The Godfather Of Technical Analysis Your Stop Losses Are Costing You More Than You Think

TITLE: The Godfather Of Technical Analysis: Your Stop Losses Are Costing You More Than You Think CHANNEL: Titans Of Tomorrow DATE: 2026-06-30 ---TRANSCRIPT--- This man spent 45 years quantifying what actually works in the markets and was the only winning researcher of the Charles Dow Award in 2020, the highest annual honor in technical analysis research. We statistically showed that any type of stops that were put in place degraded the performance of the methodology. We’re not the only ones that think that way. Stanley Druckenmiller, arguably the greatest trader of our time, he said, I’ve been trading for 40 years, I’ve never used a stop in my life. Anything can blow through a stop. If something crazy in the world happens right now, you’re going to get filled as a market order. Introducing Larry Connors, author of over 25 trading books, pioneer of the 2-period RSI, and founder of one of the most prestigious quant research firms in all of finance. Shorter-term RSIs, 2, 3, 4-period RSI, we create our own Connors RSI. What they’re really doing is they’re measuring fear. They’re either selling the market off because they’re concerned about some sort of event, or they’re just pausing the buying. What is the mechanics of the RSI that you created, the Connors RSI? I can, um, probably give an example of there are usually no edges in first-order thinking. Things that are basically obvious where the potential alpha comes into place is if you’re immediately able to move into second-order thinking. Okay, after you have your first-order companies, what else is required if you really do believe that AI is going to play itself out? Power is required. Data centers are required. We get into third-order thinking, it gets even harder. There I was looking at Duolingo. Even I was able to program the AI to teach me how to speak another language. And I’m looking at this and I’m saying to myself, they’re dead. They’re providing services that can be done by AI for free. If AI is going to win, if AI can provide these free services, who can’t compete against that? My background was I got hired at Merrill Lynch out of school, so I got an opportunity to really learn how to play the game from some of the best. And I had a bread and butter setup that was there that I pretty much used over and over. But I remember we hosted a New Year’s Eve party and I’m sitting at the kitchen table and I’m saying to myself, you are the oldest 34-year-old on the planet because we were trading right into the close and it was just, I’m not going to do this for another 30 years type of thing. What kind of a temperament or personality type does it take to thrive in that arena? I’ve seen so many people succeed and I’ve seen even more people not succeed at it. Usually it comes down to one thing. They— Hey Titans, we have a huge episode today that is with Larry Connors. Now, if you don’t know who Larry Connors is, he’s one of the most exceptional minds in the trading space, one of the most impressive guests that I’ve ever sat upon. And after the episode itself, I have to say it’s within my top 3 episodes of Titans of Tomorrow that we’ve ever done. And in preparation for today’s episode, Larry actually presented to me one of his key frameworks, something that he’s never published before, which was a huge honor. And this is his power laws, how he’s able to get the most out of the markets, the ways of thinking, the strategies, the mindsets, the execution types that minimize your downside and have have extreme upside. So what we’ve done for you today inside of the Titans Inner Circle is prepared for you today’s episode companion, which is Larry Connor’s 25 books, today’s episode, and his entire career insights distilled down into an episode companion. This resource is for you to download for free inside of Titans Circle alongside all of future guests and also previous guests, so you can get more out of each episode. If that sounds interesting to you, click the link in the description for free to join Titans Inner Circle. Without further ado, let’s get into today’s episode. Ladies and gents, welcome back to another episode. Larry, thank you for joining us. I think we have a lot to unpack, but you are the first guest to give me a framework that I believe you haven’t really shared online before. So this becomes a very nice way to set a foundation and a theme for the conversation. Before we do get into the power law of trading, which is your framework, I want to first get into alpha. Now, this is a term that everyone is hunting for, but I, I think you would have some unique takes. I want to throw it as an open question, uh, is the job of a trader to achieve alpha? Well, the job for an independent trader is to make money. Ideally, do it for a consistent period of time. If they’re fortunate enough to be able to do it for decades at a period of time, there’s a lot of work that goes into this. If there’s not alpha in place, if they can’t do better than the market averages, I usually recommend buy an index fund, do a 60/40 if they’re looking to make 5%, 6%, 7%, 8%, 9%, 10% a year. That’s a better place to be. Ideally, the job, at least for independent traders, retail traders that are not managing other people’s money, is really there to maximize. It’s to compound your capital. A few ways that we could look to maximize and compound is either beat the benchmark, create alpha, or get the equivalent of the benchmark, but minimize the downside. Instead of having a -30% year, let’s say, and then spending the next few years trying to recover your deficits, it’s have the benchmark without the downside. Which side of the fence would you be on? Well, having run two funds, it was the latter part is more important. But now that I manage my own money, it is to maximize the returns each year. Is that more related to your personal risk appetite? At this stage, yes. Yeah. It’s very much to maximize returns. That’s interesting. Time, you’d be like, I’ve got this capital, I’ve built a whole career trying to accrue it, let me now get into preservation state and not necessarily compounding state? Yeah, that’s a good question and a good point you make. Are you familiar with the barbell strategy Nassim Taleb came up with in 2007? You know what Nassim Taleb, The Black Swan? The barbell strategy basically, I’ll keep it simple, 80% of ones 20% of money would be placed in something risk-free. Bonds, okay. T-bills. Keep it in short-dated T-bills. The other 20% is there to max returns, is really there to be able to do that. Taleb has basically made a career out of this. A lot of people have embraced this. A lot of successful people have embraced it. There’s also peace of mind that’s there, that no matter what happens in the trading or things that go on, You know that 80% of your capital is liquid and is safe. As long as the US government stays in business, you’re okay. There we go. Curious now. So there’s many types of trading, and I’ve got a familiarity, but then you also threw a curveball at me, which is you don’t look at charts. So I need to then understand, first of all, systematic or discretionary? Which one would you be? I used to be fully systematic. Now it’s a combination of the two. Okay. Why the transition? Especially a good number— a number of our strategies are thematic in nature. Okay. And before we started this, we were talking about AI. So, you know, I mentioned December 2022. Yeah, December 2022 was when I came across ChatGPT. Could see immediately, you know, I was fortunate enough to be there on the internet side and could see, okay, this is game on again. This is really going to change the way things that are there. You can’t backtest a revolutionary technology. Okay? So every few years, and depends upon what industry that you’re looking at, but in this case, on a pure technology basis, there’s a revolutionary technology. There’s no backtesting that could be done. And if you take a look at people, for example, who use fundamentals, who use systematic fundamentals that were there, they very likely missed this phenomenal move that has happened in the AI stocks over the past couple of years because they were pricing things on a lookback basis, not on a revolutionary technology basis and what was going to bring out. How did that affect your decision making, or is that in the framework? It’s in the framework. Okay. In that case, let’s kick it off. So the Power Law of Trading. So if you can give me an overview of what this framework is. Yeah. If you want to read one at a time for— Sure. So we have the investment philosophy. Do you want to start off there or you want to get— You can start with number 1, which is Dhandho. I think that would be helpful. So number 1 is long strategies, thematic investing, new revolutionary technologies. Yeah, you can. If you go back a little bit higher, you’ll see the philosophy that’s there. It says Dhandho. Okay. At the top. Yes. Dhandho, which is heads I win big, tails I lose little. Yeah. Asymmetrical gain. Yeah. Yeah. So that comes from Mohnish Pabrai. The name of his book is The Dhandho Investor. Probably has had the greatest influence in my thinking. And I’ve been fortunate to be around a lot of great traders over the years and then over the decades. I don’t know Mohnish. I mean, I read the book, but it immediately resonated with me that structuring positions in such a way that heads I win, tails I lose a little, and that has had a major influence on there. A lot of things end up— you can end up on a philosophical basis, you can end up making decisions in your life just based upon ask. Okay, with this decision, is it heads I win, or when tails I lose a little, or just the opposite of that? Hey Titans, let’s take a quick break from the episode to talk about a sponsor and partner of the show, that is Ola Prime. Now, a lot of traders have been talking about Ola Prime because they were recently the winner of the fastest payout prop firm award in the IFX Expo here in Dubai. And something that you don’t see so often is that are backed by their own brokerage firm, Ola Prime Markets. And a few things that I love about Ola Prime is that they have offers for futures, forex, and crypto traders. And most importantly, they allow you to trade on over 8 platforms. And further, they do a 95% profit split, basically unheard of, which means whatever profit you make, you keep 95% of it. And most importantly, because of their award, they’re one of the only prop firms that offer a 1-hour payout through a structured 10-point 1-hour payout system. Your payouts are practically on demand, which means you can spend more time on the charts trading withdraw your profits, and go back to the markets. With all these steps, measures, and awards in place, they are truly redefining transparency and trust in the prop firm space. So if you want to work with a prop firm that you can trust and a partner of the show, click the link in the description or use the code TOT for Titans of Tomorrow to get the best prices and discounts that I’ve personally negotiated for you guys, our Titans of Tomorrow audience. With that being said, let’s get back into today’s episode. Is it a wrong assumption to think when you have asymmetrical gain or a high risk-reward play that naturally it’s inversely correlated and you would have a low win rate? Or can you have high win rates and high risk reward in free lunch? Yeah, the win rate is going to go down for sure. It will absolutely go down. Because what you’re doing is you’re structuring trades in such a way that you’re risking one unit, everything comes into a unit size. You’re risking one unit. It’s done with options. It’s done with long options. You can sleep at night, you know exactly what that position what you can lose. But if you’re long calls, for example, theoretically, the price can just run to an unlimited number. In the real world, that doesn’t happen. But you structure positions in such a way that you’re risking one unit with the goal of making many units that’s there. If you do it in verticals, you know what that max you can make. I’m not a big fan verticals, especially with revolutionary technologies, because no one knows just how far these stocks can run. And we’ve seen this now all the way through with this AI cycle. They just keep going and going and going. Companies that I would have never imagined, things that I had positions in, would have moved up as much as they moved up. And even right now, you know, as we’re speaking, Micron Technologies, obviously memory is an important part of AI. For those traders who’ve been out there for a few decades, they know the history of memory, they know the history of Micron. It’s a cyclical stock, runs up, run, then it goes down for a number of years, and then it runs back up. Micron has moved from, I believe, $100, it’s now above $900 a share as we’re doing this. We got into it only a few months ago at $400 with long options, so this 500-point gain that’s there. And if they’re going to price this from a cyclical play, which remember, it was always cyclical, to a secular play, meaning this is going to be inherent in AI, they need to reprice Micron. I nor anyone in the world knows just how far that stock could go. It could reverse back down, or it could go up. We’re talking hundreds of points. It could literally go up thousands of points. When we talk about a— when we talk about price going up, initially it could be driven by the fundamentals of it, the industry and the revolutionary technology, but then it can be extended further towards what we would call a bubble, which is then euphoria, hype. Sorry, we have euphoria, hype, and then it can just get overextended, and then you start to think, should I mean revert? Should I start to take profit out? Or you can also think, the market can remain irrational longer than I can remain solvent, and you just ride the wave. How would you position yourself when you’ve already got the extended move now And now there’s a— you’re looking for asymmetrical gain, but the gain to hold is maybe now negative risk reward because you can forego what you’ve unrealized to gain maybe a little bit extra. And maybe the asymmetrical goes to now symmetrical to then the other way. Sure, sure. So there’s a couple of answers. So you asked a couple of questions within that one question. That’s very good. You know, number one, The worst thing, if you’re looking for asymmetrical gains, the worst thing you could do along the way, worst thing any trader can do along the way is chop off those gains. Stress, you need to be there. Two of the companies that I was in last year, I handle a number of fairly large books, so I can have 100 positions on at any given time. Amongst the two largest gainers last year were companies I would have never have thought they would have run. One was GEV, GE Vernova, and the other was Palantir. Okay. And as they kept going up, first I didn’t know GE even spun off Vernova. That was there. The AI identified that. Palantir at $30, it was overpriced. At $40, it was overpriced. At $50, it was overpriced. And I don’t know what the high was. I think it got to $180, $190. So one never knows just how far it’s going to go. Being in the options and especially being in the long-dated options, it gives a chance to be able to run. One of the points you’re making there, it is greater risk because what’s happening is those options are moving. Hypothetically, let’s say you paid $20,000 total, your position is $20,000 total. If that’s now a $200,000, it’s moved up 10x, are you going to risk $200,000? On a hypothetical million-dollar portfolio? Are you going to put it at risk with one stock? And that’s where protection comes in. And I’m a big advocate of basically going in and buying protection there along the way. They’re out-of-the-money puts that basically says no matter what happens to the stock, if it reverses significantly, if the bubble’s going to burst, however it’s going to be there, I’m going to be protected. This is the minimum I can make with those puts. Okay? Usually, people, especially the audience, and the style of trading we would have is we have a philosophy, we’ve generated a trade idea, then trade execution, we’re in. Then we have a stop loss, which is to protect ourselves, where it seems like you’re not using a stop loss or even a mental stop loss, you’re using hedging systems to protect your downside. What’s the reason for this? Well, we published back in 2009, got a lot of interesting comments about this, but we statistically showed that from, I believe we started the test results, might have gone back as 1985.— and we used the S&P 500 stocks— that any type of stops that were put in place, whether it was 1%, 2%, 5%, we literally went up to 50% stops, which is really not a stop, degraded the performance of the methodology. We’re not the only ones that think that way. If you take a look, Stanley Druckenmiller, who’s arguably the greatest trader of our time, 30, I believe it’s 30 consecutive years of profitability. He was George Soros’s head trader that was there. He has this— I keep this picture up there. He said, I’ve been trading for 40 years. I’ve never used a stop in my life. So he’s averaged 30% a year for 30 years, audited performance that’s there. Other people that are out there, Ewan Sinclair. I’m going to mention two authors that people should read their books. Ewan Sinclair, another gentleman’s name is Hari Krishnan, that’s literally his name. Each have PhDs in physics, each have serious institutional bank test experience, large hedge fund experience. But if you take a look at, I believe it’s Sinclair especially, he basically shows that it’s better to pay the theta decay than to have a stop in place. Because the reason there is that anything can blow through a stop. If something crazy in the world happens right now, those stops, you’re going to get filled as a market order. Isn’t the idea to have a stop to prevent yourself from being victim to an unforeseen circumstance? Sure. After doing this for 45 years, it’s better to have puts in place. Very interesting. The next question for me therefore becomes is we had another guest on the show that I really enjoyed with Rishi Narang. And he argued the same thing. And he said, actually, think about it. If you’re entering a position and price goes down against you and where your stop loss would be, wouldn’t the logical thing be to actually add more if the underlying reason for you getting into the position has not changed? Yeah. That actually makes a lot of sense. Yeah, it does. The other thing that people don’t— on the surface, it makes a lot of sense. And I know a lot of traders, successful traders that do use stops. When you run the test results, when we’re running test results, we’re running things like in that example, there were millions of sample size, were millions and millions over many market regimes that were there. What they’re doing is on a mean reversion basis, for example, they’re missing out all the times you get stopped out, and then it goes higher and gets stopped out. What they’re doing is they’re missing the moves on the upside, and they’re accumulating losses there along the way. I found it to be, especially over the last few years, far better to basically have those puts in place and most importantly, let those positions run. As much as we’ve all been taught, take things off the table, no one ever went broke catching a register, one leaves too much money on the table, because you just don’t know how far any of these stocks can move. HARI KRISHNAN] For some reason, this doesn’t feel intuitive to me. The reason is we’re betting on an outlier scenario that it just keeps on running. But apart from a unicorn, or in this case, revolutionary technology, along your career, would it not be a larger opportunity cost of things that you were hoping would keep on running, but then go back to your breakeven, and therefore you left money on the table on large increments? It happens. Yeah. I mean, ideally, if you’re setting up, if you’ve got a large enough move, that’s there, and that has to be identified ahead of time. That’s all part of the systematic part. It basically assures that the gain, a portion of the gain is locked in. But sure. How would you do this? Would you use, let’s say, an EMA to trail your position? So there are certain things— and there’s certain things that I work with a group of about 50 professional traders. We get together once a month. So there are certain things that basically, out of respect to them— OK. Fair enough. You’re in the ballpark that’s there. Cool. I want to get into the next part, which is asymmetric trading. It’s similar to the first one where it’s win big and lose small, but then it’s risk one unit to make multiple units. How would this differ from the previous point? It’s the same point. It’s very much the same point. The majority of my portfolio, both on the long side and short side, is looking to basically risk one unit with the goal of making multiple units. Even after doing this after 45 years, nobody can predict where things are going to be a month from now, 2 months from now. Right before we came on here, the semis moved significantly. They just reversed. And who knows what got announced that was out there. When it comes to position sizing, before I get into the question, I want to understand, would you grade a setup? Would you have something that you can consider A+ or high conviction versus lower conviction? And is the lower conviction but still worthwhile? Still has an alpha inside of it, is it still worth trading? Or are you— because you’re looking for the asymmetrical gain, you’re specifically waiting for high conviction plays and then loading up risk? Yeah. So it depends upon the strategy. I’m trading multiple strategies, both on the long and short side. There’s different timeframes that are going on over there. On a high conviction basis, there are certain strategies that’s there, especially on the short side. There’s going to be limitations as to what’s there. When we’re shorting and going into positions, in no way do I believe these companies are going to go to zero. In a couple of cases, that they do. But we’re looking to basically capture that sweet spot for whatever reason that’s there. But go back and— I’ve got a couple of thoughts on this. Go back and ask that question again, because I want to make sure I cover both. Okay, yes, it was regarding when you want to— because we got into risk. So before I understand what is risk one unit, because then it would be okay of your account size or whatever the case may be. I want to understand before the risk, it’s the conviction, because it’s how do you determine a thesis? Because you’re not looking at the charts, but there is many pillars. It could be fundamentals, it could be sentiments, it could be XYZ. And then those amalgamated together, would you try and make it quantitative and grade each things? Because a lot of things can be subjective, like the fundamental side of it. How do you quantify something that is a subjective thing? And then as a result of that, how do you determine conviction and therefore risk? Usually, the risk is a dollar amount, which is a percentage that’s usually predetermined ahead of time. And it’s very rare that I’ll go into something that’s high conviction. At the end of the day, I, like everyone else, have opinions on things. And I can’t tell you the number of times I have had trades that were basically put in front that should have been there and absolutely there. And I overruled them, didn’t take the trades. The stock would end up going. There are other trades that have gone on there along the way. I would have bet anything that this can’t miss. And they did miss. So try to do equal position sizing. Did get a little bit heavier with Micron, did go a little bit heavier on that. I believe the initial risk might have been 1.5 times that was there. But this is basically a little bit of discretion where it’s coming in. If per chance this was going to move from a cyclical valuation to a secular valuation, it had a long way. And if, you know, if it does play itself out, um, if it does move secular, it has a long way to run from here. No predictions, I have no idea where it will go, but I want to be there. The main thing is to be there if it does play itself out. 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So standardized risk makes a lot of sense to me, but I do meet a lot of traders that, uh, uh, on high conviction plays size up. And they usually give me this idea that 80% of my profits come from 20% of the year. When the market is hot, you gotta go in XYZ. Um, this brings me back to then discretion, because how do you do that systematically? Uh, and then you do see a lot of the legendary traders we hear about, they are discretionary traders. It seems you are more systematic now. Becoming more discretionary. But can we start to unpack what is discretion and where is the right place to deploy it? Because in your case, it’s not necessarily on risk. Yeah, the discretion— again, going back to the example that I gave on the thematics and revolutionary thematics that’s there, that can’t be systematized. I think we were talking about that earlier, maybe before we came on the air. But in 2022, December 2022, when I first got on ChatGPT and said, okay, this is the internet all over again. If that was going to play itself out, how would I be able to go run a backtest on these companies that were there? And even back in 2023, there are a number of questions there along the way, valuations. NVIDIA was overpriced. That was there. There’s a very well-known professor at NYU who is on the corporate finance side, well-respected, has written a number of books on valuations. And he went out to CNBC and he felt NVIDIA at the time was at $400 and change. It’s before it split 10 for 1. And he said Nvidia was worth $250, which would be $25 in today’s— and we’re over $200 a share. So in looking back, he was doing his job. There’s nothing wrong with that, but there’s no backtesting to be able to do that. So that’s where you’re really on a thematic basis, you’re building your positions, working with the AI. We work very closely with the AI to basically identify what those positions could potentially be. We build our positions in such a way, risking one unit with the goal of making many units for the times that they do have those moves. Very nice. Let’s get into now the first principles, which is undeniable truths. Markets go up, markets go down. How would you be using this? Been doing that for a number of years. And very much first principle thinking, just for everyone to know, is very much undeniable truths. That’s there. Musk has built all his businesses around first principle thinking. He doesn’t have an engineering background. He doesn’t have anything in space. Type of background, SpaceX is going public here tomorrow. He builds from first principles up. Bezos does the same thing. So first principles are undeniable truths. What’s an undeniable truth for the market? Markets go up, markets go down. Okay. What happens there is that’s where the heavy lifting begins. Okay. If markets are going up, what strategies are going to be traded? How are they correlated to each other? How are you putting together those strategies? And the short side, how are you putting together your strategies there? On the short side. I run a fairly delta-neutral book, which is basically I come in most days, and they’re really— unless there’s something crazy that happened overnight, I’m pretty much sleeping comfortably. So, I’m not really making any prediction of where the market’s going to go. And I’m not running a market-neutral, it’s a delta-neutral, but I’m balancing my deltas. To basically come in fairly neutral each day. Again, this is me coming out and saying, no one can predict. Maybe some people claim they can, maybe they can. I’ll say I can’t predict where the market’s going to go on a day-to-day basis. If the job of a trader, as we earlier described, was to make money, hopefully through alpha, and predict where price is going to be to do it, what would be the correct framework if it’s not to predict price? Structure the trades in such a way, basically, to— it gets into a fairly complex system, and it’s got to be done at a step at a time. But it’s structuring your trades in such a way that if there’s some— if they have a reason to be bullish on the market, it’s basically putting together positions in such a way that in case they’re wrong, first, they can predetermine what the dollar risk is. That can be done with long options. And number 2, what happens if they’re wrong? And what I do is I hedge all the way through. I hedge out to a degree market risk, industry risk, and even on an individual stock basis, I’ll hedge out the risk. And it’s not completely hedged out. I mean, hedging is going to cost money. You don’t want your hedges to pay off at the end of the day. Hedge is going to cost money, but what that does is basically balance. It allows for balance to come in and smoother returns over a longer period of time. With first principles in mind, let’s talk about some myths or speculations of what could be first principles, and then you can agree or disagree. One would be Buy Low, Sell High with the pendulum of fear and greed. Yeah, true. I’m not going to argue with that. Okay. The reason I mentioned this one is because buy low, sell high obviously seems like a timeless principle, but then a lot of people do end up trading momentum or breakouts, which naturally, relatively speaking, is buying high. You’re not waiting for the retracement, you’re waiting for the breakout. What are your thoughts on that style? So there’s a few thoughts. Number one, if anyone goes in and uses AI and looks at my background, What will happen is because of things that are published over the years, it’s very much going to have me on mean reversion systematic trader. I haven’t published as much over the years. And so, that was very much the way I traded. It was mean reversion. That goes all the way back to the ’90s. Systematic was there. We always kept a portion of the money, anywhere from 10% to 20% for special situations. That was there, but it was mostly systematic that was there to go along the way. I’m really not a big believer in lumping now— are you a mean reversion trader? Are you a trend following trader? There’s cases to be made for all of those. And I can keep going back to a couple of examples, Corning Glassware, for example, once on AI. Came in, obviously optics were going to play a role. Corning Glassware is an old company, has been around for decades. My grandfather owned Corning Glassware. But if optics were going to play a major role, which they do, they play a major role in AI and the buildout, they were going to be one of the prime winners. That’s there. By the time we got into Corning, I think we got in $60 a share on the options. I believe I still have the calls on them. It had already moved up significantly. So one looking at the charts, one could say, well, that’s a momentum trade. That’s a trend following trade. That was a thematic trade. That was basically— that’s when we identified it with the use of AI. We identified it, built the position on it. I wish I could say I was smart enough last August to say, yeah, I knew the stock was going to triple. It was going to go from $60 to $180. Of course, I didn’t. But the position was built. And that became an outsized return, which we’re still in. You take a look at Micron. Micron was at $100, got in at $400 with the calls. It hit $1,000 the other day that was there. But from $100 to $400, 25 years ago when the internet came around, there was no way in the world I would have been in that position. And when AI came about, One of the things I did was, what are all the mistakes that I made when I was trading during the internet days that was there? So I would buy a stock at $6 and it would open up, literally open up the next day at $9, jumping up and down. That’s 50%, take it off, and then watch the stock run literally to $50, $60, $70 a share. I did not want that to happen again. And that’s where the power law comes into play. The power law guides the venture capital industry. What they do is the venture capital firms that have been around for decades, they’re making multiple— take multiple positions that are there. Many of them go to zero. There’s a handful that will do, let’s say, okay. But where the real money is made is when they’re there early stage for Google or for Amazon. Now SpaceX with going public, some of the early investors that were there. If they had sold out along the way, they left a lot of money on the table. You really need to be there, just let it run, let it run, let it run. Okay, I want to also segment the reasons people would get into a trade, whether it’s fundamental, technical, etc., could either be camped into, uh, correlation-based things that come to mind as just an indicator or a moving average or Fibonacci versus causation. Now it seems to me, especially a lot of the professionals I’ve spoken to, they seemingly be in the correlation camp, especially for technicals, and I always wonder why, but how would you segment correlation versus causation in the markets? Let’s isolate it on the correlation side. It’s a big issue. I refer to it, I gave you the framework that was there. Beneath that framework, there are some of the things that we do on a day-to-day basis that basically go on, including the measurements, including the Greeks. But under correlation, next to it, it says the silent killer. Okay. People don’t realize how things are correlated. That’s there. I don’t think the industry has done a very good job in showing correlations. They’re still teaching it the way that it was taught in the ’80s and ’90s. It’s found its way into textbooks. But there is, there is, there is an immense amount of correlation that’s in place at any given time. So you bring up a really great point and I can probably give an example of just how correlation, just how extreme it can get. So in 2008, after Lehman busted, that was their September, October 2008, markets went into a freefall. Okay. Great financial crisis occurred. So you have your ETFs and then you have your inverse ETFs. Good. Okay. If the ETF went up 3%, the inverse theoretically for the day should go down 3%. ETF goes down 3%, the inverse should go up 3%. There were multiple days in a row, and it would be good for the listeners, they can go back, look at the charts there on the inverse ETF. There were multiple days in a row that both the ETF and the inverse ETF dropped. Okay? And the reason for that? Everything became correlated to each other. It was a need for cash. There were margin calls, there was liquidation going on all over the place, and it was a grab for cash. Anything that had any type of liquidity, they were selling. Okay. And it offered phenomenal, phenomenal opportunities for a short period of time. You know, we got a chance to take advantage of a few of them, but I have some friends that really were able to take advantage of it during that period of time. So correlations can seize, you know, can really move together. One of the things that I teach, and I’ve been teaching this now for 20 years, is that traders should be looking at dynamic correlations. And what that basically means is, I know still inherent to some degree, correlations may be quoted on a 2-year basis or a 3-year basis. Well, that’s not right in my opinion. They should be done on a shorter-term basis and then blended. So you might have a 3-month correlation, a 6-month correlation, and a 12-month correlation that blends together to give the numbers. They end up using it more as a static indicator, meaning they set the date and that’s it. It should be more dynamic than that. And it should be shorter dated because things, especially in the markets, we’re one big global market. Things can basically become correlated real fast, faster than ever. With also correlation in mind, where I was in my head is why does a support level seem to work at times? Why does a Fibonacci— why does a 200 moving average pinpoint respect? Because there is— there shouldn’t be an underlying reason, but it does. So then it begs the question to me, is it just something that’s self-fulfilling? Because if everyone believes, everyone acts on it, then it becomes— which then does sound good, but then I also think, well, the market is supposed to be zero-sum, so it’s player versus player. So if everybody is acting one way and then it does happen, it’s not zero-sum, it’s everybody won together. Then it breaks down this concept. What is going on here? Well, we’ve been publishing the 200-day moving average since— and quantifying it since I think I first did it in 1999. Back then, technical analysis in that sense of using a 200-day moving average, they didn’t use it. It wasn’t there. What’s interesting is that Someone who was my co-founder in one of the companies, he was the head of trading for Fidelity Capital Markets. And it was rumored that in the ’90s, it was rumored that he and his 92 traders were moving up to 10% of the volume on the New York Stock Exchange. Okay. And he said within Fidelity— and I don’t have this, this is basically just repeating a story that was there— they used to have a room, a chart room. Okay. All these fundamental analysts that would be there, everything was done through phone, but they would know where the 200-day, where the 50 was. They had all the charts that were up there. Now, the marketplace knows those 200 days that’s there, 50 is also another popular number that’s there. But now you’re also playing on the other side. The quant hedge funds know this, high frequency knows this, they’re going to be playing off that. Some of it is self-fulfilling, yes. But if one just simply traded off the 200-day moving average, and look back over a sustained period of time, it doesn’t net out to— there’s not alpha in there. I finally have a special offer to share with all of you from the US, or my futures traders, which is over 20% of the listeners of the show. And that is Alpha Futures, a leading futures prop firm that is working with Tradovate and NinjaTrader that are compliant with CME regulations, with the largest end-of-day balance drawdown in the industry, a 90% profit split, and same-day payouts. And with the most competitive pricing in the industry, with accounts starting at just $79. On top of that, just by being a viewer of the show, you get up to 40% off all evaluations. So why not get started with an evaluation right away, trading $50,000, $100,000, and you already know the power of prop firms and larger capital. So go ahead and use the link in the description or code TOT for the best prices in the industry plus the best discounts in the industry to make this a home run offer if you are a futures trader. Is it a correct belief of yours that you believe greater alpha/dislocation/asymmetric opportunities exist when there is maximum greed or fear in the market? Yeah, very much. How would you look to quantify? Would it be through technicals? Is how you understand greed and fear? Yeah. If you take a look at the— when I first published, it first started as a 4-period RSI and published it as a 2-period RSI. I think it was back in 2003. That was a dead indicator. Welles Wilder created it back in the ’70s. He did some brilliant work that was back then, but it was a 14-day.— and I know a lot of charts still default to 14-day— we couldn’t quantify it. It just really couldn’t quantify it. But one afternoon, I was working on my Bloomberg terminal. Bloomberg just had tremendous amount of data in there. Living on the West Coast, so a lot of free time in the afternoon, markets close at 1:00. And I started seeing that as I was shortening the RSI period, I could start seeing pattern recognition. I could start seeing that this was beginning to move with the on a mean reversion basis, especially when these stocks— but I should say, especially SPY was above its 200-day moving average. What I’ve ultimately learned from that is that those shorter-term RSIs, you take a look at the 2, 3, 4-period RSI, we create our own RSI, Conners RSI. What they’re really doing is they’re measuring fear in the marketplace. What’s happening is that One of two things, they’re either selling it off, they’re either selling the market off because they’re concerned about some event that might be going on out there, or they’re just pausing the buying. Portfolio managers will say, you know what? PPI is coming out, CPI is coming out, unemployment’s coming out this week, Fed’s making a decision tomorrow, I don’t need to buy today. I’ll wait till after the decision to do this, especially if they’re buying in size and going to be holding positions. So that’s in a sense measuring some sort of fear. They have a fear of that event. What will happen is, again, because of the lack of buying, the RSI will sell itself up, will come down to some sort of levels. So using RSI very much is, in my opinion, is less to do with technical analysis and more to do with the fact that it’s a measurement of fear. We’ve shown to be able to do it with VIX. 30-day VIX, if you take a look at the shorter-term VIX that’s out there, but also 3-month VIX, 6-month VIX gives tells as to what portfolio managers and how they’re positioning themselves that are in place. Those are ways to measure fear. Then there’s other traders out there that basically can put on CNBC and they’ve been doing it long enough, and they know that this fear that’s there. What is the mechanics of the RSI that you created, the Cardas RSI? Yeah. So, without going into the details, because it’s in the public domain, anybody can look it up. We made it available for free to be able to do it there. So, you’ll see the 3 components that’s there. And for those who are using Bloomberg and— a handful of other platforms have it built in there. They’ll be able to, they’ll be able to use it. Cool. What is the way that you’re generating trade ideas? So I know we’re talking about, um, you’re looking for asymmetric gains, you’re looking for revolutionary technology, and let’s say you’ve generated a trade idea, uh, with the thesis behind it. How do you execute upon it? Yeah, um, number one, it’s important not to overpay for the options. Okay, so The second layer after that is after the decision is made is how are they pricing the options? The advantages you have that when we’re holding positions, I’m a big believer in time horizon diversification. If I’ve got a thematic in place, I might buy a 6-month, a 1-year, and a 2-year, hypothetically, that’s there. If I’m doing a shorter-term trade, especially things on the short side, I have to be more precise in making sure I don’t overpay for those options that are there. So implied volatility is going to play a big role. And if I can get fair pricing that’s there, certainly, want to take the trade. If something is just— let’s say earnings are coming out tomorrow on the company, implied volatility is going to be spiked. I’m not going to take that trade. I’m not going to overpay to that degree. So, it really is looking— the trader should be looking at, am I paying fair value for this option? Is it overpriced? And to what degree is it overpriced? If you’re looking at a couple of years, 1 to 2 years, it’s okay to pay a little bit more. On a shorter-term basis, probably one’s putting themselves in the hole. They don’t want to be overpaying for volatility. With the idea that you’re looking to hold this for a long time and you’re looking for huge asymmetric gain, I guess the exact execution is not going to make a difference. You would just rather get in rather than wait for complicated intraday models to get in. Absolutely. Yeah. Fair enough. Again, if the option is fair valued, it’s— that position is going to get put on. It also has to get filled, some of these positions, there’s wide spreads. What type of size can you put in? Sometimes you have to work the trade, which means it may take a couple of days to get the position on. But again, probably the best suggestion that I can make to everybody, make sure you’re not overpaying for the option, especially on a shorter-term basis. Good. The next one, number 5, is applying first and especially second and third order thinking. So this would be different to first principles. Yeah. So as you know, as we were talking before we got going here, let’s go back and use AI for example. Let’s go into 2023. So first order was going to be you have to own the semiconductors. Okay. So it’s going to be NVIDIA, it’s going to be Taiwan Semiconductor, it’s going to be Advanced Micro Devices. You can go through the first order companies that are there. There are usually no edges. In first-order thinking, things that are basically obvious that’s there. Unless you’re really, really early on it, we’re pretty much all wired to think in first order. Where you start getting edges in place, where the potential alpha comes into place, is if you’re immediately able to move into second-order thinking. And Wall Street traders have gotten better and better at this. 20 years ago, this type of thinking was usually a handful of hedge funds would would know to automatically do this. But second order thinking is, okay, after you have your first order companies, that’s there, let’s say the three I mentioned, what else is required? If you really do believe back in 2023 that AI is going to play itself out, what’s required? Power is required. Data centers are required. So that second order thinking basically allowed us to get into— I say us, it’s really myself— get into positions that were there. That were in power-related companies, that were in data center companies. And, you know, you may ask, you know, how do you come up with all this knowledge? How do you come up with all this information? Knowing how to properly prompt inside the AI, AI is able to do this. Now, this back in ‘23, I think we were on GPT-3.5, you know, and now it’s 5.5. You know, we use Extended Pro. But it was able to basically identify companies that I nor even if I had a research team would’ve taken us weeks to find, able to do it instantly. Vertiv is an example that just keeps running and running and running. GE Vanover is another one. Those were identified back in 2023. So that second order thinking is a good way to be able to do that. Okay. When we get into third order thinking, that gets even harder. Okay. And third order thinking, can be the suppliers to the suppliers. And that is— you usually have to wait that out. If you’re doing good third-order thinking, you’re usually going to have to wait that out. We’re waiting for the marketplace to realize, oh yeah, this company is going to benefit. The company is basically showing— they’ll come out a quarter or two quarters down the line, and they’ll show this rapid growth that’s there. Maybe an expansion in the gross margins. The way I primarily use it is if this is going to win, meaning if AI is going to win, who’s going to be on the other side? Who’s going to lose? Okay. And that’s really where on the short side, those provide great shorting opportunities, especially if you’re there early to be able to do it. Would you apply first, second, and third order on the contrarian side too? If AI is going to win, who’s going to lose? And then first, second, third order all the way on the losing side too? On the losing side, it really became pretty obvious. It was fairly obvious. And in a few cases, I was way too early. Okay. I’ll share that story with you because oftentimes, if you’re correct, you’re usually early with it. Okay. But on the third order side, there were certain things that were there, it was quite obvious that as GPT and a few others were bringing out the images and the graphics and things like that. Companies like Fiverr were going to get hit. That was obvious. But I went through a couple of option cycles not making money on Fiverr because the marketplace hadn’t caught up. And then all of a sudden, it did. I believe it might have had the 30 puts. It was somewhere in the 30 range. Stock, when we exited, was at $11 a share. AI, they can’t compete. Many of those services that they were advertising on the Fiverr platform have been obsoleted. They could be done for free. Others were on the education side. Another one is on the legal side. LegalZoom was low-hanging fruit. It was quite obvious that many of the baseline services that LegalZoom was doing, AI was able to do it and do it for free. That stock has gotten hit very hard. The one I was wrong on early on, okay, Duolingo. So are you familiar with Duolingo? Okay, great company. And there I was looking at Duolingo. And I could see that even I was able— I’m not a programmer— even I was able to program the AI to teach me how to speak another language. And I’m looking at this. And I’m saying to myself, they’re dead. Most of these education companies were— Coursera had gone down, Udemy had gone down. Chegg had gotten hit first. Chegg was the first one that was there. I felt Duolingo could miss. And this is the difference between going in and having a short position, having protection in place and not. I think I had shorted at $175 with puts. And the stock proceeded to move up to $500 a share. And as I was going, my options expired worthless. And as the stock is going higher and higher and higher, I’m saying to myself, what am I missing? Really, what am I missing here? Again, I work pretty closely with the AI. AI is basically dug in as they’re— you’re not missing nothing. You’re really— they can’t compete. I’m not going to pick a top on something that would just keep racing and racing and racing. But ultimately it broke and it lost a couple hundred points pretty quickly. I was able to put on a short position that was there, meaning on puts, rolled them a couple of times. I still think I have a little bit of position in Duolingo, but the stock is trading at $100. It got under $100 a share. They’re providing services that can be done by AI for free. That’s number one. I understand they do a lot of AI that’s in there. The gamification is great. The community is great. They had brilliant marketing in Brazil that they did on TikTok, and that really brought on a tremendous amount of business for them. But I’m not looking to take Duolingo to zero. What I’m essentially doing is looking at it. If AI is going to win, if AI can provide these free services, who can’t compete against that? Now, today, many of those stocks have sold off significantly. Earlier this year, we saw it on the software companies that’s there, and they’re still trying to figure it out. I’m also in that camp. Who is going to win on the software, on the software side? Like, who’s going to be able to transition on the eugenics side? And who really is just providing services and processes that are in place that, you know, Claude just dropping, you know, Phi Phi, bring out a cable, Fable, you know, can’t make a difference. Well, with AI able to replicate and replace, in the case like you’re saying with Duolingo, the idea makes sense, but then But the things that are hard to quantify is, as you were saying, community, brand, marketing, the entertainment element of it, gamification. How would you consider these things? Or is the philosophy, well, I’m not trying to make it go to zero, so I’m just trying to get a reprice? Yeah. Having been doing this for 45 years, I’ve yet to meet a short seller who was successful waiting it to go to zero. So they may exist out there, but we don’t wait for it to go to zero. I’m not taking those pieces into place. What I’m really looking for— it’s a great question that you just asked— I’m looking for waning, w-a-n-i-n-g. I’m looking for waning demand. I’m looking for demand that basically, they’re not going to be able to maintain their growth. And over time, many of these companies were growth stories. If they can’t grow, the market punishes that. And if there’s going to be less and less users over time coming in. Again, I’m looking at it over a longer-term period of time. It doesn’t mean that they’re going to go out of business, but at the end of the day, waning demand is not a place that momentum buyers or growth buyers are going to run up a price of a stock. What is the art of timing a thesis with the idea of mining? I don’t want to tie up capital because it’s an opportunity cost of not deploying it elsewhere. Yeah. One fairly simple indicator that basically gets me into these positions. I’m looking for price to basically tell me, okay, they’re beginning to move out of there. Okay, what I’m never going to do is I’m never going to try to pick a top. Okay, I want some price confirmation that, that will be there. Um, so that price confirmation is basically, okay, this potentially— they’re beginning to unload the stock, they’re beginning to move it out, and that ends up giving the signal to be able to do it. Another thing, you can just do it if it’s on a watchlist. Company comes out with earnings. And basically, you start seeing the demand waning that’s there. They’re not going to come out and just say, we’re going to lose to AI. You know, these are run by very smart individuals, the publicly traded companies, you know, especially the S&P 500 companies. Those people run the companies. They don’t get those positions unless they’ve succeeded in their life. They come up with solutions. The board of directors are constantly talking about this. But at the end of the day, if they can’t compete, you can’t compete against free. For example, if there’s waning demand that’s going to come in there, it’s going to show up in the numbers somewhere in the numbers. And during that earnings thing, you’ll see, you’ll see it there. The market is pretty smart. The market will price it down fairly quickly and that will often trigger the opportunity. It’s already gone down to a degree. It triggers the opportunity, though, that the selling may continue. We saw this in the software stocks. Over the last 5 months. Because then the next part of the framework, um, is long, short, and protection. How would you like me to unpack these with you? How are you doing? What’s best for the listeners? Well, the, the bridge that I’m thinking as we’re going through this conversation to help cross towards the audience is most traders are going to be day trading, and they’re going to be most— I mean, the viewers are going to be primarily technically driven. So we’re actually on the opposite side of the spectrum with yourself. So Either we can also talk about your beliefs on what do you think of this? Is it worthwhile? Because a lot of people are also not finding success in doing so. So we could either ignore it as a topic and keep going into your strengths, or we could go into, okay, what are they doing right or wrong here? Yeah, whatever you think is best. I think let’s touch on it just to hear your thoughts and expertise, because I’m sure at some point you’ve considered it, or you’ve probably seen a lot of people thrive or fail in trying to master day trading with technical Yeah. So, I come from— my background was I got hired at Merrill Lynch out of school and finished up my career on that side at Donaldson, Luftkin Jenrette, DLJ, which is just absolutely phenomenal firm, got bought out by First Boston and Credit Suisse. So, I got an opportunity to really learn how to play the game from some of the best that was there. Very fortunate to get hired by those two firms. It was basically when I came into the market, I think the Dow was at 700. Okay. Couldn’t have timed it better. All right. So we were compensated quite well. Okay. And good lifestyle, able to live in good places, moved out to Malibu, California before it became crazy. So across the street from the beach, it was a very comfortable lifestyle. I don’t come from that upbringing. I come from a traditional middle-class upbringing that’s there. To go from that, to be able to move over to there’s no more income coming in. I went out, started my own private partnership. Plus, I had separately, the futures were traded separately. That was there to supplement my income. The futures trading was there that was mostly day trading. Almost all day trading. Okay. And I had a bread and butter setup that was there that I pretty much used over and over and over again. So over time, that bread and butter setup, the edges have dissipated. If I try to do it today, others have figured it out that was there. So day trading is a hard game. For myself, I found it to be mentally hard. That was there. Okay. And I remember after the first year, it was a good year. It was successful. Needed to be successful. Had 2 children at the time. Now I have 3. Got a great lifestyle. And there’s no income coming in. This really has to work. But I remember we hosted a New Year’s Eve party that year and we had neighbors that came over. And I’m sitting at the kitchen table. And I’m saying to myself, you are the oldest 34-year-old on the planet, okay? Because we were trading right into the close. There were things that were going right into the close. And it was just, I’m not going to do this for another 30 years type of thing. So day trading, you know, some other people that I know who have done it for decades, they’re wired to be able to do that. Okay? So one really has to know You know, what kind of a temperament or personality type does it take to thrive in that arena? I don’t know. I’ve seen, um, so many people succeed at it, and I’ve seen even more people not succeed at it. Um, usually it comes down to one thing: they usually have greater risk controls that are in place. I, you know, you know, I know you’re a big believer in this, that But from what, in reading about you, you’re a big believer that if there’s not an edge in place, nothing is really going to matter. 100% spot on, very much agree. So they have some sort of edge in place. What may not necessarily be the entry that they have in place, it will be some sort of exit strategy that’s superior out there. We worked with one gentleman, got a chance to see him trade live. He’s a futures trader that was there. He had a systematic entry that was in place and then a discretionary exit. Okay. We went in, we backtested his systematic entry that was there. He entered every position in the hole, meaning he had a negative edge. Okay. Yet there he was year after year, at least to see that on the exchange that was there. It was a year after year putting in substantial performance. What was happening is he had his exit strategy, which was more discretionary, was superior. That was there. So that’s where his edge was placed. He might have thought his edge was in the entry. If you quantified it, it wasn’t. It was his exit. I find the tension between edge and psychology very curious, because prior, my beliefs of psychology is something that’s overspoken about, and it’s usually a scapegoat, because you don’t have an edge, but it’s easier to blame your psychology. But as I’ve gotten older, I’ve realized that a lot of it does tie back to psychology. The reason I say this is because I think I would have a hard time, uh, interacting with the markets like yourself, because I think I am a little bit impatient in the sense of if I’ve got this huge idea and I’ve tested it and I’ve put a lot of time and effort to generate this idea, and then I place it, I want to kind of know if I’m right or wrong soon, as opposed to waiting months, even, even years. Absolutely. Which kind of caters then for me to the instant feedback loop of, um, day trading. But then the other side of it is discretionary on profit-taking. So this is something I used to do, and then I started to realize, well, what are the, what are the things that I’m targeting? And there can be many technical levels on a screen. You can have 10 lines on a chart, and all of them have a reason. How do I decide? Well, then discretion. But discretion can just be something like fear and greed masking as a good idea, which then became the problem. So then I tried to make everything as systematic and data-driven as possible. What is your interaction with your own psychology and then fundamentals, technicals, and everything else for trade ideation. Yeah, I very much relate to you because the majority of my career was spent as a mean reversion trader. The sweet spot of mean reversion is that 3 to 5 trading day window that’s there. We’ve quantified it, we quantified it for decades, we’ve published a number of strategies. For as many as we publish, we probably have 5 to 10 more. For every one, there’s 5 to 10 more that we haven’t published for whatever reason that’s there. So you get this instant feedback on a mean reversion basis. It’s basically, you know, it’s there. This type of style of trading where a power law trading where you’re waiting for things to play themselves out and one never knows, it just doesn’t happen overnight. Early on, it just— you if you’re committed to it, which obviously, I’m committed to it, you learn to live through these times where there’s going to be drawdowns, there’s going to be periods of times that there’s going to be periods of times that basically, maybe make a little, lose a little, that will be there. Just coming out of last quarter’s earnings, it was amazing how many positions I was in on the wrong side of earnings. And even to the point that got so ridiculous, I actually texted my assistant who doesn’t know anything about trading. I actually texted, I told her, I said, I cannot believe how many times I’ve been on the wrong side. And the returns are good for the year. I’m really comfortable with where they are. And they’re on target of where my target is for what I’m hoping to achieve for the year. It was earnings after earnings. I maybe told her this at about 3:30 in the afternoon, last 30 minutes I’m trading there. 4:01 comes, company comes up with earnings, boom, it just gets crushed again. And I said, consistent as hell. And it’s like, you learn to play it out. It’s basically— early on, it’s hard, but if you’re doing it for a period of time, and you believe in it, it gets easier and easier and easier. And it really is nice when it’s right. All it takes is a few trades to basically play themselves out to be able to do that. There’s another part to that when it’s on. So I had this happen last year, one of the quarters, probably 65% to 70% of the positions I was in, wrong side of earnings. Okay. The next quarter, probably 65% to 70% was on the right side of earnings. That’s there. It tends to balance itself out. So it’s a belief in the methodology itself. Do you think it’s more important to build— there’s many ways to make $1 million. There’s many ways to find edge. So therefore, is it more important to find an edge or a style that’s congruent with your personality, or it’s find something that makes sense theoretically, and then your psychology can be molded around it? First, absolutely the first. Does that therefore imply that there is a bit of rigidity in what is your own temperament and psychology? And yes, you could put in frameworks and systems and meditations and whatever, but it’s not usually going to be a needle mover. Yeah. Um, the, the, the The wiring, I’ve worked with a number of traders along the way, a number of floor traders, both from the New York Stock Exchange and also from the CBOE or the Chicago Exchanges would hire me to mentor them to teach them how to trade off the floor. Very much enjoyed doing that for a number of years. And to see the success a number of them went on to have, that was there. But they all had different temperaments. They all had different things that they go through. There is no right or wrong temperament that’s there. One needs to know themselves. For myself, it very much fit me. Reversion trading very much fit for me in the ’90s, in the 2000s, and even in the decade after. It became, as I started building out this framework that we’re talking about over here, I became more and more comfortable with it, was able to basically apply, to take strategies that I had never published before and then bring it in. And then you just learn to get better and better and better at it. It doesn’t matter how many years you’ve been doing something, especially with trading. I wake up every day as day one. I need to learn something new. I need to get better. I need to get better. And I don’t need to get better for financial reasons that’s there. That’s the way I’m wired. And with the markets always adapting, I think it’s even more important that people are just constantly learning and learning and learning. And the final part to that is studying things, for example, that were published 20 or 30 years ago, or learning things from floor brokers that basically were buying on the bid and selling at the offer, and it’s still inherent being taught by the brokerage firms and being taught by others. I know they’re well-meaning, But I don’t believe someone’s going to put in consistent substantial returns year after year after year from strategies that have essentially been obsoleted or been arbed out. This is an important point. A lot of episodes we haven’t published, and it’s because I get this feeling of like you had your golden era, and now you’re living off that with your public reputation. Absolutely. Is curious to me because you do see certain principles that are timeless, certain technicals that people are still trading and believing in that were published decades ago. And now even, it was a question I had later on, but we can bring it now, which is you have like a pendulum between efficient market and inefficient market. And as we approach efficiency, there’s less or there’s more effort to get alpha, and therefore people don’t put the effort in, and that swings the pendulum the other way. And then there’s a lot of alpha and XYZ. But then as we move towards AGI and as a lot of people are harnessing AI, alpha would become more odd out and harder to find. I then do wonder what is the future of the markets, and especially these timeless technicals that everyone’s trading, what happens then? Yes, good questions. You’ve got a couple of questions in there. Take the first part of your question for us. Re-ask that again, because we can do this one piece, one step at a time. Yeah, we can start off with efficient and inefficient market as a pendulum. Is this an accurate way to view the market? Yep. So, this is the advantage that retail or independent traders have here today that didn’t exist before. What’s happened is it’s a very dynamic industry. The industry is constantly adapting, constantly bringing out new product sets there. When I started trading, I think options traded on a quarterly basis. It was then monthly, weekly, and now we have our dailies. There was no such thing as leveraged ETFs. The market is continuous. Continuously or the industry is continuously innovating to be able to do there. With that, and this got brought on especially thanks to Robinhood, COVID played a role in it, that it brought in millions. And I think Robinhood’s platform is somewhere between 27 and 30 million traders alone in there. A lot of retail traders that may be very intelligent, they could have advanced degrees, they could be doctors, you go through the whole thing. But they don’t have market intelligence. They don’t have the experience for people who have been doing this for many years or people who are trained to be able to do this. There are a number of retail products that are essentially been brought out there. And those retail products provide opportunities. You’re really trading— these are products or markets that the institutions and the hedge funds can’t trade in because because there’s not enough liquidity in them or won’t trade them for whatever reason, the risk managers won’t allow it. Hedge fund industry has changed significantly. When I was doing it back in the ’90s, if you walked in with 30% returns a year, it was like, “That’s good. You’re the 10th person we’ve seen today that has done 30%.” That doesn’t exist today. Today, if you take a look at Millennium, you take a look at Citadel, if you take a look at Point72, What they’re doing is they’re putting in 1% on average, 1% to 1.25% a month, but it’s consistent money all the way through. If you take a look at the risk parameters that’s there, they pull money pretty quickly from the pods that they have in place. Teams that will be in place, they’ll give them a certain amount of money. If they draw down, depending upon the firm, they’ll cut it in half. And if they draw down for any sustained period of time, They’re gone. It just basically gets replaced. So they may be amongst the best risk managers in the world. If you have the ability to invest in a Millennium or Citadel, Point72, there’s a number of these firms. What that leaves open is because they’re so risk averse, they can’t, for example, trade this power law strategy that’s there. They can’t go through months where. There’ll be months where it won’t make money. They can’t go through months. The Sharpe is going to punish the upside moves. There’s outsized months that occur over there. So TINA is going to become high, but they’re answering to sovereign wealth. They’re answering to pension funds. And what do the pension funds want? They want that 11%, 12%, 13% net of fees year after year after year. No one loses their job allocating money to these firms that are there. That provides the independent trader with the opportunity to go places that the hedge funds can’t go to. That’s number one. Number two, with all the many millions of newer traders that have come in, they don’t have the same expertise and knowledge. This conversation that we’re having right now, they wouldn’t even begin to understand probably two-thirds of it. They provide mispricing all over the place. You can see it in the option markets. There are a couple of Thursdays ago, there was volatility that was floating around out there. And you can see from the size, it’s retail orders that were there, 100% vol selling for 500. And I will not take that trade unless if I get hit in this trade, will this mean that something else in the portfolio will flourish from it? But when you see things like that of retail traders putting in orders at 500% vol when it should be priced at 100 vol, right? Maybe a simple example is that you have a piece of property, it’s worth $100,000. And someone says to you, “I’ll give you half a billion dollars for it.” Okay? You’re probably going to say done to be able to do that. So I could go through this, an endless list of them. There’s inefficient ETFs that are out there. AI can help people find those inefficient ETFs. There’s ETFs we were talking about before that are built to go to zero. We published that back in 2009, 2010. VXX, UVXY, UVIX. Take a look to boil on natural gas that’s there. Now take a look at the many 2x futures-related cryptos that’s there. BITX, which is Bitcoin, 2x Bitcoin futures. ETHU, 2x Ethereum. Go through the list that are there. They’re structurally built to go to zero. They’re rolling option. They’re rolling futures on a monthly basis. This is structurally inefficient. And really what you want to do— market makers are smart, they price that into the option price. Ideally, you want to have some indicator that will be able to trigger, when can I be entering this? Where’s it safe to enter this? And you just really want to be there. If you take a look at BITX, and what’s today, June 11th? Is that right? Today’s June 11th, I believe. 10th. 10th? 11th, sorry, you’re correct. Yes. So today’s June 11th. If you take a look at the decline that BITX has had over the past couple of months, it’s just been going down and down. Obviously, Bitcoin has been going down, but also, they’ve got a structurally inefficient— you’re getting this tailwind that they have to sell low and buy high month after month after month while it’s in contango. The conclusion I’m getting from this is, let’s say the institutions for better or worse are incentivized to be mediocre. Look, just get the 10%, 11%, 12%, and you’re not really rewarded for being or chasing alpha beyond this. Therefore, you leave pockets of inefficiency, and therefore the edge for a retail trader is actually in where you trade, not how you trade. Yeah, I don’t know if I would classify him as being mediocre. One of the funds that we ran was a low volatility fund. It was built that way. I’ll tell you, it was harder to do do 7%, 8%, 9%, 10% returns a year and make money most months and have a high Sharpe ratio, let’s say a Sharpe ratio of 2. I found it harder for doing that for many years versus what I’m doing now, which the returns are, knock on wood, at least up through today, significantly higher on an annual basis. They know what they’re doing. They’re providing a phenomenal service. They’re running Brilliant people, they’re running. It seems paradoxical, but why is it harder to make consistent but less gains rather than consistently over decades making larger gains? Yeah, there’s no room for those losses that will occur there along the way. Someone is trading on a mean reversion basis. If you take a look at any of the books that I published, and many of those strategies continue to hold up, they got to be done on a trade-by-trade basis. Some people have moved them into a portfolio, which is— no matter how many times I said in the books, these are not portfolios, these are individual trades. They still run on a historical basis and now running 3 decades and even up to 4 decades, 75%, 80%, 85% correct in price that’s there. What happens, though, to the 10%, 15%, 20% that are not right? You’re not making a lot on the mean reversion trades, but you’re making it often. There’s a lot to be there. It’s what happens when there’s a sharp market sell-off. August 2011 is an example where mean reversion got hit pretty hard during that period of time. How do you protect from there? And maybe it’s just tied into decades of experience. Maybe it’s just tied into knowledge, maybe it’s tied into the fact that I have no one to answer to, just myself, but I do find it easier, psychologically easier to be putting in much higher returns than doing that 8% to 12% and keeping that Sharpe ratio ideally above 2. Would you argue that technicals, if you correctly find an edge, is the best place to find the consistent gains? Gains? Restate that, please. Right now, when we’re discussing the asymmetrical gain and the kind of outsized returns that you’re able to achieve, is because you’re betting on the right things, uh, with— as the world changes. But if I was to think, how can I achieve, you know, 1% a month consistently for decades? Would the best way to do that be strictly technicals? No, no, it would be strictly money management. It would be how you structure your trades. And there were not many good books out there that basically talk about structuring trades. It’s a boring topic. You put on CNBC all day and no disrespect to the many guests that they have on CNBC. I know a handful of them and I’ve actually worked with one of them for a number of years. CNBC is basically which stocks are going up, they’re focusing stock, stock, stock, stock, stock. If someone was sitting there and saying, well, I’m going to have this stock and then basically go into option land on how they’re going to structure that trade, and then how they’re going to put in hedges in place, that doesn’t fit the narrative. So there are not many books that are out there. You asked me earlier if I ever thought of writing any more books that were there. That’s an interesting topic to me. Another interesting topic is correlations that would be there. But to answer your question, it would absolutely be done through the structuring of the trades. It’s done on the money management side, as long as there’s an edge in place. The other part of the earlier question that I had, which is how— there’s two parts, but the first part I want to get into is technicals that don’t seem to expire when everything else in the world has changed. Tell me what you’re thinking. I lean towards, um, two things. One is that, uh, the self-fulfilling thing that we mentioned earlier. Number two is, um, from a retail lens, it seems like everything is about technicals. Maybe it’s because just when we search online how to trade, these are the things that often come up. But when I look at the professionals that I’ve spoken to, technicals is often an afterthought. And even when I, I proposed it to you you’re not focused on the entry. It’s just, I got to get in somewhere at the right time, but plus or minus a bit is not going to make a difference on the net gains I’m going to make. So then there isn’t time or effort or energy spent there. Plus the idea that everyone is following similar things just makes it a strong, strong tide. Yeah. Um, so you’re basically stating that technicals may play the least important role in things, uh, to, to professional or institutional guy, yes. But it doesn’t mean it’s right or wrong. It just means they have the more significant capital that influences the market. But yes, I would say that. Yeah, I agree with that. And I’ve agreed with that since the 1990s. I didn’t become a CMT. And I know the people at CMT, they’re good people that’s there. There are a number of CMTs. They do a good job. For me, as I began the process, I registered, was going to become a CMT. And when they’re putting patterns in place, whether it’s trend lines, head and shoulders, or all the things that we all originally learned from when we first started that’s there, if I couldn’t quantify it, I had issues with it. Because it just— for me at that time, I needed quantification in place. I needed to see statistical evidence. And today, this is much more common. In the ’90s, it was basically looked down upon that that was there, people were doing this. The quants weren’t known as quants, they were known as system vendors. Nothing worse to be called than a system vendor. But thanks to MIT, thanks especially to Andy Lo, Professor Andy Lo, and he’s done tremendous— the first generation of financial engineers, the first generation of quants were born. Out of MIT and very much thanks to Andy. So for technicals, for me, RSI, for example, is a technical indicator. Okay, we’ll be lumped under a technical indicator. But as we were talking about earlier, for me, it’s a fear indicator. It basically is a measurement of fear in the marketplace. And then it could be quantified. That’s what we did with Conners RSI. Conners RSI, was the first and still may remain the only technical indicator that has quantified results behind that. And people, they can find it online. We made it free. We made it available so they can download it. They can see the formula. They can go back into the testing with it. You know, again, for me, it really does provide— with that said, I have friends who are quite successful, been doing it for decades. And they’re chart readers, they read charts, they’ll read something that’s there and have been able to stay in the game and done quite well for themselves for many, many years. So I’m not taking anything away from chart reading. It doesn’t work for me, for myself. Reading between the lines here, I’m assessing that technicals for you is more a representation of human psychology And therefore, as we trend towards more AI utility in the market, will that be eroded or will that still remain ever-present because it’s still a human deploying an AI-generated idea? No. If you want to segue this into the AI, it might be helpful, but I’ll leave it up to you if we want to segue this into the AI. I think it’s important. Okay. Yes. Okay. So there’s a few things with the AI and as we were speaking before we got on the air, So I saw ChatGPT, as I mentioned, December 2022, and said, okay, this is going to change things. I used it as a knowledge base that was there. I don’t program. I don’t— haven’t had the need to program. My director of research was literally the senior developer of Excel in the 1990s. His name is Cesar Alvarez. So he’s brilliant. That was there. So I never had really a need, been able to surround myself with good, good programmers. Gentlemen that basically, you know, the company that is handling our area and building out the AI and the gentleman who leads it for them is doing a phenomenal job. Okay. I don’t need to get involved with that. I just see the end result and see, you know, you know, want to make sure that it’s working on the AI side where people stand today is that most people don’t understand that the output from the AI, number one, is going to be biased. I’ll get to that second. Okay. Number two, it’s very much dependent upon the model that they’re on. Okay. And I’ll use ChatGPT for an example. That’s where most people start. They changed the user— the UI— interesting— overnight. But up until now, there are 7 different levels. Of ChatGPT. Okay. You had Instant that was there and that was free to everybody. Still is. You have the thinking models and the thinking models was the 5 series. And that was a big advance that they had over there. That was a big breakthrough that they had within the thinking models. There’s a— I think it’s called— there’s a fast thinking, then it defaults to a standard, then it’s one that’s extended, and then there’s the highest level that’s there. Then if you pay $200 a month, and I strongly suggest that anybody who’s doing this for trading and taking this seriously pay the $200 a month, it’s the best $200. Altman also announced earlier today they may lower the pricing. So we’ll see if that plays itself out. But within there, there’s two other levels that’s on the pro version. So there’s the highest level is pro extended. It. Okay. Pro Extended is usually going to take between 12 to up to 20 minutes to get an answer to be able to do that. What we published, I presented this a couple of weeks ago, I put that there was there with the group that I work with, is that was able to show, and this is the AI basically showing it at what grade level. So, you know, for those who are not in the United States, in the United States, the grade level is is, you know, kindergarten through— grade 1 through 12 is high school, then university or college is another 4 years, master’s would be another 2 years, PhD would be 4 to 5 years. That’s there. Okay. People who are using GPT Instant, which is the free version, are getting the equivalent on a trading question— I specifically kept this to trading— okay, are getting the answer, the equivalent of what an 8th or a 9th grader. Okay. An 8th grader today would be answering. It’s there for the masses there. It very much is there. Do you want to trade? Do you want to put your money at risk? With an answer from an 8th grader, right? You get into the thinking models. And as you go up, it keeps moving up. It will move up. But even at the highest level of the thinking model, what it’s doing is it’s giving to you as a first or a second year finance college student. That’s there. Again, at the end of the day, do you really want to be, you know, they have some knowledge, but do they have that type of knowledge that’s there? You move it into the extended, okay, into the Pro version. And the highest level, the Pro, is the extended version. What you’re beginning to get is you’re beginning to get answers at a PhD level. Okay. So now think of where we are. Same question, ask the exact same question. Depending upon which of the models you’re going to get answered by an 8th grader, or you’re going to get answered by someone with a PhD. Okay, that’s the first part. Okay. Where most people look at and use AI today, this will likely change. But where most people have been using it is they use it to ask questions. They use it as a chatbot that, that’s there, ask a question, get, get, get an, get an answer that’s over there. What AI does better than giving answers. It’s a better falsifier. And we as traders want truths. We want to get to absolute truths that’s there. Okay. A lot of the books that have been written out there, there’s a lot of things that are basically discussed. There’s a lot of things that have been outdated. It’s a lot of things that have been arbed out. We want to get to the truth. Simply putting in, ask that same question and telling it to red team, red, just red team it, which is the most basic falsification. Very, very basic falsification immediately lifts the cognition to a much higher level. Everything jumps up a few grades that were there. Okay, that’s the beginning. And then just keep using it. You know, you were mentioning the way you were using it before we got on the air in Claude. You’re using multiple levels of falsification that’s there. What that’s doing is that’s getting better and better answers, getting better and better truths. At the end of the day, even if it goes to AGI, this is where domain experience comes in. On the trading side, I have the advantage on that. 45 years, been able to work with some of the best and got to know, got a chance to write a book with arguably one of the best traders being Linda Reschke out there. Linda and I still remain in touch. That’s my domain. I have domain knowledge. I can go back in my memory into things that I did in the ’80s, ’90s. I can piece things there together. That’s an advantage I have on the trading side. If I came in from another— ask that same— ask basically a question on something that I don’t have domain knowledge, I’m going to get an answer that’s likely going to be a 9th or 10th grader, and I’m not going to know the difference. I have no domain experience. I encourage people, run with what you know. Okay. And that really is, if you’re going into trading, for example, trade— if you don’t come from a finance background, if you come from an entrepreneurial background, sold a business, knows a certain industry in place, they have such a competitive advantage over the rest of the world. They know things inside. They have unconscious competence. They have the highest level of mastery that’s there. And if it’s in real estate or no matter what the industry is, whether it’s biotech, real estate, I could go through any of these. And I’ve worked one-on-one with a number of these people. And most of us take for granted, well, if I know it, everyone else knows it. And, you know, very much they can go far, far deeper having that domain knowledge. So number one, get your bottle down, spend the $200. It’s worth it. Number two, 2, use it to get to the truth. Okay. Red team at a minimum. Okay. And then GPT will give other suggestions to be able to advance the red team. And then number 3, domain knowledge is a must. Okay. A doctor, for example, using GPT is going to be able to go far deeper than, you know, I assume you don’t have a medical degree. I’ll speak for myself. I don’t. Yes. Okay. So they’re going to be able to go far deeper than the two of us can. It makes sense. Therefore, for me, the question becomes, in utilizing AI as a trader, is it in testing your beliefs and just having, you know, someone to brainstorm with, but then you don’t have the ability to decipher what is good and bad because of the domain knowledge you were mentioning? Or is it better using as a tool to backtest and other ways to interact with AI is basically the question. Yeah, both. And I can address these. What the, what the AI does, and Claude did it. Claude, I’m a big fan of Claude, but Claude does it the worst. There’s confirmation bias there. Okay. So they’re going to tell you how smart you are, how handsome you are, how this, how that, how brilliant you are and all the things that’s there. Someone that I work with and he just picked up, he’s prompting at a good solid level, but he’s, you know, he’s still learning there along the way. Claude told him that his prompting exceeds what it sees from— what was the firm that they basically did? It was either Citadel or one. Yeah. Number one, it doesn’t know what’s talking to anyone at Citadel. Number two, Citadel is not going to be putting the prompts in there. It just hallucinated. Just basically just told them that was there. There’s ways to be able to do that. Telling it in the prompt, be brutally honest. Will get it to straighten it out to some degree. All right. It will still basically tell you all these things about yourself. But what you’re looking to do is basically, you know, you want to get it away from that confirmation bias. If you allow it to have memory, which mine does have memory, I have 2 years, now almost 3 years of conversations that it has memory of. I’m sorry, it’s about 2 years. That’s when they start allowing the memory that goes in there. So So it pretty much knows me inside and out. It knows the way I think and those things that are there. I have to be very careful that it’s not telling me what I want to hear. Okay. And I think we all do. It really is a way to basically utilize AI at a higher level. It’s also a phenomenal teaching tool that was there, all the holes that I had. Fragmentation that I had in options knowledge, I was able to within 3 months pretty much move myself what I would consider to be on a professional level, an intermediate level trader up to professional level knowledge, but I’m getting feedback continuously because I’m going into the marketplace, seeing how it played out, put it back in the AI. So, these are all ways that it could be there. AGI will never be able to, at least in my opinion, will never be able to take the domain authority and knowledge of anything that I haven’t published, for example, or that hasn’t been published out there. It only has things that have been published. I’ve spoken to a variety of guests on the show, and a unanimous common denominator between all of them is the emphasis they put on data and actually knowing the inner workings and the insights of your edge and your performance. 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Do you think, um, because now AI becomes a wonderful way to empower yourself with more and more knowledge and diversify your level of knowledge, but I do wonder, does— is that a worthwhile pursuit in the sense of does more knowledge equal better trading performance? 100%. 100%. I, you know, I can’t guarantee performance. Nobody can. You know, we’re, we’re an industry, but there’s a stronger correlation. Yeah, yeah. I mean, you know, we’re not, we’re not in physics, so it’s the, the is that’s there. But absolutely, knowledge plays a major, major role. And that knowledge has to go— that knowledge really has to go beyond what has already been published that’s out there. It’s connecting dots and putting things together. And you have the top part of my framework that’s there. A lot of pieces to it. Yes. Well, let’s refer back to it. So I’m curious because you mentioned it before, and it is jumping a bit, but the convexity side of things. Yeah. So, we can start with first on the hedging side. As I mentioned, I’m continuously looking, constantly looking out, how can I hedge out market risk? How can I hedge out industry risk? Obviously, AI and optical, that’s there. I have memory. So, I can hedge it out with the ETFs to be able to do it to a degree. And how can I hedge it out to such a— point that I’m not hedging out all the potential gains that’s there. You can underhedge, you can overhedge. They are both things that continuously get working on. Convexity plays a big role because if you take a look at the great wealth creation done in short periods of time, they were done from convexity trading. That if you go to the original Market Wizards books, there’s only one options trader in there, Tony Saliba. Tony’s brilliant, had a phenomenal career, phenomenal business career also. But Tony was long convexity when the market crashed in 1987. And he was able to do that. We jump ahead to 2008. ‘08, if you take a look at John Paulson, he was long convexity from the great financial crisis that’s there. Jump ahead to 2020, yeah, 2020, Bill Ackman was early readings on COVID. He’s there in New York City, was basically able to build convex positions. How does one build convex positions? I’ll keep this simple. I’ve been through a few market crashes. ‘87 was the first, so you see how these things play themselves out. What happens there is that you’re building a certain percentage of the portfolio. Usually the recommendation is 1% to 3%. I’ll go up to 5%. I believe I have enough alpha in place that I can go 5%. I want to be there in a market crash. It could happen this year, could happen next year, might not happen until next decade. It’s going to cost. It’s done by basically having far out of the money I’ll use this example, SPX or SPY calls. Let’s say it’s SPY. They would go out into 2027, go out into 2028. They’re going to be ridiculously out of the money. The S&P is in the 700s. We’re talking about buying things in the low 500s, 400s. I even have options that go out, I think a couple— it’s more than a couple of years that that are in the 300s, that’s there. Long vega, long volatility. Market sells off, that’s there. Those things can potentially, depending upon how the portfolio is structured and depending upon how heavy one is, those things can make a year, can make a year, can make a decade. They can make a career. I have a handful of friends that literally in different industries at different times that were always long convexity that made generational wealth from one trade because they were long convexity. If you take a look at some of the— I mentioned Ackman. He’s done it successfully at least twice. Another phenomenal hedge fund manager, billionaire hedge fund manager, Seth Klarman, deep value investor, but he uses convexity. Panic plays a big, big role that’s there. The other thing that happens is if there’s a substantial sell-off, S&P, you know, SPY goes from the 7s down to the 400s, implied volatility is going to be spiked through the roof. Okay? Those options are going to have gone up likely many, many times what you pay for it. It could be 50 or 100 times what you pay for that. Now, there’s no liquidity in the marketplace. There’s all this panic in the marketplace. The risk managers have shut everything off. Is they’re in protection mode, that’s there, and you’re providing the liquidity. You’re flush with cash. You can convert those options, cash them in. And now let’s say you have a favorite stock and it was trading at $60 a share. Well, it’s now at $20 a share. Maybe the fundamentals didn’t change, but it’s at $20 a share simply because they had to get rid of the stock. They needed liquidity that was in place. So now you have a second potential profit center. You get your portfolio protected on a big sell-off, may turn into a substantial once-in-a-lifetime sell-off, plus you can go long. You have the liquidity, you’re the buyer at that place. I’m willing to give up up to 5% a year. 5% of your account or 5% of your gains? 5% of the account. Oh, okay. Yeah. Usually, the recommendation is 1% to 3%, but I believe I have enough alpha in the strategies that— Again, this is— I can see why it’s called a power law. When— it’s not if, it’s when it happens, it becomes a huge opportunity. Very interesting. Have you been able to do this in any previous crashes or something you recently started to think about? Inadvertently, without the knowledge of knowing it, I was able to do it in ‘87. In the ‘87 crash, there were all sorts of signals that it was there, that this thing was— this bull market that had been running up since 19— I think it was ‘82 at bottom also, it was pretty much a 5-year run. So I was long options at $1, $2. I just loaded up, really loaded up. I was in a position to be able to do that. None of my children were born at that period of time. It’s still my money. And I was loaded. Options that I bought for $1 opened up on Monday morning $20, $25. So it was 20, 25 times the money. It was a substantial At the time, it was in ‘87. I was still in my 20s out there. I think I was 28 years old. And there’s this avalanche that was there. Here’s the mistake I made. I just grabbed it. It was like, done. If I waited to the end of the day, those same options were trading in the 60s. So where I made 20 times the money in the morning, if I had just simply held a piece or held the whole thing until the end of the day, it was trading in the ’60s. So I’ve been able to witness it. And also fortunate enough to know a handful of friends that have been able to do it in other markets. One of them did it in the— it was either the coffee market or the orange juice market. But he was on the floor. He was in his 20s at the time. And he was long convexity. And there was a freeze. And it was up limit day after day after day after day after day. He was in his 20s. He’s now 55 and still going, but it was generational wealth created from one trade. So it’s actually— it’s a new concept to me, but it’s very interesting because now I can build a career trying to grow my accounts, or I can just use that as a vehicle to then one day have this big generational wealth event. Yeah. Nassim Taleb, that’s his— he’s author of a number of books that are out there. Was a floor trader and a brilliant mathematician and statistician. So, they have a fund that basically, this is all they do. It’s there for the crash. So, they’ll go years losing money to be there for that time that it makes— literally, they’ve had quarters, at least reportedly have done thousands of percent for the quarter. It’s not something I could do. I’m looking to basically compound my account at a fairly healthy rate. I don’t want to wait around, but I certainly want to be there if and when the next one comes. I’ll be there. Very impressive. The next part is portfolio construction, which is a nice segue to what we’ve spoken about. This could be 1% to 5% of your account. Count towards this Black Swan event opportunity, how would you construct the rest of your account portfolio? There’s a long side, there’s a short side, there’s a hedging side, and then there’s a convexity side. My rule of thumb is I don’t risk more than 1% in a position. This is why I’ll often have— I can handle 80, 100 positions at a time, I will use leverage to be able to do this and plus with the option, I’m getting I’m getting greater use of capital to be able to do that. If I’m wrong, lose a percent, not a big deal. You could be wrong 5, 6, 7, 8, 9, 10 times. It really is there to be able to do that. That 1% will make a difference on the options. If I was outright trading equities, for example, if I was going to take a position, that 1% is not going to make a dent. I could be dead right on something. It could end up doubling. If it doubles, I made a percent. It isn’t there. Risk management and position sizing there, it’s an individual choice to be able to do this. My children are now all grown up. They’re doing well, but while they were growing up, my responsibilities were different. I needed to make sure there were private schools. We lived in good areas. That was there. And I really needed to make sure that I wasn’t putting capital at extreme type of risk. Everyone knows what’s— the question they need to ask is, what is best for them at that given period of time? Interesting. Yeah. And then where is the net worth? How is it sprinkled around? It could be in businesses. It could be in real estate. It could be there. There’s no one rule of thumb, for me, it’s 1% per position max. Because you’re not using a stop loss, are you just sizing for zero? I’m sizing for zero. I go into every trade assuming I’m going to lose 100%. Got it. Yeah. I’m never disappointed. Fair enough. This is actually a nice point you mentioned, which is diversification outside of the markets with— because previously, when you were in employment, you had a salary, then I guess that acts as a nice cushion. But now when it’s your money. And not a fixed salary tied to your profession, does that add a burden or does that make it more difficult? Or do you now use cash flow in terms of property as the replacement? Yeah. So up until ‘94, I was— yeah, I started in the industry in ‘81 and up until ‘94 when I went off on my own, right place at the right time. We were well compensated and DLJ especially compensated us quite well. I enjoy business as much as I enjoy trading, and I love trading. I also very much enjoy business. I enjoy business models. Along the way, I have built multiple businesses that’s there, they can go through different stages there. Some of that will play a role depending upon if the businesses were funded or if I self-funded them, depending upon with the liquidity if there was an exit event, others have just been unwound. We let them basically unwind. There’s 2 of them that still pay royalties from things that we did many, many years ago. But at the end of the day, I view my primary source of revenue coming from trading. But again, it really goes into everyone’s psychology, the thought process of it. You know, how important is it to the family, you know, whether there’s some sort of maybe family money in the background. Um, you know, in my case, my, my parents were working people. And, uh, yeah, curious what drives you at this stage in your career where, um, you, you were considering your children’s— your responsibility towards them. Now you don’t have the same weight on your shoulder, but then I wonder if you are still driven by money, because you’ve also authored a lot, and therefore it seems like you want to be contributing to the industry. And you are— seems very pensive through this conversation. So I do wonder what drives you at this stage in your life. Um, you know, the, the game is always there, play to win, okay? It’s, it’s there. Um, you know, a little bit of it is that if I’m going to take something up, I’m going to basically try to go as far as possible. I’m not good with hobbies. Um, I tend try to look to see if there’s competition with those hobbies. So that play to win is just basically built in. I did get a little bit bored there along the way, 2018, 2019. So at that point, what was I? I had turned 60. I don’t really count age. My family tends to live a long time. You know, my father’s still going. He’s 92. Oh, wow. Self-sufficient. And yeah, it’s— and, you know, his line goes pretty they go into the hundreds in some cases. So I don’t really view it as that. I view it to be more to be— I need to be intellectually stimulated and need to be intellectually challenged. I need to be around people that basically are smart people that are there. And what I ended up finding is that I just was— I was growing somewhat bored. Which I had before from the marketplace. So we ended up starting another company completely unrelated. It was more just based upon a framework and a model that I had put together and ended up put together a good team, ended up doing quite well. And that was interesting. And as that was beginning to, beginning to unwind on that, had the option basically expand it out or I can wind it. As that was beginning to unwind, That’s when AI came along and that was game on. And honestly, you know, we’re now in 2026. I have never been more excited about the future than I am today. It’s just the opportunities today. I’ve never seen them so great. What is it? What is the moment in your career you’re most proud of? Hopefully, there was a contribution made there along the way. One of the prop traders, one of the floor traders in Chicago, he built one of the largest prop trading firms in the world. He hired me as he was making the transition from the floor to expand his business upstairs. We stayed in touch with each other after. I mentored him, I worked with him. And I was out in Chicago speaking at a conference. So we got together and he kind of stated it in such a way. And I really don’t think in these terms. So I’m going to give you his words. He goes, you must feel pretty proud of yourself that you basically led a generation back in the ’90s and early 2000s that basically opened it up for people. I don’t view myself in that way, but I read what it said about AI. And if I’ll just put myself in AI, not under my name, but just under— I’ll go into Gemini or Groq and see what’s there. Probably overstates it, but if I’ve played some role in influencing people and helping them to get there, and maybe just guiding them. Right now, it’s more like, what doesn’t work? What are things that are not there? There’s no alpha in CNBC. And again, no disrespect to CNBC, but as you could see, Putting together a framework and having systems in place and being long and short and having there is a far better way, in my opinion, to be managing money than just trying to pick a stock that’s going to go up. I mean, even, even joining us on the podcast today, I think, is an extension of this to impact hopefully a lot of people that are watching. I want to, I want to move on to the last part of your framework, which is trade construction and management. So we’ve spoken about a lot of these things sprinkled throughout. But one of them that you’ve written is profit taking. So it seems like you’re not a fan of it, but it’s in your framework. So can you elaborate on how you would delicately do it? Yeah, depending upon which of the strategies. So let’s keep it consistent here. We’ve been talking about long thematics that’s there. Number one, I’ll state this again because it can’t be stated enough. If one is truly going to trade the power law, you need to let the prices run. And you brought up some very valid points. They’ll reverse. There’s certain things that will be there. But one never knows just how far it could run. I mentioned GEV. I mentioned Palantir. No way in the world would I have said that those things were going to go up thousands of percent from Well, it was hundreds of percent. Palantir, yeah, Palantir. Palantir, I think, went up— I think it might have gone up about 1,800%. That was the underlying stock. The options were phenomenal. GEV is another example. Micron back in January at $400, it felt like it was going to go higher, but how it feels doesn’t really matter. It’s how far it goes. It could have topped out the other day at $1,000, or if they reprice it— I’ll speak for myself, I have no idea how far they will run. I want to be there though. If I built the position, if I made the right selection that’s there, I want to be there if in fact it does play itself out. So profit taking basically comes in first. I’m going to hedge that position out in one way or another just to go in. If it’s going to be a Micron, I’m going to be short DRAM. It’s a new ETF, DRAM is the symbol. So I’m going to have some position, whether it’s short DRAM, or I’m going to have some puts on DRAM to basically protect there. As Micron keeps running up and keeps going there, I’m usually buying insurance along the way. So I’m buying puts that’s there. I’m basically evaluating, okay, worst case scenario, if this reverses. Where am I guaranteed? And that’s what the options do. They basically, as long as the clearinghouse can clear the trade, where can I guarantee the— what is the minimum amount for sure to be able to lock in that gain? And then it really is, as expiration starts coming up, it’s building positions there to let it go out. Again, I’m looking at multiple timeframes. And with the knowledge, again, I don’t know if Micron— I think it’s at 900 and change right now. I don’t know if Micron is going to go back to 400. I don’t know if Micron is going to go to 7,000, 8,000. And if it does turn secular, you can make an argument. It’s hard to know when there’s nothing on the left and it’s just running. Would you look at then market flows that you can see the money does flow between commodities and indexes and you just see money supply moving, would you consider this or this would be above this also? Yeah. You brought up something just before that, which is a really good point. Okay. When you’re trading in this style, what you’re essentially doing is you’re chopping off the left tail. Okay. What does that mean? Okay. So you have a bell curve of what your distribution returns are going to be. Is going to be. That’s going to be there. In thinking— and I don’t naturally think in terms of shapes. I’m data, so I can see patterns in data. It takes a while. Those who do think in shapes or have a geometry background have a big advantage. Option traders have a big advantage. Professional option traders have a big advantage. But if you take a look at a bell curve of returns, that’s there. What the silo trading does is it essentially chops off. That left tail that could basically run against— I’ll never be naked short something that could theoretically run to the upside consistently. So what I’m constantly doing is I’ve chopped off the left tail, at least I believe I’ve chopped off the left tail. Through the hedging with options. Through the hedging, through the options, to predetermine the risk. And what I’m doing is I’m letting the right tail go as far as it could go. Does that make sense? Now, now it connects to me actually, visualizing like this. Okay, okay. So essentially, yeah, you’re shifting the bell curve to the right whilst cutting the left, therefore having the odds skewed in your favor, which comes back to a power law basically. Exactly. Uh-huh. Okay, um, okay, looking, looking through the rest of it, the last part is adjustments. That, um, piques my curiosity. What do you mean by adjustments? I guess once you’re in the position and it’s running in your way you tweak things along the way, or is it back to when the expiration comes, you rebuild? Well, a little bit of— well, it’s both. I’m going to adjust my Greeks. I’m basically running a delta neutral, Philly delta neutral. I might bias in one way or another if I have some signal that’s there, and that’s usually a mean reversion signal. That the market has a higher probability of basically rising over the next few days, I may skew a little bit to the positive side on the deltas. And then if there’s a negative bias in there, I’ll skew onto the negative side. If we’re in a bear market, I will definitely be skewing more to the negative side. So I’m basically looking at the markets, and especially when things get volatile, I start at 4:00 AM. That’s when pre-market basically begins trading and get a good feel of what’s being able to do there. Sometimes there’s nothing to do, but I can make some adjustments there. There’s also at times, at times, there’s some offers or bids or things that are out there that might be retail orders. If they’re there, and it makes sense, I may take the trade. But it’s really there to prepare and make the adjustments. By 6:30, I’m pretty much up and running. I know everything that’s going on. And by 9:30, everything, all the orders are put in. The one thing I don’t like about the options market, which they’re now correcting, is the fact that why can’t we trade 24/7? To me, it’s archaic. The CBOE just announced that they’re going to begin option trading, open up option trading on 20 stocks, the 20 most liquid stocks. I believe next month. It’s going to start at 7:30 as opposed to 9:30. It’s a step in the right direction. We’re eventually going 24/5. And then I would expect somewhere in the, you know, in the future it goes 24/7. But those are the adjustments that I’m going to be making along the way. Okay. There’s an element of just discretion, and discretion is just based upon experience that that would be there. Do I— at the end of the day, I’m not quite sure if I add too much value on those adjustments. But the last part I want to actually touch upon is you mentioned biases. So there’s many biases that can exist from survivorship bias to confirmation bias, X, Y, Z. Have you had to battle any of them? I believe we all do. I mean, we’re built in with all sorts of biases that are there. I became a lot more aware of biases and also, for lack of a better term, the term that they use are mental models, probably about 6, 7 years ago. I think it was Shane Parrish, he’s written 4 books that are out there, first made me aware. Charlie Munger, really made it aware. Probably one of the most— if one of my children came to me and said, look, I want to do this, day one, I would have them read Poor Charlie’s Almanac. Charlie Munger’s thinking is just absolutely brilliant that’s there. From his thingies, which one do you resonate with the most? For me, it was inversion. I never thought— Absolutely. That’s his favorite. Yeah, that’s his favorite. Do you use inversion? Do you do it for yourself? Yes. Yes. Okay. Funnily enough, it was something I wanted to mention, but I let it go, but I’ll bring it back, which is buying and selling. Now, we would assume, especially as a technical-driven trader, you’d have a long and short 50-50 split, unless you’re long only or XYZ. Said. But for me, I haven’t tried to be, but it’s skewed about 80/20 towards selling. And for no other reason than it’s just in my head. And when I invert my chart, literally, if I’m looking for a buy position and it doesn’t look good to me, I will invert it and then sell position, and it just all of a sudden just looks better to me. So I use it in the literal sense and also in this sense as well. Excellent, excellent. Do you feel you can get better and better? Well, I don’t know if I’m leaning into my bias and making it worse by encouraging it, uh, but I’m using it in this when it has definitely helped. Yeah. Have you worked with AI on it? I haven’t actually. Yeah. Work with AI on it. It will open up your eyes. It will keep— you’ll get better and better. Anyone will. It’s just— it obviously understands it to a great degree and it goes further and further. So yeah, that one, I can certainly get better and better at that. I think we all can. The one on the business side that really resonates is what Charlie said. He said, tell me the incentive and I’ll show you the behavior. Okay. No, I’m sorry. Show me the incentive and I’ll tell you the behavior. And if you think about it, the simplest way to think about it is in the legal profession, they bill by the hour. Okay. What’s the incentive? Take your time. Take your time. Keep billing. Find other things to be able to do. Not all, whether they’re doing it consciously, unconsciously, that’s there. But in looking at the things that are there, some of those biases, but it really begins though with mental models that’s there. It really begins with heads I win, tails I lose a little. That to me probably has had the biggest impact on my trading, especially in the last few years. Looking at things from asymmetrical basis, that’s there, especially looking at things at first principles, that just became obvious. First principles are making the obvious obvious, but you can build. That’s where you can end up building. And then doing first, second, and third level thinking. We’ve gotten to the point now, and I’ll speak, I’ll let you know how the AI basically refers to it. A lot of people basically state that they use second order thinking. The AI AI, and I’ll refer to it as my AI because it has the memory there. It came out one day and basically said, even the quants give lip service to second-order thinking. And basically, then went further, this is what true second-order thinking looks like. It was pretty eye-opening because then you get a chance to say, you know, maybe I’m giving just lip service to it. This is another way to be able to go deeper and deeper and deeper with second-order thinking. And then third-order thinking, need to be patient with it. And that’s the— that’s a harder— that’s gone there. And we’ve even built things, haven’t implemented it yet, but looking at fourth order thinking and even up to fifth order thinking, that’s way out there. Yeah. Okay. Yeah. Well, I feel like I already know what the answer could be, but I want to ask it anyway, which is we’ve got power laws, we’ve got the using AI, and we’re talking about a lot of cool topics. But what would be something maybe unrelated to what we’ve already spoken about, but something that you want want somebody that’s watching that’s probably in their first 2 to 5 years of their trading career, often in their late 20s, early 30s, what advice would you want to give them about their trading? Risk management. With the people that I’ve known for decades and who have succeeded for decades, they were risk managers first. I think Jack Schwager has done a great job, especially with his first few Market Wizards books that were there. I’ve gotten an opportunity to know a number of the people in those two books, or have worked with them in one way or another. They couldn’t be as different. Their personalities are different, their upbringings were different, the style of trading was different. I was there. They were phenomenal, phenomenal risk managers. And they usually position themselves in such a way that the returns were asymmetric, that they understood how to basically build those positions. The other thing, and this is true just with anything in life, it is dig in. It really is. It’s not going to be making money every single month that’s there. I think the industry did a really good job of trying to put those people out of business who were saying, retire from your job, quit your job, make your living from trading. It’s a lot harder than that. This is an acquired skill. None of us were born to basically do this. And I didn’t wake up one day with this knowledge. This just keeps building and building and building. And hopefully, you and I will be together, let’s say, a year from now or 2 years from now. You’ll be smarter. I’ll be smarter. We just keep getting better and better and better. Just stick with it. With it. AI will— using the right way to use AI, tremendous amount of that knowledge is in there. And things that would have taken me— when I was talking about on the options side— would have taken me years to be able to do, I was able to condense it in a few months. So, and that’s a power law in itself. Yes. Larry, thank you very much for your time. This is awesome. This is a pleasure. Thank you all so much. Great questions. Boom! That was, that was really good.