging markets around the world. And this is a great story because, the story of financial markets, I I would say, the last couple of decades is indeed the story of rich Western countries losing some, profitability in the trades that they do kind of in in the developed countries, right, like as a re as a retiree or as an investor. Right? Like, the the the edges, the returns to capital just aren't there. And so they've started to ship all their capital to all these emerging countries. Right? Countries that are in development that need capital, and there are great opportunities there. And so anytime a US investor buys a share of e EM, Jane Street Capital springs into action and buys the few thousands of stocks in all these emerging markets and takes care of all the crazy market data issues and regulatory issues. And what ends up happening is this incredible flow of capital from from rich developed nations to emerging markets, and everyone just flat out benefits from that. It couldn't happen without trading. It couldn't happen without financial markets. Okay. Now just like to start wrapping up today with some quick closing questions. Sure. What's the biggest lesson that you've learned through trading and and the markets? I think it's the thing that you already touched on, which is it's something new every day. There's always something new to be learned. There's something to be improved. And you can think of this as sort of this dreary, like, I have to keep getting better. Otherwise, bad things will happen. But honestly, that's the good stuff. That's what makes the job interesting. Yep. Excellent. Alright. What about the best trading advice you've ever received? So I think it goes back to my my 2nd rule. You're never happy with the size you did. If it was a good trade, you should have done more. If it was a bad trade, you shouldn't have done it. And so you have to make your peace with this thing about being dissatisfied with just about every decision you make. Okay. How about, do you have any favorite trading books? So I think if I think back to when I was an engineer, the thing that got me into thinking about a career in trading was the Poker Face of Wall Street by Aaron Brown. He talks about it's super interesting. He talks about sort of the history of The US financial system and how surprisingly intertwined the game of poker was in the sort of 18th, 19th century development of The US financial system. And so that was a pretty good connection for me. And so that's the 1 I kind of keep thinking about. Yeah. Cool. Alright. And now finally, what's the best way for listeners to either get in touch with you or to learn more from you? Sure. So the website for the book is wwwlawsoftrading.com. And you'll learn about the book, and you'll learn about the laws. I've got some cartoons that illustrate them, that sort of thing. And the thing obviously for your, your audience is very sort of trading specific, but the big message that I wanna put out to the broader world about this book is that these ideas that surround trading and the laws that that operate in them are very broadly applicable and make you a better decision maker just about everywhere else. And that's what I do now as a consultant. I I help, tech companies sort of improve their decision making processes, improve their operations. And so if you're a tech manager, if you're, somebody who wants to think about how they improve their decision making process, then, yeah. Send me an email. I'd love to talk to you. Yep. Awesome. I'll put a link for the website up on my website as well so people can find that easily. Awesome. Well, thanks so much for your time today, Augustine. Is there anything else that you'd like to mention before we wrap up? No. I think, as I as I think I said at the beginning, I mean, I enjoy I enjoy talking to people about these ideas. The idea of improving the world through getting people thinking about their decisions a little bit better is something that, obviously, you know, you have the podcast and so you're obviously sort of in the same boat. And so, yeah, I just really enjoy the opportunity to to talk to you and to, you know, help out your listeners to the extent that I can. Awesome. Alright. Well, thanks a lot for that, Augustine. And I recommend that people go and check out the book, the laws of trading. It's due to be well, at the time of the recording, it's due to be released in in a few weeks to a month, I think. But perhaps it's out now when you're listening to this. So go and check that 1 out. Alright. Well, thanks for spending time with us today, Augustine. And, you know, it was really great chatting to you and just touching on a couple of the points in your book. So I wish you all the best, and thank you. Thanks a lot, Andrew. I really enjoyed it. Alright. Cheers. Bye. Okay. Well, that's it for this episode. Thanks for listening. I hope you enjoyed the show. Come on over to bettersystemtrader.com. That's where you'll find all the previous episodes, all the transcribes, all the show notes, and all the free weekly trading tips. Bettersystemtrader.com.