100 Million Trader His Best Trading Strategy Market Wizard

TITLE: $100+ Million Trader: His BEST Trading Strategy (Market Wizard) CHANNEL: Chart Fanatics DATE: 2026-03-15 ---TRANSCRIPT--- This trader is highlighted in the next Market Wizards book with a hundred million dollars plus of verified profit. The best trade of my career, I very much applied this simple system combining some of these concepts and then I just trailed it prior bar lows and it just trended right back. The beauty of this is this is going to apply to every product and every timeframe. I’m trying to get the odds as high in my favor for a bounce. I’m trying to make the reward as big and then Welcome Lance Breunigstein to Chart Fanatic. On this episode he goes through step by step so that you can follow along and look to implement this into your own trading. The way I process my trades is at any given moment in time I am constantly waiting all the factors dynamically. I would say rate of change is one of the most important factors I’m looking for. So we can build the same framework and the same theory using There will be times where sentiment is priced for euphoria and nothing can ever go wrong and there will be times when sentiment is priced as if nothing will ever go right again. And the truth is No matter the asset class, this strategy is for you. Learn from a true professional trader first hand for free. The beauty of this is you can say, “Oh wow, I can make 10x my money as long as the US doesn’t default.” So at a 99.99999% win rate you can make 10x your money. In this type of chart pattern that as a long would be like trade of the century because so many people that are taking these paper cuts or are not finding effectiveness in these strategies, it’s because they’re playing the chart that they think looks like this but it’s really going up and down up and down up and down and it’s really grinding. One of the most common mistakes people make is they’re Welcome everyone back to Chart Fanatics, the go-to channel for all of the very best strategy and concept breakdowns of some of the very best traders in the world. Talking of which today we have a phenomenal trader back with us. We did a Words of Wisdom episode in January and in the same year we’ve been very blessed to now get a Chart Fanatics. He has actually over a hundred million dollars in verified profits. He’s going to be in the next Market Wizards series. You already know who it is, it’s the one and only Lance Breunigstein. Riz, always happy to be here, so happy to be back and now doing Chart Fanatics which I’ve been quite the avid consumer of and so for the audience today not only do I have a trade but more so what I want to do is teach the audience how I think and show them how I build these frameworks and these systems for not just one strategy but how do I think and analyze the market structure and the price action for any strategy so that they can apply this and make it their own in a way that will lead to success in any product, any different strategy whether it’s continuation or mean reversion. And for me specifically we will be focusing on mean reversion or the capitulation style trades that I am probably most known for thanks to the good old Chat With Traders podcast back in the day. So the premise I want to leave lead with is this. Markets are extremely efficient. Markets are extremely hard to beat and most hedge fund managers underperform and most traders fail. And my basic assumption for almost anything is that the starting price that we see stocks or any product trade at is the right price. And with that assumption in mind you then need to ask oneself, what might lead to a situation where we’re out of equilibrium? And so anytime in trading the concept that drives every single decision you need to make is expected value. What is expected value? Expected value is your win rate times your reward if you win minus the odds of losing which is generally one minus the win rate times what you risk if you lose. And so with all my trading I try to think about why might this be out of equilibrium? Why might there be something with positive expected value here? And to do that one of the things we can focus on is mean reversion or of course continuation. And so for this I’m going to be solely from a perspective of mean reversion and why might something reverse the move it’s made and how can we take it away from a random coin flip, right? The the whole analogy of if I flip a coin it’s going to be 50/50, heads I get a dollar, tails I lose a dollar, nobody’s making any money except between commissions, fees, everything else. In fact you’re losing in trading. And when I think about this framework you can start to come up with some ideas and some logic. And that’s exactly what we’re going to do now. So I would ask the audience to think if a stock were to go down one penny, say the S&P goes down one penny is that necessarily enough to incentivize someone to buy that that they otherwise wouldn’t have wanted? Not really, right? The S&P’s extremely expensive if if you’re buying SPY or something and it’s not really going to incentivize that. So the first variable I would say is the size of the move. Size of move. And now if all of a sudden the S&P 500 didn’t just move one penny but it moved $10, $50, $100 in the case of SPY, all of a sudden that might entice people to buy. So the size of the move is a factor that matters. Now the other question I would pose is, okay, if the S&P were to move say 5% that might be appealing if that percent move is over one minute or a second. It’s going to be far less appealing if the S&P moves 5% over a year. I don’t think anybody on Earth is going to say, “Oh wow, I would want to short as much SPY as possible if we went 5% higher over the next year.” Vice versa, I don’t think anybody would say, “I want to buy as much SPY as possible if we went down 5% a year.” So that timeframe, the speed of the move, that’s going to be our second variable. So now another thing that’s going to affect whether we want to buy this is of course is there the presence of news? So if something fundamentally has changed then we might not want to buy it at a certain price. If all of a sudden it turns out that the quantum computing stocks for example can do their magic and quantum computing works and it’s solving stuff, all of a sudden that news would be really huge and change the the probability spectrum of those cash flows and the fundamental value of those companies. Vice versa for the quantum computing stocks, if all of a sudden it turned out that quantum computing will never ever work, that is a fundamental shift to the value of those companies. So when we’re thinking about mean reversion we need to be aware, was there a fundamental change in that actual equilibrium price, right? Because we’re trying to find stuff that’s moved away from that equilibrium and if uh the fundamental value of the company has changed and all of a sudden the equilibrium is is changing as well. Another factor we can consider is how many days has something gone up or down in a row. So I think most efficient market theorists would say if if something has gone down many days in a row it’s still an independent probability and they would say, “Okay, at any given time it’s still that coin flip.” I would say from experience and I think most traders just just know this intuitively that is absolutely not true. If the S&P is going down 3%, 3%, 3%, 3% and it’s doing that eight days in a row, the probability that it’s going to go up on the ninth day is by no means still 50/50. That coin flip, the more days in a row you’re going down or the more days in a row you’re going up that coin flip starts to shift much further in your favor. So number of days in a row we’re adding to our list. Number of days in a row. Hey guys, before we get into this incredible episode I want to say a massive thank you for all of your support so far on both Words of Wisdom and Chart Fanatics. We have grown immensely and are still the fastest growing channels in the trading industry. Now a way to give back to every single one of you, if you want profitable strategies completely for free, go to chartfanatics.com, the link’s in the description, put your email in and every single week we will send you a free PDF with a profitable strategy of the guests that we host. As well as on the website you can go straight there and you can go through the library of strategies completely for free, just input your email. On top of that we launched a Chart Fanatics free Discord community that has already over 10,000 members of traders across the world. We have our live traders from Chart Fanatics live in there. I’m documenting every single one of my trades in there and we have exclusive discounts, massive giveaways and so much more just to give back to every single one of you. Let’s not forget updates on every episode and things that we are bringing to this industry that’s going to change it forever. But for now the links for that are in the description. Let’s get into this episode. Now like I said, we want to find stuff that is no longer efficient around that equilibrium. So what leads to things leaving an equilibrium or a some level of efficiency is of course when market dynamics can’t really be a free fair market or when there’s market structure forcing things in a certain way. So one thing that tends to happen, and we saw this during COVID, is there can be forced liquidations. So, there’s a lot of big players that are levered, or there’s a lot of times when there can be redemptions, or vice versa, you can be short and get margin margin called, or you can lose the short availability. So, there are times when the market structure is forcing price action that is going to leave equilibrium. And if some hedge fund needs to sell hundreds of millions of dollars or billions of dollars of stock, somebody’s got to find that that that buyer that’s going to take it, and that clearing mechanism is going to be a change in price. So, another thing that leads to leaving equilibrium is going to be forced uh forced buying or selling. Why else might we leave equilibrium? I would say that the more experience I’ve gained over time, now going on 15 years, I would say I’ve only increased my appreciation for how much sentiment is what’s driving stock prices. Even at the time of this recording, we have seen massive moves in Bitcoin, we’ve seen massive moves in MicroStrategy, SanDisk, Micron, Nvidia, Palantir. What fundamentally has changed over the last couple weeks of this filming? Truthfully, not that much, but the sentiment around AI and some of this cloud computing and the growth and the profitability of it is what’s changed. And so, sentiment can be a huge factor. And there will be times where sentiment is priced for euphoria and nothing can ever go wrong, then there will be times when sentiment is priced as if nothing will ever go right again. And the truth is, somewhere often in the middle. So, sentiment is another key variable we’re going to consider here. Now, let’s continue to build this out. What would you be more interesting interested in buying in a panic? Would you be interested in buying a $5 million market cap biotech stock with very shady financials that nobody knows anything about and no analyst coverage, or do you feel more comfortable buying the S&P 500 or Apple or Bank of America or Berkshire Berkshire Hathaway, that is. Obviously, the larger the company, the more diversified and the more stable it is, the more interesting. So, we’re going to add another variable, which is diversification and market cap. And implied in that market cap, is there some stocks that have a million eyes on them? Stocks like Apple, Nvidia, Palantir, those have a ton of eyes. But then if we go to small cap world, those are far less transparent and far less efficient. It’s going to have less attention to them. Another factor to consider is how stable is that specific security? Does it have cash flows that you can link into? For example, most fundamental analysis is based on the present value of future cash flows. So, people are trying to find the value of Apple’s future cash flows, or if you take something like a bond, like a Treasury backed by the US, they’re trying to figure out the present value of those cash flows, and it can be a very quantitative equation. Stuff like Bitcoin, of course, is a little bit harder to value. Bitcoin, I would argue, is almost purely based on supply and demand rather than fundamental cash flows. So, another thing is going to be how quantitative the security is. Don’t mind my leftiness, either. You know, some say I’m the the devil’s spawn, I guess what happened there. And um So, we’re starting to build this framework of obviously a bigger move is going to make something more appealing for uh mean reversion. And same with the speed of move, whether there’s news, the number of days in a row, forced buying and selling, sentiment, how diversified is the market cap, how quantitative. And so, all of this stuff starts to build us this framework. And so, now with expected value, going back to that, I would argue that some of these variables start to shift that equation in your favor. And so, if something very very boring and stable starts to make a very very sharp large move, especially on no news, all of a sudden, I would argue that it’s no longer a random walk. That probability of a bounce increases, the expected value also in turn increases, and same for reward increasing, which improves expected value, and the risk is actually decreasing. So, now here’s the thing. Expected value equals probability, and that needs to be factored by the wins and the losses. So, here’s my question to you all. Let’s say, as a thought experiment, that Apple goes from its current price, and all of a sudden, it’s trading at $1. What is the probability of something like Apple bouncing from $1, assuming no news and no fundamental change? It happened super fast. I would argue that the probability of that is going to approach 100% and I would argue that your wins, you’re going to be making something like, I don’t know, 100 times plus your money. And what actually is your risk? Your risk, if Apple somehow panics, just as a thought experiment, to $1, your sole risk, even if Apple magically ends up bankrupt the next day, which I would argue is like 0.000001, your risk is still $1. So, if we were to do this math and know that we can make, you know, literally 100 times plus our money while risking a dollar, if we go through that math, the expected value I’m going to do a color change for this. The expected value is going to be really really big. So, the other thing that I want to point out with this example is something magic happens in this example. Because we’re going to the downside, we have this lower bound. That lower bound of $0 is actually amazing, because it’s the most you can ever lose. And the difference in shorting is there is no lower bound and there is no upper bound. Shorting, of course, you can lose infinity. Something can go from 100 to 1,000 to 10,000. And even if you want to say, “Oh, that could never happen.” We’ve seen that in small cap world, some crazy prints happened that really can blow up traders. We’ve seen stocks do some crazy crazy moves, even IPOs like Circle this year. So, to say, “Oh, something like that could never happen.” Obviously, yeah, okay, saying something’s going to reach 100 million or something is a little hyperbolic, but my point is, there’s a structural difference in shorting a stock versus buying a stock. So, for this framework, we can even add buying versus shorting. We can add lower bound of $0. And what we’re doing here is we’re building this framework of how to think. And once we’ve built that framework, I like to start to then test it with some real world examples. So, now we’re going to build a framework with with some examples. Let’s say we get another COVID panic or whatever the next black swan is, and all of a sudden, stocks are panicking really quickly, really fast. So, let’s go with the following examples. We’re going to go micro cap and it goes down 90%. We’re going to go MSTR. Love that example. And let’s say that’s down 90%. Then we’re going to say Bank of America BAC. Oops, that looks awful. I’m going to say that’s down 90%. Then we’re going to say the S&P 500 down 90%. Then we’re going to say gov bond down 90%. Futures traders, it’s time to hear about Apex Trader Funding, the largest futures firm in the industry. They have completely changed the game with their new evaluations. 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Up to 20 accounts as I mentioned, and one day to pass. Now, the other thing that I love about Apex and not only can you get 20 accounts, but there’s different account sizes. So, from 25K all the way up to $300,000 accounts. So, you can get 20 of any of the account sizes that you choose. Not only that, you have various trading platforms from WealthCharts to TradeOgre to Rithmic, the choice is yours. So, make sure you use the code CF to get up to 90% off on evaluations right now using the link in the description below. Trade at Apex today. Let’s go back to the episode. So, using that framework, we can start to think about this now. The number of eyes on this microcap ticker, the number and amount of capital on the sidelines that wants to move into microcap if something crazy is going on in the world, guess what? Not that many people. The probability of this bouncing or then bouncing all the way is going to be very low, right? I’m not going to like that. So, then if we take something like MSTR, which of course just largely despite being a software company holds Bitcoin. And so, Bitcoin in a crisis and in in a forced liquidation and a panic, I don’t really know how that’s going to perform. I think some Bitcoin maxis would say, “Oh, Bitcoin’s going to go up.” I would say I’ve no clue. I would say it’s going to function like a risk asset like we’ve seen in the past. What should that risk asset be worth? I’ve no idea. So, this is going to be better, but I’m not going to love buying that. Bank of America. So, Bank of America is a very, very large company. It’s a bank, it’s stable, it’s got pretty good deposits, it’s well regulated for the most part, like especially post-2008. I’m not saying this can’t go bankrupt or that something bad can’t happen, but it’s a hell of a lot safer than something with, you know, a bunch of debt buying Bitcoin. Um and so, this starts to be kind of appealing. But then, do I want Bank of America, which we’ve seen financial crises, Bank of America almost went bankrupt back in 2008. Even safer though is going to be a diversified basket of the 500 largest companies. And so, once we get that diversification, this becomes even more appealing. then, something magic happens, especially now our most extreme example. Government bonds. So, if it’s a US government bond, first of all, it has a very calculatable, quantifiable value. If that bond is supposed to mature and be worth par of $100 and it’s down 90% and it’s trading at $10, the beauty of this is you can calculate that, okay, as long as the government the US does not default, which if the US defaults, microcap is probably screwed. MSTR, you know, you can make some argument on Bitcoin, but Bitcoin, but for example’s sake, that’s not going to be good and its debt is going to be a mess. Bank of America is definitely defaulting if the US is defaulting, and most companies in the S&P 500 are probably wrecked. And so then, the government bond is going to be extremely safe out of those. And because you have a quantifiable value, if it’s trading at $10 and par is $100, first of all, oops, lost the cap. This is you know, risk of the job here at Trustmatics. And so, the beauty of this is you can say, “Oh, wow, I can make 10x my money as long as the US doesn’t default.” So, at a 99.99999% win rate, you can make 10x your money. And so, this framework is then how we start to go through examples and how I start to think about this stuff. And this all sounds still very theoretical. But it is through this framework we can then jump to real-world examples. And doing that, you go through the charts. And now, we’re going to dive into the parts that people really want, which is chart patterns. So, any trader worth their salt should be saying, “Okay, Lance, all that theory is great, but how does this actually play out in the charts?” I hear you. So, let’s dive into this. So, going back to some of those variables like speed and rate of change, I would say rate of change is one of the most important factors I’m looking for. So, we can build this same framework and the same theory using chart patterns. And let’s say we’ve got one pattern. How would you describe that, Riz? I’d say quite bearish. Bearish, but would you say steady, crazy, panic?

steady by the looks of it, yeah. Steady. And so, I think generally when we describe something as bearish, I think if I had to guess, what your eyes picking up on is our slope. Oh. Color change, here we go. Our slope is I don’t know. Maybe negative .5 slope. Obviously, I don’t have any access, so there’s no real computation there. But nevertheless, so we can then start to say if it’s negative .5 slope, it’s kind of a steadier move. It’s not that much of a change. There’s not real panic. And rate of change, obviously if something goes from 100 to $1 in a flash, that’s really appealing, right? So now, we can start to say okay, this gets a little bit more aggressive. Then we can start to say that gets even more aggressive. And then, if we take this to an extreme, we can get really asymptotic where something really waterfalls over. Yeah. And so that, if we then go in terms of slope, maybe we have a negative one. Maybe we then get a negative three. And then maybe this goes and approaches like a negative 10. So, some of the other variables we touched on were the boringness and how stable something is. So, now imagine this. Imagine you get something that is exceptionally, exceptionally boring. Oops. This was a double dare. Don’t No, don’t don’t don’t question the one DaVinci B. So, this is extremely boring. Something has been stable in this range for a really long time. Let’s even take something like silver. Silver tends to be pretty boring. Or even more boring, a currency. And so, this is also what I love about these thought experiments. We know that currencies tend to be more boring than silver and gold. We know that silver and gold tend to be more boring than Bitcoin. We know that silver and gold and currencies tend to be more boring than stocks. And that Apple and Bank of America are going to be more boring than microcaps. So, if we get the most boring thing in theory, what we really would love is let’s say we break down and then something that’s normally boring makes an exceptionally large move. So, we go from color change, we go from boring, and then out of nowhere we go to extreme moves. This, I think the formal, official term is we love, and doing that gives us smiley face. Do you find as well like this setup that we’re looking at? Is this more of a bigger picture idea versus if say, you know, let’s say the average movement on the S&P is, I don’t know, let’s say 1% in a day, but then one day it does a 3 or 4% sort of move either side aggressively and sort of matches the other rules where it’s happened within that day and that time frame. Is it still the same concept to do maybe a day trade using the same framework, mental framework, or is this really done for like the bigger picture swing to maybe positions or trades? So, the beauty of this is this is going to apply to every product and every time frame cuz it really works as a fractal. And these concepts are universal. And so, when we get into the real examples, you’re going to see how these patterns play out very much in the real world. And I think one of the most common mistakes people make with mean reversion is their selectivity. And so, people will often say, “But Lance, if I’m doing something like the right side of the V where I wait for that turn, it’s death by a million paper cuts.” And my answer to that is it’s all about these concepts, which are fairly simple, but applied extremely selectively. And so, if there is something like this with minus .5 slope, and then we kind of break, I’m not playing that. And so, we’re going to get to the tactical of how we how we trade this stuff, and that’s going to be the key is there’s nothing to say if something’s boring, like yes, we might reverse, but that’s kind of what happens. So, how do you prevent How do you prevent yourself from buying here, losing? Buying here, losing. Buying here, losing. Buying here, losing. So, much like with our framework, we’re trying to stack all of our odds in our favor. And what happens is if we get something that looks like this rather than like that. If we get something that’s moving on no news. If we get something that’s down 1 2 3 4 5 days in a row. If we get all these variables in our favor, what ends up happening is rather than being a coin flip and rather than being the theoretical random walk of 50/50 and rather than making $1 for a win and losing $1 for a loss, what ends up happening is our win rate goes up, loss rate goes down, this goes up and that goes down. And so, in stuff like this extreme example, whereas versus that one, our reward if we do a 50% retracement, might just be that. Now, the beauty is when something panics, if we do a base case 50% retracement, all of a sudden, our reward, rather than that, might become that. And when we go through the examples, you’re going to see that’s exactly what I’m looking for. I’m trying to get the odds as high in my favor for a bounce. I’m trying to make the reward as big. And then, through certain trading systems, we can very much limit our risk. When you do that, expected value goes through the roof and we, again, end up happy trader. In terms of frequency, before we move on, what sort of frequency would you say this looks like on a on a monthly or yearly basis, depending on the time frame? Sure. So, it’s always going to matter just how extreme because all this stuff’s on a spectrum. For all these variables, we’re thinking about these different things. And so, I would say in in a very micro structure on the intraday, this stuff is panning out every single day. Now, the question really is how selective do you want to be? Are you going to wait for pocket aces? And how do you define pocket aces for your product, your time frame, your strategies? Pocket aces by definition are going to be more rare. You might want the really, really huge multi-sigma move. You might want the four five six days down in a row or four five six days up in a row in something extremely boring. So, the more you go on the selective spectrum where you need all those things in your favor and you’re really jacking those variables up, that’s going to be rare. But, these concepts and these patterns are playing out every single day in just about every single product. So, let’s finally bring this all back to trading systems and how we can actually execute on this. So, if you follow what I’m saying, essentially, the chart pattern is going to show a lot of those variables. And the more those variables we get in our favor, the better. And nevertheless, that’s all great, but we need to be able to execute. So, how does one execute? And that’s where I bring in a concept that I call the right side of the V, which at its essence is saying rather than buying on the way down, if we instead wait for the turn and buy on the way up over here rather than there, the beauty is that now we have a stop. That’s our stop. And then, we can catch this retracement. And most people, again, fall for that trap where if something has a slope of minus .5, what happens is, first of all, if this is something going from $500 to $499, the issue with this is our reward on a 50% retracement, if we just go back up there, not drawn to scale perfectly, haters on the internet, but our reward might just be $0.50. Now, the difference is flip some caps here. Imagine if this panics out and we went from $500 to $450 and then when we turn, we can actually end up bouncing. Instead of $0.50, we can bounce $50. And not only that, but the people that are willing to step in and buy at that discount, here they’re just getting a $1 discount. That’s nothing. That’s a That’s a 0.2% discount on a $500 stock. Here, they’re going to get 10% discount when a stock goes from 500 to 450. You get so many more incremental buyers, you get so many less incremental sellers. And so, your probability is going to go up, your your reward’s going to go up, and the beauty is you’re going to then have your capped risk. Do you find What is that one of the biggest mistakes you see people making when trying to implement the right side of the V? Far and away, they’re not thinking about all the variables. They’re taking way too simplistic of a viewpoint. And that’s why we built that framework of all the different variables to think about. Because what so often happens is if you’re not considering what does the daily chart look like, what does the intraday chart look like, what’s the slope, the rate of change, how far are we above or below a Bollinger Band or away from the moving average, how boring is this security, how many average trading ranges have we done. So, even those variables I listed in the beginning, that’s really just a subset of the infinite factors we can be thinking about. You can also be considering what is the market doing overall, what are comparable stocks in its sector doing overall, what are different seasonal patterns. There’s literally infinite things and variables you can systematize on. So, now what ends up happening is with the trade decision, we’re going to take all those variables and we’re going to keep a mental rubric. The way I process my trades is at any given moment in time, I am constantly weighing all the factors dynamically. So, every second, every minute, every day as all these variables change, I’m trying to constantly handicap how good that expected value is. So, in my head, I’m almost running this mental tally with all these variables. And so, of course, some variables are going to be more important, but all of them are on a spectrum. So, now think about it like this. Rate of change, daily chart, intraday, um boringness. So, if I could extend this to infinity, the reality is I would have all those factors. And what I’m doing is I’m just kind of like having this mental tally. Like let’s say I rated each variable from from 0 to 10. Let’s say the rate of change was amazing. We really started to accelerate. So, maybe I’m going to give this a nine. Maybe the daily chart, we’re actually panicking to some support level, to some long-term support. If that daily chart’s amazing, that could also be like a nine. Maybe the intraday was a little bit steadier, but it’s still good, just not as good as that daily chart. So, the intraday’s going to be a six. And so, despite all those good factors, this is actually in kind of a volatile sector, maybe it’s semiconductors these days, and it’s been kind of run up a lot. So, boringness, it actually only gets a two. It’s not that boring. So, in my head, what I’m doing is I’m kind of adding these up. And so, this is a total of

And so, something like this, maybe this gets in scientific quant terms one smiley. And so, something like this, I might be willing to trade. And maybe I’m going to give this B risk. So, maybe 26 equals B risk. And maybe if this got a score of only 20, that would be C risk. Maybe if this got a score of 15, that’s just no trade. And so, what most people do is they’re not even considering all these variables. They’re not weighing all the variables on a spectrum. And then they’re just oversimplifying it and just saying, “Oh, if this turns, I’m buying.” Rather than saying, “Oh, we didn’t meet all the requirements, this is a no trade.” Now, of course, let’s say we were 10 10 10 10. So, 40 might be A++. risk. And so, this is the framework of how I’m thinking about all these capitulation trades. And this is not one of those simple things. Like people want a simple answer. They want to know if X happens, do Y. And I think so many people get frustrated or think I’m hiding secrets when I tell them that like, “Look, there’s a lot of nuances and a lot of variables.” And the beauty of trading is every play is similar, but every play is different. No play is exactly the same. And so, if you’re trying to just strictly memorize if X do Y, it’s never going to work because it’s not that simple. It’s all these variables. Like if you were trying to draft a basketball player and you said if tall draft him, like okay, tall is a very important variable, but like um if tall but has no arms, that’s probably not a good draft pick. If tall but has no coordination, that’s probably not a good draft pick. If tall but 700 lb and and can’t run, not a good draft pick. So you can’t have this oversimplification. It really needs to be Wait, if I’m drafting and betting on this player, I need to weigh him on this full spectrum of variables that are important to me. You’re never going to have everything and look, maybe maybe the play is um not great for boringness, but that’s made up for by this and this. So when we go through my examples, you’re going to be seeing exactly how all this plays out and I’ll even go through some of those. So shall we finally at long last dive into these?

Yeah, let’s do it. Should we quickly before we do look at um the entry like drawing element of the entry? Cool. With that framework and understanding those generalized charts, how does one then actually define that specific entry? And that’s going to come down to defining that change in trend. So even though this could be a master class in itself, this is going to be called defining the change in trend. So what might happen is we might break a trend line. So this break of trend line might be it. If something is panicking and really holding, we can have something that’s holding prior bar highs. And that break is going to be what signifies that break of trend. Prior bar highs. Now of course, this holds true for uh even though this was a downtrend, of course it holds true for an uptrend. Even though this is prior bar highs, it holds true for prior bar lows. And so you can even have a general trend that is um we’re going to do and call this kind of got to unsheathe my my weapon. So Your lower lows and your lower highs. Exactly. So lower lows, lower highs, but then we break that and all of the sudden we get maybe higher highs. And higher lows. And so break of lower lows and lower highs. Then in the most extreme scenario, which I’ll squeeze in up here, there’ll be times where when you really go asymptotic and really panic and that slope really waterfalls, here’s a thought experiment. If Apple were to go from 100 to 99, 98, 95, then it panicked all the way to $1 in one bar and the break of prior bar highs was up at $98, I wouldn’t wait for Apple to go from $1 to 98. So in the most extreme situations, I will be willing to buy an intra bar turn because the reward and the probabilities and the risk are just so in my favor. So in the absolute most extreme scenarios, I’m actually going to be buying kind of that that intra bar turn as that then starts to reverse higher. And we’ll see that come into play as well. So those are the entries. Then of course our stops. Yeah. Well, you’re about to do that I guess. Yeah, actually and I’ll even use good old red. So in something like this, it’s going to be the lows of the move. Uh in something like this with the prior bar highs, it’s also going to be the lows. And in something like uh the break of lower lows and lower highs, when we then start to make higher highs and higher lows, it’s going to be if that pattern ends up violated. So if this ends up coming all the way back and we don’t hold the higher lows, then this is going to be where I get out. And this is also going to be low of move. So that gives us our entry, that gives us our um stop. As far as then how long we hold, there can be the same same pattern. Where if something is trended using prior bar highs, I’m going to expect that to potentially in the best cases trend and hold prior bar lows. If something was trending and holding lower lows, lower highs, once that breaks, I’m going to expect higher highs and higher lows. Um in something like a more extreme example, often that I’ll still just give prior bar lows. Okay. And the same on this side, just the prior bar Exactly. And I’ll explain some of the pros and cons. And now the truth is, again, people want simple, but it’s not always so simple. So there will be exceptions and how do I define those exceptions? It’s going to be weighing all those factors involved. So if some trade is absolutely amazing, like let’s say it got like a 100 out of 100, if we finally break the trend and we haven’t like let’s say this was coming from like a mile away, we break that trend. And let’s say as this develops, I don’t necessarily want to stop out here if this is coming from like all the way up there. So there will be audibles and still just based on expected value. Exactly. In terms of this one here, would you be able to set an entry as like a a limit or a stop order because of the nature of let’s say these are daily candles? You could just put that order in the market above that daily high to automatically enter. Absolutely. Yep. So the beauty of this is especially if you’re trading a higher time frame, this can be very hands-off where you already have your entry and you can have that in the system because the prior day’s bar is already defined. And then as that pattern unfolds, you can very much just have your stop and it’s a very hands-off style of trading. And what’s so funny is trading is complex, it’s hard, but when you apply it to the right situations, it can be these simple systems that are effective. Like in my the best trade of my career, I very much applied this simple system combining some of these concepts and then I just trailed it prior bar lows and it just trended right back. And now we’re going to go through actual chart examples now. Yeah. Let’s do it. 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So now that we’ve gone through the concept in its entirety, especially in terms of picture perfect what it should look like and the idea of it, now we’re actually going to go through chart examples on the charts where yeah, what the reality actually looks like uh when identifying these type of trades. Cool. And we’re even going to go in reverse order. I’m going to show you that these concepts are timeless and I’ve been collecting charts for my whole 15-year career and the even funnier part is I learned from my trainer who has collected charts since 2001. And if you go back to 2008 in the banking crisis and the financial crisis, these concepts still hold true. These trades still existed. I suspect they’ve existed forever throughout time and for all I know, will continue existing forever through time until the AI overlords take us over and replace us as traders. So this OCLR example is going to be back in 2016 before some of the young whippersnapper traders that we know were even even alive. That’s how old we’re getting, Riz. And uh so this we’re going to 10 27 2000 16. Okay. Like I said, we’re going to 10/27/2016. And so this was the stock Oclaro. And we started to trend weekly off the open. And so now, back to that theoretical concept, this right here I would describe as kind of slow and steady. It was like that first example that I asked you about. This is maybe a slope of minus 0.5. We then start to accelerate. This becomes a slope of maybe -1. And this is where we get that asymptote that I was discussing, that waterfall. Where we go, steady steady steady, we start to accelerate, then we crash. And so if we go on back on some of these variables, what we can say is this was pretty stable off the open. We were in a form of equilibrium. The rate of change crescendoed, we then waterfall. We get a massive massive spike in volume, which is one of the major ways I define capitulation. The stock has now fallen over 25% if my rough mental math is uh correct. And uh about 20%. Fact-checked myself. And so this is like a really really huge move. We can even then consider the daily chart. And on this daily chart, what do we have? Okay, it was like pretty stable. The stock wasn’t particularly run up. And look how boring these average trading ranges are. On a normal day we’re getting maybe like a 30-cent move. So this really was an extremely large move on the daily chart. The volume was exceptionally large on the daily. And so this multiple time frame analysis is how I weigh all these different variables. Uh Oclaro I believe uh we’re going back well now. This was just semiconductor stock and and was pretty boring. Pre-AI boom. And then the beauty of this is this was holding prior bar highs almost this whole way down. And so people often ask, well, what if it’s not trading super cleanly? What if it doesn’t do prior bar highs and hold it the same way or make some clean beautiful pattern? Well, guess what? You don’t need to trade it. And that’s about that selectivity. Where so many people that are taking these paper cuts or are not finding effectiveness in these strategies, it’s because they’re playing the chart that they think looks like this, but it’s really going up and down up and down up and down. And it’s really grinding. And it’s showing price acceptance. Like this bar is price acceptance. I don’t want this bar. I want this. Where all of a sudden these bars are multiples of these boring bars. Like look how big this is. We just showed you on the daily chart that a normal average trading range was 30 cents. This stock is moving 30 cents per bar now. And off the open, we were barely moving 5 cents. So that’s like those are the nuances that make this so exciting. And I like you can see how much I love all this stuff. And like it just reminds me back of the old old days of like learning and building these frameworks and doing these these mental games of building these experience and and with these charts. And so now, this was getting really big. Volume capitulates. So this to me, like this is really an A an A chart. Um And you can buy this intra bar or you can wait for that break of prior bar highs and enter right around 725. And then give that an initial low down there. Start to trail it prior bar lows, which effectively gets you out close to this moving average right around 757. And so people ask, how do you get the win rate and and estimate that? So obviously all these variables are on a spectrum. So I know that if I’m doing my little mental rubric and something is like, oh man, this trade’s a 95 out of out of 100 or like a a 90 out of 100. Like I’d give this And now this is all theoretical, right? I have no mental rubric. But I would say this is like a 90 out of 100. This is a lot of good qualities. I know that when something has that many good qualities, the odds of this bouncing, this was probably like a 70-80% bounce. Now, if we were to go back here and you and this were to break the trend here and you were to ask me about that, I would say that would just be like a total coin flip. If anything, it’s less likely we bounce cuz we’re just trending lower. So that might even be 40%. And so as this starts to really accelerate, as this waterfall, and it goes a bigger distance, multiple average trading ranges, what’s happening is your probability of a bounce is shifting from like a theoretical 40% and then it’s going maybe 50%, 60, 70. And then is that finally this huge volume capitulation and turns, that’s going to be like a 70-80% win rate. And as you start to catalog these, you can backtest and collect these chart patterns in the past and then calculate win rates. Or you can forward test and see when you do this type of trade, how often does it end up tending to be a winner? And that’s how you build these statistics. And then you can over time calculate your math. You can say what was this distance? Okay, it was maybe about 30 cents or so. Then you can say what did you end up making? About 30 cents. But the key here is even if the risk reward is equal, the beauty is that the win rate is so high and that makes this a really solid trade. But notice how this was picture perfect based on some of those chart examples. And I’m using that framework of all those variables and nuances to judge just how good this is. And it’s not as simple as just the intraday chart. It’s all those variables together. Would you say one mistake that people make is that they will try and hold so, yeah. Classic once we’ve gotten down here as part of this move is we’re kind of playing on the fact that there’s a lot of emotions in the market and we’re expecting to have some sort of bounce correction and mean reversion, right? Um do you think there’s a lot of people who may execute this well, but then they’ll try and hold for two, yeah, to back to the highs or back to the, you know, where, you know, basically complete the move back up? And therefore, where they should follow the rules and the system, they end up making that mistake of allowing those emotions of how low we’ve come and then that greed of, okay, this is how much I can make if we get to here or or you’re back to the highs. Do you find that that’s a mistake that a lot of people make? Yep. So of course, a lot of times you do need to factor in reality, which is this stock just panicked all the way below $7. Will people be rushing to buy this at 840 or 830s when you could have just had it 20% off, little bit less than 20%. I know people will get me for that one. But when you could have had it at this discount, are you going to race to immediately buy it back at 830? No, of course not. And yes, it it theoretically can happen, but the odds are stacked against you. So that’s why I love using this moving average as a form of equilibrium. This is just part of the Bollinger Bands. It’s a 20-period MA. And so I view this as just equilibrium. And so often times we do bounce there. So I can use that as a rough price target in my mental math estimation. So if I’m wondering how far can this bounce, uh and I’m trying to weigh weigh the mental math and approximate it, I can just say, okay, at this bar the uh prior bar high was 725. And this moving average at the time was was at 788. This of course will come down with these lower bars factoring to that equation. But I can know, okay, like if this bounces sharply, I might make 50-60 cents. If this starts to bounce less sharp, maybe I only make 30 cents. And overall, this was what I would describe as a pretty typical expected outcome. Like this would almost be my base case expectation for this this pattern. Like very very typical where we held prior bar highs on the way down. Big volume capitulation. We turn. We hold prior bar lows on the way up and bounce all the way to that moving average. So for me, as far as just kind of textbook, uh I would call this like a nice like A trade. It’s a single. Like this is I love that. Beautiful. So now, we will go to another one in the history books, which is this NGD on 1/31 of 2017. So NGD is a gold stock uh still in existence today. And what we see is the stock uh had news of prior day, had a weak sell-off, uh closed really really weak. But then it was that next day that we did even even bigger volume and had this uh capitulation mean reversion ask pattern off the open. And so again, what we got is And actually, let me even jump back here for context for another second. This stock is again normally very boring. In terms of boring sectors, gold stocks are quite boring. They trade off the metal, right? It’s it’s it’s it’s a pretty quantitative thing that they can say if gold prices are this, this is where the stock should roughly be at. Most gold stocks if gold stays the same and you’re a developed gold company, it’s not going to go up 500% in a year and it’s not going to fall 90%. It tends to be stable overall. And these average trading ranges, we’re talking about an average trading range of maybe 5 to 10 cents, maybe 15 cents, maybe 20 cents. And so what ends up happening is yes, we get news and it’s a big move down. So you do need to adjust for that recent volatility. And so then this starts to sell off. We hold prior bar highs. We then get that same volume capitulation. The stock has moved, I don’t know, 25 plus percent now, which is pretty awesome. And it’s that same pattern where we can buy that break of prior bar highs. This holds prior bar lows and now we catch this move up to here. So, I’m going to go back to those prior variables we used. This stock was very volatile the prior day on news. This stock was less stable off the open and was making kind of a bigger move from the start unlike the OCLR we had where we had that equilibrium. And we have this nice panic, but it doesn’t really crescendo and waterfall as much. So, what ends up happening is this ends up having a weaker bounce, which is totally fine. And so, overall, if I had to do my little rubric, I would say this is an acceptable play. Uh but the other issue is our risk to lows when we buy here at 252 or so, our risk is 13 cents. And because of this big wick on this candle, that’s actually a pretty far stop. So, if we were to calculate the expected value on this, it would end up being just okay. And so, that’s how I’m using this this rubric, right? It’s it’s Okay, I love that this is a boring stock. Love love love that the it’s a boring stock. I love this volume capitulation when normally stocks do the most volume off the open. Yet now, almost 20 minutes later, we’re doing this move. We easily could have opened at 250 rather than opening at $3. We traded and trended down and then capitulated. So, there was also the news the prior day, so the average trading range is is bigger. All these different factors including this wick as I described it increasing our risk. So, those nuances are what makes this play far more marginal than the OCLR example. And I would give this okay, maybe it’s worth it. This would kind of be a fine super small, maybe like a C trade. You do a little bit of risk and it’s and it’s okay. And what you’ll find also is when you get all your variables in your favor, you end up having a better bounce. You might bounce to the moving average or even beyond it. On the trades that are much weaker in quality, you’re more likely to have a weaker bounce or no bounce. And then of course, if the slope was super steady, I would expect even worse of a bounce. So, do you see how that framework of understanding price action and why this that logical framework can be applied to give us kind of that spectrum of outcomes? Yeah, so it then allows you to have a more realistic outcome. Going back to what I was saying on the last one is like, you know, is there issue of people trying to hold too much? And kind of that will come down to one the emotional side, but equally, would you say that more people get emotional because they lack that sort of understanding of the variables that they haven’t done that mental framework of okay, what are the variables dictating is possible on this particular trade? So, then it’s easy to then allow your emotions to hijack you in the moment because you haven’t really understood what the market’s really representing to you. So, then kind of goes back to that point where a lot of people blame emotions when really it’s that lack of insight and work, right? Yeah, but I love love how you said that and it’s true because the more you have done the work, you understand the framework, you understand price action, you have the reps, you have the charts, you have all these patterns memorized, when you have done that work, you have this deeper understanding that allows you to be more confident and less emotional. And you have that experience to trust in the pattern. You know that oh wait, I’m holding in this case may maybe I’m holding 10 8 or 10 9. You know your hand and you know how to play it, so therefore you can act way more accordingly and it’s less of a guessing game. The other thing I would say is the truth is for the average trader, most people, you’re actually giving a little bit too much credit, I will say. Because the truth is what most people are doing is they’re buying here and they’re stopping out. They’re buying here and they’re stopping out. Then when it stays steady and it’s less capitulatory, they’re still fighting it. Then they’re like, “Okay, maybe rather than stopping out, I’m just going to hold on to some.” Then it really accelerates and they hit out. Mhm. Then they’ve just lost once. They’ve lost twice. They’ve lost three times. Then when the turn finally comes, they’re licking their wounds. And I don’t mean that to mock less experienced traders. Trust me, I have done this mistake a million times. I still do this mistake sometimes. And even when I sometimes fight on the front side before the turn and I’m buying and I take some losses, even when I do that, like I still fight and struggle with those emotions and I need to say, “Oh wait, Lance, like you’re you’re you’re you’re not waiting for the turn.” And so, people do this and even I do this and I got to say, “Whoa whoa whoa.” And that awareness only comes from experience. But that’s what most people do is they’re taking the losses on the front side and then they’re losing when it capitulates and then they give up for the bounce. And it’s not just beginners, it happens to me sometimes. It happens I work uh and and mentor other seven and eight figure traders. And so, there’s a trader this year who I have the utmost highest admiration and respect for and he got stuck fighting the quantum short and then wasn’t in it for the turn. So, it happens to everyone, but that’s actually how our base level psychology Yeah. can get us when we don’t have the experience and that awareness to say, “Whoa, take a step back. I need to wait for this turn. This is my system.” And we all make those mistakes. Yeah, and the worst the worst worst worst case is that people will go through that and then they will flip to selling cuz they think that’s the right and then Oh wait, yeah, that’s that’s when you say, “Oh wait, maybe this is going to zero. You’re right. Yeah, I’ve I’ve done that too.” Um if I wish I wish people could see how bad I was in the beginning. And if people think Lance had any raw talent for trading, they’d be greatly mistaken. I had no raw talent. I was a steaming pile of dog where I did the exact opposite of what you should be doing. Yeah. And only from doing that a million times and, you know, slapping myself and beating myself up and saying, “Lance, come on. Like what’s wrong with you? Why can’t you do this?” It took so much so many reps, so much training, so much mental awareness of don’t buy the front side. Don’t buy the front side. Don’t buy the front side. Lance, no matter what you do, don’t buy the front side. Wait for the turn. Wait for the turn. Okay, I think this is it and you don’t buy. Then you’re like, “I think this is it. I think this is it.” Then you buy up here cuz you’re like, “Oh wait, this it’s definitely bouncing and turning.” Then you chase the top. Then you stop out there. And so, I’ve made every psychological error and mistake in the game. I’ve let every base emotion ruin me and do the bad trade. And it took many it literally took me years to reprogram myself to not do that. And it’s a constant refinement. Like it it’s like uh it’s I always laugh how David Goggins is is like, “No, you don’t understand. I am a piece of I am a lazy piece of and every day I need to convince myself to not be a lazy piece of shit.” And I think people think that like good traders are robots or unemotional and it’s like, “No no no, you don’t understand.” Like literally every day in my trading, I need to say, “Lance, don’t be a dumbass. Like fight those emotions. Fight those emotions. Fight those emotions.” And I still sometimes am a dumbass and do the wrong thing. But the awareness increases over time and your experience level to be able to say, “Whoa, okay. Like most of the time I’m good. This time I messed up, but I’m aware and now I’m fixing it.” Yeah. And so, it’s it’s never this game is never easy. Never. Let’s take a break for a minute there guys cuz I want to tell you about our incredible sponsor, TradeZella. TradeZella is the number one trading tool in the entire trading industry. TradeZella allows you to become a more profitable trader. Allows you to make immense progress as a trader no matter if you’re a beginner or an advanced level trader because it makes journaling easy. It makes journaling something that is fun and enjoyable and something that is interactive. So, no matter if you’re a crypto trader, no matter if you’re a futures trader, no matter if you’re a forex trader, no matter if you’re a stock trader. All you have to do is select your broker, your platform of choice, and connect it to TradeZella and it will automatically sync your trades and pull all of that data onto the dashboard, making journaling and finding your edge and adapting your edge so easy. In collaboration with TradeZella and Chart Fanatics specifically, we are actually getting the playbooks from the episodes that we’re filming with these incredible verified traders and adding them as playbooks onto TradeZella so you can actually go on there and see the rule sets already predefined. So, make sure you check that out as well. Now, you can actually get 10% off your monthly subscription using CF10 on TradeZella right now. But more importantly, I would say CF20 for 20% off your yearly subscription with TradeZella. The links for TradeZella are in the description below, so make sure you go check them out. Use CF20, get 20% off your yearly subscription, become a better trader today. Now, let’s get back to the episode. Okay, another example I love. One of the most famous moves kind of of that COVID time frame. Okay. Which is going to be a fun one. Okay, this was July 29th, 2020. And so, this was one of the craziest trades during COVID. Um uh guy, I can’t even remember the actual headline. It was it was somehow Kodak got involved with like Operation Warp Speed back in in COVID. Mega short squeeze where this stock was like super super boring. Super. Let me see if I can even, you know, like look at this. So, this stock on average was moving 10 cents. Uh very boring. I think we all know Kodak is the camera company. That is uh unquestionably a shitty company for quite some time. It has done nothing. Then it ends up uh somehow involved in operation warp speed, explodes going higher, and so then a lot of people that were short ends up being a massive liquidation. So So when we think about this, Kodak, very boring company, very old stable company, and one that’s ultimately struggling, people get get kind of caught. We do a massive gap up. So we know this company is stable and it’s a huge move on the daily, and this volume is like is is unlike anything just ever seen. Like For comparison, you cannot even see volume bars here. I think that’s a pretty good sign of of how extreme this is is you visibly cannot see the volume of what it was prior doing. So that’s our daily analysis. We’re now going to jump to 729. And this is 729 2020. And so I use a 2-minute chart, but of course this applies on on any timeframe. And so what we see here is the stock starts to move off the open. Nothing Yes, it had that prior day move, but nothing like so face-ripping and unbelievable, and the stock starts to go. We start to pull back. We then curl up. And this was already a big gap up at the time. So a lot of people are probably piling in short thinking it’s done for. And then what happens is we break out. Huge volume comes in, and then massive price expansion. Now keep in mind, the stock on the actual news didn’t even move up that that crazy. And now we’re just purely skipping prices. To go from 20 to 60 on a stock that was just a couple bucks beforehand, this is crazy. Not only that, we are super far above the upper Bollinger. We’re really far away from the moving average. At the time of this of this peak, the moving average was at $26, and the stock is at 60. So it’s over over 50% lower is the moving average. And so really crazy move. And again, we’re holding these prior bar lows. So super sharp trend, the kind of reverse waterfall. And then we get that break of prior bar lows, and we get that turn, especially this intra bar turn of that shift of momentum, where we’re green green green green green green green. And again, the same way in our framework I was talking about number of days up or down in a row, it’s a fractal that applies on any timeframe. So one bar, two, three, four, five, six. Seventh bar up, and it reverses, then boom. And so that simple system here, now of course this is one of the most extreme examples. Like this was one of the best trades of 2020, but it follows that framework of this was a very boring stock making an exceptionally large move, and this intraday chart was probably 10 out of

10. So this had so many variables, where if I did my little rubric and added it all up, this was probably like a 95 out of 100. The main risk for this? This was a short. And so God forbid you pile in short, and then somehow we we we really lock limit up and we get halted, there’s a lot of uncap risk there in something like this. Now imagine if this stock was a stable $100 stock, then it the next day panicked to $80 on the on bad news, then we opened up at 60 and panicked all the way to 20. Like imagine if we reversed these prices and made this the the downside. And something went from 100 to 80 to 60, then panicked to 20 like this in this type of chart pattern, that as a long would be like trade of the century, because you can make so many multiples on that. And well, it was a very boring stable company at 100. So just a few days prior in theory, it was this like that’s how these concepts apply. And so this would be like a 95 out of 100. The con, of course, is hey, just in case this were to not work, the short side is more dangerous. And as a result, I might want way less than if this was a long, but nevertheless, I still want a lot because the reward on this was amazing. You ended up making um over over about $20, which is which is phenomenal. Definitely, yeah. And then the risk is still kept to lower in terms of yeah, about $8. So then you’re getting that closer to well, over one to two in terms of its risk reward uh on this.

Exactly. Yep. So you’re talking about, I don’t know, probably about a three to one risk reward. I’d say the probability once this turns after a move like this, so many up bars in a row, is again probably at least 70%. The only con is is that tail risk. Just God forbid you get stuck, but that’s What’s the reality of of speed? And so in this case, as you said, these are 2-minute candles and bars. Uh you know, in terms of being able to execute effectively, you know, get the right pricing, the right risk on, etc. How does that that work? Do you have to have sort of hot keys? Is there a certain elements that are going to be really efficient or or almost necessary to execute properly for these sort of trades? Yep. So for something intraday like this and this particular example, this was very quick, but then of course you could have caught this print and then more liquidity in here. So this was within within seconds once this turned. Um and then you’re definitely wanting to use hot keys. You’re definitely needing to be super quick on the keys. If you’re trying to point and click in something like this, not not the area you want to be in for sure. And that being said, there are examples which I can even now jump to where you’re operating on a daily timeframe, cuz these concepts, like I said, are fractals, and you can do the same thing and apply it on the daily chart for the people that aren’t day trading, that aren’t super quick on the keys, or trying to find strategies that are more conducive for part-time jobs and part-time trading. Let’s jump to one of those. We’re going to go to a recent example as well. And so this happened in October 2025. Oh, nice. And so this is the ticker UAMY. And this is one of those just critical metal rare earth stocks. And so normally, this stock has been quite boring. And we’re even going to get context long-term. So this stock um I think the technical lingo is this was a piece of for a really long time. Um I mean, we’re trading at 20, 30 cents. It’s a piece of And we start to break out. We start to break out. We’re going up. And even this year though, amidst all the trade tariffs and the the US-China trade war, we’re still only about three bucks. And so what ended up happening is some of the rhetoric around the rare earth metals starts to accelerate, and this breaks out very very aggressively. And going back to our framework, this is a stock that had been exceptionally boring and exceptionally a piece of And you need to be a little bit careful just because these these market caps, the again, on that spectrum in that framework, market cap, the lower the market cap, the more risky this is. You’re not going to see something like Nvidia or Tesla make a move like this though. So that’s kind of the pros. You get these crazy moves. And so this breaks out. And now look at these initial bars. Even on these breakout bars, we’re maybe moving about a dollar. But look what happens. We hold prior bar lows. One, two, three, four, five, six, seven, eight. Maybe it’s like nine bars if I had to eyeball it. Yeah. And then the range of these bars accelerates. So even versus a couple months ago, a range on some of these bars, we’re talking the low to high is maybe 35 cents. Even when we start to get volatile, we’re talking about a range of of low to high of like a dollar. Oops, a little bit too much. And so what we see here is okay, dollar range. Then we start to have like a $3 range. Then all of a sudden we start to have a $4 range. And then we have close to a $5 range. So this stock is really capitulating to the upside. It’s doing so on massive volume again. It’s holding prior bar lows. We’re far above that upper Bollinger. We’re really far from the moving average. Yes, there’s news in the sense that there’s the trade war going on and some of the escalation between China and the US over over the metals, but there’s nothing fresh per se. That’s kind of what’s been driving this whole move to begin with. Nothing so fresh on to explain this acceleration. And when we go through those variables, we start to say, “Wow, this is really really good.” Between the volume, the magnitude of the move where the stock has over doubled in a matter of a week or two. We’ve done so extremely cleanly. The price is going kind of asymptotic. And all of that is is really favorable to do this. And so you could have traded this on a intraday basis, but then you can also trade this on a swing basis, where when we break prior bar lows is right here at about 1550 or so, you can short that and give an initial stop up to there, and then trail using prior bar highs. And the distance to the moving average is is pretty good. And we ended up not making so amazing a reward, but we do end up making about I don’t know, three bucks or so. And the other thing is past this first initial day, your stop and your risk then starts to trail. So once this day kind of elapses, your risk only ends up being a dollar. And so there’s also other ways you can structure this trade, because I don’t know if there’s ever any absolute optimal way to do this, but what I would say is you can backtest or or use this framework for, okay, if this wick is really far away on the prior day and I short here, maybe I just want to give it to the the highs of this bar. And a lot of times that can be acceptable. And you what you’ll want to do is see how does that affect your win rate? How does that affect your risk and reward? And all of this ends up being acceptable and it kind of just ends up being like your own personal belief in your data and everything else. And that’s kind of some of the art and nuance of looking how good is this intraday? How good is the intraday setup that I think it’s going to trade cleanly? How confident am I we won’t break here versus up there? And this is another just kind of textbook awesome swing trade example that traders could have could have done this year. And it’s very much applying those same concepts and that framework where I would give this again, being to the short side, it’s a little bit riskier, the market cap’s a little bit scarier. Uh this wasn’t particularly super liquid. So I would I would give this probably maybe a B plus A minus uh just because this move was so far from the moving average and the scale of it and how boring it is. So it’s all those variables coming together. Which as you said, so like you know, factoring in the market cap and the short nature will still distinguish cuz I think a lot of people always, as we’ve talked about a few times, they would see an opportunity and then just execute accordingly not taking in these different variables that really do change in in terms of the actual trade setup that’s presenting. Yes, and if we go to some comparables, like this USAR, this USAR was another uh rare earth name. And if we look at this chart, this was a fine short, but this to me it wasn’t moving as cleanly. We had some down days in here. We had these red bars. It wasn’t as clean of a trend. This actually ended up working and and would have been fine, but for the most part, I’m trying to use my framework and go for the most extreme examples. So I’m shorting the UAMY just because the magnitude, the cleanliness, the amount of up bars, all those nuances help increase my win rate. And so even though this USAR ended up working, in the aggregate, those decisions add up and it’s the difference between me avoiding a lot of the losses other people take and then me also sizing up the best ones much more aggressively and doing that concept that I often talk about, that exponential bet sizing. Because to your point, like it worked out this time, but then all the times it doesn’t work out, that’s always the trick, right? The time it works out, you usually don’t take it and then the and then you try every other time and it doesn’t work. Or the worst case is the one time you do try it, it does work out and now you’re convinced every time that it doesn’t that it’s okay cuz that time it worked, that time it worked. And that becomes a spiral in itself. Yep, and the thing is you’re always going to have losses, right? And so you need these wins to really offset all those other trades. I think most traders, we all make mistakes, we all lapse in selectivity. So you really got to make the really, really good charts count. And so to give you uh really recent on one just to make it fun. So we’re recording this in late November just before uh good old American Thanksgiving. Uh and so this Bitcoin chart, what ended up happening is we were we had a lot of price acceptance and we were maybe a little weak, we tried to break out, we get these highs, we kind of collapse, we get a lower high, we get a lower low, we get a lower high. So this is one way to define the trend. We’re also now below this moving average. And so we were this was a sharper move, but price acceptance, a little nothing move, but now this is almost like the third leg down. And so the more legs, that’s another one of those variables where I love stuff that has made like three legs or more down because the more legs, the more probable of a bounce. And the more legs we’ve gone, the more I can argue, wait, equilibrium price is like up here, not just not just down here, but up there. And so in this example, uh we had this initial leg, weak bounce, uh even smaller next leg, but then we start to really panic and then we flush out. And so this flush out was the first time we’re kind of meaningfully below the Bollinger band, we’re really far from the moving average. Like here, we’re just kind of in the range, we’re not far from that moving average, we’re not below the lower band. Bollinger band. Here it’s it’s okay, we’re just barely. Now this is multiple legs, this is the highest volume flush out we’ve had. And now we get Bitcoin, this fell kind of like I mean, from that prior close, like that was it almost a 10% move. And if you were to go to this intraday, which we will, you will see this was very, very panicky. And so this is what then sets up a a potential long and even a swing long. So now we’re going to jump to that price action. The other thing I’d say is Bitcoin on the spectrum is hard to value and that it’s not quantitative, there’s no cash flows. That being said, Bitcoin is pretty accepted at this point. Like it is very institutionalized, there’s ETFs, everybody’s watching it, there’s a lot of capital kind of arbing it out. And for the most part, it’s it’s pretty steady. Like look at look at some of these bars. We’re talking about a 1,000, 2,000 bar range. And then, like I said, we had an almost $8,000 range. So now we’re going to jump to that intraday. So now look at this. Right around 2:30 a.m., we got this massive, massive liquidation. And so I mean, I was asleep during this. Um I did have bids in, which was which was amazing. And so this is so big where this to that chart example that we did earlier is one of those times where you might want to buy intra bar because the waiting for that turn here, at that point, if you’re waiting to buy up at 84,000, most of this move is already retraced. Like Bitcoin just fell 5% pretty much in in 4 minutes. Massive, massive move. So that’s where it’s a stop is harder, like you might need to wait for an intra bar turn. Or, and I know this is kind of heretical to even say, you might be buying some front side for small size without a stop. Like I absolutely will buy stock, crypto, whatever you want to call it. I will buy stuff on the front side, but my size is so much smaller. And in the case where, I mean, I was literally asleep, I had bids in. So when I’m doing something blind, I’m even smaller, right? And so this made this panic and that’s one of those situations where you can buy front side. And then look at this bounce. So this massive, massive bounce, almost a full 100% retracement. Why was this retracement so big? Because this move is so extreme. This was the most asymptotic, most waterfall-y, most panic we’ve seen of any of the examples. Look how stable this was. This was not even moving, I don’t know, $100 a bar maybe, $100 a bar if that. Then out of nowhere, we drop $4,000. A 5% move in 4 minutes. So that is one of those things, we’re super stable. This is like the probability of this bouncing is so high, but you got to be careful if you’re buying front side. And that’s why sizing is key. But then it’s not surprising to me that this bounce is like 80% that this holds prior bar lows and does so well. So that is amazing, but then we end up rolling over. And so what we end up getting is we bounce, but then if this is kind of the the high, the higher low, the higher high, we break that higher low and we then start to have a lower high. And then we have a lower low, lower high, and then we panic. And so then I’m sure a lot of people flushed out, but we reclaim. And so then even here, we kind of break that that trend where this was the low and that was a lower high, but then we break it. And not only that, we also break that that moving average, which was a little bit of resistance. And so then you can re-enter and structure this trade. And now say you’re a swing trader. If you’re a swing trader and you bought some intra bar, you can then trail this using prior bar lows. And so part of the appeal of this being becoming a swing trade, and I’m at the time of this recording still long some of some of this Bitcoin for that reason, is this was leg one. To me that was leg two. This was a way more capitulatory leg three. This was the highest volume of the past few weeks. Like I said, it was the most extended. The intraday was a really big panic. We break trend. So then if I want to do this as a swing trade, so I had bought some, I scalped some out as as this bounced. Now I’m still swinging a core. And so I’m just doing this, initially it was going to be to lows. Now it’s just prior bar lows. And so I don’t know when I’ll get stopped out, but for me, if this does bounce well, the moving average is all the way up there. So it’s feasible that I mean, now like today wasn’t so great, yesterday was a really great close, but it’s feasible that this could, you know, bounce into the low 90,000s or even if this was a really strong bounce, which is not happening today, there’s a world where I could have seen this bounce to like 95,000. And so that’s like a real world example of how I’m structuring these trades and combining all these concepts where Bitcoin has been extremely stable. We did lose almost 30% actually more than 30% of its value over a couple weeks. Okay, like nothing’s really fundamentally changed like the market had it had its own little pullback and like the market panic is kind of what led that to flush out in the way it did. So, it’s understanding that okay Bitcoin’s like look, you can’t quantify it but it’s pretty boring. The daily chart’s awesome. The intraday was a panic and using that framework and then defining a trend to kind of capture this stuff. Definitely. And just final question there before we wrap up in terms of a scanning for these opportunities, how does that look from your perspective? Are you looking at things that are are going more parabolic then identify you know, are we looking to turn? Like how does that look from the sort of identification side of things? Yep, so all of the above. So, I have daily chart filters that are scanning for stocks above the Bollinger Band Okay. or below the Bollinger Band. I have filters that are scanning for number of up days in a row and down days in a row. So, you can build filters where it says I want to see patterns that are holding that prior bar lows pattern or the prior bar highs. So, I’m a million percent scanning that. I’m always looking at the most in play stocks and I’m always trying to move to where the best setups are. Never do I wake up saying oh, I am going to trade A B and C today. I wake up with the mindset of I’m going to trade whatever’s offering the best opportunity. Love that. Lance, I’m sure there’s plenty more that we can go into and hopefully we can have you back on Chart Fanatics but thank you for going through all of this with us today and everyone at home, drop a comment of your biggest takeaway from this episode. Any questions you have, throw them in the comment section below as well. As always, you will find links for Lance in the description below so make sure you check those out and other episodes are on screen right now so check those out also. Hit like, hit subscribe and this has been Chart Fanatics. Until next time, take care.