The Mathematical Trading Trick A 23 Year Old Exploited For 969 Percent

TITLE: The Mathematical Trading Trick A 23-Year-Old Exploited For +969.8% In 12 Months (Full System Reveal) CHANNEL: Zero to Alpha DATE: 2026-05-16 ---TRANSCRIPT--- Imagine losing on almost four out of every five trades you take. 731 losing trades in a single year. That sounds like a disaster. That sounds like someone who should close their brokerage account and never open it again.

The money in your account, it didn’t do too well. It’s gone. But what if I told you that those 731 losses combined with just 209 winners produced a 969.8% return in 12 months. A return so extreme that it set a new world record in the stock division of the US investing championship, beating out 579 competitors from around the globe. That’s exactly what Martin Luke did. And no, it wasn’t luck. It wasn’t leverage gambling. It wasn’t meme stock moonshots. It was a system. A mathematically precise system built on one counterintuitive insight that most retail traders will never accept. What do you mean? I I have $100. Not anymore, you don’t. Poof. The size of your stop loss matters more than the direction of your trade. Today, we’re going to break down the exact framework Martin Luke used to produce this return. The math behind his tight stops, the specific chart setups he trades, the position sizing formula, the tools. Martin Luke is living proof that entry, quality, and discipline risk management are the only things that matter. Let’s get into it. Stan now more than ever you need to understand the importance of saving money. Through Christian’s streams and methodology combined with Mark Minvini’s books on risk management and stop setting, Martin began to build a framework, not a strategy based on prediction, a system based on survival and asymmetry. Let’s look at the raw numbers because they’re going to challenge everything you think you know about what profitable trading looks like. 209 winners, 731 losers, a win rate of 22%. So, my win rate is further decreased to 22%, but I don’t really look at my win rate that closely. He doesn’t even care. And here’s why he doesn’t have to. Let’s compute his expected value per trade. Expected value equals win rate time average win minus loss rate time average loss. That’s 0.22 to 2 * 15% minus 0.7 8 * 2.5% which gives us 3.3% minus 1.95% equals positive 1.35% per trade. Positive expected value on every single trade despite losing almost four out of five. Now think about what this means over 940 trades in a year. If every trade has a positive expected value of 1.35%, the compounding doesn’t just add up, it explodes. The trader with the 60% win rate, the one who feels like they’re doing great, actually has less than half the expected value per trade of someone who loses on 78% of their trades. The math doesn’t lie. And this connects directly to what we proved in our last video. Remember, the riskreward ratio doesn’t create edge. Your entry quality creates edge. The ratio is just how the edge shows up in your equity curve. Martin Luke is the real world case study of that principle. This is the section of the video that I want you to pause and screenshot because what Martin showed in his Trader Lion presentation is in my opinion one of the most important mathematical relationships in all of active trading. And it’s almost never taught. So if you look at the blue line, this is for the 25% return trace. So if you are tightening your stop from like 3% to 1.5% um for a 25% return trade, then you can gain a 8.34 uh risk multiple. So in other words, that it actually can compensate you for a um for eight losing trades. So, if you’re getting stopped out from by by like eight times in uh eight times just by tightening your stop, you can still um gain an advantage uh by just tighten your stop from 3% to 1.5%. Scenario A, entry at $100, stop at 97, that’s a 3% stop, target 125 for a 25% gain. The R multiple is 25 / 3, which equals 83R. Scenario B, same entry at $100. Stop at 98.5. That’s a 1.5% stop. Same target of

125. The R multiple is 25 / 1.5, which equals 167R. Look at that curve. Below a 2% stop, the R multiple doesn’t just increase, it accelerates parabolically. This is the mathematical magic trick Martin is exploiting. The exact same trade, same stock, same entry, same eventual price target produces dramatically different results depending on how tight you can get your stop. R multiple equals trade return divided by stop width. This is a simple division, but because the stopwidth is in the denominator, as it approaches zero, the R multiple approaches infinity, it’s a hyperbolic relationship. This is why Martin obsesses over getting his stop to 1.5% or less.

The the entry is really really right. So, it’s like a maybe like sniper approach. So if I’m not correct and I I take a loss, uh that’s mean that means I’m not entering in the right time. The tight stop isn’t just about limiting losses. It’s a position sizing multiplier. When your stop is tighter, you can take a larger position while keeping your dollar risk identical. This is how 0.5% risk per trade translates into the position sizes that produce 969% returns. Let me show you the actual math. Say Martin has a $50,000 account. He risks 0.5% per trade. Maximum loss per trade equals $250. Now watch what happens when we change nothing except the stop. Scenario A, the wide stop. Entry at $25, stop at $24.25. That’s a 3% stop. Risk per share 75. 250 divided by 75 gives us $333 shares, an $8,325 position. That’s about 17% of the portfolio. Scenario B. Martin stop. Same entry at 25, stop at 24, 62, 1.5% stop. Risk per share 37 1/2. 250 divided by 37.5 gives us 6667 shares, a $16,675 position. That’s 33% of the portfolio. Same stock, same entry. Same $250 at risk, but the tighter stop just doubled his shares. And if you’re following along on Trading View, try this yourself. Open the long position tool. Set your account size. Set your risk percentage and just move the stop. Watch the position size change in real time. The tighter the stop, the bigger the position because you can afford more shares within your risk budget. Now, if that stock runs 25%, which his average winners do, the wide stop, 333 shares times $6.25 profit per share. That’s a $2,081 gain. An 8.3R winner. Martin’s tight stop. 667 shares times$625. That’s $4,169. A $16.7R winner. Same $250 at risk. Double the profit. The tight stop didn’t just improve a ratio on paper. It put him in twice the shares. The R multiple math and the position sizing math are working together, compounding his edge on both sides simultaneously. One winning trade compensating for 16 losing trades. This is the engine of the entire system. Not prediction, not high win rate. A symmetry through precision. I really um enjoy like um setting a really tight stop and then seeing the stocks to um to um like uh go like really um um right away or take takes. Yeah, go right away uh from my stocks. Now that we understand the math, let’s talk about how Martin actually finds the stocks he trades. Martin uses three scanners daily. Scanner one is the pre-market gap scanner. This identifies stocks gapping up on heavy volume before the open. It flags potential episodic pivot trades, stocks making news-driven moves. Scanner 2 is the potent scanner. This scans the previous day’s strongest performers. When multiple stocks from the same industry show up on this scanner, Martin knows a theme is heating up. Scanner 3 is the leader scanner used on weekends. This scans for the biggest movers of the past 30 days. It captures sector rotation and longerterm thematic momentum. So from the screeners, if I’m seeing multiple of the stocks that is in within the same industry. So for example maybe yesterday um but yesterday was a down day but still there are like for example these mining company like the metals names are really strong like there are lots of metal metal names that going up then I would uh I would develop a sense that okay so metals could be another like but metals is an existing leading theme so it’s not an a potential one but when there’s one theme that is not the existing leader that um keep popping up or pops up uh within the same day. There are lots of the names that pops up within the same day. Then it would um really catch my attention. Once a theme is identified, Martin categorizes stocks into a tiered watch list. Lead means the 9 EMA is above the 21 EMA, which is above the 50 EMA. This is the strongest momentum. These are buy candidates. Mediocre means mixed EMA ordering. Watch but don’t act. Lag means the 9 EMA is below the 21 EMA which is below the 50 EMA. These are the weakest and potential short candidates. This filtering process eliminates the vast majority of stocks from consideration. Martin is only interested in the fastest moving names in the hottest sectors, stocks with an average daily range above 5%. Because those are the stocks that can produce the R multiples that make a 22% win rate system profit. This is the core of what made 2025 different from 2024 for Martin. In 2024, he traded primarily breakouts. In 2025, he shifted heavily toward pullback entries. figured out that like the breakouts starting to um to be to to work less if less effectively or have has a lower win rate. So it I got stopped out from the breakouts more often and stocks tend to shakes me out and they go um to the to the original direction. So I think okay maybe I should try to learn pullbacks too because I also I see a lot of um more and more stocks trying to pull backs into the support areas and find support and then just bounce back right from the supports and so I decided to like um learn some pullbacks. Let’s break down exactly why with a real trade on Nvidia. And this is also Martin’s first setup in action. the first pullback to a rising 9 or 21 EMA within a constructive base. This is his bread and butter. You’re looking at one chart, September through November 2024. As the price action unfolds, I’ll show you where each trader enters and then we’ll compare the math. In early September, Nvidia puts in a base low around $101. Over the next 3 weeks, price rallies inside that base. The EMAs stack bullishly. The 9 crosses above the 21 and by September 26th it reaches

That becomes the resistance level, the ceiling of the base. Both traders are watching it. Then the stock pulls back. It drops from that ceiling down toward the rising 21 EMA bottoming at 11514 on October 2nd. This is exactly the pattern Martin hunts for. A stock that runs up, pulls back into a rising EMA, and snaps back. The faster and sharper that bounce, the stronger the signal. So, here’s where the pullback trader acts. October 2nd, price bounces off the 21 EMA, he enters around 117 on the 5-minute chart. Stop just below the candle low at 11514, risk 1.6%. He’s in the trade before the breakout even happens. The breakout trader is still sitting on his hands. He needs price to clear 12767 before he can do anything. Five trading days pass. October 3rd, the stock closes at 122. October 4th, 124, climbing back toward that ceiling. The pullback trader is already up 6 or 7%. The breakout trader is still watching. October 7th, price finally pushes through that September ceiling. The breakout trader buys at roughly $128. But look where his stop is. All the way down at the base low, $101. That’s over 21% risk. Now look at the table. Same stock, same rally to 148.88 by November 7th, but the numbers tell two completely different stories. The pullback trader risked 1.6% to capture 27%. That’s a 17:1 reward to risk ratio. The breakout trader risked 21% to capture 16%. Less than 1:1. One trader turned tight risk into a massive R multiple. The other needed a wide stop just to stay in the trade. Same stock, same move. The only difference where and when they entered. That’s the structural edge of the pullback. A tighter stop because the entry is closer to support. A lower cost because the entry happens before the breakout, not at it. So, I really love the stock that is gapping up and then reverses or just the stock is um opening lower and then just go just go down and just um falling into the support level such as the EMAs for this case or sometimes the angle VWAP.

The second setup Martin relies on is the anchored VWAP break and retest. VWAP stands for volume weighted average price. anchor it to a swing low and it shows you the average price since that date. Weighted by volume, it tells you who’s been in control, buyers or sellers since the anchor. Same stock, Nvidia, August 5th, 2024. The Japan carry trade unwinds, global markets crash, and NVDA drops to an intraday low around $90. That’s your anchor, the capitulation candle. the exact moment panic selling burned itself out and new buyers stepped in. Drop an AVWAP from that low and for three straight weeks, every single pullback bounces right off it. Price climbs from 100 to 129. The AWAP rising underneath the entire time like a floor. No candle closes below it. Buyers are firmly in control. Then earnings hit on August 28th. The stock gaps down 6%. Two trading days later, September 3rd, the entire semiconductor sector gets destroyed. NVDA drops another 10% in a single session. Price has now fallen 20% from its high, but the AVWAP from August 5th is still climbing from below. It’s heading straight for price. Watch what happens when they finally meet. The very like the um important message that I wanted to to to show is the price is really reacting. I I’m actually like if if is um if the indicator is I don’t care if the indicator is really like fancy or really like the the the formula behind it like it’s got to work. It’s important to like know yeah it’s important to know um the the basic part of it but the most important part is whether the price is is reacting and whether it really works. So I think Wer Anchor web works really well. Now zoom into September 6th through the 11th. Price has been selling off for nearly 2 weeks, but look at what’s quietly building underneath. The anchored VWAP from August 5th has climbed into the 104 area. The 21 EMA is declining into that same zone from above. The 9 EMA is curling right into it. And sitting just below all of them, the $100 round number, a level every single trader on the planet is watching. Four completely independent levels, all converging in the same $8 window. This is what Martin calls a multiple edge entry, and it’s the highest conviction version of this trade. One group of traders is watching the AVWAP. Another is watching the 21 EMA. Another is watching the round number. They’re using different tools, but they’re all seeing support in the same zone that concentrates buying pressure into one tight area. The entry comes on the bounce from this cluster. Stop goes just below the lowest level, roughly 2% risk. When the when these supports level are lining up, those are the really key levels that um I wanted to uh engaged in and and you can have an edge. you have you will have the highest edge if you’re buying those areas. So if an so if a trader buys uh buys at the anchor VW web and also there are another trader buys at the 9 EMA and another one buys at the previous highs or any supports level then you you can like there are there would be the highest probability point that the that the stock will find supports at. This is Martin’s version of a VCP like setup. Instead of Minveni’s multicontraction volatility pattern playing out over weeks, Martin looks for microvolatility contraction, an inside day, or two tight candles followed by a range expansion via gap up. The stop goes at the inside day low, giving him an extremely tight risk. Now, let’s compare the two side by side. Mini’s VCP unfolds over weeks to months. Three to four progressively smaller pullbacks, say 25%, then 12, then six. The entry comes when price breaks above the base on volume and the stop sits below that final contraction. Typical risk 7 to 8%. Martin’s inside day breakout happens in days, one or two inside days where the range fits entirely inside the prior bar. The entry is a gap up above that range and the stop goes right at the inside day low. typical risk 1 1/2 to 2 1/2%. Both systems identify the same phenomenon. Selling pressure drying up before a move. They just operate on different time scales. But Martin’s tighter entry allows for much larger position sizing, which is exactly how he generates those parabolic R multiples we discussed earlier. Now, let’s see this on a real chart. Same stock, Nvidia October

2024. After that September bounce, NVDA rallied back into the low30s and stalled. October 14th, a full range candle. Pause. Mark the high. Mark the low. That’s your first range, the box. Next two days, October 15th and 16th. Both candles fit entirely inside that prior bar. The highs are lower, the lows are higher, the range tightens. That’s your second range. smaller, quieter, compressed. The sellers have completely dried up. Then October 17th, TSMC reports blowout earnings before the open. And Nvidia gaps above everything, above the inside day high, above the range ceiling. That gap is the entry and the stop goes at the inside day low. Under 2% risk, range contraction expansion. That’s Martin’s trade. One more critical piece. Once Martin identifies a daily setup, he drops to the 1 minute or five minute chart to time his actual entry. The daily chart tells him where to buy. The intraday chart tells him when this multi-time frame approach is how he consistently achieves those sub 2% stops. Normally I would look for a um really really really fast um um a a flush to the downside into the supports level which is on the hourly uh 9 and the 21 EMA. Uh is it the 9 or 21? Yeah, a 9 and 21 EMA in the in the hourly and then I will f I will look at the 1 minute or the 5 minute or the 15 minute candle for the first breakout of the previous bar high. Let’s walk through a complete trade from identification to position sizing to exit using Martin’s exact framework. The stock is ION Q. September 2025, right in the middle of his competition run. Step one, the weekly chart catches Martin’s attention. Look at the week of September 1st. The entire weekly range is under $3. That’s the tightest candle in 6 weeks. The highs are compressing, but the lows keep stepping higher. 37 38 40. [snorts] That’s a coil. Volatility is contracting while the trend stays intact. Both EMAs are rising and tracking close together. This stock is loaded. I really want to point out this quantum setup on the weekly chart because on the daily it looks a little bit messy like this was a chopping around undercut the 50 pulling back to the 150. But on the weekly, it’s actually looking much more cleaner and better, especially on this huge um pin bar also the inside week. So these two like the pin bar in the inside week just like um yelling at me like is you know this one is really setting up. It could be another leader. It could be the really good VCP also the cup of handle. So on the weekly really really stands out um from from me.

Step two, the daily chart confirms the setup. Zoom into the base forming between August 29th and September 8th. Seven trading days. The stock chops sideways between 40 and 43 while the 9 and 21 EMA quietly converge underneath it. By September 8th, the gap between those two averages is just 27. On a $40 stock, that’s almost nothing. And right at $43, you’ve got a ceiling. The doc has tested that level three times and failed. That’s the resistance Martin is watching. Because when a stock finally breaks through a level it’s been rejected at repeatedly, the sellers at that price are gone. There’s nobody left to sell. September 9th, it breaks above

43. September in 11th, it pulls back and bounces right off that same 43 level. The old ceiling becomes the new floor. That’s the entry day. Step three, the 5-minute chart. This is where Martin actually pulls the trigger. September 11th opens at 4434 and immediately sells off. For 15 minutes, the stock drops candle after candle all the way down to 43 39. That’s the support test. It’s tagging that same $43 level we just talked about on the daily. Now watch what happens next. 40 minutes from 950 to 10:30. The stock goes nowhere. It chops between 4375 and 4433. tight, quiet, but underneath that quiet surface, something is happening. The 5-minute 9 and 21 EMA are converging. The gap shrinks from 20 cents to 10 to
44. And at 10:30 a.m., they touch zero gap. The same pattern that showed up on the weekly. The same convergence that formed on the daily, now it’s appearing on the 5-minute chart. Three time frames, one signal. The crossover fires at 10:30. And at 10:35, the next candle breaks above the prior bar high of 4419. That’s the entry 4420. The stop goes at
45. Just below that support test from the morning sell-off. 80 cents of risk on a $44 stock. That’s less than 2%. And from 10:35 onward, the stock never looks back. It closes the day at 47, opens the next morning at 4733. And by the end of September 12th, ION Q hits 56, an 18% gap day, the kind two of move that only happens when selling pressure has completely evaporated and buyers overwhelm the book. That gap day doesn’t come out of nowhere. It comes out of everything we just watched. The weekly coil, the daily convergence, the five-minute crossover, the setup created, the conditions, the entry captured them. Now, let’s do the math. Martin’s account is at $150,000. He risks half a percent per trade. That’s $750. That’s all he’s willing to lose. Entry price 4420. Stop 4340. The distance between those two levels is 80. 750 divided by 80 gives him 937 shares. That’s a $41,000 position, about 28% of his portfolio. All from risking half a percent. Here’s the chain. 0.5% risk flows into a 1.8% stop, which creates a 28% position, which captures the entire move. If the stock runs, and it runs from $4420 all the way to $73 by mid October, a 65% move. That $41,000 position generates $26,986 in profit from $750 of risk. That’s a 36R trade. Think about what that means. Martin could lose 36 trades in a row, 36 consecutive stopouts, and one single winner wipes all of them out. He’s back to break even. Everything after that is profit. You don’t need to be right often. You need to be right big. Now multiply that by the quantum names all moving together. ION Q, RGTI, QBTS, all setting up and breaking out within days of each other. Martin enters three or four simultaneously. When an entire sector moves, you don’t need one big winner. You get three or four at the same time.

You can see a one good trade like could give you more than like 20 hour or even 30 hours. So, you can compensate for your previous losing trades. um for like 30 times. So if you’re getting like in if you’re talking really like an extreme case, you’re getting up you’re getting stopped out for like 30 times before you getting into this trade, you can still you can still be break even. Martin’s exit strategy is more flexible than his entries and that’s deliberate. First partial sell 10 to 15% of the position when the stock moves up more than three times its average daily range from entry. Subsequent partials sell another 10 to 15% each time the stock makes a notable extension on the hourly chart final exit close the remaining position on the first daily close below the 9 EMA or on a decisive reversal handle if the stock is extended. my cell rules. I actually don’t have a very strict sell rule. I would sell partial into strength in uh when it’s up three hour or five hour. But um sometimes if the market is really strong and I um sometimes would not take partials if um if I think it is um the markets is really strong and I have um huge cushions on other positions and yeah I sometime would would just hold the whole positions that trail the whole position along the along along the upside. But um generally I would uh sell into strength when I think it’s really extended on the lower time frame. Let’s see how that plays out on ION Q. September 12th, the day after entry, ION Q gaps to $52. That’s three times the average daily range from his entry. First partial, he sells 15% 140 shares. locks in about $1,000 of profit while the position is still running. September 24th, the stock pushes to $67. This is his second partial target take profit. He sells 140 shares, books, $3,200 of profit. October 6th is his third target take-profit. He exits another 140 shares at $78 for another $4,700 profit. He’s now sold 45% of the position across three sales and locked in over $8,000. But the remaining 517 shares are still riding. Then October 15th, for the first time since the breakout, ion Q closes below the 9 EMA, 7241 versus the average at 7463. That’s the signal. He closes the remaining 55% at $73. That final lot, 517 shares, generates almost $15,000 by itself. Total profit across all four exits, $23,26 from $750 risked. That’s a 31R trade with partial selling along the way. 31R from half a% risk. Notice the asymmetry in his rules. His entries are mechanical and precise 5-minute breakout of prior, R high, stop at candle low, exact. His exits are discretionary and flexible selling into strength, adapting to market conditions, monitoring the overall portfolio. This is deliberate. Tight entries protect capital. Flexible exits maximize the upside of winners. No honest trading video should only show the highlights. And Martin, to his enormous credit, was completely transparent about December. After 11 months of extraordinary performance, Martin suffered a 26% draw down in December 2025. Nearly all of it was self-inflicted. December, this is overtrading. And then um you can see the table below. So I take around um maybe around seven 70 80 trades in December. And uh I you can see 46% of the trades I think is it’s is it’s really bad trades. When I mean bad that uh that I think I shouldn’t have taken it uh in the beginning. So a lot of them are the I think a little bit random trace. It becomes like a vicious cycle. So I keep jumping between longs and shorts but they don’t have much follow through. And then um I just got um punched in both in like like slapped in in in both ways. Trades taken 70 to 80 avoidable trades 46%. Core problem flipping long short in chop root cause overtrading plus behavioral slippage. I think December there aren’t there aren’t any like significant losses like most of them are really like death by thousand cuts and also the um original like the the the the gift back in the profits like the profits in the off uh existing loans that I’m that I’ve taken in in November. So um so it they all ask together like um my um my longs are the the profits that my longs are pulling back right and then there that that’s the draw down that’s the first draw down and then I started okay should I started doing some shorts and then then this this is the second draw down and then that’s the flip between the longs and the shorts and this just further increase the draw down this is a critical lesson the same tight stop system that produces incredible returns in trending markets creates a specific vulnerability in choppy rangebound markets. Each stopout is small, but when you take 40, 50, 60 trades in a month and 78% of them lose, those small losses compound into a significant draw down. If Martin takes 70 trades in December with a 22% win rate wins about 15 trades times AVG winner reduced in chop say 5% equals about 75% gross gain losses around 55 trades times AVG loss 2% equals about 110% gross loss net approximately minus 35% gross before partial profit. offsets. The lesson isn’t that tight stops are bad. The lesson is that a tight stop system requires discipline to stop trading when the market environment turns hostile. Martin himself identified this. The best way to do would be like trading less. So, um really wanted to trade reduce the number of trade this year too. Yeah. Win rate is irrelevant without context. A 22% win rate with a 6:1 reward to risk ratio produces more expected value per trade than a 60% win rate with 1:1. Tight stops are a position sizing multiplier. Cutting your stop from 3% to 1.5% doesn’t just reduce your loss, it doubles your position size at the same dollar risk, which doubles your profit on winners. The relationship is parabolic. Entries must have predictive power. Martin uses multiple time frame analysis, EMAs, anchored VWAP, volume, and sector theme identification to find moments where the probability of a move higher genuinely exceeds random chance. The system works because the entries have edge, not because the exits are clever. The same system that produces 969% can produce a 26% draw down in a single bad month. Risk management isn’t optional. It’s the difference between a career and a blowup. Weekly charts provide the big picture that daily charts hide. Martin repeatedly identified winning setups, including the entire quantum computing sector trade by checking the weekly chart when the daily looked messy. in the beginning of your journey, I think it’s good to like just copy other traders uh uh uh teach you or share and then but I think in the as you progress as you trade more and have more experience and know more about uh on your own then you you should like maybe um like adjust it a little bit to like make it more suitable for you and and develop your own style. And this is really important. I think Martin Luke started with $1,300 and a university textbook he describes as actively harmful to his trading. He survived a 50% draw down that would have ended most traders careers. He studied for 2 and 1/2 years before his equity curve even recovered to break even. And then he produced the greatest single-year return ever recorded in the stock division of a competition that has included names like Paul Tudtor Jones, Mark Minervini, David Ryan, and Ed Thorp. He did it with a 22% win rate, a 1.5% stop-loss, and a system built entirely on mathematical asymmetry. No evidence, no trade. If you found this valuable, subscribe for more breakdowns of the real math behind trading. And if you haven’t seen my other videos, the Kamegi deep dive and the upcoming mathematical proof on riskreward ratios, go watch those next. They’re the foundation everything in this video builds on. See you in the next one.