AD Derivs. Podcast (Ep. 75) - Euan Sinclair

Speaker A: Foreign.

Speaker B: Welcome everyone. Thank you for coming to the Amber Data Derivatives podcast. I'm here with Ewan Sinclair. Uh, for anyone who's new to Ewan Sinclair, he is a doctorate in physics, a prop trader, um, a, ah, background in risk management and author. He's also an advisor to Amber Data Derivatives. So you in? How's it going? Good.

Speaker A: Thanks for having me here. So you got all dressed up for the occasion. I appreciate that.

Speaker B: I don't know if that was sarcastic or not, but thank you. Um, so I kind of want to structure this conversation around. You wrote these letters really around a training psychology called the Theta Pigletters. Um, the way I would describe them is maybe a little bit of a personification of sort of the pitfalls that traders face and some of the sabotages or self sabotages that traders face along the way. Um, it's really interesting especially because a lot of your background in your authoring has been time series analysis, a lot of technical details. What inspired you to write the Theta Pig letters?

Speaker A: Um, so it was really a sort of a vanity writing project. Um, I always. Okay, so you know, C.S. lewis wrote the Narnia books. He was very religious and he wrote a ton of religious books. One of them was called the Screwtape Letters. And leaving aside the religious stuff, which a lot of it hasn't dated particularly well, the format's very interesting to me. It's a senior demon writing these letters to his apprentice demon telling him how to tempt people into sin. And I just think it's a fantastic format. It's a really interesting way of. It's just interesting. And also it kind of lets you sort of say terrible things to people without sort of making it sound like it's coming from you. It's not as preachy. And also demons are, uh, are bad. So they're allowed to be kind of nasty to each other. So I kind of think every, every field would benefit from having one of these. And I'd always just kind of wanted to sort of do it and I don't know why I started just kind of started doing it and it was so much quicker than the technical stuff because there's no equations to get right, there's no formatting, there's no um, numbering of equations and stuff. So you just write these things and they're all self contained, just like one page letters. And it doesn't have to be in any really either. So it was really just a vanity thing. I honestly probably won't publish it because I don't think a publisher would Be interested in something that's 50, 60 pages long. I could put it on Amazon, but I can't be bothered. Um, so it's out there. People can find it on the Internet. I don't care if people give it to other people. Anyone who says you make money from books has just never written a book.

Speaker B: Well, we'll link it in the show notes for everyone, so whoever wants to read it. Highly, um, recommended. So you had this framework for traders in the theta pig letters. You know, edge execution or implementation? Risk management psychology. So I think it's kind of interesting to jump through each individual point. So maybe if we start with edge, you know, how do you define edge? Where does edge come from? Um, are there different types of edge? Maybe you can start there.

Speaker A: Yeah, so that's something I've changed my view on a bit over the years. Um, edge has got nothing to do with mathematics. Edge is like a phenomenon that exists in the world that you can quantify with mathematics. So, um, take a sporting example, right? If home teams cover the spread more often than away teams, that's an edge. Because that is something that's not priced in the market. And it's purely an observation, it doesn't require any quantification at that point. So with markets, it's like things trend. That's an edge. And now how you quantify that? Well, now it's all moving averages and Kalman filters and trend lines. There's a lot of things you can do, but they aren't the edge. They're a way of quantifying it. And frankly, if you identify the edge properly, it doesn't really matter what you do after that. You can do stupid things or slightly better things or really good things, but you still find people who argue about should you be a trend follower or should you be mean reverting. It's like two children arguing about whether kung fu is better than karate. You're completely missing the point. If the thing is trending, you should be a trend follower. So that's where the edge is, it's identifying that phenomenon. Um, and a lot of. There really aren't that many things in the world. There's time series momentum, there are spreads which mean revert, there's cross sectional momentum, there's carry, um, and then there's risk premier. And that's sort of it. And everything else kind of goes in those buckets. And once you've learned it in one area, you can always port it to another one. You don't have to reinvent the wheel. Like there really Aren't that many wheels, you know, And a lot of when you came into crypto, you came from tradfi, right. And a lot of the things that worked in crypto, um, was straight out of TradFi, probably 15 years earlier, right. Like that on chain exchange, arbitrage. That was the same stuff people were doing when the Bund was half electronic and half on the life exchange. So I think that's what engine is. It's the identification of a phenomenon and then you quantify. So I think a lot of quants kind of start throwing mathematics at the problem first without thinking about what's actually happening here. Like in the real world, forget about your model.

Speaker B: Yeah, I love the real, uh, world perspective. So when we talk about risk premia, you view that as like a persistent phenomenon. It's not going to disappear. And to me, that makes a lot of sense, um, when I try to relate that back to the 3D world. So risk premia. So if I look at the human existence, let me know what you think about this. So if I think about human existence, well, the life experience is inherently dangerous. So I think people will overpay for safety. And that might be in forms of, you know, taking a salary job instead of entrepreneurship, or, uh, maybe being polite instead of having a hard conversation or anything where you can take, um, the safe route. And I think when we think about risk premia, you've made the point that convexity, you would always pay a premium for convexity, because if convexity is fairly priced, who would ever sell convexity?

Speaker A: Right.

Speaker B: Is that how you view the persistence of that from Nanma?

Speaker A: Yeah. And I think looking back to sort of that evolutionary idea is a really good thing. I mean, that's where we came from. We're very heavily incentivized to hedge away risks, and we're very heavily incentivized in situations of uncertainty to take the safer way. Right. It's like if you see a shadow in the grass and it might be a tiger, you run away. You don't think, well, my expected value says it won't be a tiger. So I'll stand here, uh, you know, picking oranges or whatever you were doing before you saw a tiger. So the downside is so much greater and you only get one go at it. So we are definitely built to minimize risks like that. Um, in general, there are some risks that we will take. Like, you know, the disposition effect. Right. It's like we take profits too quickly and we let losses run. You can see this in an evolutionary perspective as well. It's, um, if you're a hunter, gatherer and you kill an animal, right. You are not going to say, oh, you know what, I'm gonna just have a little bit of this animal, I'm gonna store the rest because it's gonna go off in two days. You eat the whole damn thing, Right. So you're taking that profit. On the other hand, if you go hunting and you don't find anything, you keep going and you keep going and you keep going because your downside. Yeah, you can't stop your downside. You have to be able to find something to eat. So a lot of these things do, uh, come back to evolutionary psychology and risk. I mean, there's a reason that utility theory all starts with these basically the same shaped utilities. Right. Humans want to maximize wealth for a given level of risk. We don't just want to maximize wealth. Right. No one's risk neutral.

Speaker B: Yeah. Interesting. Yeah. And markets are truly a human phenomena, so it makes sense that a lot of those things exist there. Um, so there's a couple things from the edge section that I thought were interesting. One, I would call it in the traps in our thinking. One is one point you mentioned was that being smart is not edge. Being smart might help you find edge, but it's not edge in of itself. Um, and often I've noticed in the markets, like arrogance can be expensive. Um, what's your thought there around being identified with being smart as a source of edge or kind of some context around that point?

Speaker A: Yeah, well, I'm certainly not going to say the wrong way of taking this is to say, oh, it's a disadvantage to be smart. I mean, it clearly is not a disadvantage to be smart. Smart is a good thing. Having more of a good thing is better. But being smart certainly does correlate with other things. And the problem in the markets is if you're smart, you've probably gone through all of your life not making mistakes, figuring stuff out, and you think you can figure out the market in the same way. That's a mistake. That's a problem. I find engineers have more than others because they're used to building things, they build systems. And the markets are a complex adaptive thing. If you build a system, you're always going to be playing catch up as the market keeps evolving. Um, so I think that's a trap you can get into because you're smart. And I think realistically, once you've reached a certain level of intelligence, the marginal payoff for being smarter above that probably isn't all that Great. But it's certainly being smart's a good thing as long as you realize that's a starting point and you don't just say, well, I'm going to be smarter than everyone else in the world. I mean, think of the arrogance it takes to say that, right? Um, anyone with a smartphone and a bank account now can be trading, right? So you've got billions of people, their collective opinion on the value of Tesla. You really think you're going to outguess that for the next five minutes? It doesn't really matter how smart you are. Uh, so I think smartness can definitely go with arrogance and it can definitely be a. It's the arrogance that's the problem. It's not the. If you, if you're self aware, that covers a lot of these problems.

Speaker B: I love that, um, something else you said which I thought was interesting is, you know, paraphrasing m here, but edge is ugly. Edge is messy. What does that mean exactly? I say that

Speaker A: that could be, uh, There's a guy I've done work with, um, from Twitter, probably know him as Robot James and Robot Chris, his, uh, partner. They're always saying edge is a messy thing. In that it goes back to that idea of edge is a phenomenon, the market's trend. That's the thing. You know that one little tiny thing, markets trend, all the other stuff you lay on top of that, you're quantifying and smoothing and trying to adapt something that is a really tiny little piece of information. And you've got to be honest all the time with how little, you know, you know one tiny little thing about the world and everything else in the world is against you. So that's what I say by Messi. It's the signal to noise is very, very low. And you've got to kind of accept that you can't make that go away. You can't get knowledge where there is no knowledge to be got. Um, and I think a lot of people think that they can sort of out mathematize that noise. And there's nothing. You can't do that because you can't add knowledge to the world. So I think that's what I meant probably. And then you've got to accept that any edge you find is going to be small. And I think the way to do it, generally speaking, and this is very general because it depends on what kind of trading operation you're in, et cetera, you're better off finding five or six things that, uh, all work. Okay? So they've got A sharp ratio of 0.8. They work a bit and that's all bad. Warren Buffett's Sharpe ratio was about 0.8. That's fine, but it won't make you a billionaire. So you have five or six of those, you put those together and suddenly your Sharpe ratio is up to one and a half or two. And that's the start of if you're just doing this part time retail. There's nothing wrong with that. There are plenty of hedge funds that take a Sharpe ratio of two. Uh, and I think people spend too much time trying to really make a small edge perfect rather than just saying, you know, most of the way there. I'll get something else.

Speaker B: Yeah, it's really interesting. Yeah. One of the things you had kind of mentioned, um, one of the demons was a demon of essentially overfitting and complexity. Um, that kind of plays in nicely into that kind um, of jumping to the implementation or the execution side. So if I relate this back again to the 3D world, um, you know, there's a lot of edge in eating healthy versus eating unhealthy and there's almost no cost to it, but it's very hard to implement. It's not, you know, if it was easy then it wouldn't be an issue. Um, when I think about executing edge or implementating edge, um, you know, one of the traps we just mentioned, complexity. Um, you know, where does hedging come in to this? Is hedging a uh, valuable proposition? Does it just add transaction costs? How do you view, like the implementation of a strategy to capture edge?

Speaker A: Um, okay, so there are three different kinds of hedging, I think, and they sometimes get conflated and put into one bucket. And they're not. The first thing to do is to identify this is my edge and then try and hedge all the other aspects of the world that aren't that. Um, it's like isolate your edge and you do that by hedging away everything else. So in an options world, that's my edge is volatility. I'm going to hedge my directional risk. I'm m going to hedge my interest rate risk. I'm going to hedge my dividend risk. Now in reality you can't hedge your interest rate risk or your dividend risk in most cases. Certainly small traders can't. You can kind of keep yourself down to neutral. So that's the sort of hedging where you want to reduce exposure to things you don't have any edge in. Because the ultimate expression of risk is everything that isn't an edge, which is sort of why trading's hard. There's one thing in the world that's your edge and there's everything else can go wrong. So removing as many of those things makes sense. That's a good kind of hedge. The bad kind of hedge is when someone says, well, I've looked at my strategy, it's got positive expectation, but it's really negatively skewed. I don't like that. So I'm going to put a stop in. So the worst I can lose is, you know, I've got an average win on this trade at 1%. I'll put a stop in. So worst I can lose is 1% and then I've got all this fat tail on the upside, I'm going to be great. The problem is as soon as you've done that, you've changed the distribution. You haven't just chopped a bit off, you've changed it. Right. You're going to get stopped out on a lot of trades that would have turned into winners.

Speaker B: Right.

Speaker A: And that's the wrong kind of hedge because you've taken something that works and you've decided you don't like what the market's giving you. You want to somehow, by mathematics, change that distribution into something you can live with. And at a certain level that's fine. But those kind of hedges can't be, oh, I, uh, don't like losing more than 1%. Those kind of hedges should be like, I can't afford to lose more than 20%. They should be catastrophe hedges. Not like, oh, I've had a bad day, but I've just lost my house. M so I think most people try to cap their losses way too tight because they're trying to make the trade into something they like and the market doesn't care whether you like it or not. You know, it's like people like, I don't want to sell volatility, so I'm going to do this or this or this. You can do whatever you like after that. But you'll make money selling volatility. It doesn't mean you have to do it. Mhm. But that's what the options world is going to come back to. You can't consistently be long volume and make money. You can be long volume sometimes and make money and you don't have to be uncapped short. But just because you don't like something isn't a reason for doing the opposite. The market doesn't care what you like. And so I think that's the sort of hedging, hedging for comfort is not. You're getting paid to do something uncomfortable. It's like any other business. You get paid to do something that's a valuable service that other people don't want to do for some reason. Right. So you're a plumber. Uh, you're selling insurance. Selling insurance is bad, right, because you make all these little wins and then you lose a ton of money when there's a flood. But it's a valuable service. People will pay you for that. Service trading's just the same. It doesn't always look like that. But for you to make money, you have to be giving the world something it wants. So like market making, right? You're providing liquidity. Buying dips, you're providing liquidity when other people aren't providing liquidity. Selling options, you're giving the world insurance. Most things that pay well kind of come back to you giving the world a service.

Speaker B: That's interesting because, uh, when I think of Warren Buffett, he says, when everyone's fearful, I get greedy. The idea that that's essentially buying the dip. Buying the dip is essentially the realized version of the short volume trade. You're stepping in with your money when everyone else.

Speaker A: Yep.

Speaker B: Needs the liquidity. And that's a huge source of alpha. That's really interesting. Um, that brings us to risk management. So there's, um, a couple things here in the risk management side that I thought was pretty interesting. So you already mentioned that using a stop changes the shape of the distribution and it's not edge in itself. Um, but there's, you know, you've talked a lot in your past books about Kelly Criterion. Um, maybe, you know, um, maybe that plays into sort of using the stop or not using a stop. Uh, but in the theta pics papers, it seemed like using something simple was the, the right result. So even if it's just like 1%, uh, risk on trade is like a great place to start. I know for my own personal trading, just having a fixed amount of money in the account and pulling the money out, that's my hard, hard stop. Um, kind of. What are your thoughts on overfitting, uh, risk management or too many criteria or how do you view the best way to do that?

Speaker A: Yeah, I think the first thing to do is realize that when you're trading, sometimes it's um, okay to take a shot. You know, you've got a hunch, you buy some teeny puts, you know, it's a hunch. There's no real analysis behind it. But the worst you get, you're not going to lose too much and it keeps you interested and it's fine. Right? And that's sort of why we all started doing this. You can't do that with risk management. You never take a shot with risk management. And I think the thing that most people, when they're starting at least get wrong is they don't have a process that they've set up in advance by coming up with these rules on the fly. They think they're all okay and then suddenly they've lost 10% one day and they're like, uh, ah, what do I do? You should do what you've written down that you were going to do previously. You should have that planned. You shouldn't have to make complicated decisions when you're nervous. You're not going to be thinking clearly and it's impossible to put yourself in that situation in advance. Um, it's very tempting to think, no, I'll be steely eyed and calm and collected and I'll. You won't. You'll be like everyone else and you'll be like, uh, ah, but you can put yourself in advance into a plan. If the market is down 10%, this is exactly what I'll do. And then you stick with that. Having a process like that, like I'm always going to rebalance, so I've got 10% of my money in this strategy always. So whether it makes money, loses money, whether, uh, it's going really well, whether it's going really bad, that's your rule. If you just stick to that rule, you're always going to, you're going to be miles ahead of the game at that point. And I think that's the biggest mistake people can make is, you know, there have been plenty of studies that show that equally weighted portfolios do about as well as any optimized portfolio can come up with. So there are lots of reasons for that. And you can go into the mathematics of it and show that it only works in certain circumstances and blah, blah, blah, blah, blah. But the important thing is if that's all you do, you're a long way ahead of the game. So that's the sort of simple robust thing that. Is it optimal? No, but it's robust. And usually robust is better than optimal because optimal is only ever optimal according to one criterion. Right. Whereas robust kind of means you should be okay pretty much all the time.

Speaker B: Interesting. It's like over optimizing is the trap basically in the risk management.

Speaker A: Well, as soon as you've Said over something, right? That qualified fire means it's a bad thing already. But generally that is a big problem all the time, right? Like overfitting, um, over optimization, looking at specific cases. Um, you want to keep, especially risk management, keep it at a fairly high level, like very simple rules. Um, like honestly, the way I do a lot of Kelly stuff and I've got to differentiate the stuff that I do at work and the stuff I do for my personal trading, right. As well. But I do it works a lot more complicated, right? Because I've got a lot more resources and you are haggling over every little basis point. But for your pa, that's not the thing because you don't have the same constraints, you don't have the same goals. Um, so usually what I do for my portfolio rule is I look at everything I say are these, are, uh, any of these trades basically the same thing, right? So if I'm short volume spurs, I'm short volume on the queues. I'm going to treat that as one thing, right? You're not going to say, I'm going to give 20% here, 20% here. You're going to be like, no, that's my short volume bucket. But if I'm short VIX futures, I'm going to say that's a bit of a different thing. And then I'm basically going to do a vibes portfolio and I'm m going to say, what am I actually happy with here? I'll put 20% into this, 20% to this, 15% to this, and 40% into bonds. Do I feel okay with that? And then you sort of run through the scenarios in your head and if you just do that, you're going to be miles ahead of the game. And if you want to get a bit more complicated, look at the volatility of each of these things, maybe do an equal volatility weighting bucket. But I don't think you should be messing around with covariance matrices. You're just going to be fitting to past special cases. So unless you're going to do a lot of work, I'd keep it really simple.

Speaker B: Yeah.

Speaker A: Cool.

Speaker B: I love the uh, vibes approach. I mean, I'm always taking inventory of my positions, always thinking through scenarios, rebalancing.

Speaker A: What's the worst thing that can happen, right? Is you're like, I thought I liked this position and now I can't sleep. It's too, it's too big. I mean, there's no one that made you do that. So you've Got to actually look in advance again. Look in advance because when you're in the crap, you're not going to be able to make good decisions. You have to. That's why planning is so important, because it forces you to think in advance about things that will happen at a point where you're not going to be thinking clearly.

Speaker B: Yeah, it's a great point, especially if you have a position and, uh, you kind of get jammed with it. Oh, now you really don't think clearly. That's.

Speaker A: Yeah, because now you're thinking, if I get out, I'm going to regret it if it comes back. But if I don't get out, I'm going to lose all my money. And it's, uh, you're not special. Everyone is going to fall into that trap. Actually, that's an advantage pros have, is that they'll have a risk manager who's making those decisions for them. And that's why we separate risk management from trading is because hopefully the risk manager isn't emotionally involved in all those decisions. And for them it is just a game of like, nope, too big. Cut it. So much easier. Other people's positions are so easy to manage.

Speaker B: Yeah, it's very interesting. Um, this brings us to kind of the last section and we'll jump to some market things and we'll wrap up with some fun this or that questions. But on the psychology side, so you had some examples of, like, some good trading journals with reflection on them. Um, you had this nice thing, my mood before. Then I write my reflections and my mood after. I thought I was really nice. Um, just kind of in the 3D world. Uh, I used to. This is kind of embarrassing. I used to be so afraid of flying. Flying was terrifying. Logically, I know that's the safest place ever to be, but emotionally, very gripping. Um, when something happens in trading, you show some examples, like some reframing, some exposure. Um, maybe you could walk us through an example of that. What would be, uh, a training journal, like an event that happens. A trading journal. Would you reflect that? How do you reframe that? How do you, um, see the automatic reaction into, um, a more appropriate reaction?

Speaker A: Okay, so I've always kind of made fun of the whole trading psychology world. And I think that's still. I still think that's basically the right thing to do. Because there are people who will tell you, oh, psychology is the most important thing there is. Right. If you've got your psychology right, you'll be fine. That is almost inutterably dumb because if you really think that's the case? Take your Zen psychology down to the casino and play roulette. Unless you've got an edge in solid risk management, having the greatest psychological balance in the world isn't going to help you at all. But having said that, having a bad set of trading psychology and you're always nervous and scared and no confidence, overconfidence, lurching around from one to the other, that can definitely mess you up. Um, you see that in sports, right? Um, no one is ever going to play for the All Blacks because they really, really want to do it more than everyone else. If you're too slow, that's it. You're. It doesn't matter how much you want it. On the other hand, we've all known people who are really talented who just didn't care. So that's an example of where the bad psychology is messing them up. So I've sort of come around to the idea that it is important. The next thing I hate about the general sort of approach to it is that people will tell you it's very important and then not give you anything that's actually going to help. Because knowing that overconfidence is bad isn't going to stop you from being overconfident. That's just like someone, oh, um, I'm your athletics coach. It's like, coach, how do I do better? And I say, you should run faster. I mean, yeah, it's true, but that's not going to help you run faster, right? So knowing you're making these psychological errors and someone saying that, you know, you should really just knuckle down and get through it, it's not going to help you. So I was trying to sort of figure out some practical advice that I could give someone. And I think this is sort of where I've come to in my technical approach to the markets as well, is I'm trying to take academic research and distill the simple trading bit from it. And I think when I started maybe 20 years ago, I would look through the math and I would stay at the math level. And I was reading back through my options trading book the other day for some reason, and I'm going into optimal hedging and I'm talking about Hamilton, Jacoby, Bellman equations, and I'm like, why was I going into this? I mean, I don't think I was doing it to show off. I think I really thought that was vital knowledge, but it's really not. It's not the important bit again, it's the Map. It's not the territory. So I think this is what I'm doing with psychology now as well. I'm trying to take things that actually work and put them in a form where the trader can use them. I'm trying to sort of be a trading coach if you want. Um, and again, I'm not doing this out of the goodness of my heart because as you know, I'm heartless. I'm not doing this to help anyone else. I'm doing this really because it's a learning process that I've gone through and I just, I like writing stuff down. Um, part of it's just arrogance, right? You expect the world to pay attention to what you're saying. So thanks for everyone watching. Um, so anyway, I was trying to come up with a set of rules in the psychology world that would help. Traders often do this, right, where we're like, our situation is just so different. The rest of the world can't possibly understand, but it's not. There have been psychologists who've been trying to help people get through addictions and depression. They're the big two where this really helps. And the old fashioned sort of psychoanalysis involving lying on a couch talking about how your parents were mean to you, that never really helped anyone. Seems like it should. But it's got a terrible hit rate, right? I mean, people will literally go to those psychoanalysis class sessions for the rest of their lives, which isn't really an indication that anything's happening. But there is a thing called cognitive behavioral therapy which is not a way of curing the underlying problem. Like if you're addicted to cigarettes, you're still going to have that addiction in you, but it will give you a set of tools for basically managing that problem. So it's been shown to be very effective for addictions, uh, anxiety and depression, as in you're still going to be depressed, but this will stop you killing yourself. So that's a step forward and you can get on with your life. And it's a, uh, a way of dealing with the problem. And that's exactly what we've got as traders. You don't want like a way of getting rid of these emotions. That's not going to happen. You can't muscle your way through it, but you can. One very useful trick is to take it outside yourself. Like write something down. Like when you're like trader's block, right? You're like, uh, I can't do a trade because I'm stupid and I'm never going to get a good Trade again and I'm always going to be losers. That sounds really bad, but if you write it down on a bit of paper, I'm never going to make a good trade again. Suddenly it just sounds like kind of pathetic and whiny and stupid, and you're just like, come on. I'm just completely overreacting. So getting it outside yourself is a really useful technique. Talking to someone else. Useful, uh, technique, frankly, if you can't talk to someone else, invent a imaginary friend. It helps. And you know what? It sounds dumb. Do you care about sounding dumb? Would you really want to make some money? Because it does help. So I would recommend if anyone really wants to work on these problems, and I don't see why everyone wouldn't. The books you should be looking for are cognitive behavioral therapy books, but not about training psychology. You want an actual psychologist who's done the stuff. Actually, Brent Steenbacher. He's about the only person I've ever seen who's written anything sensible on this. And his day job is as a psychologist, like a counselor. And that's what you want. You don't want someone who studied this. You want someone who is a cognitive coach. Um, so I just thought that was very interesting stuff.

Speaker B: Yeah, that's a great framework. I like that a lot. Um, yeah, venting. Venting is so important. I view that, uh, as quite a great tool. Even on the positive side, like throwing spaghetti against the wall in terms of ideas and getting someone's feedback, it's great. Um, that's also a great reason to have a training desk. Uh, if you're on the desk, you can share ideas.

Speaker A: Having a good partner is really helpful. Um, few people are lucky enough to have that, really, because there aren't that many good traders. So the chances of you sitting beside one, it's pretty slim. But you can learn together. That helps. Um, just talking through things, I mean, that's like anything, right? If you, you know, I don't know, depressed because your dog died, talking to your friend, it makes you feel better. Yeah, of course, I'm told I haven't got any friends and my dog hasn't died. Um, so, yeah, that, that sort of treating trading not as a special case that, you know, no one understands our angst. It's just, dude, it's just another aspect of life. Do what you would do with anything else. You know, talk to people, get out of your head, go for a run. You know, this idea that you should be so immersed in the markets that you think about it all the time. That's just really stupid. You know, take the dog for a walk, unless he's died, in which case you go to the pub and talked about it with your friend.

Speaker B: Cool. So kind of just jumping into some, ah, market, some market aspects, um, and then we'll wrap up with some um, some fun questions. So, you know, we just had the, we just had uh, ibit, which is for anyone who's new to crypto, is basically the spot bitcoin etf, um, that ended up being sort of the biggest venue for bitcoin options over the past 12 months. And it's just surpassed derebit. It's neck and neck, but it's basically surpassed it. Um, you know, does something like IBIT, in your opinion, change the nature of the market? Um, these types of new, uh, investment vehicles and the fact that all the optionality is found on top of the spot etf as opposed to onshore offshore exchanges.

Speaker A: Yeah, it has to. Right. Um, like you definitely see in Tradfi, if a product is listed on a different country's exchange, that changes the nature of that product because you get a different group of people trading it. You get different calendar and feedback effect. It definitely changes things. I think the IBIT bitcoin thing is kind of similar because I kind of think of crypto as existing in its own world. It's a separate thing from tradfi. Right. It's got its own traders who do things for their own reasons and it is a different thing. So definitely think having IBIT definitely pulls that closer to the tradfi world in a way that the CME futures just didn't. Um, I don't really know why, but it seems like the CME futures really had no effect on the way that whole thing hung together. But now it's in a nice ETF package. I mean people love ETFs. They don't expire on you. You can just buy them and hold them, go away, forget about them.

Speaker B: Yeah, it's very interesting, uh, in sort of that same vein, this is maybe a little bit more inside baseball, but if I think about spx now that there's such a concentration in sort of tech stocks and Nvidia such a big part of the market cap, um, does that change, does that sort of concentration risk change the nature of sort of the downside tail of vix, um, because I would imagine there's less diversification effects if we get sort of a real downward moment. Um, do you think about that? Like the, the composition of the S&P 500 and the passive investors and spy and stuff like that. Change it from 20 years ago.

Speaker A: Yeah, it definitely has. We're seeing. This is the highest concentration I've ever seen of the heavy concentration in the Mag 7 for example. And I can't think of the actual numbers, but I think it's the highest it's ever been. And it definitely changes things in a way you're saying it's like we are now much more vulnerable to those big stocks. We're nowhere near as diversified as we used to be. And furthermore those big stocks now, if you go back 30 years and look at the biggest stocks in the S and P, it's going to be things like Lockheed Martin and Honeywell and J.P. morgan, General Electric, but um, low volume stocks. Whereas now we've got, it's almost like the NASDAQ stocks. The big crazy high volume stocks are the ones. You know, the floor on VIX now is very different. So people will sometimes be like, I don't understand, the market keeps going down. VIX won't drop below 15. 15 is kind of the new 12 because of those heavy concentration and high volume stocks. Uh, and furthermore the VIX isn't going to come down a lot when short dated at the money options are carrying so well. I mean they're already kind of cheap in terms of the realized volume. Um, so yeah, we do think about that. And I think it goes back to something I said in the theta pig letters as well. When people will back test something over 40 years and they go, this thing's worked for 40 years. But the exact, the market now is not the same. Uh, it's always changing and this is a very obvious change. But people think you can just throw more and more data at a problem, but you're not because you're throwing irrelevant data at the problem. Like you can't look back in like 1970s and compare that to today. You can't even look back in the mid-90s, back when all the stocks were trading in eighths, right? And it's got some, some guy in the New York Stock Exchange. Whereas now it's all, you know, sunk pennies and dark pools and the world's just changed. And I think that's one problem people have with back testing. They, they forget that they are ah, literally testing against a totally different thing. Like the s&p 20 years ago is not the same product as it is now.

Speaker B: Yeah, that's very interesting. Kind um, of last market related question here. Uh, you know we had April of this year, kind of a very volatile event. Then, uh, we had August of last year during a BOJ hike of interest, uh, rates. Uh. Oh, yeah. August 2024. That was kind of a, a big, I think, Vix 60 moment.

Speaker A: Yeah.

Speaker B: How do you trade those moments or how do, how do those, um, impact you, especially if you're kind of leaning short ball? Is, are those special times? Are they just normal times?

Speaker A: Uh, so there's two things, right? There's what you have on before that happens, and the way you trade that is according to the plan that you've got in advance. So you don't have to make any special decisions in that period. So that depends a lot on literally what you had on. If you were long volume, you're happy. If you're short volume, you're sad. But the great thing about volatile periods is that they cause dislocations and relationships that are normally very solid get put out of whack. And this is why the best trading always happens at high volume periods, because things are happening going back to what something means as opposed to the numbers. Volatility is not standard deviation of returns. That's a manifestation of volatility. Volatility is uncertainty. And so when the market becomes very uncertain, a lot of people are doing different things and things like the VIX versus the NASDAQ vix, um, like last August, Right. The VIX went significantly above the NASDAQ vix. Interesting, right? Exactly. You've been around long enough to know that that doesn't happen situation. And so when you look at the stats, um, you had at least a day, two days to figure this out, to notice it. Like, people were emailing me. Uh, it was not a blink and you'll miss it situation. You look at the stats, that happens like 3% of the time. So that's a great situation. You can just say, well, I don't really want to put a volume trade on here, but I can go short the vix, I can go long NASDAQ vix and that spread's going to come back into line. Um, so that sort of thing, um, you'll get dislocations that happen at high volume. So the worst thing that can happen to you isn't that you lose money going in, it's that you lose so much money you can't trade.

Speaker B: Right.

Speaker A: Um, because your advantage is finding things with edge. And if you're seeing things with edge and you can't trade them, that's. That's the worst thing that can happen to a trader.

Speaker B: Yeah. You missed the whole boat.

Speaker A: Yep.

Speaker B: That once in A every five years opportunity is basically right and you shouldn't lose so much.

Speaker A: You can't trade because that's part of your plan leading up to it. And no one's going to know. You're not always going to be positioned on the right side for that stuff. In fact, usually you won't be. So you have to have that planned in advance. And then you can start looking around. You don't have to look at individual things. You don't have to be like, when am I going to sell the vix? Because that's a really hard thing to pick that top. But you can be like, well, I don't know if the VIX is overpriced, but I know it's overpriced relative to the nasdaq. So why don't we do a Q's straddle against the spy.

Speaker B: Love it.

Speaker A: Cool.

Speaker B: Okay, so last set of questions here. These are kind of rapid fires, just for fun.

Speaker A: Okay.

Speaker B: Okay. So I'm going to ask this or that questions, and you basically pick out one or the other. And there's not too much context. So hard skill or soft skill?

Speaker A: Going to go with hard skill. If you've got hard skill, you can always soften them. I don't think you can go the other way around.

Speaker B: Cool. Asia or Europe?

Speaker A: I once got into trouble with the Bear Stearns HR department because I was typing in a question Google about options, and I literally typed in, are Americans worth more than Asians? And, uh, that raised a pretty big flag. So having said that, uh, I gotta go with Europe. Some of my favorite cities are in Europe. I really like Paris.

Speaker B: Okay. Oh, yeah, I like Paris, too. Um, Tony Stewart or Ewan Sinclair?

Speaker A: Uh, Tony's a great guy and he already hates the amount of publicity you gave him by saying that. Um, whereas obviously I'm an attention whore. Um, Tony's one of the best traders I've ever met. I'm naturally nowhere near as good as Tony.

Speaker B: Okay, Tony Stewart it is. Uh, writing or mathing?

Speaker A: Uh, I do both. Like, I literally will sometimes spend Saturday night messing around with probability problems. I mean, I'm still trying to solve this Kelly Criterion problem that I've been working on for 10 years. Um, the writing stuff I'm doing now is so much easier than that that it doesn't require anything like the same concentration.

Speaker B: Okay. Uh, being early or being late?

Speaker A: No, you gotta be early. That's a, that's a given. Um, being late is. It's incredibly rude. Right? It's like you're basically Saying that you're. You're more important than someone else. And it's always better to arrive slightly early and, you know, have your shit together than arrive late and be flustered.

Speaker B: Optimist or pessimist.

Speaker A: Uh, I would love to be one of these people who's optimistic, but I'm just not. Um, so I wouldn't even say I'm pessimistic. That's. It's not glass half broken, half full. It's plus have broken. You cut your hand, everything's going wrong. So I've got to go with pessimism on that one.

Speaker B: Interesting, because I kind of tend to think that short volume is naturally optimist and long volume is naturally pessimist.

Speaker A: You know, I think optimism is one of the worst things you can have as a trader, because if you think things are going to get better, that is sort of just a recipe for complacency. Um, whereas I think pessimism is more of a drive to make you work.

Speaker B: Tea or coffee?

Speaker A: I hate tea.

Speaker B: We won't tell that to Tony. Um, reading people or reading markets?

Speaker A: I don't think I'm any good at reading people at all. Um, like, really bad. Uh, like, I can offend people. Like, I've offended you. Like, to the point where you called me and asked if everything was okay, and I didn't even know I'd done anything bad. So I'm terrible at that. But I don't think I'm any good at reading markets either. I don't really know if that's a skill that actually exists. I think it's a skill that a lot of people hope exists. Um, so when it comes to the actual markets, I'm pretty much more on the numbers side.

Speaker B: Cool. Well, thank you so much, everyone. This is the Amber Data Derivatives podcast with Ewan Sinclair. We'll catch you next time.