Entry Strategy

Mark walks through a recent Schwab (SCHW) purchase to demonstrate his setup in real time. The stock formed a large base, tightened up on the right side, and produced a reversal recovery pattern — a specific setup Mark named where a stock undercuts a prior squat low, reverses, and closes strong. Mark entered at 79.45 as the stock moved through the pivot level, getting about 45 cents of slippage. He monitors a five-minute chart alongside the daily and weekly, but he never trades off intraday charts alone — even his day trades are based on the daily setup. When the stock gaps up but the gap is microscopic relative to the pivot, he does not consider it extended.

The host asks where Mark places his initial stop when buying right at the open. Mark explains that for a swing trade, the day-one stop may differ from day two. The key principle: if a stock needs more than 5-8% of room, the timing of the entry was not precise enough and the entry point was not tight enough. The stop is not just a risk tool — it is a selection tool. Mark will not enter a stock that requires a wide stop because the volatility means the 'bucking bronco' can knock him out on normal noise. Tight entries from volatility contraction patterns allow tight stops, and tight stops allow larger positions for the same dollar risk.

Lance introduces the concept of a reference price as the anchor that defines trend in real time. Using the GME intraday chart from January 28, 2021 — the stock melting down 210 points — he shows how waiting for the counter-trend (a break of prior bar highs) transforms what looks like fighting the trend into trading with it. This single shift in timing — waiting for the reversal confirmation rather than guessing the bottom — eliminated his biggest drawdowns and turned his mean reversion from a source of losses into a source of gains.

Lance wraps the presentation with four audience challenges: define all the ways you identify a trend, make a list of rules based on trend vs. range-bound conditions, systemize reasons why trends begin and end, and dissect your own trading to find where trend thinking can optimize your strategies. Host Richard opens Q&A with questions about structuring mean reversion trades with a catalyst, finding stocks with no fresh news that are still in play, and using price spike and volume filters to identify the right names.

Diving deeper into identifying the right side of a V-bottom: Lance looks for daily charts that are exceptionally extended and intraday charts showing capitulation volume. His key heuristic is 2x volume — the capitulation bar should show at least double the volume of the prior bar, ideally on both daily and intraday timeframes. But the first and most important step is trading the right names: 99% of stocks are noise most of the time. The edge exists only in stocks that are truly in play with trending, exceptional moves.

Lance explains why he uses two-minute bars: it is not magic, but a practical timeframe. Technicals are fractal, so the same concepts apply to any bar size. His entry uses the prior two-minute bar high (for longs) or low (for shorts) as the trigger, and his trailing stop uses the same prior bar levels. When a stock breaks a prior bar high and holds, the trend is confirming — and when it breaks a prior bar low, the trend may be ending. The method is mechanical, repeatable, and removes discretion at the moment of execution.

Lance describes his preparation before the trading day: identifying key levels on in-play names, setting alerts at those levels rather than staring at the screen, and mentally rehearsing the specific criteria that would trigger action. He emphasizes that knowing your criteria dead cold before the open prevents the most common category of mistake — reacting to price movement in real time without a pre-existing framework. The mental state when a setup triggers is readiness, not discovery.

After nearly blowing up, Ryan spent a weekend reviewing every stock he had bought over the prior year and found one repeating pattern: he was buying extended stocks — names that had already moved too far from their base. His fix was radical simplicity: buy only at the exact breakout point, right where the stock comes out of a proper base into new highs. That discipline produced his first major winner almost immediately (Circuit City, then called Wards). The rule is mechanical: draw a line over the majority of the base; the buy point is there, not at the highest tick. Buy where institutions are forced to buy — at the breakout — and you're aligned with the heaviest volume.

“I'm only gonna buy exactly at the buy point, exactly where the stock was coming out into new highs above the majority of the base.”

Ryan's first championship year validated the buy-point discipline, but the next lesson came from position sizing: he was taking positions that were too large and not giving them enough room, getting shaken out before the move could develop. His fourth year was flat, his fifth he came in second, and then he won three US Investing Championships. His core insight, reinforced by O'Neil, is that the patterns that create big winners are timeless — a Bethlehem Steel chart from 1915 has the same base, same breakout, same volume signature as today's leaders. The only thing different is the name at the top. Human nature doesn't change, and neither do the charts it produces.

For stocks already extended — Ryan uses the example of UPSC going from 150 to 400 in three months — he advises watching for pullbacks near the 21-day moving average for possible re-entry, rather than chasing the extension. The math of further upside versus a potential 30% correction changes dramatically once a stock has already made the big move. Chasing an extended stock means your risk-reward is inverted: you're risking a large correction for whatever upside remains. Waiting for a proper pullback or a new base resets the risk — you enter at a defined level with a defined stop, the same as any other entry. The discipline is treating every entry with the same standard regardless of how much you wish you'd caught the first move.

After a pullback in SNDK, Ted explains his framework for re-entry: he waits for the stock to reclaim all key moving averages with all slopes rising before adding. He specifically uses the 20 SMA rather than the 8 or 21 EMA because the SMA keeps him out of false starts and reduces frustration — a principle he frames as maximizing reward-to-aggravation, not just reward-to-risk. The inside day low-volatility contraction, confirmed by his RMV indicator flashing below 5, is his precise entry signal. He never adds to a loser — averaging down is explicitly rejected. All position additions come into winning trades with confirmed momentum behind them.

Ted walks through how he scaled into the SNDK position. He started with a half-size position given the holiday-period uncertainty (thin volume, tax-loss harvesting, choppy conditions in late December), then added as the stock confirmed strength — reclaiming rising moving averages and respecting the 10 EMA. The pyramid approach: a starter position at the initial entry, a full-size add when the trend re-establishes, and a trim if the stock loses a key level. He also shows where he added a small starter in a leveraged GDX product (Nugget) using the same framework and it worked immediately, allowing him to pyramid as prior highs became support.

Ted walks through the GLD trade as a case study in a non-earnings momentum setup: gold has no EPS, but it checks every other magic elixir criterion — narrative (de-dollarization, government debt, geopolitics), liquidity, high linearity, and a 10-year cup-with-handle base. He initially passed on an earlier base feeling it was too slow, then re-entered when gold reclaimed all moving averages with tight volatility. The setup was confirmed by cross-referencing GDX futures: when the futures chart showed the same base, same moving-average reclaim, and same volume signature, the ETF entry had institutional-grade confirmation.

Ted quickly applies the same magic elixir framework to two more positions. Nugget (a leveraged GDX product) was a small starter at a 20/50 moving average reclaim with an RMV flash; it worked immediately and he pyramided into strength as a prior high became support. Silver (SLV futures) exhibited near-perfect linearity — consecutive tight flags holding the 10 EMA day after day — and his one regret was not pyramiding more aggressively at all-time highs. A bearish engulfing triggered his first trim but he held through two 10-EMA undercut-and-reclaims before the final new high squeezed shorts. Across both trades, the pattern is consistent: the best setups are the ones where holding is easy because the trend is clean, and the main mistake is not sizing up when the chart is screaming.

Host asks what an A+ setup looks like. Gon walks through a real example: a low-float stock that gapped up pre-market, faded out intraday, then formed a base at a reference level — a short-squeeze setup. His buy point is the breakout of the intraday high after that base has formed, with increasing volume as it reclaims the level. He doesn't read the news or care about the catalyst — he doesn't even know why the stock moved. What he cares about is the squeeze pattern: demand showing up, fades getting absorbed, base forming. On high-conviction A+ setups, he goes all-in — full account — drawing on Lance Breitstein's advice to go big when the trade is genuinely easy.

“My buy price is my stop loss — the moment it takes out my entry, that tells me the setup failed.”

Gon shows DPST as a masterclass in halts and squeezes: a 15-minute chart full of halt-up bars, running over 1,000% intraday. He deliberately stayed out during the initial frenzy because there was no tradeable entry — the stock was halting up too fast. Instead, he waited for the post-halt consolidation, when volume dried up and the stock went sideways, forming the base that signaled the next leg. He contrasts this with another stock that showed the same pattern on a smaller scale: pre-market strength, post-open fade, sideways base, then squeeze continuation. The playbook repeats across tickers and timeframes.

Gon walks through two more live trade examples. TPST: after an initial squeeze, the stock went sideways and formed a base rather than fading hard — he entered on the breakout of that base's high, using the base low as his stop. AVGR: same pattern — big move, sideways consolidation at a key level, squeeze continuation on a fresh catalyst. Both illustrate his recurring playbook: the continuation base after a big first move is often the better trade than the initial spike, because risk is better defined and the move that follows tends to be even larger.

Gon walks through a VFS trade: a slightly higher-priced stock ($21–22) that formed a bull flag on the open. He missed the initial entry because the move happened too fast — he didn't believe three bars was enough confirmation. He's now experimenting with holding for bigger moves rather than peeling off too early. As Mark Minervini advises: 'always keep chipping up' — take some profits to build a cushion, then let the rest run. It's hard to add back to a position when you're already at full size, so he's working on sizing in a way that leaves room to scale into strength rather than only peeling off.

April 27th was the trade that changed Gon's trajectory — a tight base formed on top of a prior base, entered with full size, and ran significantly. He recognized the VCP-like characteristics: the stock was consolidating above the lows of the prior base, showing strong relative strength. Because the risk was tiny relative to the potential reward, he went in with conviction. The trade worked — but more importantly, it was a validation of his ability to recognize high-quality setups in real time, not just in hindsight. It was the moment his chart reading crossed from academic to applied.

Tito adapts his option structure to the volatility environment. When IV is low, he trades naked long options — the premium is cheap and there's less time decay working against him. When IV is high, he uses debit spreads — buying an option and selling a further out-of-the-money strike to offset the expensive premium. He walks through a HOOD example: the stock pulled back to a level where he could risk $500 on a debit spread paying 1:3, versus a naked call that would cost more and suffer faster theta decay. The structure choice is governed by what the IV environment allows.

Tito discovered through his own data that Mondays and Fridays are his best-performing days. On Mondays, stocks emerging from tight consolidations often break out early, and options IV hasn't yet caught up to the move — so as the stock surges and IV expands, the option position gets paid on both delta and vega. On Fridays, zero-DTE options provide a different edge: if a stock like Tesla has only moved half its weekly range heading into Friday, the options are dirt cheap, and a skilled trader can bet on statistical mean reversion for asymmetric returns. Tito doesn't trade zero-DTE heavily, but the Friday dynamic is real.

Tito walks through his Tesla trade from September 2025. After a big drawdown from April highs, Tesla formed a multi-month base with higher highs and higher lows on declining volume — the classic contraction pattern. The 10, 20, and 50 SMAs crossed back and stacked bullishly for the first time since May. The horizontal breakout level at 357-358 was clear and unambiguous — he prefers horizontal levels over trendlines because two traders see the same horizontal level but different trendlines. On Monday September 8th, Tesla broke through but sold back down. Tito took his biggest loss of the year on the failed entry and got out near the low of the day.

Tesla set up again days later and broke out for real. Tito re-entered with the following week's 380 calls, priced around $2-3. His thesis: if this was a real Tesla breakout, the stock could move 30-40 points based on prior history, putting 380 in reach — and those out-of-the-money calls could go to $20. The trade worked: within two days, three-quarters of his position was off at 8-10x, driven by both delta and the IV explosion that accompanies a Tesla breakout. By the following Monday when Tesla gapped into the 420s, the remaining calls were worth $40 — from a $3 entry. The trade succeeded because Tito trusted the setup even after the initial loss, separating the failed entry from the still-valid thesis.

Tito's most memorable Apple trade was the August earnings. He waited until after the results came out and the next trading day began before entering. The setup featured volume drying up into earnings, price action tightening, and the stock surfing along the SMAs — what some traders call surfing on the SMAs. Apple had a history of making big runs, and the crossback of the moving averages set up a clean entry. The options went 10x, and Tito scaled out aggressively along the way — selling portions at 50%, 100%, and 200-300% — with most of the position off the same day. When a trade moves that far that fast, he'd rather lock in gains than swing for more.

RKLB had made an all-time high at 33 in January, sold off with the market, then began uptrending with an SMA crossback in April. After getting rejected at 33 twice, a low-volume pullback was quickly reclaimed — a buyer showed up the next week. Tito bought August 40 calls (roughly two months out) to trade the 33 breakout, giving himself enough time for the thesis to play out. The stock ran to 50 in two to three weeks, and the options went 5x. He was mostly out by 50, a psychological round number. The trade was powered by a fundamental catalyst — Rocket Lab was on pace for 20-plus launches in 2025 — layered on top of a clean technical setup.

Tito shares examples where option premium provided an edge unavailable from price alone. During the GME meme cycle, puts were so expensive post-run that buying them was a bad trade even if the stock fell — the premium collapse would eat most of the move. Conversely, call debit spreads during GME uptrends offered extraordinary risk-reward because the skew was so extreme. On a separate occasion, SLV puts refused to fall even as the stock rose — the persistent bid hinted at a looming reversal, and within 15 minutes the top was in. The lesson: option premium can act as a leading indicator when it diverges from price action.

Tito describes an XLE trade from January 2025. XLE had been stuck in a 100-120 range for roughly four years, and after a selloff took it to the bottom of the range, the RSI was deeply oversold on the daily. Rather than buy calls and fight potential further downside, he sold put credit spreads — collecting premium while defining his max loss. He also bought January 2027 $50 calls at around $3 as a lottery-ticket overlay: if energy really ripped over the next two years, these deep-in-the-money LEAPs had asymmetric upside. The trade illustrates how options let you price out specific scenarios and build position structures that match your conviction level and time horizon.

In February 2025, Tito took his biggest loss of the year so far on MicroStrategy. The setup looked promising — a higher-timeframe wedge building, horizontal resistance at 340, and an inside day on Tuesday after a strong Monday. His plan was to buy the inside day breakout. His mistake: he entered cents before the trigger actually broke, anticipating the move rather than waiting for confirmation. MSTR never made a new high and became the high of the day. In hindsight, the SMAs were stacked to the downside — he was fighting overhead resistance — and Bitcoin was similarly weak. Anticipating the entry turned what should have been a missed trade into a real loss.

Kristjan explains his core framework: stocks that make large multi-year moves do so in a staircase pattern — a leg higher, then a sideways consolidation or pullback where the volatility contraction tightens the range, then the next step higher. The setup is to identify stocks in a confirmed uptrend building one of these bases, and to buy when the tight consolidation breaks out to the next stair. Not every stock moves this way, but the best breakout candidates follow this structure consistently enough to make it a repeatable, systematizable approach. The pattern is the same whether the stock is at $10 or $500 — it’s the structure that matters.

Kristjan buys everything at once and aggressively — no scaling in, no waiting. He uses opening range highs (the high of the first one, five, or sixty minutes) as entry triggers, with the corresponding low as his initial stop. A one-minute opening range gets you in earlier with a tighter stop but has a higher failure rate; the sixty-minute range has fewer false starts but a wider stop. He accepts being stopped out intraday frequently — sometimes within two minutes of entry — because getting out fast and getting in precisely is how you keep losses small. Hesitation, he argues, only makes entries more expensive: you wait, the stop doubles in size, and now the risk-reward is broken before the trade has even started.

Weinstein walks through a series of charts to explain how gaps function as signals of institutional conviction. When a stock gaps up as it transitions from stage 1 to stage 2, confirmed by a move above its long-term moving averages, that breakaway gap is one of the strongest buy signals available. Even more powerful: when a subsequent pullback fails to fill that gap, it demonstrates that real demand stepped in and held price above that level. He notes that while roughly 90% of gaps eventually get filled, the 10–15% that do not — including a gap from 1962 on the Dow Jones that has never been filled — carry exceptional predictive power. News-driven gaps that fill quickly signal the opposite: the move lacked institutional backing.

“The 10 or 15% that don't get covered — that's a very powerful signal.”

Asked how to pick the best stocks from the many transitioning out of stage 1, Weinstein explains his forest-to-trees approach. The first filter is the overall market environment. The second is group strength: a great chart in a weak sector is worth less than a good chart in a leading group, so identify the leaders first. Third, check for minimal nearby overhead supply — prior price highs create resistance that absorbs buying and stalls moves. Finally, require volume confirmation on the actual breakout: without institutional participation showing up as a notable volume spike, the breakout lacks the force to sustain. All four boxes need to be checked for a setup to earn A+ status.

“Plus it's got volume coming in which shows that people are excited to do buying.”

Weinstein introduces his proprietary 4B- rating: a stage 4 stock that has been thoroughly destroyed, built at least a small base, reclaimed the 50-day MA, and has room to run with no nearby overhead supply. The minus suffix indicates the stock is no longer in free-fall but hasn't yet developed into a proper stage 1 base. For short sellers, the 4B- is the signal to cover; for aggressive early-entry traders, it marks the first point where a tentative long becomes defensible. Weinstein emphasizes that buying at 4B- requires patience — the stock may need months to fully transition into a stage 2 breakout, but the risk/reward at this late-stage-4 inflection is structurally favorable for those willing to wait.

“It's no longer a grade of whatever that stage is.”

Williams explains why he considers comparative strength — comparing related markets like corn against soybeans, or heating oil against crude oil — more actionable than traditional relative strength rankings across all stocks. A market that has held up best during sector declines and rallied hardest within its group is the one to buy; the weakest within the group is the one to sell short. He describes how his market focus evolved from thin, seasonal markets like eggs to deep, liquid futures — Treasury bonds and stock index futures — where his own orders cannot become the market and his stops fill as intended.

“Comparative strength is much more important than relative strength.”

Williams explains how Bill Meehan — who tutored three traders including Williams — combined a fundamental directional framework with Williams's technical timing to produce a system that worked. Bill taught Williams how to determine where the market was headed over weeks and months; Williams developed the entry mechanism: a volatility breakout system built around the opening price, introduced around 1982. The logic is straightforward: calculate an expected range for the day, bracket a small distance above and below the opening, and enter in whichever direction price breaks. Williams notes the system worked powerfully in pit-session markets but became less effective once electronic trading eliminated the defined opening range, though the concept still applies to stocks and swing trading setups through patterns like the OOPS reversal.

“We just bracket that — a little bit above and below the opening.”

Williams begins a live chart walkthrough by demonstrating comparative strength with two airline stocks — American Airlines and United Airlines. At a point where the sector was rolling over, American Airlines had made a higher high while United had not, making United the weaker stock and the correct short-sale target. Williams explains the principle: in a bearish sector environment, sell the weakest member — the one that could not rally as far — because it is likely to fall the hardest. He extends the concept to futures markets, looking for comparative strength relationships within families like stock index futures to determine which contract offers the best risk-reward for the directional view. The walkthrough shows how he identifies these setups on real charts with price structure alone.

Williams continues the live chart demonstration by walking through a complete trade from entry to exit. On the entry side, he looks for simple, repeatable setups: a higher short-term low in an uptrend or lower short-term high in a downtrend, trend line breaks, and the market trading above the recent high with seasonal and commercial support confirmed on the weekly chart. The entry directly determines his initial stop placement, and he uses a mechanical trend-following tool to trail the stop as the position moves in his favor. On the exit side, he uses price targets based on a methodology he learned from a 1960s book by George Seamans, taking profits when the market gets extended rather than waiting for a stop-out. He is candid that his entry techniques are no better than anyone else's — the edge comes from the layered preparation done before the trade is placed.

“My entry helps me with my stop-loss.”

Ted Zhang explains how a COVID quarantine in spring 2020 — watching his father's CNBC during a crashing market — was his entry point into trading at age 19, with no finance background. With no technical knowledge he noticed a structural pattern in SPACs: these shell companies traded near the $10 net asset value floor because shareholders would be repaid that amount if no merger occurred, creating capped downside with open upside when a merger rumor hit. He began accumulating near NAV and selling into announcement rallies — a self-discovered, intuitive understanding of asymmetric leverage before he knew what the term meant.

“Somehow just like some way without even learning, I intuitively understood asymmetric leverage.”

Host asks how Ted developed market knowledge so quickly without a finance background. Ted credits trial and error: diving into the COVID crash with no technical knowledge, he built his edge around SPACs by observing the structure — $10 NAV floor, asymmetric upside. The VTIQ/Nicola SPAC was his first major win: bought shares near $18, the definite merger agreement was announced, the stock ran to $70-80, and Ted sold all shares around $76 after a small pullback. He is candid that in 2020 with the Fed pumping liquidity, it was like shooting fish in a barrel — there wasn't a lot of skill to it. The broader SPACs ecosystem — Lucid, Tattooed Chef, Chamath's IPO series — kept feeding the edge for six to eight months.

“That was really the first big trade that got me into it. And back then in 2020 with the Fed putting so much money, it was just like shooting fish in a barrel.”

River's evolved CANSLIM checklist — internally called 'super stock criteria' or 'magic elixir' — screens for: high ADR and ATR (the stock must actually move), linear price action rather than erratic volatility, prior history of large sustained moves, big-volume ignition, and a hot theme or catalyst. Earnings and revenue growth are ideal but not required (Bitcoin has no earnings). Ted enters primarily on breakouts and episodic pivots — strength-based entries. Connor builds positions during pullbacks against rising moving averages. Their complementary entry styles mean the portfolio reaches full size more efficiently than either approach alone, and their genuine disagreements on specific trades serve as a quality filter.

“If it has everything like Nvidia, like SMCI — that's when we'll size the biggest.”

Ted expands on the Ted-Connor entry split. Ted enters at breakouts and on episodic pivots (gaps on catalysts) — buying strength. Connor builds positions during pullbacks against rising moving averages — buying weakness within an uptrend. Their complementary styles produce genuine disagreements that serve as a quality filter: if both see the same setup from different angles and still agree, the conviction is higher. If they disagree, the conflict surfaces considerations neither would have caught alone. The result is that the portfolio reaches full size across a range of entry points rather than concentrating risk at a single price, which naturally improves the average entry and reduces the emotional weight of any single fill.

“Connor enters on pullbacks, I enter on breakouts and episodic pivots. Having those different perspectives makes the total sum much more powerful.”

Steven argues that the best traders actively guess what the majority of people behind their screens are thinking and position against it. Every buy and sell click represents a human decision made under emotion. He warns against copying strategies without understanding the psychology behind them: buying because 'there's a higher high from the previous day' is meaningless if you don't know what the pattern represents in terms of human behavior. A strategy has to make sense fundamentally — on the level of psychology, not on the level of company fundamentals. The edge is in knowing what the crowd will do and being positioned before they do it.

“You kind of have to guess what people are thinking behind the computer because everybody basically clicking their mouse, making their decisions. So making a counter strategy of the majority people of what they're thinking is very important.”

Steven reveals the exact filters he uses to select trades: the stock must be up at least 20% on the day, have traded over 1 million shares in pre-market, be priced above $3, have a market cap under $1 billion, and float under 100 million shares. That's it — five criteria, rigorously tested, producing the best statistical results across thousands of trades. When asked why these specific numbers, his answer is straightforward: because he tested every variation and these produced the highest returns. The criteria narrow the universe of thousands of tickers to a focused watchlist of actionable setups. Having a tight, testable scan eliminates noise and reduces the decision fatigue that drives impulsive trading.

“I only use tickers that's up 20% for the day. Traded about over 1 million shares in the pre-market. The price has to be over $3. Market cap should be under 1 billion initially and float has to be less than 100 million. That's it.”

Steven explains what it means to truly know your strategy: not 'I think the stock will go red around here,' but knowing the minimum resistance threshold, the exact average pullback percentage (down to one decimal — -26.4% on the first red day, for example), and the precise exit criteria. He contrasts this with the typical retail trader who enters because 'there's a higher high' and exits because 'it feels like it might bounce.' He argues that if you're trading full-time, you must look like a full-time professional — and that means every decision is anchored to a specific, tested statistic, not an impression. You should be able to answer any question about your strategy with a number, not a feeling.

“I ask you what's the best minimum threshold resistance for you to short at — you will be able to give me an answer. What's the minimum pullback percentages in terms of decimal points for a red day? You will be able to give me an answer. Not you sitting there, 'OK well I think it's going to go red.'”

Steven addresses the tension between systematic criteria and intuition. When a setup meets all his statistical filters but something feels off — typically because intraday volume is behaving unusually, or a stock at resistance is showing abnormal buying absorption — he sizes down to 1/10th of his normal position rather than skipping entirely. He estimates that intuition plays a 20-30% role in his trading, primarily on the exit side: knowing when to cover half based on volume exhaustion patterns versus holding for the full statistical target. The average drop on his setups is -26.4%, but actual drops range from -5% to -50%. The statistics give him the framework; intuition — trained by thousands of repetitions — tells him which end of the range the current trade is tracking toward. Intuition is not mystical; it's pattern recognition operating below conscious awareness.

“Yes, it happens. Small size — that's the correct answer. One tenth of the size.”

Ariel describes the simple scalping formula that worked during the 2020–21 uptrend. In a strong trending market, draw horizontal lines at previous resistance areas. When price breaks through and then pulls back to that level, two forces converge: dip buyers stepping in against the level, and trapped short sellers who didn’t cover on the breakout now buying to exit near flat. This psychology turns old resistance into new support. Ariel used level 2 to read bid/ask acceleration, bought 1,000–2,000 shares for a 15-cent bounce ($300 per trade), and lived by the phrase ‘buy red, see green’ — buy the red candle, sell as soon as it turned green. The strategy broke in 2022 when the environment shifted from trending to choppy.

“Psychologically, previous resistance can become support because you have the dip buyers against that level and you have shorts who didn’t cover who are now getting a chance to get out. So there becomes twice the amount of buyers against the level of previous resistance.”

Luk credits Kullamägi with the biggest shift in his trading: moving from traditional breakout entries with 5–8% stops to aggressive entries from tight ranges with much tighter stops. Kullamägi emphasized that the best time to buy is when a stock breaks out of a tight range, and he drew trend lines differently from what Luk had learned. Above all, the lesson was to respect stops and manage risk first. Luk says those principles became the core of his own system.

“The biggest lesson I learned from him is how he manages his risk... tighter stops... tight ranges.”

Studying past winners such as Amazon, Adobe, First Solar, and Plug, Luk noticed a repeatable pattern: stocks that make big moves rarely revisit the low of the breakout day. Instead of gapping up 10% and down 15%, they grind higher along rising moving averages, which gives traders a logical place to set a tight stop. He cites Dan Zanger's line that winning horses don't back up at the starting block, and argues that if price takes out your stop, the entry was probably not the optimal buy point.

“Normally when a stock makes a big move it tends not to revisit the low of the breakout days... That's how I build my confidence for setting a tight stop.”

Luk's default entry is a break of the prior day's high, especially when the day before was an inside day: the tightness often precedes a strong directional move. He also uses opening-range highs, intraday range highs, and prior-week highs, and he sets stops at the low of the day; if the distance between entry and the low of day exceeds 5%, he switches to the low of the five-minute entry candle. The goal is always the same — a precise, low-risk entry where the stop is obvious.

“I really love inside days because of the tightness... after an inside day the direction the stock would go would normally be a strong trend.”

Luk explains the mechanics of opening-range high entries: the first one-minute candle after the open sets the range, a break of its high is the entry, and the low of day is the stop. If the opening-range breakout fails but the setup still looks intact, he looks for a re-entry at an intraday range high, using tight ranges and the 9 EMA as guides, with the new low of day as the stop. He uses one-minute charts immediately after the open and switches to five-minute charts after the first five-minute candle forms, preferring five-minute for less noise and a higher success rate.

“I really love the five minutes one because there's less noise and there's a higher success rate.”

Luk admits his SMCI entry was not his best: he bought after the breakout rather than at the prior-day-high trigger, partly because he was afraid of missing the move. What saved the trade was the weekly chart — a roughly six-month base that never violated the weekly 21 EMA and kept making higher lows and higher highs, followed by two tight weekly candles in January 2024. The weekly chart gives him the bigger picture and confidence to hold through daily noise; he prefers weekly context to support a daily entry.

“SMCI has been building a base since August... around a six-month base... it never violates the weekly 21 EMA.”

Luk's COIN trade was not a conventional breakout. He bought near the low of the day as price tried to reclaim it, because Bitcoin had formed an inside day and was breaking prior-day highs; he expected COIN to follow. Waiting for COIN's own prior-day-high breakout would have made the stop too wide, so he used the low of day and an anchored VWAP break to define risk. He later panic-sold instead of following his sell rules, then watched COIN set up another breakout without him — a reminder that even a good entry can be wasted by poor execution.

“I didn't wait until COIN gave me a proper breakout setup... I'm just using the low of day when it's trying to reclaim back from the low of day... the stop would be too wide.”

Luk bought AMC at the five-minute opening-range high and was stopped out when the breakout candle's low failed. He stayed with the idea, waited for the stock to form a tight range near the 21 EMA on the five-minute chart, and re-entered on an inside-day breakout. As price took out the high of day he raised the stop to the breakout candle's low — about 3.2% risk — and rode the position for roughly 170% before selling half premarket into strength near the declining monthly 9 EMA and 2020–21 swing lows.

“I bought the opening range highs on the five-minute candle breakout... I keep watching it until it forms a nice range near the 21 EMA... I bought the inside day breakout.”

SOFI was a cleaner, more traditional breakout than COIN or SMCI: after a move from $7 to $11–12, it pulled back for three days and consolidated near the 9 EMA, then opened in the upper part of the prior candle and took out the prior day's high. Luk entered there, set his stop at the low of day, trimmed a portion at six risk multiples, and closed the rest when price posted below the 9 EMA and growth names started breaking down in December. He had planned to trail on the 23 EMA but lost conviction in the broader market.

“It's a much cleaner breakout... three days of pullbacks and consolidation near the 9 EMA... I set my stop at the day low.”

Luk traded COIN's post-election gap as an EP without examining fundamentals — he only reads headlines to understand why a stock is gapping, then focuses on the chart. COIN gapped more than 10% premarket near prior swing highs; he entered around the opening-range high as it cleared the swing highs and kept risk under 3%. He trimmed at seven risk multiples and closed the rest when COIN closed on the 9 EMA, as December breakouts began failing.

“I won't look at the fundamentals of the EP... I'm just going to glance through the news and see the headlines... then I'm focusing on the charts.”

Luk entered SoundHound at the opening-range high with a 4% stop — wider than he normally accepts — because he did not want to wait for the prior-day-high breakout and widen the stop further. The trade worked, but he then sold poorly: he did not follow the 9 EMA and exited on what looked like a bearish reversal, only to watch price find support at the 9 EMA and run another 80–90%. He skipped the later breakout because the general market made him skeptical, which he accepts as part of trading.

“I entered at the opening range highs and I used a 4% stop... The lesson I wanted to point out is the poor selling... I didn't follow the nine-day [EMA].”

QBTS built a tight flag near the 9 and 21 EMAs after failing to push higher, then opened strongly. Luk bought the opening-range high but was stopped out within two or three minutes; he re-entered when the stock held and tried to break out again. He emphasizes how much difference a precise entry makes: a move that looks like less than half a bar on the chart can be 8–9% of risk. He sold most of the position into strength on accelerating volume and parabolic extension, and the trade alone contributed about 80% of his December profits.

“This trade alone contributes 80% of my profits in December... I bought the opening range highs but got stopped out... I still managed to find a re-entry point.”

Luk's short setup mirrors his long setup in reverse. He looks for a stock in a downtrend whose key EMAs are converging, then waits for a rebound into those declining averages to be rejected; he enters near the resistance rather than waiting for a breakdown of the prior day's low, and sets his stop near the high of the day. Because the risk is defined tightly, the trade can offer a high risk-reward even though he is not trying to catch a long-term decline. He leans toward shorts when the indexes are also near resistance and the market is in a strong downtrend.

“I take shorts near the converging EMAs on the declining EMAs... I set my stop near the high of the day... I'm more aggressive in taking the shorts.”

Host and guest walk through a Reddit short: a leg down, a shelf, a rejection at the moving averages, and an ideal entry into the 9 EMA with the stop at the high of the day. Luk explains that he exits shorts faster than longs — mostly selling into strength rather than trailing a moving average — because he is only trying to capture a move to a logical support level such as the 150 EMA, not a home run. He had already covered near the lows and felt no regret when Reddit kept falling.

“From the exit of the shorts, I'm taking the exit more aggressively than the longs... I'm not catching home runs in the short.”

Luk's recent short examples are SMCI and MicroStrategy. He shorts when the weekly chart is in a downtrend and the key moving averages are compressed and declining; for MSTR, the declining weekly 9 EMA is the level he wants to see reject price. On the daily, he enters at prior-day-low breakdowns or opening-range lows and covers quickly, reducing short exposure when the market bounces. He is careful not to crowd too many correlated shorts at once.

“The weekly chart is really on a downtrend and the key moving averages are really close to each other... MSTR should be rejected from the declining 9 EMA on the weekly.”

Ang has relationships with many of the traders he once studied, but he rarely acts on their ideas: if a name does not fit his own criteria, he will not trade it, because he will not have the conviction to hold it through a pullback. Taking someone else's conviction creates the worst outcomes — exiting early, or blaming the other person when the trade stops out — and he insists that treating trading as a business means taking full accountability for every decision. Asked how he found what fit him, he describes an experimental phase that produced his long-side setup: a Stage 2 uptrend, a pullback, a wedge pop above the 10- and 20-day exponential moving averages, then a tight mini launch pad.

“If I trade their idea, I don't have the conviction to hold on to it.”

Ang noticed that the traders he studied were all describing the same setup in different language: Oliver Kell's wedge pop and base, Minervini's VCP, and Qullamaggie's move that tightens as the 10- and 20-day catch up, forms a higher low, and breaks out. He tested those ideas with real money until he found his own version. The same experimental logic applied to risk: the standard 1% per trade sounded sensible, but after 10 or 30 consecutive losses the cuts compound into a serious drawdown; he found that 3–5% builds more failure into the system and suits him, and after a stressful Q1 2025 at 0.5–1% he moved to 3–5% from Q2 onward.

“They're all actually the same concept, just set differently.”

Ang says he no longer feels much FOMO, but he still beats himself up when a move is inside his strategy and he fails to execute — the recent example was watching Micron gap down toward its 10-day and rip higher without buying. When that happens he reviews the failure in his process and his mental state, including anything outside trading that may have cost him focus. He completely missed Sandisk's monster run, twice, and has learned to treat the market as an unlimited stream of opportunities: instead of chasing, he works on finding a way into a leading theme through a pullback to a moving average, because leaders tend to go further than expected.

“In the stock market, it's an unlimited stream of opportunities... there will always be another opportunity around the corner.”