Today I chat with Euan Sinclair, Partner at Talton Capital Management and author of the books Options Trading, Volatility Trading, and the up-coming Positional Option Trading.
We begin our discussion with Euan’s experience as a market maker as I try to get a better understanding of what a market making operation really looks like from the inside and how it has changed over the last 15 years. Of particular interest to me, given how much market makers have been villianized in recent years, were Euan’s comments on misconceptions about market makers.
We then turn to the buy side, where Euan has spent recent years and is largely the subject of his new book. We discuss common mistakes, sources of edge, thinking about directional versus volatility bets, and the seemingly overwhelming degrees of freedom that options trading offers.
I know I walked away from our conversation with both an increased appreciation of the nuance in these topics, but also several new ideas for both edge and risk management.
Please enjoy my conversation with Euan Sinclair.
Corey Hoffstein 00:00
321 Let’s do it. Hello and welcome everyone. I’m Corey Hoffstein. And this is flirting with models the podcast that pulls back the curtain to discover the human factor behind the quantitative strategy.
Corey how Hoffstein is the co founder and chief investment officer of new found research due to industry regulations, he will not discuss any of new found researches funds on this podcast all opinions expressed by podcast participants are solely their own opinion and do not reflect the opinion of new found research. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of newfound research may maintain positions and securities discussed in this podcast for more information is it think newfound.com.
Corey Hoffstein 00:50
Today I chat with you and Sinclair partner at Talton, Capital Management and author of the books option trading, volatility trading, and the upcoming positional option trading. We begin our discussion with UN’s experience as a market maker as I tried to get a better understanding of what a market making operation really looks like from the inside, and how it has changed over the last 15 years. Of particular interest to me, given how much market makers have been villainized in recent years. We’re Yuans comments on misconceptions about market makers. We then turn to the buy side, where Yoon has spent recent years and is largely the subject of his new book, we discuss common mistakes, sources of edge, thinking about directional versus volatility bets, and the seemingly overwhelming degrees of freedom that options trading offers. I know I walked away from our conversation with both an increased appreciation of the nuance in these topics, but also several new ideas for both edge and risk management. Please enjoy my conversation with you and Sinclair. You and thank you for joining me today really excited to have you on the podcast.
Euan Sinclair 02:04
Yeah, thanks for asking. I imagine you are pretty excited. I’m pretty awesome to talk to.
Corey Hoffstein 02:09
Well, beyond that, beyond the wealth of information you have I guess what’s super exciting for me is I did have been I’ve heard from Q VR on earlier this season and last season. And I think there’s more and more people who are listening to the podcast who are really excited about the world of options. And I think you’re gonna provide a very different and complementary perspective than what Ben has provided. So I’m really excited to get your thoughts for the guests who maybe haven’t heard of you before, would you mind starting off with a little bit of your background?
Euan Sinclair 02:39
Yeah, I was born in New Zealand. I did my undergrad in physics there. Then I went to England, and I did a PhD in physics, theoretical physics, actually chaos theory. And at the end of that I was looking for a job. And I’d always thought I was going to be a physics professor. But then I kind of got a better idea of what they did on a day to day basis. And didn’t want to do that. If I been really good. That’s a different story. But in academia, you’re either a superstar or you are nothing. So I was looking around for a job. And this was 1995. And it was soon after Nick Leeson blew up bearings Bank, which was possibly one of the first sort of modern derivatives disasters. So it was getting a lot of press in England. And trading in general in England is nowhere near as sort of mainstream as it is in the USA. And I don’t know why that is, because there’s a lot of gambling that goes on in England. I think it’s mainly due to the structure of the markets. There were huge transaction costs, big taxes. But anyway, no one that wasn’t really Korea path anyone ever thought of, until this when I started reading stories about him and like New Scientist and things when they were talking about rocket science and how people were hiring physicists and engineers. And I mean, this was in the days before your master’s in financial engineering existed, if you wanted to learn Black Scholes, you got a book and learned it yourself. There was no one teaching us stuff. So I kind of just fell into it. And I was lucky that I was hired by a small firm of market makers. And I think being a small firm was great, because you get to do a lot of things. And you kind of are fairly self directed. And being in a market making firm, I think was great because you end up it’s like you do a lot of trades. So it’s like your learning process. You can get a lot of feedback. Whereas if you’re in a bank, OTC desk, you might only do one or two trades a week. So I think you just get a very concentrated learning experience. And I knew nothing. I mean, I could have ended up on a sales desk. I could have ended up being a structure or a quant or a coder. I had no clue. So I just think I was very lucky in that first job. I’d love to dive in there on the market. Thinking side of the equation, I think for a lot of us who operate in markets, market making is still somewhat of an opaque mysterious part of what happens. It’s certainly electronic market making and high frequency trading has grown significantly over time. And it’s gotten a lot of headline press. But I think there’s very little transparency for most of us as to how market making has really changed in the last 20 years. And as someone who spent considerable time on the market making side, I’d love your thoughts on that. Yeah, it’s almost not the same job, that’s almost unrecognizable, obviously. And I just want to start here, I make fun of market makers a lot, my call them, see how stupid they are, and how lazy they are, and all this kind of stuff. But it’s not flow trading, you don’t have any captive flow, it’s a very, very difficult trading strategy, you are completely at the mercy of the order flow, and you have massive amounts of adverse selection. I mean, you have to make a market on everything. If you make a perfect market, the customer will be like, Oh, that’s a great market, I’m not going to do anything. So you get every mistake you get traded on. So it’s a very, very difficult, very low margin business. So when I started, it was sort of still at the end of the life floor. And there were still open outcry floors all around the world. And the skill involved then was largely about being fast. I mean, if you could make a market in a four way strategy, like give me this calendar spread with two of these coals and you can do it instantaneously. You’re the first one, the broker he is when the customer trades, he’ll trade with you, and then split up the rest amongst everyone else. So the core skill was being really fast for arithmetic, because that was execution. And execution is still a very important part of market making trading, we see it now everyone knows our high frequency trading, you need really fast machines and fast lines and co located servers and so forth. Back in the old days, it was just the ability to add up numbers quickly and then scream loudest. And it’s a real thing. That was an important skill. And I wouldn’t in any way minimize that by saying that’s not real trading or anything it absolutely is. The other great thing about market making learning how to trade is when a market maker makes a trade, at least in theory, they get half of the bid ask spread their theoretical values 10, they make the market nine bit 11, like by nines. That’s in theory, a one tick profit. The hard thing is keeping any of that money. Because you get this adverse selection. A lot of the people you’re trading with have either flow that they’re going to use to drive the market one way or real information. There’s a market making, you can’t do anywhere near the sort of analysis that positional trader can do as a position trader, you might sit down and analyze volatility for three or four hours and then do one trade. I mean, as a market maker, you’ve done 500 trades in that time, you can’t even remember what the first ones were. So keeping the money is really difficult. So market makers become very good risk managers, because most of the position skill they have is risk management. It’s identifying where their positions can go wrong and finding the cheapest ways to hedge that. It’s entirely about managing the risk of the business rather than risk of the position.
Corey Hoffstein 08:29
Have those risks changed over time, I’m thinking as you’re talking about going from open outcry, maybe someone who’s trading is trading on a couple of names to more electronic market making where you might be trading hundreds of names very, very quickly. It’s a different style of book and I immediately go to some sort of catastrophe like Knight Capital Group losing 400 plus million in 15 minutes, I imagine that would be potentially harder to do in an open outcry type model. So half the fundamental risks of market making shifted over time.
Euan Sinclair 09:02
Yeah, that’s a good point, the market risks themselves haven’t really, I mean, you’ve still got the risk of the stock going to zero or blasting 300% higher or volatility doing whatever. But the technological risks obviously have increased enormously. You have to be aware, can I keep trading if my internet connection goes down? Whether my technological backups, and in the early days before a lot of these things were completely automated, you would still have problems with brokers doing an execution over the computer. It was literally the brokers about to say I’m gonna throw an order in the strike, and you have to throw the opposite order in 123 Go. So there was that kind of thing. Now, that doesn’t happen today. But you get similar sort of issues, your execution issues are significantly different. Because you know, back in the old days, if you you’re not going to say some 1000 Sell 1000 several 1000 several 1000 of the broker is going to be like, What are you doing? How many martinis did you have at law? Whereas now those sort of electronic runaway algorithms, it’s a problem. And as you’ve seen, it doesn’t happen very often. But when it happens, it can be absolutely catastrophic. And it can be catastrophic for the people on the other side of the trade as well. A lot of these trades will get busted in a trade, you do get busted, and you’ve already done another trade against it, that’s a big problem. So you have to be aware of things like that. And if you get a really good trade that looks offside in the market, you just don’t hedge it. And you have to pull it out of your position and find out what happened two or three hours later, whether the exchange busts or not.
Corey Hoffstein 10:34
It’s what is the actual day to day, have a market making operation really look like from the inside?
Euan Sinclair 10:41
Well, I guess for most forms of trading, the important stuff gets done before the market opens. And I think that’s true with market making as well. The big thing is to check your inventory, your inventory as your clearing firm knows that against the inventory that your systems have or what you think you have. That’s where almost all problems begin. If you think about all the derivatives blow ups, there’s always details about whether it happened because the stock moved or with a volatility moved, or when there’s a problem with the specifications behind a trade. None of these things can hurt you unless you have inventory. So inventory is always your primary risk. You look at Nick Leeson bearings, didn’t know what his positions were. You look at Sumitomo. He was hiding the positions. You look at Kerviel hiding the positions, you look at a lot of the hedge funds and Ponzi schemes that have blown up, the investors didn’t really know what was going on. So inventory is by far your biggest risk. And we were always told that in the morning before the market opens, square up your inventory, your check your p&l, that it was correct. But you can always change that later, you can always find prices that were wrong. But if your inventory is wrong, you’re just trading in the dark. So I think that’s always been the big issue. It used to be you’d go to an out trade meeting at the exchange in the morning, talk to the brokers and try and figure out who did what, maybe check the tapes. But now it’s mainly a matter of checking the logs, making sure that the trades you did with a broker got picked up correctly by the clearing firm, that kind of thing, making sure none of your technology is broken, making sure all your vaults are sort of where you set them the day before. I mean, you may have a system that slightly adjust your volatility overnight. But obviously it was 30, the day before. And it’s to that morning, you’ve got a problem. And you check for corporate actions, like any of the stocks, have earnings, and so forth. Again, a lot of the stuff is tracked electronically, it’s just really a matter of checking it. And making sure even if everything’s operating on an algorithmic basis, you have to be aware of it. Because you have to know that Delta Airlines have earnings this afternoon. This is what I can expect, rather than it’ll be in your system. But if you’re like, why am I selling all these Delta Airlines straddles or whatever, you need to know whether that’s a good thing, or whether it’s a new flow that you just haven’t accounted for. And then there’s a lot of sitting around and complaining.
Corey Hoffstein 13:12
I would say that market making as a whole and especially with the rise of high frequency trading has been somewhat villainized over the last 1015 years and admittedly a bit of a tourist in the volatility space. But I love sort of listening to the chatter, especially on Twitter. And one of the things that comes up all the time, is this idea of market makers pinning for example, what do you think the biggest misconceptions are about market making?
Euan Sinclair 13:36
I think it’s interesting. You said, well, they are not in the game anymore, have been villainized over the last 10 years, because things have actually got considerably better. When there was floor trading, particularly at Well, a couple of exchanges are really bad New York Stock Exchange was terrible. I mean, often the specialists would just sit on your roll out without even filling it even when you know, it’s through the bid or the offer that he’s showing. There were a few pets in life that were absolutely appalling. And some of the tricks they did. I mean, it was just the most grotesque market manipulation, not taking trades when you said you want all this kind of stuff. Now that things are electronic, you just can’t do that. If you’ve got a market out there and someone hits it, you get filled. So I don’t think the market makers are better people. But the way the market structured, definitely better for customers now. And high frequency trading is the same, it gets villainized. But it’s certainly decreased, spreads enormously. I don’t like the idea that they essentially act as market makers when they feel like it. But when the market really needs liquidity, they tend to not be there. But that’s more of a problem about the way the market is set up and regulated. We could always just say if you want to post to a prices, you’re a market maker and you have to do this 80% of the day. I mean, a lot of places have those rules. The way we’ve got the exchanges set up here, particularly in the stock world where there are so many exchanges. I mean, a lot of the exchanges just wouldn’t put a rule like that in place because it would limit their traffic. But yeah, the other really big misconception is the idea that market makers have any control over what’s going on, like they’ll pin a stock and expiration. So all the customers options go out worthless. I mean, again, I’m not saying they wouldn’t do that, if it was possible. But market makers are generally the people who are most at the mercy of order flow. And the way pinning, for example happens, it’s actually just a feedback effect, if you will. Let’s say a market maker is long, a lot of options, he’s long the 100 straddle, he’s gonna get longer and longer gamma as we come close to expiration. So his gamma hedges are coming tighter and tighter. So the moment you drop below 100, he’ll start buying frantically the moment you go above 100, he’ll sell a lot, and that hedging pressure will end up pushing you back to the strike. So the pinning is happening, it’s a real thing. But the one who’s getting hurt by it, and the one who’s causing it as the market maker, I mean, they don’t really have any control over it. And rather, there wasn’t a pinning effect if they were long gamma. But because they are the ones who are most aggressively delta hedging that causing that, and that most aggressively delta hedging, because in terms of capitalization and leverage, they kind of have to, whereas a big hedge fund customer, they might hedge, but they’re not doing it, every cent.
Corey Hoffstein 16:30
Now, I know you have since moved to the buy side, I would love to know how has your thinking about the world of options changed from going from market maker to actually constructing buy side strategies and trying to profit from options.
Euan Sinclair 16:47
I think the big difference is in the number of Delta hedge is you do and the way that changes your view of how options work. If you think about the very simplest example of an option, you buy a call because you think the stocks going up, what you’re really interested in is the terminal value of the stock. As a market maker, you’re delta hedging several times a day. So you’re very, very exposed, not just to the terminal distribution, but to the path. When market makers worry about volatility, they’re worrying about volatility along the stocks path in time. Whereas when a buy side is worried about volatility, they’re more worried about the dispersion of the stock at the expiration of the option. There are certain stochastic processes where those things are essentially the same. But the market doesn’t know that. And in practice, those things are not the same. And that’s the big difference. And even when as on the buy side, I delta hedge, but I try and delta hedge maybe once or twice a week, it’s a very different view of path dependency. It’s kind of like the number of times your delta hedge, it’d be like, if you see a piece of laid concrete on the ground, you think it’s a perfectly flat surface, but to an end, it’s an incredibly hilly surface, he’s going up and down across through valleys where the market makers the end, he’s going across every little tiny bump, whereas the customer is just looking at things from a much much I wouldn’t say it’s just a different viewpoint. And it really does change things. When it comes to
Corey Hoffstein 18:29
thinking about identifying profitable opportunities on the buy side. What is your general framework is there I know on like, when you think of equities, we might have a framework about different types of factors that we might harvest or risk premia from or behavioral premium. Are there certain structural effects we can try to exploit? When you sort of think about generating trade ideas in the option space? Is there a framework you’d like to use?
Euan Sinclair 18:54
Yeah, I think you’ve hit upon the first one. I think it’s very important when you do a trade, and I think this is definitely true for options, because you’re always dealing with the variance premium, you have to know if your edge is coming from a risk premium, or a genuine inefficiency. The variance premium, for example, is a risk premium. It’s generally speaking, I hate this nuance. Nuance is a word people have completely forgotten. I’m about to say talk about the variance premium, and then someone is eventually going to say, you said the variance premium is always there. No agent, the variance premium means that options are usually overpriced relative to the subsequent realized volatility, but not all the time. And that premium is very variable. So it’s a risk premium, but it’s not always fairly priced. You are collecting risk. You’re taking on risk when you sell options. That’s true thing but you’re not always taking on the right amount of risk for the profit you’re getting. So if you’re trading a variance premium, For any risk premium in general, you have to know the dynamics of that premium. When it’s expensive, why it’s going to be expensive when it’s cheap, why it’s going to be cheap. And it’s a difficult trade because those markets tend to be not necessarily efficient, but very well studied. But it’s like, if you’re a gambler, that’s the equivalent of gambling on the NBA, you can make money on it, but it’s really difficult. And you’re going to be making small amounts of money. But on the other hand, that’s always going to be there, you can always trade a risk premium. So it’s something you can sort of build a business around, because you know, it’s going to be there. The other types of traders, the inefficiency, the little wrinkle in the markets that people just might not have noticed. And you get that in the equities, quite a lot around special situations like rights issues around earnings events around stock, splits, takeovers, and so forth. These are the sorts of trades that you can identify as good trades, but the trick is putting them on, because those situations can often be very illiquid, they can be difficult to get into and they can also subsequently be difficult to get out of. And you can’t build a business around those to the same degree because you never know if they turn up or not. Like I’ve got a vix trade, which has literally never lost money. I’ve done it for the last four years, it has never had a losing trade. I mean, I’m not saying it never will. And the payoff to the winter loss ratio is probably terrible. The losses when they turn up, and probably 10 times the size of the wins. But I’m still ahead if that happens. On the other hand, it only turns up four or five times a year. So when it turns up, you’re like, Great, I’ll do it. But I can’t build a hedge fund around that kind of trade. So I think first of all, you’ve got to split your trades into inefficiencies, and risk premia. And identify which of those you’re dealing with is important because it tells you how you should be dealing with it. You can trade an inefficiency, often as big as you can. Whereas with a risk premium, you have to treat it much more cautiously. But you know that you can keep trading it forever. And the other way I tend to look at things is I think of trades as either situational, or model driven. This is kind of a complementary approach, like a model driven trade is something where you’ve got a model that describes the entire state of the world. So Black Scholes, for example, would be Model Driven, you have a value based on your inputs, obviously, for every option, every strike all the time. Whereas, say, for trading options over earnings, it could be like, I don’t really know what the straddle is worth. But based on my historical analysis, I know that they tend to be overpriced, you’re not making a trade, based on a theoretical value, you’re making a trade based on similar situations that have happened in the past. Because those trades tend to be you tend to be at the uncertainty level, rather than the risk level is difficult to know what your actual statistics of any given trade are. They tend to be more profitable. But they tend to also individually be quite noisy, because you never really know what good one and bad one is, you just know, overall, this class looks like this. Whereas the Model Driven trades tend to be less profitable, but you can have a lot of bread from them, because you can literally be trading all the time. So I think that’s a useful organizing principle as well. The Model
Corey Hoffstein 23:37
Driven trades, strike me as something that you can lose a lot of money on, if you just have the wrong model for the way the market operates. Right, you can, perhaps try to fit the volatility surface, and you can see where options are priced above or below your fits. Maybe it’s just a very generic concept. And if it’s below you by and above your cell, but if your surface is just wrong, or you’re missing some sort of event, it just seems to me like it’s could be inherently a very easy way to lose money. If you’re modeling the world incorrectly. How nuanced does that model really need to be? Do you think?
Euan Sinclair 24:14
Yeah, when you’re trading according to a model, you have to have a good model, that sort of, I wouldn’t say it’s obvious because a lot of people kind of miss that step. But I would say if you’re relatively small relative to the size of the market, so let’s say I’m trading s&p options, and I think pretty much everyone is small relative to the size of that market. I’m not going to boss the market around with any one of my trades. When I become wrong. All I’m really losing is half of the bid ask spread. Because it’s unlikely I’m going to be always systematically wrong for a long period of time, because eventually my p&l statistics which you have to monitor as a separate kind indicator, if you’re right or bought, eventually they’re going to tell me I’m wrong. And let’s say I think something’s worth 10 And the market is priced at five, I’ll buy some, then I’ll buy some according to my edge, my perceived edge, according to whatever sizing principle you adhere to, I’m not just going to keep buying it and keep buying it and keep buying it, I’ll be long at five. And that’ll be wrong. But the true value is likely to be four and a half, I’ve only lost half a point, I haven’t lost five or anything. So a lot, if you’re trading in relatively liquid markets, it’s difficult to make money. But it’s also really difficult to lose a ton. Because unless you’re really big, and you’re pushing the market around, you’re only really going to be systematically off by the costs.
Corey Hoffstein 25:47
I want to go back to a point you said, and it was a subtle, subtle sentence, but you were talking about the variance risk premium, and you’re talking about it being on expectation versus always being there. And there has been some discussion lately about just the scale of the options market, really growing so substantially, potentially the role of institutions adopting call overriding programs and put underwriting programs actually depressing the variance risk premium to the point where it maybe doesn’t even exist anymore, or just has become incredibly, so much harder to squeeze out in recent years. So you’re looking at some CBOE indices like the iron condor, the butterfly, and they’ve completely flatlined since they launched, in your opinion, is this a crowded trade? Are there other issues at play? Or is this just pay, sometimes things go out of favor,
Euan Sinclair 26:39
probably all of those things, it’s definitely true. There have been some big institutional funds set up to harvest the variance premium. And they’re not doing it in a particularly sophisticated way. So they are definitely lowering the value of it. And sometimes possibly, it could be negative. And we’ve seen that definitely early this year. I mean, this year, without a doubt, we’d sold options, you’re just not having a great year, you would have had a very tough time. In March and April, obviously, I think 20 or 30 years ago, you could have the variance premium was so strong and so persistent, you could have done almost anything and made money from it. So you can just blindly sell iron condors you can blindly sell butterflies, you’ll be fine. I believe it’s still going to be there in the future. And the reason I believe that is because there’s not just one reason for it. There are psychological reasons, there are distributional reasons there are your basically by selling options, selling insurance. And every insurance company has been around insurance is a great business, you get paid for selling insurance. And I don’t see why the options market would be special. It’s been studied in every country that has options. It’s been studied over all the time periods we have I found references to it going back to 1895 I find it hard to believe it’s gone away and it’s gone away forever. On the other hand, just like everything, you have to become more sophisticated in the way you trade it. It’s not the incredibly simple trade it used to be. And one of the reasons it used to be a very simple trade is because it was harder to execute it. I remember on the life floor when I was clerking at the side of the footsie pit 1000 Lots straddle was absolutely enormous people would be talking about that for days. Now you can do 1000 lot without even thinking about it. It’s not even an all or anyone would consider a big this is I feel as a part of my book that isn’t going to age particularly well over the next couple of years. But I do believe in the variance premium. And I believe that when any factor like this goes through tough times, a lot of people rush to say it’s dead. Like in your world and the stocks, people have been talking about how value was dead for years. And it’ll probably come back. Because once everyone starts investing in growth, will the growth stocks get massively overpriced them in value relatively is cheaper, it’s just sort of the way it is.
Corey Hoffstein 29:13
And to your point about nuances, even in the value space, if you had done something reasonably intelligent and value, right, not just a naive sort of price to book, but you did a composite. And you did it intra industry, and you’re careful about avoiding your unintended bets value did work until about 2017. So now you’re just talking about a two year drawdown instead of last decade. And I have to imagine it’s much the same with the variance risk premium, that perhaps those naive trades have really stopped working to your point but there are other ways in which it can be tackled. And further to your point, the pendulum swings, right. If there’s profit opportunity and outsize profit opportunity, people are going to pursue it. If the p&l starts going the other way people are going to get out of the trade and it might breathe life back into the trade especially if it’s something that deserves to be there for a risk basis in the market or behavioral.
Euan Sinclair 29:58
Right and I think that’s definitely true. I mean, I’ve pretty much been short volatility for the last four or five years, and it’s pretty much made money, you’ve never got a good story as evolved seller. If you’re running a long vol fund, you can always write some sort of great story about how the world’s about to end and the hell this is time it’s going to blow up. And this time the tails will pay off enormously. And when you write, you’ll end up on CNBC and get tons of free advertising. As a volume seller, you’re only story is, I don’t know, I think the world is going to continue to do pretty much what it’s always done. And that’s not a very good story. The same old story is not a good story, because people have heard it before. But it doesn’t mean it’s not true. So I just think it’s very unlikely that a thing that’s always been there is just going to completely die. I just can’t see it. And the other thing is all the Long’s right now, the persistent low vol. Guys, they’ve got a very recent period, they can point back to where everyone remembers, everyone’s going to be, but Oh, but 2020, everyone’s going to remember 2020, no one’s going to remember what 2017 was like. Because you don’t remember the years when not much happened.
Corey Hoffstein 31:12
So you briefly mentioned your book, which I would love to sort of switch over to, you’ve got a new book coming out called positional option trading, which you were kind enough to show me a sneak peek of your most recent draft. And I really enjoyed. Before we dive into that, though, I would love to know, I mean, you’re a prolific writer, what sort of draws you to writing these books? And why the new book?
Euan Sinclair 31:34
I mean, I think in a lot of ways, it’s the same thing that draws you to doing podcast. I mean, it’s sort of interesting. I mean, I’m not making the same sort of personal connections that you might be. It’s like, you read a lot challenges, you know, fill in the holes, in your knowledge. There’s stuff that you thought you knew, but didn’t you learn completely new stuff? And you’re always organizing your thoughts? I think organizing the stuff, you know, is sort of an underrated skill. A lot of people now are saying, No, you don’t need to go to college. But I think one of the great things about a college education that you don’t get, if you just read books on your own, is you get things put into a structure, like a narrative structure you like, this is the way Ancient Greece Greek history related to the later Roman history. Whereas if you just read it on your own, you’ve got to put all that stuff together, it’s much more difficult. And I think that’s a really important part of learning. And I really liked that. I actually kind of just like the writing aspect. I don’t like the editing. And I don’t like doing all the graphs and putting equations and it’s kind of miserable. But occasionally I’ll write a sentence. And it’s just like, Yeah, that’s actually a really nice sentence. I like that. I mean, that’s not Hemingway. But it’s for me, it’s good. It’s like, you know, when a hacker hits a nice golf shot, that’s not Tiger Woods, but they still get the thrill of doing it.
Corey Hoffstein 32:57
Absolutely. So let’s dive into maybe some of the content of the book. And I want to be careful here not to give too much away, because I really think people are going to get a lot out of this book. But as I read it, there were certain questions that came up that I couldn’t help but turn to ask you about. And so one of the things I wanted to ask you about, and this is maybe more broadly about by side in general, but what do you think are some of the biggest mistakes people make when they start to apply options on the buy side?
Euan Sinclair 33:26
I think the biggest thing when people get involved with options is they pay way too much attention to the individual strategies. Like I’m going to do a broken wing Condor on the stock. And I’m not saying those things are not important, like we just discussed. When you’re trying to get the variance premium, the exact structure of your trade now has become much more important than it used to be. So getting the structure of your trade is correct is a good thing. But the important thing, the initial thing is to know what your age is coming from. Actually, why do I have a statistical advantage here over the market? Like if you’re a stock trader, the first thing you think about isn’t portfolio composition. The first thing you think about is what stock should I buy? And then how does it fit into the rest of my portfolio, and options, traders tend to get that the wrong way round. They think about the structure of the trade. And if you listen to CNBC or watch some garbage on YouTube or whatever, that’s what they’re always talking about. It’s like, you can sell this iron condor and you can make this amount of money 90% of the time. Incidentally, the iron condor is a very, very dangerous trade, but not for the reasons people might think it is. The big problem with that is when you do trades, you get feedback. As I said before you eventually get feedback from your p&l. The problem with the iron condors you’re going to have an awful lot of winners, and not very many losers. So it makes doing statistics on it very difficult because The only statistic that matters is your average. And you don’t really see the average with a very, very skewed payout trade like that you see the mode. And the mode is unbelievably good. Trades like that are difficult. For that reason, even if it works. And the iron condor, because of the variance premium, usually has age, but you’re not going to know how much edge because of that problem, so you don’t have a size of the trade. But anyway, if you’re looking at CNBC, the things they’re talking about on a trade I like, let’s do this call spread, because it has this profit of winning, sorry, this chance of winning, and it can make this profit. I’m not talking about why. And then I’m talking about the price of the call spread, people don’t pay enough attention to the price of these options, as the price of getting into the bid. Everyone’s always complaining, you know, I bought a call the market went up, I didn’t make any money. Well, that’s because you pay the wrong damn price for the call. I mean, you can talk about Vega, and delta and gamma and all these things and love there. And they’re important. But there are ways of translating market movement into dollars that like a p&l attribution scheme, you don’t make money because he had delta or your gamma, we have theta, you make money because the market moves or the market does that I think people kind of get all that kind of confused. And the most important thing to do when you do a trade is look for your edge. And then the cause of that edge. How big do I do that trade? And how does it fit into the rest of my portfolio? Like, I think the most important thing with investing in any situation is your p&l number. That’s your age. The next most important thing is the smoothness of your p&l. And that’s kind of your historical risk. And finally, how does all that work in one trade fit into my whole portfolio of trades? And options, traders on the retail side, at least tend to get that completely backwards. And I don’t think there’s much difference between the average buy side and the retail in terms of how they think
Corey Hoffstein 36:59
one of the things I found really fascinating in the book, especially someone who came up more as someone who came up more in the equity space was actually your focus on equity factors as being a source of potential return when applying option strategies. So I think specifically, you point out that a lot of these factors, if you take one of the legs, you can actually use options to generate returns from selling vol perhaps on the expensive or cheap leg value. How do you and why do you think this transferability applies?
Euan Sinclair 37:35
Well, this is one of those things actually where I think the buy side will have an enormous advantage because market makers don’t think in those terms at all. I remember when I was market making, I was trading options on the ticker HD. And trading it for like two years before I realized that that was Home Depot, I thought it was Harley Davidson. I had no idea. And I often tell that story to people in that like what an idiot. Like that wasn’t it, it made no difference to any single situation I’ve ever encountered. It’s just a completely different game. Normally, when people have valued options in the past, they’ve gone through time series analysis, tried to calculate historical volatilities, then they use like a Gatch model or something to forecast Vol. 20 years ago, that was a great way to trade options, that’s all you needed to do. And then you could buy or sell based on that, and you can make money. That really isn’t the case anymore, most of that stuff now was really heavily picked over. And if you do a search for gosh, on SSRN, or something, you’ll find 1000s of papers. And there are hundreds of different kinds of Gosh, it’s become a complete academic sort of specialty, people spend their entire life studying this stuff. Whereas if you look at factor models and options, last count, I could find eight papers. It’s just not a thing that people have looked at. And a lot of options traders think in terms of very short dated weeks and months. Whereas the fundamental factors play out over the years. And I think again, that’s a place where the average option traders isn’t looking. So it’s sort of in that respect different to the variance premium where everyone’s now vaguely aware of it. And now it becomes a matter of can you do better than everyone else. Whereas this other stuff, it seems it’s not unmined. But it’s much, much less picked over than the time series stuff. If I was starting completely from scratch now, but unfortunately, one of the disadvantages of getting older is that you end up with such a lot of sort of legacy knowledge that it becomes hard to sort of start over in a sense, but if I was completely starting over, I’d be looking at fundamental factors, using them to directly predict volatility. And I think there’s probably enormous engine there. And I think that’s the that will also apply to commodities. That’s where I would go. I’ve seen evidence in these papers on I’ve done it myself that this stuff there. And like I’ve done it in a really simple way, you know, I’ve just looked at value indices and so forth. And I think if you didn’t Well, I think there’s money in there. And I think that’s where the buyside should be crushing it, because that’s what they do all day. So what you should be doing. So
Corey Hoffstein 40:18
Black Scholes, I guess one of the first things you learn when you do go through one of those financial engineering programs that we mentioned a little bit earlier, is that when you’re pricing options, you’re in a risk neutral probability environment, that at the end of the day, drift of the underlying should not be part of your input into how you’re pricing the option. But at the end of the day, the return of an unhedged option is clearly affected by the underlying return, that sort of end p&l that you make from buying a call is going to be truly affected by did the price of the underlying go up enough? So how should directional traders sort of think about this and think about the impact of volatility as the core pricing mechanism when sort of selecting and managing their trades?
Euan Sinclair 41:04
Yeah, people often seem to be kind of skeptical or baffled by the idea that return shouldn’t go into your option pricing model. But that’s actually the case in most things in life. If you think about it, like certainly, when you’re pricing a future, you don’t say, what’s the price of corn going to be in two years, you say, what is my carry cost of corn over the next two years, it’s true, like, if you’re going to go and buy a painting, or whatever, you’re gonna go and buy a Picasso, everyone knows that the price of the Picasso was going to go up. But that’s doesn’t impact the price of it. Now, what impacts the price of it now is what it’s worth relative to other paintings now. So it’s, it’s our value. And that’s the reason most of these things are priced the way they are, because if they aren’t, you’d get up in the Black Scholes is just a fairly complicated dynamic arbitrage. But that doesn’t mean you can’t put your return into your pricing model, you can actually adjust Black Scholes you can, instead of having the interest rate in there, you can put a factor that relates to return in there, that’s fine. And that can give you your subjective value of what the option is. And if you’re trading directionally, that would be the way to do it. Because that would be how you balance the implied vol premium. With how much you expect the option to make over its lifetime. That would be the pricing model way to do it. But you’re going to not be in an arbitrage free world. And if you insist on trading like that, other people will be able to take advantage of you. And like I said before, only by the width of the bid spread, and you’re buying it for a different reason and all this stuff. But you won’t have things like put call parity, but there’s nothing to stop you doing that. But I would say no one really does that. In that sense, people buy calls because I’m gonna buy the 105 corks, I think the stock is gonna go to 110, well, you can kind of do better than that you can put, I think that’s going to have a 10% return, you can put that into your pricing model, then you can work out the entire distribution of results, you can work out actually what your percentage chance of winning might be, as opposed to just looking at the delta or the option and thinking that has something to do with that, which it doesn’t.
Corey Hoffstein 43:23
So one of the things I’ve noticed in again, being a bit of a tourist in this space is the way people present trades over time seems to be very different. So I’ve, for example, I have noticed that some people will post an iron condor, a butterfly, p&l over time, price with a constant Vega notional, I’ve noticed people will price it with a constant dollar spend or say I’m rolling one unit of this trade over time, regardless of cost. And it isn’t to say that they aren’t all sort of equivalent trades, but you are in ultimately at different times spending different amounts of money, which makes the p&l curve potentially very different over time. How do you think people should look at comparing trades either over time or cross sectionally to each other? Is there a right sort of standardized units in which they should be compared?
Euan Sinclair 44:15
That’s a really good question. You see that in academic papers all the time as well. People will say, Well, this option trade has a return of 1% a month. And it turns out what they mean is it has a return of 1% a month and that the option premium changes by 1% a month, which has got nothing to do with anything because if you’re long options, you pay the premium. But if you’re short options, it’s based on your margin, which has got nothing to do with very little to do with the price of the option. It’s mainly to do with the risk of the big move. So they have to in that case, well they should calculate their premium based on margin. And they don’t, which is why you have to be very careful when you look at academic studies, particularly on the short both side. There’s no real correct way to do this, I prefer to think in terms of constant Vega. Because eventually the profit from an option is going to be Vega times the difference between implied and subsequent realizable, on average, that’s absolutely what’s gonna happen. And so I think, if you consider it, it’s the equivalent always buying 100 shares, as opposed to always buying $1,000 worth of shares. Vega is kind of like the unit for option trading the natural unit like that. But again, sometimes that vaguer is going to cost you more in terms of margin. So it’s not? I don’t know, there’s no real one answer to that. It’s important, though, because you have to make sure you’re talking about apples and apples. And you see some, and we know who I’m referring to here, you see some hedge funds, who will talk about their enormous returns? And what they mean is the enormous return on the long options premium, and not the amount you would have made had you put $1 into their fund, because they didn’t invest all of their funds into the long premium, did they? So there’s stuff like that where you actually have to look at the you have to go through whatever the details of what they’re actually doing is. I mean, there are standard accounting ways to do this, but not everyone follows it, particularly in the hedge fund world, you don’t really have to do whatever you like.
Corey Hoffstein 46:37
One of the things that I always find really, candidly overwhelming about the option space is just the sheer degrees of freedom in which you can place a trade not only choosing which underlying you want to look at but trade structure, trade type, different expirations, different tenors, different strikes in which you can place the trade. I’m left always feeling like there is an optimal choice. But it seems like optimal is always perhaps a bit subjective. But when you’re thinking about, you’ve got a particular perhaps event type trade or directional trade you want to put on given underlying How do you start thinking about calling through that parameter space and figuring out how exactly you do want to structure that trade?
Euan Sinclair 47:20
Yeah, I do think one of the great things with options is you have a huge amount of degrees of freedom. And one of the really bad things about options is you have a huge amount of degrees of freedom. I don’t really think there is an optimal answer. I think you can get it wrong. But I think it’s hard to get it optimally, right? Like if you’re long options, it’s very difficult to get long options based on your study of realized volatile in the past, because that’s not going to be pricing in this impending catastrophe that you think’s going to happen. So the reason you got to be long options is typically because there’s a catalyst with a particular time associated with it. And that’s easy. If it’s like a Brexit vote, or an election or earnings number, there’s an actual given time. But even if you’ve got a hypothesis about something that might happen more generally, like you might think, I don’t know if the dollar is going to be devalued over the next two years. Again, you still have the time period, it might not be a day. But if you don’t somehow have a time period, you might not really know enough about the trade to do it at all. So you have to spam that. You can’t do that on the short vol side. Because on the short vol side, you’re literally saying nothing’s going to happen. So in that case, you can do a time series analysis, you can say where is my variance premium, highest, given the structure of the implied vol surface, and you can then choose your optimal trade based on the edge coming from the variance premium, but also based on the risk the cause of the particular trade you put up. Now people start getting old concerned about risk with options, because your payoffs are nonlinear. And even if you hedge, you’re going to have nonlinear results. And it’s going to be path dependent, and all the stuff and so again, there’s no single answer. But you can, for example, use something like the generalized Sharpe ratio, which takes into account kurtosis and skewness as well. It’s not perfect, but then again, no one thinks the Sharpe ratio is perfect for evaluating linear investments either. When I say no one, I mean, a lot of people do, but they shouldn’t. You’ve got a look at a lot of different risk things. I look at the Kelly criterion, but it’s telling me my best traders, I don’t really look at expected value. Because all that’s really going to tell you is like buy all of the teeniest options that you think may end up in the money because the ones with the most leverage are the ones that are going to have the most expected value according to your hypothesis. So I don’t find that particularly useful. I also look at probability of Making money, whether I should or not, is a different thing that shouldn’t really come into it. If I’m maximizing a Kelly ratio, or a Sharpe ratio, that should be the driver. But I’m also realistic, this trade is not being made by a robot, for better or for worse. I mean, sometimes people will say algorithmic trading is better, because it avoids this kind of thing. But I think it also doesn’t capture some of the other things that I know. So this is sort of the downside of doing things. In this way, I’ll get to put in a broader range of knowledge than my model has in it. Because I know stuff my model doesn’t. But I also have to deal with my psychological biases. When you’re young, you read about behavioral finance, and you think, haha, this will let me find out how dumb everyone else’s. And you think you’re not going to fall for that stuff. But as you get a little bit older, you realize you do and it’s more of a matter of managing it.
Corey Hoffstein 50:58
One of the things you mentioned early on answering that question was this idea of a time aspect. And this is something in the equity world, I think, goes woefully overlooked very often, there’s an idea of a certain style might have decay in the signal. And so there’s an expectation as to how long you would hold a trade or a trade will converge. But there’s nothing that necessarily boots you out of the trade. And maybe more sophisticated folks might think about opportunity costs. But there’s this sort of joke that a bad trade becomes an investment in equities, because you can just sort of hold it forever. In options, though it is a very critical component there is this idea that there’s a defined end of the trade date. And so I guess my question to you is, how does the known expiration of an options contract change how a manager has to think about constructing and managing their book?
Euan Sinclair 51:54
I don’t think it’s that different from equities. Even though each individual option has an expiration date, your trades doesn’t need to, I think people will often say when should I get out of the trade. And the answer to that is you get out of the trade, when you don’t have any edge left, you don’t do a trade for three weeks, you do a trade and evaluate it continuously over the three weeks. When you have no edge left, you get out of the trade. If you still have edge, and you think the edge is in the 30 day volatility range. Well, initially, you might do the 30 day option. And as it becomes a 20 day option, you may look to roll some of that exposure back to the 60 day option. And so you’re hoping to maintain your exposure at that right level. And then you put the costs in. So you know the cost of doing that trade, so you’re not going to do it instantaneously. So I think it’s actually the rebalancing, and the cost aspect are more complicated. But I think it’s really the same as any trade you do a trade well, when there’s an edge. And when there’s no edge, you don’t do the trade. It’s like one of the reasons I don’t believe in stops, in general, is because you do a trade until there’s no edge. So sometimes if you buy something, you hope it goes up, because you’re a trend follower or whatever. And in that case, if it goes down, it’s not because you’ve lost money you get out, it’s because you’re wrong. And the fact you’ve lost money is correlated with you being right or wrong. Whereas if you’re in a spread, and you buy the spread, because you think it’s gonna go back up, and it goes down, well, you might not get out because that might mean you’ve actually got more edge. So you don’t get out at that point. Just because you’ve lost money. If you ever had to get out of the trade, because you’ve lost money, you’ve done it the wrong size, you get out of the trade when you’re wrong.
Corey Hoffstein 53:47
We spent quite a bit of time and your book spends the majority of its time discussing options as sort of the instrument of return generation. I think there’s a whole flip side thinking about trading when you’re wrong about using options as a vehicle for managing risk as well that I think goes very overlooked in biocide investing. So, for example, you have someone who’s a deep value investor, who’s certainly been in a pain trade as of late, is there a way to use options to hedge that in some way of giving them exposure to tech names that perhaps is able to reduce some of the pain and maybe there’s a bit of a cost to carry there. But it’s a nonlinear hedge that they can sort of put on? What are your thoughts on the idea of using options for more of a risk management vehicle than a return generation vehicle? And how does that sort of change your framework for evaluating them?
Euan Sinclair 54:42
I’m not sure it changes the framework that much in that you’re always got to think about expected value and risk. And in this case, it’s more that you’re putting emphasis on the risk rather than the expected value, but it’s still the same process. There’s a few things you said there First, I think you can evaluate the idea of your position with the stock with a pot, rather than the stock on its own and the put on its own. So you can do the same sort of risk reward analysis that I might do for selecting an option on its own. It’s just you’re doing it on that portfolio, that’s perfectly fine. That’s a good thing to do. I don’t know of many people do that. I think people say things like, Well, if you’re going to hedge your options, buy an at the money put. Whereas I think there’s a lot more to it than that. And you should know you’re buying a put with the lowest variance premium. You should know if you’re buying a put with the lowest transaction costs, if you think the lowest variance premium and the putt is the front month at the money. Well, it may not make any sense to buy that if you’re going to have to roll that every month for the next year. Maybe you should buy the one year option, even though you’re paying a bigger variance premium. Another thing you could do is sort of a diversification using options by doing a covered call. The covered calls are really rare example of a retail strategy that makes a lot of sense. Because you’re collecting the variance premium, you are essentially using that variance premium is a diversifying effect, you’re still long Delta, you’re selling at the money call your long, 50 Delta, but you’re now diversifying it by turning some of that delta risk into a variance premium risk. And that has I mean, it may stop working because of the Condor thing you said. But again, the variance premium is something I would bet on. You mentioned something about the idea of using options, sort of your long, some tech stocks and you want to buy options on the tick index as a hedge. I think that’s where a lot of things can start to go wrong. If you want to hedge you should buy the options on the actual product you’re trying to hedge if you at all can. What you’re talking about isn’t really a hedge. It’s sort of a correlated trade that should work most of the time. But they have a nasty habit of not working when you really need them to. I’ve seen people say in the VIX, Etn space, ETF ETF, whether like, I’m sure you’ve actually got the notes got the bigger the K, but the uvxy upside calls that I want to buy as a hedge, you’ve got a huge bit of spreads or by some via text calls, that’ll be fine. Well, you might have thought it was fine, except some of the VIX ATMs blew up and others didn’t. You’ve really got to do your hedge with the thing you’re trying to hedge. And if you can’t afford to, if that’s too expensive, then maybe look at the whole trade. Because the hedge has got to be part of your trade, rather than something you tack on at the end.
Corey Hoffstein 57:47
Where do you think the biggest risks lie for someone managing a book of options?
Euan Sinclair 57:52
Okay, they don’t lie in the options. That’s the misconception that people think it’s like, I’ve got massive exposure to the fifth moment or whatever, no, you don’t, what you have is massive exposure to a liquidity crunch, you have massive exposure to the fact that your exchange might get blown up by a terrorist, you have massive exposure to the fact that your firm might blow up because of something else someone else did. If you go broke because of market risk, you’re just an idiot, the thing you should be worrying about is going broken away, no one else has gone broke before. I mean, that’s legit. I had a problem once where the Euro stocks completely restructured their index, they went from a Pan European index where you had to have certain representation and every country to a market cap index across Europe. So the index value stayed the same, but the four would change ridiculously because all the dividends change. And I got incredibly picked off. Because of that, in the option space, I ended up with a huge forward position and the forward I think went from like 23 to 40 or something like that it was enormous. And people will sometimes say, Well, you should have thought of that. Maybe I should have but it never happened before. You can’t think of everything that’s never happened before. Those are the things that you’ll actually have major risk about, and you can’t think of them all. But you should know as many of those as possible that have happened to other people. Like if you were trading an index now and that happened to you. Now it’s your fault. If it’s the first time. Well, I don’t know maybe it’s not your fault. But there’s no excuse for not learning about the things other people have done wrong. I think that’s where the biggest risks lie in any trading. market risk, especially like realized kurtosis risk or something. I mean, come on. That’s all bullshit.
Corey Hoffstein 59:46
Well, you and I got just one last question here for you. It’s sort of the last question I’ve been asking every guest this season. 2020 for so many of us is just sort of been an upside down year. Lots of weird things going on. Love to end with a bit of a note of positivity. hear what’s something you’re really looking forward to in the future?
Euan Sinclair 1:00:03
Wow, it’s amazing. You’ve come to me for a note of positivity, because it’s not really my forte. But I think when things are bad, it’s always tempting to say they’re going to continue to be bad. I think if you have to look at the world, the best time to be alive is almost always now, on average, obviously, some people go through terrible things, but the world does tend to get better. So I’m going to sort of hope and assume it’s going to I’m not a huge believer in the fact that we’re going to come up with a vaccine and the next year, vaccines don’t tend to happen that quickly. They’ve never happened that quickly before. We still don’t have a vaccine for AIDS or whatever. Oh, sorry, you want me to be positive, though, I do think the world will tend to get better again, I think. And that’s when the variance premium is going to come back again. And so I love the option sellers might get on CNBC this time.
Corey Hoffstein 1:00:57
Are you and I can’t thank you enough for joining me. I know it’s been entertaining and educational. So thank you for your time. Thanks very much.