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0:00 a rocket scientist turned trader ranked officially the fifth best in the entire United States. >> You need to understand two things. How to lose money and what your reaction will be to the loss and how you're going to act. And the second is you need to understand what it is about your logic that went wrong that caused you to lose money and be able to distinguish bad luck from bad process. >> Introducing Samir Varmmer, a PhD particle physicist turned 8-figure futures trader, consistently beating the market for the last 30 years. In this episode, Samir reveals how in designing algorithms, he discovered that market manipulations are just hidden iceberg orders and how a leech on the whale strategy is the best way to catch a ride alongside the market movers. The liquidity of the stock market at any given instant in time is not very big. An actual retail stop order can move the market even though you wouldn't expect it to because at that moment in time there isn't much liquidity. Liquidity exists over periods of time. At instance in time, it doesn't really exist. So I give you a perfect example. Um, if you're holding a position overnight, do you get nervous? Can you sleep? If you've had a bunch of losses in a row, do you freak out? I think I'm pretty good at You're pretty good at handling that. Just those two questions already suggest you could probably do intraday trend following. The place that you would probably want to do this is opening range breakouts. And you could basically find like a 10, 15, 20 minute range, wait for the breakout, and trade in that direction the rest of the day. It is funny. In two questions, you've described my approach. just describing that price signature of a predictable area. Stops are likely below. Price goes, grabs the stops and then goes in the direction they predicted. A stop loss hunt. It's a dynamic I've explored a lot with many guests and I never come to a clarity of what's going on here because it gives the illusion that there
1:35 is a higher power in the market and they are coming to the inferior and exploiting them. What is the mechanics of what is going on here? Cuz I see the signature all the time. That's a superb question. Here's the answer to that. I wondered about that for years. >> Hello ladies and gents. Welcome back to another episode. I have to say so it's it's been a long time since I've been this excited for an episode more because I know I'm going to have I'm going to have a journey today with you and we're going to explore a lot of things. Uh I think it's a cocktail of a lot of insights and original thought uh your career credentials not only going from physicist to then publishing things to then being a leading I want to say hedge fund manager but then also being a non-conformist which is is a wonderful mix. >> I'm the proudest of the last. >> Uh so it's going to make for a very vibrant conversation. I want to I want to kick off with a little bit of context on your journey because you you've taken a career that is not a typical route the the physics background that you have that you're still very much involved with with publishing and connecting that to finance and then obviously having success whether it's algorithmically and your strategies I want to explore but you can give insight of what's happened over the last few decades to arrive to this point. >> Yeah. So, huh, I I actually started off uh as an electrical engineer. Um, and I got my bachelor's in electrical engineering, but I honestly didn't enjoy engineering very much and I really wanted to do physics. So, I switched back to physics, which is really what I wanted to do in the first place. I became a particle physicist at the University of Texas. And then the uh uh we were building this thing called the superconducting super collider, which is going to be a real physics experiment which where we might discuss uh discover something new. uh the US Congress uh as I say Congress critters are infinitely wise uh in their infinite wisdom canceled the project uh which meant I didn't have a job and had to find something else to do so I became a trader um in October 93 I read this uh very beautiful article written by Matt Ridley in the economist called the
3:27 mathematics of markets and basically the article said that there's a bunch of people now all of a sudden on Wall Street that are using mathematics to make short-term predictions in the financial markets >> and I said oo that's interesting and then it used the buzzword chaos theory and I said ooh double ooh because I'd published in chaos theory as a graduate student and I said ah this is fun um I'd read a lot of economics uh so I said well this sounds like nonsense we know the efficient market efficient markets hypothesis this can't possibly be true and of course I didn't have a job uh so I started playing around with chaos theory in the financial markets and very rapidly discovered that far from it not working it worked very nicely at least theoretically so since I didn't have a job I figured hey I into this. And so I started my own trading company. And so the first thing I ever traded was uh the S&P 500 futures. And I did that using chaos theory. And as far as I know, I was the first guy to algorithmically trade the S&P 500 futures using some advanced mathematics, not just like you know moving averages or something like that and that worked quite nicely quite some time. So that's where I started as a futures trader. >> Wow. I I want to I want to begin with an open paradox I want to say which is how can a trader the endeavor is obviously to make money. How can someone achieve consistent outcomes from chaos theory an inconsistent or random market? So there are there are really two aspects to that. One of them is psychological and the second one is your edge. So the first thing you have to ask yourself is everyone and his uncle is trying to make money in the market. So what exactly is it that you have or that you think or that you can do that is different than other people? That then becomes your edge. But the second problem is that you can once you get reasonably good at this, you can find more than one edge. But that edge then has to be congruent
5:15 with your personality. >> If the edge is not congruent with your personality, you will never be successful with the with the trading strategy even if it works. So I give you a perfect example. Um by and large you can break trading strategies up into two groups. They're either counter trend or trend right? So breakouts are trending, moving averages are trending. Uh on the other hand you have things like MACD and so on which are technical indicators that are counter trending. If something goes up you short it, something goes down you buy it. That's counter trend and vice versa. But uh the thing is that when you have counter trend strategies typically you make um a lot of positive gains and the occasional big loss. >> So you have a lot of positive trades. So maybe you're 65 70% positive trades. On the flip side, if you're if you're trading trend trading, you maybe make 30% positive trades or 25% positive trades, but the positive trade will be like 19 times bigger than your losing trade. But some people can't deal with being wrong five times out of six or four times out of five. So it wouldn't work for them. So you know they'd get whipsawed in a moving average strategy for example and they just say no the seventh time I'm not going to take the loss and that's the time it goes up 200%. >> So you have to find the edge and then you have to find an edge that is congruent with whatever it is that you can live with. And it the the the reason the trading journey is so hard is that you have to lose a lot of money to begin with to learn what A works and B works with your personality. >> Mhm. With this word congruency, what are the variables of types of trading personalities? Let's say swing trading, scalping or fundamental technical, all these variables, but also then personality types of risk aversion or the ego to not not being liking to be wrong. How would you connect these? So to know okay, I'm X kind of person. I'm I'm Y kind of person. What should this
7:03 lead me towards in terms of behavior? >> So the first question you can ask yourself is if you're holding a position overnight, do you get nervous? >> Can you sleep? >> Yeah. So then you would need to scalp or day trade. >> The the second question is if you've had a bunch of losses in a row, do you freak out or can you handle that? >> I think I'm pretty good at handling. >> You're pretty good at handling that. So you're probably in that case just those two questions already suggest that you could you could probably do intraday trend following. >> Yes. >> And most likely the place that you would probably want to do this is opening range breakouts which are fairly successful in the equities >> and um we actually traded this for quite some time with Joe Richie in Chicago. um which was uh opening range breakouts on stocks and you could basically find like a 10 15 20 minute range on many stocks wait for the breakout and trade in that direction the rest of the day >> and you'd be making more pro I mean you'd be on average profitable it's funny in two questions you've described my approach >> which is pretty interesting uh what are the let's describe your personality type with because I know you're pretty much the opposite you you're doing trades that are one year in duration or maybe even longer >> um what is your personality and how have you connected that to your trading behavior. >> Yeah, that's that's a great question. So, my personality is that I actually hate having to make decisions, which is a strange thing for a trader to say. Um, and the reason I hate having to make decisions is that I can always think of the nth variable that is not part of the n minus one I just thought about. >> So, I decided years ago that a I'm a physicist, b I like systematic stuff, so I'd need to be a systematic trader. And so, I've been a systematic trader forever. I started off as a short-term trader. uh uh but the issue is that I realized back in 2003 that alpha from
8:49 short-term trading is going to become harder and harder and harder to achieve because there were more and more people trying to do it. So >> efficient markets >> efficient markets and and there's only a limited amount of alpha you can get anyway and of course the shorter term your uh your trade is the less money you can run through it. >> Oh because you create the alpha >> decay. Exactly. You create the alpha decay by just trying to take advantage of it. So I decided that I would try to become a um longer term trader and then I said you know I'm I I hate being having a majority opinion on anything on any topic. It makes me uncomfortable if people agree with nonformist. >> Non-conformist. Exactly. So what is it that a a systematic or a quantitative trader equities trader would not do. And the answer is twofold. One increase their time frame to beyond a year. Nobody does that. >> And the second is stop looking for alpha. And so I did both and that's really what >> let's begin with why is that the majority consensus to not hold trades for that duration and so forth? Because by and large when you're trying to build a um a trading model as opposed to an investment model um what you're trying to do is you're trying to find a dislocation in the market of some kind and then you're trying to find a signal of that dislocation and then you're trying to find um whether you can put sufficient capital through that dislocation so as to be profitable. So I'll give you a perfect example of this by the way which I think is still true. Um if you take say the S&P 500 uh ETF spy >> m >> and you divide it up into its daily um into its intraday return open to close and its overnight return close to open you will find that more than 100% of the return of the spy takes place overnight i.e the the on average the spy goes down during the day. >> Interesting. >> Yeah. Exactly. But taking advantage of that is pretty difficult and the reason is you can certainly buy you know market
10:49 on clo open and then yeah no buy market on close sell market on open you can do that >> but there's only a limited amount that you can do that's the first issue before you start to move the market too much >> and the second is of course that you are then subject to the reason it's positive of course is that you're getting paid for taking overnight risk. >> Mhm. So that's that's an example of an edge that exists in the market that's pretty difficult to arbitrage and yet it's right there and you can see it in the data. >> Interesting. >> So on the other hand, if your trade is lasting more than a year, whether it takes you an hour to get in or two hours to get in, the whole day to get in, you don't really care. And that's that's the arena I wanted to be in. Um we started to discuss with Joe uh light speed limits which is to say the amount of time it takes light to get from your computer to the trading arena right and when we started discussing that I said I don't want to do this anymore okay let's take a moment to talk about a partner of the show a leading prop firm that is funded next it's important for me to listen to our community to see who are you working with and how can we make your experience better and the main feedback I heard is trusted payouts quick payouts ability to scale and afford affordable prices and Funday Next has ticked all of those boxes. Not only being a top three prop firm in the industry, but also having on demand payouts and every 10% you gain on your account, you will double your capital for free. And because in this industry, trust and reliability is the most important factor. An important guarantee that they have is that if you do not receive your payout within 24 hours, they will gift you an additional $1,000 to your payouts just for being late. So to unlock all of these benefits and work with a leading prop firm in the industry funded next, check out the link in the description or use the code toot. Exploring this of of extended time
12:35 horizons. I'm not sure the correct way to phrase it, but I want to basically say that as the time horizon extends, the degree of variance also extends to the analogy of if I put a gun to someone's head and said, "Where is price going to be in 10 minutes?" You can have a 90% confidence it's a box about this big. If I say where's it going to be in one year, it's a much larger box because a lot of things can happen that are valid today and you couldn't foresee as time as time goes on. >> Um how do you account for that? Okay, so that is an absolutely brilliant question and uh in fact that's that's really the crux of in my opinion all of trading. What I real I started off like essentially everybody else under the sun trying to predict things >> short-term market movements using chaos theory. um alpha generation strategies for scalping um uh breakout systems whatever these are all predictions what I realized in my old age with all this gray hair is you need to stop predicting things you need to start reacting to them and so my system is actually reactive not predictive I don't predict anything but you're reacting to today's information >> and hoping that that today's information carries through for maybe a year Yeah, walk me through that. So, what what tends to happen this is more true in the equity markets than anywhere else. What tends to happen in the equity markets is the following. This is this is this is not a well-known fact, but it should be. Um, take any line that follows the uh price of the equity market at some distance. Um, and you could, the easiest is to just take a 200 day moving average because everybody else under the sun does. It doesn't matter what you do. You can take any long-term line you want as long as it follows the the price action. >> If you now ask what percentage of the return of the market takes place when it's above that line, it'll generally be around 2/3. >> Okay? If you ask what percentage of the risk takes place above that line, it'll
14:44 generally be 1/3. And then vice versa, if you look below the line, the risk will be approximately 2/3 and the return will be approximately 1/3 more or less. These numbers are all approximate because depends on the line and so on. What that tells you is that the risk versus return trade-off is not constant. >> Okay? And the mistake that I think large numbers of equity traders make many times, by the way, they know better, but they're forced by the risk management committees to do it anyway, is that they are forced to take positions regardless of what the risk outlook is. And so you may say, what does that mean? So I'll give you another example. Um I wrote a paper on this gosh 20 years ago now. Um supposing you take the correlation of all US stocks to the S&P 500. So you take you know stock one and its correlation stock two and its correlation stock three it's correlation and you average it and you the let's say the correlation is over the last I don't remember what number 100 days it doesn't matter and you average the correlation today over the last 100 days and then you average it tomorrow and average and so on. As that average correlation goes up, the rate of return of your long short strategies goes down automatically >> because the S&P >> Yeah. As the average correlation of the average stock to the S&P goes up, >> the rate of return of any long short strategy is going to go down. >> Why? Because it's baked in. Basically, >> it's baked in because when you you're you're trying to make the difference in the return between the two. As the correlation goes up, the difference in return comes down. Mhm. >> But nevertheless, you are forced very often by your investment committee or by your um what is the I forget what the term is by the people that allocate money to you. Okay. >> That you're basically told no no you can't take advantage of this fact. You need to have your exposure on at all times. >> Similarly, the same thing happens with
16:38 mutual fund managers that are constantly frightened of being behind the index. Right? So they can't do things to actually actively manage the risk in that way and so they don't. >> Does this imply a negative correlation to the S&P is favorable? >> Yes. If you could find one >> just trade non-correlated things. >> Yes. So the so the ideal thing would be of course to find a negatively correlated asset and stick it in your portfolio along with the positively correlated asset and the two correlations will will offset and in fact the negatively correlated asset could even lose money. >> Yes. But as long as it doesn't lose too much money, you're still better off. >> But that's very hard to find. Very hard to find. Um, so you try to find an uncorrelated asset, which is also, by the way, pretty hard to find. What about this idea of being a non-conformist in strategy? What I mean by this is not necessarily a non-conformist in price because then you're just trying to pick the top, but more let's say looking at the CO2 reports, commitment of traders, and seeing, okay, everybody is long. 95% of people are long. Therefore, who is going to carry that trend forward if everybody's already long? Therefore, using positions as a reversal format, which would be by definition non-conformist. It would work if you could get the data uh fresh enough. Number one, and number two, if the uh uh imbalance was extreme enough that you would feel pretty confident about taking the opposite position. 955 probably still isn't good enough. If I had to guess, >> okay, >> um, I would probably want I'm making this up right now because I haven't tested it. I'd probably want it to be like 982 or something like that. >> Does that happen in real life? In >> very rarely and in those very rare circumstances like George Soros used to know this in his gut. Um, you take the opposite position >> like you know when he quote broke broke the bank of England remember the famous trade that's exactly what he was doing
18:28 in effect. I I want to explore the idea of self-fulfilling prophecy when it comes to the coot report where is the market truly random or is it a law of cause and effect of human psychology or is it a law of cause and effect of the large money managers who if they position a bias that bias must play out by virtue of the capital they put in. So all of the above >> is the answer and so let's go through that in some detail. So the first is you have to um um there's a guy um Joe Stiglets who won a Nobel Prize in economics. I forget when now um anyway he uh came up with a I think Sanford Grossman I forget. Anyway, Grossman the Gman Stiglets paradox and the Grossman Stiglets paradox is a statement that the market suppose the market was completely efficient. Well then nobody would trade in it because there'd be no point in doing so. So then no one would trade the market which means it would be inefficient which means of course everybody would trade in it. So there has to be a balance of inefficiency. Yeah. There's a pendulum and the pendulum will presumably then settle in some equilibrium where there's just enough inefficiency to make it worthwhile for you to do the research to find the inefficiency. >> Right? That's the Grossman Stiglas paradox. So if you take that to its logical conclusion the answer is for your question all of the above. You have to do all of those things. What what is your thoughts on patterns specifically where not necessarily pattern traders but uh in the randomness of the markets there is predictable pockets because human nature at certain extremes or certain situations will act in a predictable way. >> Um is our job to find inefficiencies or is our job to find pockets of predictability? >> Both. >> Okay. >> It's it's our job to find anything that makes money. >> That's my my my position. >> Which one do you prefer to exploit? Um, I generally try to prefer to exploit um, uh, situations where I'm pretty sure that the statistical odds are in my
20:26 favor. Whatever they are, it doesn't matter to me how I find them. Um, and also I prefer not to exploit patterns that disappear when I exploit them. Let's walk through what a pattern is first of all because a pattern can be correlation causation but on top of that it can also be something that is optically a pattern but behind the scenes in the orders the behavior may be different to another time that pattern appeared. >> Sure. >> What what is your first thoughts on pattern traders? >> So the first thing to think about is um as you just said human psychology. >> So it is true and this has been studied quite a lot now in economics. Um people like to place trades at round numbers. >> So you'll find more trades at zeros or fives or 2.5s than you will at you know 2.1 or you know so 99.17 is going to have a lot less trades than 100.00 just just as an example. That's something you can exploit. No no no question. >> The second thing you can exploit is what the CEO of Renaissance called patterns that seem to repeat but have absolutely no good reason for existing. um Peter Brown, is that his name? Um he said these these patterns are so completely illogical that if you try to get logic out of them, you would never trade them and that's why we do and that's why they work. >> Now maybe he's blowing smoke. I don't know. But it actually sounds >> Does that Does that imply a job of a trader is not to know why the market moves? It's simply to react and not understand why it did. >> Yes. Because I think that we make a mistake as traders and my biggest losses by the way which we can talk about some of them have come from thinking I understand things um is from thinking that we need to understand stuff whereas it's a complex system computationally irreducible in the terms of my book and because because it is that way it means that trying to understand it is a futile quest and you shouldn't try >> as a scientist as a physicist who explores for answers was this quite the
22:24 confrontation when you came into the finance world. No, because I started off like everybody else thinking there were the explanations for things. So, so I should actually tell you about my very worst trade. >> Please do. >> Um, my very worst trade took place during the dotcom bubble. Um, and I may get the numbers slightly wrong, but the idea is is roughly correct. Uh, when I was tra this was for my own account. Um, because I was trading futures at the time and this stocks was my hobby at the time. Um, so I I actually made 10% on my very worst trade. And you'll say, "How can that be your very worst trade? What a ridiculous thing to say." Here's why. I bought Sevil Systems, symbol SEBL, at something like $5 split adjusted. I held it to, I think, 120. I may be wrong, but something like 120 split adjusted. And I sold it at 550. Yeah, that's right. I was greedy on the way up and then on the way down I kept saying, "No, no, it's going to have to bounce. I'm just going to wait for it to come back up before I sell it again." >> So, I sold it at 550 when I essentially, to use the common term, puked it out because I couldn't take it anymore. That was the very worst trade I've ever done. I I've had losing trades which are not as as stupid as that one. >> Are you Are you saying it's the worst because of the opportunity cost of what could have been? >> Exactly. And and also from the fact that psychologically I did everything wrong. >> Everything. I identified the correct stock. >> I more or less identified the correct time to sell it. >> I then didn't pull the trigger to sell it. Then I had regret over the fact that it didn't pull the trigger to sell it. >> And then I kept having regret over the fact that the price was higher the last week or two weeks ago or 3 weeks ago. And as it plummeted down, I kept saying, "No, I'm going to wait for it to bounce." And it didn't. >> A very relatable story. >> Absolutely. I' I've done it >> for the last two years. A proud sponsor
24:09 of the show is a topranked leading prop firm, Alpha Capital. And for the years that I've been working with them and the thousands and thousands of viewers, you guys that have been working with them through the discount codes of Titans of Tomorrow, it's clear for me to see why they are top ranked prop firm in the industry. They have also reached a monumental milestone of $100 million in payouts. And with the multiplestep plans and the multiple package types they have, there's going to be an option catered specifically for what you're looking for. So, you can buy an evaluation account catered to your needs at the most competitive prices. And with our discount code toot for titans of tomorrow, you're able to get the most unbeatable unmatched prices in the industry with a leading trusted prop firm. And with that being said, let's get back to the episode. I want to explore therefore and on the back of this an area that people don't maybe consider. >> Obviously, everybody talks about risk and they talk about my final take-profit level, but the the what happens in between. >> Maybe it's a bell curve in the sense of it might go 5% to my target and then reverse. It might go 99% and then reverse. uh and and maybe it's a normal distribution. Hence, people take partials at a certain point. How do you eradicate or minimize um opportunity cost in a system? Because it's very easy to say it's break even, no loss, no no harm. But then if you have these pockets of you know 2% 1% 2% that all went back to break even. At the end of the year, you've got a huge amount of money that could have been >> yes. >> How do you navigate that? >> So the answer is you can go broke taking a profit. >> So that statement is is false. has always been false. I don't know why people think this is a good idea. I think it's very stupid. Um, what you need to do is you need to I'm a systematic trader now completely. So, I know exactly what's going to get me in and I know exactly what's going to get
25:48 me or rather my computer does, right? But even if you're not a systematic trader, you need to know exactly what your exit conditions are going to be before you enter your trade. You you do not get to make it up as you go along. That's the error. So anchoring back to what you previously said, does this not now bring undertones of predicting, not reacting at a level? No, you're reacting. You're you're saying in advance if if you're trying to make discretionary trades, these are the types of conditions that if they prevail are going to make me pull the trigger to get out. >> Mhm. >> So the perfect example of this, I don't trade like this, but the perfect example of this is William O'Neal's Can Slim System, >> which is in a book, I think, called um what is it called? how to make money in stocks. I don't trade like this. It's not something I could do. But basically, they have very specific patterns they look for when they get in and very specific patterns they look for when they get out. And they have very specific rules for taking profits and so on and so forth. Um the point is that if you have specific rules, even if those rules are things that you do discretionarily, you can look back at your trade diary or whatever it is, you should always keep one um to see what worked and what didn't work and you can at least somewhat optimize what it is you're doing or not doing. >> The the the the problem is always when people don't have a clear plan. So I this happens with people that I advise all the time, you know, friends, um, where they'll buy a stock and it goes down and they say, "Oh, well, you know, I bought it for a trade, but now it's an investment." No, I mean, dude, it went down. It shouldn't have. Sell it. >> Sun cost fallacy. >> It's cost fallacy. >> Earlier when we were we were speaking before we started shooting, you were explaining how going through data uh and sifting through financial data when you were a physicist and and through your
27:34 career had to take that step. you uncovered certain things patterns within the data. Can you share to me what that was? Yeah. So, so interestingly um the original um uh system that I mentioned was was using chaos theory and in chaos theory what you do is you make the assumption that a physical system if it has behaved in a certain way historically in the recent past then in the very near future it's going to behave the same way. It's a form of pattern matching actually >> and um for chaotic systems which is a very specific definition which I won't get into but for systems that are technically chaotic that actually works reasonably well >> for short-term predictions and that's what I was doing in the uh financial markets on Australian futures. Now from having looked at large amounts of financial data for more than 30 years it becomes instinctive where you can look at the data and you can say hey you know that's not noise that is probably a pattern. So like for example uh the example I gave you earlier about the overnight versus intraday returns of the spy that's a pattern I mean that's not noise. Um uh it's it's just not another one by the way is the congressional effect which has weakened over the years but for the longest time almost the entire return of the S&P 500 took place when Congress was not in session >> which tells you something about politicians but that's another story um but that was a real pattern that was not something that was noise again >> now noise would be for example that again for the longest time stocks whose whose symbols began with a vowel outperformed the market as a Wow. >> Yeah. That's not explanation. >> No explan. And that's not a pattern. I'm giving you simple examples, but if you do this long enough, eventually you learn how to see a pattern. >> Yes. >> And so it turned out, this is what I was telling you about earlier, that I have a physics paper coming out in a in a proper physics journal, European physical journal, C particles and
29:32 fields, um, which I'm pleased to say will be out in the next few weeks, accepted already. um where I put my finance eye looking at a very peculiar set of data which is the mass of quarks. Quarks are the fundamental constituents of matter. They make up the inside of protons and neutrons. >> And um the pattern of their masses, the ratio of the masses of one quark to another. There are six of them has never been satisfactorily explained by anybody because they look at it and it's crazy. The heaviest quark is I think 13,000 times lighter than heavier than the lightest one. No one knows why. and finance I believe it or not I looked at the pattern and I said I think I get this and it turned out because the paper is now being published and it's being peer- reviewviewed I was right so I've actually found a pattern in the masses of quarks as a physicist yes trained as a physicist with a PhD but with a finance eye applied to physics so I think that's pretty cool >> fascinating and first of all congratulations there's no small feats >> what about the other way around taking the physics mind and applying it to finance any unique or certain >> insight you've had. So the most important thing that you need to do as a physicist coming to finance well you need to do two things. First is you need to be relatively humble which many physicists me included are not. >> Why? >> Um well because you see the reason you get into physics in some cases is because a you love physics but b it's because you are convinced in the very fiber of your being that this is the highest intellectual challenge of mankind. >> And so you think of yourself as being a pretty damn smart guy. and you probably are for that matter, but the financial markets have a way of humbling people that are pretty damn smart. >> Um, and the reason is that there's a what you would call technically a lot of noise in the financial data. What looks like a pattern isn't. And so you need the humility to be able to understand
31:22 that unlike in physics where if if there's a pattern it probably is real, in finance, if there's a pattern, it probably isn't. And so you need to study really hard >> to understand how to identify patterns that are real versus patterns that are not real. That that's the biggest thing that I would tell um physicists getting into finance. That's the place where you really have to be humble. >> How do you also segment or or come to the answer of what is a real pattern versus not if optically they are the same? >> Yeah, that so that requires an enormous amount of learning and background. So uh you need to read a lot of books on um uh economics and you need to read read a lot of books on finance. But then the most important thing is you need to read them with a very skeptical eye to see where they're wrong. And again some of the stupidest things I've ever done in my life is when I've read an economic theory and said that makes a lot of sense. Got it. I'm going to use that in the market. And it blows up in your face every single time. Um every single time. So >> interesting. >> You know, for example, people love to use risk models. So there's all kinds. There's Gach and Echot and ARMA and Arima, and I could go on with all these silly uh names. And what they're trying to do is they're trying to predict what the risk is going to be. See, we're back to predict again. Um and so basically, they're trying to tell you that the annualized risk of the S&P is going to be 23% in the next month. Or they'll say, "Oh, it's going to be 6% in the next month. There are two problems with this. Even though everyone and his uncle uses them, all the hedge funds use them, uh the proprietary funds use them, the investment banks use them, the commercial banks use them, it's crap. And it's crap for two reasons. It's crap a because those risk models work until they don't. That is to say, until the, you know, hits the fan, >> they work great. When the hits the fan, they blow up and they don't react
33:19 fast enough. That's the first problem. And the second problem is that they are mistaking a exact prediction for reality. And I think it's Kanes who said this. I I'm not sure but I think it's Canes. These models would prefer to be exactly wrong than approximately right. >> Interesting. >> It's a lot more important to be approximately right than it is to be exactly wrong. And what you the way to deal with risk is to classify it, not to predict it. It doesn't matter. The analogy I like to give is um way back when when Tiger Woods when his was in his heyday, number two was generally Phil Mickelson. Question, was Tiger Woods twice as good as Phil Mickelson? Four times as good as Phil Mickelson or eight times as good as Phil Mickelson? Does it matter? No. He was just a hell of a lot better than Phil Nicholson, >> right? It's the same thing. Is the risk high? Yes. Okay, be frightened. Is the risk low? No. I I mean, yes, great. Be aggressive. That's what you need to know. You don't care whether it's going to be 26% or 28% or 29%. So, technically speaking, what these people the mistake they're making is that they're trying to optimize what's called the root mean square measurement of error. >> And that's just as silly because that's the wrong metric by which to measure things. Because what will happen then is you're optimizing for getting things right 90% of the time, 92% of the 95% of the time. But those 95% of the time don't matter and the 5% of the time that do matter, you get wrong. >> That's the issue and that's just the wrong way to do things. When we speak about risk and and off camera you gave me a nice analogy of the 7% of funds and and how in spite of that things happen. Yes. >> But I want to explore >> risk you can also look at as each independent trade has an independent outcome. It does. So therefore risk is um just it's a collection of things that happen. But then when I bring the human element into it, well then there's confirmational bias. There's a gambler's
35:15 fallacy where the human connects the the string of losses to then affect future behavior. How do you how do you factor that in? That's hard to factor in um unless you have a reasonably intelligent risk framework that other people i.e. not the trader are running. Uh-huh. >> But that has to be intelligent, not stupid. And this is what I was telling you off camera. I have a paper coming out, I think this month, in the journal of portfolio management where I show that the most popular method of managing risk at these pod shops like, you know, Millennium is one of them and other places that hire pods of traders is just simply stupid. Um, and it's stupid in the sense that it's statistically stupid. They're leaving profits on the table. And um I demonstrabably show so this is not even my opinion that in effect the reason they're successful is in spite of their risk management not because of their risk management. And so the issue is this. So the simple-minded way of managing risk with traders is to say you have a draw down limit and your draw down limit is pick a number 8% 10% 7% doesn't make any difference and if you exceed that you're out goodbye. You can show statistically that this is just dumb. And I do this in the paper um by setting up a scenario in which um there is every advantage given to the rule and every disadvantage given to my statement that this is a stupid idea. And I still show it's a stupid idea. And so what I did in this is I took um pairs of ETFs. I found specific periods with specific investment thesis for which ETF to be long and which ETF to be short. And I picked the precise period where it was the the most profitable period for this pair of ETFs to be long one and short the other. >> So you just had to hold the trade for whatever period of time it was profitable. Trade it and you would have a profit. And remember this is in perfect hindsight. >> And then I showed that if you imposed any kind of a draw down cutff on it, you
37:18 turned what was a certain profit because you know it's going to be profitable into a loss more often than not. Why does that happen or why is this a repeating thing? The reason it's a repeatable thing is that you need to divide you need to understand why a draw down occurred. So let's say for example uh uh some um you own a stock and some piece of really terrible news came out >> right and the stock fell. Well now as the risk manager you need to understand is it because this guy didn't do his due diligence the portfolio manager >> is it because the news was genuinely unexpected? Is it because this was some bizarre thing that happened to the supplier and the person could never have anticipated it etc. So I'll give you another example. Just uh not very long ago um we had these you know strange tariffs that got imposed right all of a sudden overnight seemingly by typing them into chat GPT and then chat GPT gives some numbers and they presented them in the rose garden and the stock market of course collapsed. >> Now if you've been long the stock market then and you hit your 10% draw down were you a bad money manager? The answer is obviously not. All of this needs to be nuanced. The problem is that the way these people run their portfolios is not nuanced. It's silly. What I also mentioned to you off camera was this perception that I and I think a lot of retail traders have is that the hedge funds have got it all figured out. They have the insider information. They have all the resources. They have the top talent. Therefore, they know better than us. As I've spoken to more and more traders and people that have the insight like yourself, the more I realize it's simply not the case. if you can shed some light like you have here on on irrational behavior. What frameworks or disadvantages do these large institutions have that work against them and that things that we don't have to have to deal with as an individual trader? >> Yeah. So that's a very good question and
39:03 I I put this if if somebody buys the Kindle edition of my book in the back of it is a uh is three presentations one of which is about the future of AI in finance >> and in one of them I say that one of the problems with uh with um traditional finance large hedge funds and so on is that they hire the same people trained by the same professors at the same schools on the same strategies at the and do the same thing at the same time and then they complain that they don't have anything unique. That that's the fundamental problem. What's happened to the hedge fund industry is that it used to be run by people like Michael Steinhart and George Soros and people like that that A were risking their own money, b understood something about the markets and c um were very clearly people that had to and want to take a specific position for a very specific reason. and they made concentrated bets and they basically bet that they knew what they were doing and they applied good risk management and they were smart and all the rest of it. What it's turned into is effectively mostly not always but mostly a mechanism by which large pools of institutional capital are locked up into vehicles that charge very high fees and do not produce any significant set of returns. And uh simultaneously what has also happened is that you now have this quote war for talent unquote where you know PMs are getting these very large guaranteed you know sums of money. But in most cases um you as the retail investor are way better off than any of the institutions because all you have to do to beat essentially all of these hedge funds is buy the spy and sit at home. And in the even medium term, you will beat essentially almost not all but almost any hedge fund out there by just buying the spy. So why even bother investing in them? And that was that famous bet which I've forgotten the details of George Soros and some hedge fund manager. You remember not George Soros sorry Warren Buffett.
41:02 >> He bet some hedge fund manager 10 years ago, 12 years ago, 15 years ago. Okay. >> Some sum of money. >> I'll get the details wrong. You can Google it. that uh this manager could pick any group of funds and uh uh uh Warren Buffett would pick the S&P 500 and then the bet was that over the next 10 years this group of funds would not beat the S&P 500 and of course the S&P beat it by some ridiculous margin >> and this just keeps happening over and over and over. So the larger hedge funds are essentially now vehicles for marketing and sales. They are not vehicles for actually making any money. So an interesting inflection point I've reached in my career off the back of this is I've been training for next month will be a decade and I've been through the whole journey and the whole human experience of the market and everything it brings out of you but uh you know after after some time I I found a sense of consistency but my approach as as we explored earlier is lower time frame it's scalping it's in certain pockets of time and it removed all the freedoms that I wanted from my life and I thought this is the game this is what what has to be done as I've got more financially mature Sure. I've I've I've taken the arm this year at investing quite significantly. >> Yeah. >> One step that I did was let's say I had $100,000 in a trading account because I'm taking one trade at a time. I'm never in two trades at once cuz I'm not swing trading. >> I was not utilizing the full margin and therefore I realized 80 or 90% of my account is just dead weight. It's dead capital. Y >> So I thought this year around the tariff time, why not take this portion out, maintain my lot size or position size? So as a risk on the 10% that is left obviously I'm risking more but as an overall of my portfolio I'm risking exactly the same differences I take this money and put it into the S&P and Tesla fortunately gold and just diversified. >> Yeah. >> And now that five months later after the
42:49 tariff thing I've realized on my 90% of my account that I just put into investments >> I'm up like aggregated about 25%. Obviously, it's a it's a a fortunate window, >> but it just makes me think why bother? Like all the effort that now I've also been a bit hands off in my trading because I'm making this money here. I no longer chase the markets and and as I extend it out to the conversations that I've had and I reflect on certain conversations I've had with others. The largest of money managers are not in the lower time frame or in the, you know, scalp intraday. They just take position trades. Yes. And then all of this after you said all of this just makes me think why bother even attempting to day trade or why bother even to manual trade when you have the the beauty of indexes and such forth. What is your reflection on that? I agree with it essentially 100%. Um and this is why um in my own um you know in the funds that I run um we must be the only hedge funds maybe that don't care about alpha. Um so you know it's pretty pretty funny but it is true. What do you care about? >> Risk and only risk. So basically my idea way back when was um 20 more than 20 years ago now that um what is being arbitrageed away is alpha. What cannot be arbitrageed away is risk because risk is generally a pylon. A sells so B gets a margin call. B cells so C gets a margin call. C sells so D gets a margin call and so on. You can't there's no way of stopping that from occurring. So there's no way of arbitrageing it away. All you want to do really is figure out periods of time when that's likely to happen and be out of the market if you can. And so my idea was I'll use all of these risk models that I just post spent 10 minutes criticizing and I'll basically see what the risk is and if the risk is high I'll be out of the market and if the risk is low I'll be long and levered. That was the idea and it would work every you know work two three four years in a row
44:37 and then it'll blow up. So I after a while I got fed up of things blowing up and I would talk to people on Wall Street constantly saying hey dude this blew up and they would always say always always literally always there wasn't a single exception to this they would say yeah that's a once in a lifetime event and I would always say to them the lifetime of who a lab mouse I mean seriously and that's when the realization hit me that this is the wrong way to do things you shouldn't be forecasting risk you should be reacting to it classify >> so first of all you're referring to black swan events as the once in a lifetime thing. >> Well, they're not really once in a lifetime events. They're like, for example, every so often the S&P will drop 30% for no reason at all, right? >> Well, okay. So, you can identify reason, but like for example, the COVID crisis hit, right? So, you can say it's the COVID crisis, but on the other hand, it's not like we didn't know that there was an infection that was about to go around the world. So, why did it drop 30% in 10 days? Why didn't it drop 30% over two months? Why didn't it drop 40% over six months? I mean, it could have been anything. It just happened to drop 30% over 10, you know, 20 days, I think it was. Happy to say I was out of two-thirds of it. Um, but that's the point is that if you had if you had had a risk model and you had been running it every day and you had been basically trading through the COVID crisis, you were dead. And even the very best hedge funds, Renaissance is a perfect example, um, were not able to trade through the COVID crisis properly. They got out too late and they got in too late and that's again because they're trying to forecast risk. They're not trying to react to it. >> You mentioned a moment ago of something that is low risk and high risk which is a sense a prediction or how are you correlating high and low? >> I'm I'm in the case in in in my specific case what I'm worried about is the risk
46:23 of a draw down >> risk of a large draw down in the S&P. So because that's what I worry about. Um but obviously if you're trading something else, it's the risk of a large draw on whatever asset you're trading. Um so it it turns out that risk is pretty predictable in the stock market in the in the sense of not I can tell you what it will be tomorrow. But I can tell you that if certain conditions obtain then the chances that the S&P will fall a significant amount have just gone up. >> And if those conditions don't obtain that the chances that the S&P will fall a significant amount have just gone down. >> And that's predictable and that's consistent and you can see it throughout history. And that's sort of my edge is I know what those conditions are. >> Can you talk me through the dance that people do where they bring in psychology and then they bring in mechanical systems or something objective and then human discretion, subjectivity, intuition, it it creates a whirlwind of differences of opinions. >> Uh what is your take on it specifically because you are quite systematic in your trading? >> I don't like it. In my opinion, you need to either be a discretionary trader that has certain inputs that you look at and then you go with the psychology um from you know there are lots of people that teach you how to deal with trading psychology, how to deal with losses and so on. >> So you look at those indicators and you try to be consistent whenever these indicators are in a certain mode I'm going to do a certain thing and then you just do that. >> That's one way of doing things. The other way of doing things is the way I do it, which is you write down very specific rules. And those are rules you follow. And that's the end of the discussion. And if you don't like the rules, well, then you got to go back and change them. >> You don't get to say at the last second, I don't like this trade. I'm not going to make it. That's not acceptable. And I've never done that.
47:59 >> So why have a system that is still manual but systematic as opposed to completely automated and remove human elements? >> Yeah. So well, it depends on what you mean by human elements. So in my case the system is it tells me what to do. I just have to actually enter the trade to do it. >> But there there is that last thought of like should I and the human filter. >> Yeah. I don't and that's that's a lens of emotion. >> I don't do it. >> Okay. >> I I absolutely over the years I've trained myself out of it. If the system says to do it, I just do it. >> If I have deep misgivings about what the system is telling me, I'll still do it. >> Then I'll go back and I'll do the research and see if my misgivings are justified. If what I'm saying is correct, if there's a way of improving the system, whatever. That's a different question. That's a research question. It's not something that you're allowed to do at the moment of making a trade. That's wrong. >> So, easier said than done. >> Easier said than done. >> How do you have the discipline or the mental frameworks to be able to act when maybe your gut is saying otherwise? >> Very, in my opinion, it's very simple in one sense and very difficult in another. The the the very simple aspect of it is you have to write down the rules yourself. You have to program the rules yourself and you have to test the rules yourself. And you have to test them every single which way you can think of. Try to break them in the nastiest way you can think of. Um, and I'll give you some examples of how to be nasty to your own trading rules in a second, but you need to be really nasty to them and try to break them and just keep trying to break them until you really throw your hands up and you say, "I can't take this anymore. I can't break them." That's what you really have to do. So, I'll give you I'll give you some examples of how you try to break trading rules. So, one easy way of trying to break trading rules is to add noise to your
49:36 inputs. So, essentially, let's say that you've got um I don't know, three pieces of data. You're going to take uh the difference between the Fed funds rate and the 10-year Treasury. Uh you're going to take the current um trading volume in the S&P 500. And you're going to take uh oh, what's another good one? Uh the distance from the 50-day moving average. just making this up right just on the spot. Um, now all of those require inputs. Take the inputs which which are presumably sitting in CSV files or something like that. Write a little program that adds noise to each day, random noise from some reasonable distribution. >> Okay? >> Right now you've got a data series that has noise added to it. Now run that through your system. What you should find is that your returns should be be um by with small amounts of noise it should be unaffected and with large amounts of noise it should start to degrade and what you should see is that there's a curve that degrades as you add more and more noise to the system. That's what you really want to see. What you don't want to see and this is what happens with most systematic systems is something like this where some amounts of noise produce a good result and other amounts of noise produce a bad result. That doesn't fly. Why would that happen? >> From the fact that you your original system is not real. You fitted noise, you didn't fit data. >> You fitted noise, you didn't fit data. >> Yes. >> Which means you never really had an advantage. So, uh the classic example of this which people still do, beginning traders particularly, is they'll take say some agricultural commodity and they'll say I'm going to trade a moving average system, a moving average crossover system. and then they'll try every single combination of of the two moving averages until they find the quote optimal moving average. That is almost never going to work, >> right? And you can see that from the fact that if you just added some noise
51:32 to the system, that optimal moving average wouldn't work anymore and you'd get something that looked like this. So that tells you that the system has a problem. That's just one example. So you you have to stress you have to really say, I'm going to try to break my system. I'm going to really try to destroy it in any way that I can. And once you've run out of ideas for ways of how to destroy your system, you probably have something that will work. >> I think off the back of that leg work that you have to do, you're only left with confidence because you've got so much data behind you. You've got so much uh testing behind you that when it comes to an opportunity in the market, you probably won't think twice because you've done the foundation work, probably what most avoid uh and therefore fuel the emotions in the moment. Have you done a lot of things specifically for your psychology or is it all the data behind you and all of the numbers behind you that enable you to act in a sound way? It's it's entirely the fact that I've done I've done the work. >> It's like I think it's sort of like being a professional athlete. You go into a match, you don't know whether you're going to win or lose, but if you've worked hard enough on whatever it is that you're trying to play at the end of it, that's all you can do. >> And whatever's going to happen is going to happen. >> Um you always have to be careful how much you risk. Obviously, that's that's obvious. You should never be risking 100% of your portfolio sorts of things. That's stupid. All the people do it. Um, and you have to be willing to basically be very upset. I mean, I've had losing periods. I had losing period in 2022. Uh, in 2022, I had seven straight trades where uh it looked to me to the system, I say me, but it's the system that it's time to get back into the market. >> We missed the first drop, by the way, in 2022. It was great. Um, it looked seven straight times like this was time to get
53:10 back into the market. We took a small position and then the small position would get hit by a 7% drop the next day or 5% drop the next day and it happened seven straight times. I was tearing my hair out by the end. But I wasn't I was just upset. But it wasn't like I was not going to take the next trade >> because this is a point where the beginner trader and someone with experience shines. And that is it's better to do the right thing and get a bad outcome. >> Yes. >> Than do the wrong thing and get a good outcome. >> Yes. >> Explore why that is so dangerous because I know even myself I used to do it all the time. I took a trade I shouldn't have taken. Ended up being a win. Confirmational bias. I'm going to do that again because you're incentivized to. >> Yes. Actually, you just said it. That's that's the real reason. Um the thing is that you have to understand that that trading is meant to be a business. you. It's meant to be something you make money from. It's not meant to be exciting. >> I want my life to be as boring as possible. I I hate excitement. I don't want any nothing. Thank you. Nothing. Um I don't want to be happy. I don't want to be sad. I don't want anything. I just want to essentially be able to ignore everything as much as I can for mental equinimity. >> And if you have uh not put yourself in that state, that's when you're going to run into problems. You have to be in a state where your your system is set up, your risk controls are set up, your uh your trading rules are such and so on that you basically just trade it >> and move on. >> Do you believe there can be an idea of a trade idea that is setting up systematically in your case that you can call a high conviction play and would you modify your risk in a high conviction play? Yes. But what I would tell you is that you should have already built that into your rules >> and I I and I have. >> So you would have um categories of trade types say this is this is my A+ and so
55:03 forth down. And how do you do you maintain risk and allow large numbers to play out >> or do you say high conviction equals higher risk >> worse offset is still has an alpha uh less risk. >> Yes, that's exactly what you do. So basically based in on the expected reward and the expected risk, you have to do your position sizing. And so the most important thing there is figuring out based on whatever it is that you're doing, what your sizing is going to be. And generally speaking, the best way to do this is um um is to use the the Kelly criterion, the which is the optimal trade sizing criterion, and then take a very small fraction of that. >> What is this? I'm not. the the Kelly criterion is basically um if you have a series of trades, a series of wins and losses, what percentage of your capital should you risk on each trade to get the maximum growth. >> The problem with the Kelly criterion is that if you actually follow it, your draw downs are like 95%. No one's going to live through 95% draw downs. But the nice thing about the Kelly criterion is that it is in some sense statistically reasonable. And because it's statistically reasonable, what you can do is say I don't want 95% draw downs, but I'm willing to live with 45% draw down. Say, right, if you're long the stock market, you're willing to live with 55% draw downs actually. So, um, you say fine, I'm willing to live with 55% draw downs. So, I'm going to have my position set up such that my maximum expected draw down when lots of things go wrong is 55%. >> Say, so that's how you size your positions. So you you've already thought about your worst case series of trades going wrong, everything not working out the way you want it, and you've sized your position such that you're not happy, but you can live with it. >> And why not take the opposite approach, which is just standardized risk for every trade type uh to kind of even out the highs and lows. So that's effectively what you're doing when you
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