Moving Average

Additional trend definitions: holding above VWAP all day (Nvidia on May 18th before blowout earnings) and holding above key moving averages (First Solar weekly chart). Lance emphasizes a core principle: all technical concepts are fractal — they apply identically whether you zoom into a one-minute chart or out to a monthly chart. The same structure that defines an intraday trend defines a secular bull market.

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.

Within each hot theme, Ted narrows to the top one to three stocks — the names with the strongest fundamentals, the cleanest charts, and the highest institutional interest. He notes that recent themes have cascaded: AI drove energy plays, then software plays, then rare earths. A good theme produces multiple waves of opportunity across related sectors. The key discipline: don't chase every name in a hot sector. Find the leader — the stock that first reclaimed all moving averages, showed the tightest consolidation, and produced the most linear advance — and focus your size there. The second and third names in a theme almost always produce weaker returns with more chop.

Ted introduces a quantitative approach to measuring linearity: count how many consecutive days a stock makes a new high without breaking the previous day's low. He's building a scoring system at Reverd that tracks the percentage of time a stock stays above key moving averages over a given period, turning qualitative 'smoothness' into a numeric score. The more linear the move, the easier it is to hold — linear stocks respect the 5-day and 10-day like guardrails, giving the trader clear exit signals. Choppy stocks break key levels constantly, forcing constant decision-making and eroding conviction.

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.

As SNDK extended into a parabolic move, Ted's approach was to build a position cushion through partial sells at technical resistance and ATR extensions rather than holding everything for maximum gain. The mindset: 2.5% per month compounding equals roughly 35% per year, which is world-class portfolio management — the goal is to protect gains so the cushion allows more aggressive positioning later. A 10 ATR extension above the 50-day was his trim signal; a bearish engulfing candle on high volume warned of a potential reversal. His acknowledged lesson: he was undersized in this trade (one of the two best opportunities of early 2026), and a pyramid to 7.5% would have made the year in a single position.

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.

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.

Schwager traces trend following from Ed Seykota's era in the late 1960s — when running a simple moving average program on a brokerage firm's mainframe over the weekend was so unusual that the edge was enormous — to today, when every retail trader has access to the same tools and concepts. As trend following became widely known and universally taught, the edge degraded: more practitioners created more fake breakouts and shorter-term counter-trend moves that made staying in trends far harder. The underlying rationale still holds — real supply-demand imbalances take years to resolve, so genuine trends exist — but the return-to-risk ratio has compressed substantially.

"Once it becomes too popular, you start getting a whole bunch of fake breakouts and very short-term wild swings. The trends are still there, but they become choppier — and the edge that once printed money is now much smaller."

Once in a position, Kristjan trails his stop to the 10-day or 20-day moving average depending on how fast the stock is trending. He takes partial profits on the way up to reduce risk and lock in gains while keeping a core position running. When a stock he already owns forms a new consolidation and breaks out again, he treats that as a completely fresh trade with its own rules — the original position is managed separately. This framework keeps him from cutting winners too early or violating his risk rules when adding to a hot name. Using a trailing stop on each tranche means the worst outcome on any add is losing a defined amount, never letting a winner fully reverse.

With the broader market in a neutral state, Weinstein identifies where genuine leadership is showing up: biotechnology has been almost universally strong, semiconductors and AI-related names have been outstanding, and the Russell 2000 has finally broken above its 200-day moving average after a prolonged period below it. The Russell breakout is particularly meaningful — when small-cap stocks join the large-cap leaders, the rally becomes broader and more credible as a sustained move rather than a narrow tech-driven spike. This broadening of stage 2 action across sectors is what Weinstein looks for to confirm a genuine change in market character.

Weinstein explains why stage analysis creates the most favorable risk/reward environment for active traders. When a stock has been thoroughly destroyed during a stage 4 decline and has since built a base, the emergence into stage 2 with moving averages beginning to turn up creates an entry where the natural stop is close and the potential upside is large. Buying into stage 3 or stage 4 reverses this equation entirely: the easy move has already been made and downside risk far outweighs remaining upside. The system's entire edge comes from entering early in the cycle, before the crowd has recognized the opportunity.

Drawing on four decades of navigating every major market cycle, Weinstein argues that trader failure almost never comes from a bad system — it comes from overriding a good system when it becomes uncomfortable. His rules are deliberately simple: regardless of how good the fundamentals look, if a stock is in stage 3 or stage 4, stay away. If the moving averages are declining and price is below them, there is nothing to debate. He reflects on how his track record of catching every major bull and bear market since the 1970s came not from brilliant forecasting but from following a consistent, non-negotiable process through every uncomfortable moment.

In a live walkthrough of his Global Trend Alert newsletter recommendations, Weinstein reviews both successful positions and trades that did not work — narrating exactly what he sees and why each chart passes or fails his standards. He explains how the 50-day and 200-day moving averages define the structural backbone of any stage 2 setup, how the slope of those averages indicates stage health, and what distinguishes a genuinely high-quality base from a merely acceptable one. A chart that otherwise looks like a stage 2 setup but has nearby overhead supply — prior resistance from previous highs — gets downgraded: buyers will need to work through that supply before the move can fully materialize.

"It's not an A-plus chart because you do have supply."

Weinstein explains a fundamental change he has made to his exit rules to account for the dramatically higher volatility of modern markets. In earlier decades, his primary exit trigger was a close below the 150-day or 200-day moving average. Today, with stocks capable of dropping 20–30% in days rather than weeks, waiting for those slower signals means absorbing losses that are difficult to recover from. His updated rule: when a stock closes below the 50-day moving average, he exits immediately, without debate. He frames this not as pessimism but as adaptation — the mechanics of stage analysis remain intact, but the specific thresholds have been recalibrated to match the reality of how fast modern markets can move.

"I'm totally disciplined. I never argue with my system."

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."

Weinstein continues the gap analysis, showing how the same gap pattern that signals a strong stage 2 entry becomes a warning when it appears in an extended stock. Using the Nvidia chart, he identifies how a third or fourth gap — appearing late in a significant move, far above the moving averages — shifts the probability from continuation to exhaustion. When that late gap is followed by a terrible close on heavy volume, the warning is clear. He explains that he trimmed Nvidia positions for clients on exactly this analysis, separating the short-term tactical view from the long-term thesis: Nvidia remains a strong company, but the technical evidence argued for reducing exposure after the exhaustion pattern appeared.

"That to me is an exhaustion gap. It's late in the move."

Weinstein walks through a series of stocks on his sell list, demonstrating the recurring patterns that signal stage 3 and stage 4 breakdowns: double tops followed by 50-day MA breaks, systematic series of lower peaks indicating distribution, and head-and-shoulders patterns that breach both the 150-day and 200-day moving averages. Each break of the 50-day MA is a warning — individually survivable but collectively diagnostic. Using live chart examples from multiple names, he shows how the accumulation of these warning signals makes the eventual stage 4 breakdown predictable rather than surprising, even in what he considers a neutral market.

"Each one is a small warning — a warning heart attack."

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."

Ted points to Nvidia's post-earnings price action as the distribution warning: the stock gapped up on extraordinary news (Blackwell chips, revenue beat), the open was the high with no follow-through all day, and it closed at the lows — a bearish engulfing candle through multiple moving averages. This is one of the most reliable distribution signals: exceptional news with no price follow-through means every seller who wanted to distribute into strength has done so. The market had been building toward this: quantum computing names up 100-200% in weeks, Palantir's rapid ascent, everything going vertical. When the leader of the whole move shows that pattern, it is a flashing warning about the broader environment.

"When a stock gaps up on exceptional news and the open is the high with a close at the lows, it reveals that every seller who wanted to distribute into strength has done so."

Ted runs a structured market assessment across three layers: short-term trend (21 EMA), medium-term trend (50-day), and long-term trend (200-day). The best environment has all three stacked in order with price above the 21 and watchlists overflowing with setups. The worst environment has the 8 and 21 crossing below the 50 — which happened for the first time in 136 sessions during the late-November 2024 recording. He also reads market leaders and watchlist density as a qualitative confirmation: when everyone is frustrated and focused on one name, the environment is failing. When setups are everywhere and no one is complaining, it is game-on.

"There's times to grow assets and there's times to protect."

Ted's exit framework operates in two modes. Selling into strength: trim when price reaches 3-4 ATRs above the 21 EMA, or 8-10 ATRs above the 50-day moving average. Climax top signals that accelerate trimming include the stock heading toward 12 o'clock trajectory, multiple gap-ups in a row, 7-8 green days out of 10, and the largest daily volume ever after an extended move — institutional capitulation to the upside, not accumulation. Trailing rule: exit most of the position on a close below the 21 EMA; trail a smaller remaining piece on the 50-day or 10-week for the highest-conviction fundamental names. The combination captures both the bulk of the move and the occasional multi-month runner.

"Always trail a piece and sell into weakness because you never know how high a stock's going to go."

Ted emphasizes the importance of studying market history — looking at what happened in prior cycles, prior corrections, prior bear markets — because the same patterns repeat. The moving average stack (8, 21, 50, 200) encodes trend health in a single visual, and the 200-day is the final decider: below it, you do not want to be long. Ted also discusses measured-move expectations and how the concept of symmetry (first leg = second leg) helps set reasonable profit-taking zones. The discipline of always reviewing history before forming an opinion prevents the recency bias that causes traders to believe this time is different — it almost never is.

"If we look at history — what's happened in the past, what creates market cycles — those same things are what create market cycles today."

Layer four — market environment identification — is the hardest to develop and the most valuable. Ted explains: not all strategies work 100% of the time, but there is a period when your strategy is in favor — that is when you push the gas and do most of your trading. Layer three, progressive exposure, is the mechanical implementation: automatically increasing size and position count when feedback is good, automatically reducing when it turns negative. The host asks what process Ted uses to identify when conditions favor his system. The key is learning to read the market's posture: is the trend healthy? Are leaders acting well? Are watchlists full? These qualitative signals, combined with the moving average stack, tell you whether to grow assets or protect.

"Not all strategies work 100% of the time, but there is that period of time where your strategy is in favor and that's when you want to push the gas."

Don, River's co-founder, built the firm after watching his father-in-law suffer a 50% drawdown at Morgan Stanley while battling cancer during the 2000 dot-com crash. That experience drove the firm's core value proposition: match S&P returns with dramatically lower drawdowns by using active trend-following to move toward cash when markets deteriorate. MSTR and Bitcoin in late 2024 illustrate stage 4 downtrends in real time — both are below a declining 40-week and 200-day moving average with no basing structure. Ted will look for stabilization and EMA recapture before considering re-entry; he is not a mean-reversion trader and will not buy the dip into a declining trend.

"Nothing good happens under the 40-week, especially a declining 40-week and declining 200-day moving average."

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."

Ted explains his application of Weinstein's stage analysis framework using the weekly chart and four simple moving averages (10, 20, 30, 40-week SMAs). Stage 1: price choppy around the MAs after a downtrend, lines flat or slowly turning — the base-building phase where institutions accumulate quietly. Stage 2: 10-week stacked above 20, above 30, above 40 — all rising with slopes aligned, price above the 10-week — this is the uptrend, and the only stage where you want to be long. Stage 3: lines start flattening, price oscillating across them — distribution, where institutions are selling into strength. Stage 4: price below a declining stack — the downtrend where you short or stay completely out. The full cycle typically takes 2-4 years. Stages 1 and 3 are where traders lose money: Stage 1 can last years, chopping up anyone who tries to anticipate the breakout; Stage 3 looks tempting because the stock is still near highs, but institutional distribution means every rally is being sold. The operating rule: do not trade Stage 1, do not trade Stage 3. Long only in Stage 2, short or cash in Stage 4. Ted emphasizes that these stages apply to every liquid market, from stocks to crypto to indexes.

"Long in stage two, short in stage four. Looking at the alignment and slope of the 10, 20, 30, 40 will literally keep you out of trouble."

Ariel’s early P&L was comically small — $3, $5, −$8, −$10 days — because he wasn’t risking anything, just figuring out the platform. There is no single book that tells a new trader how to do everything: how to add a moving average to a chart, how to find gappers, how to read level 2. You either ask people or figure it out yourself. Once he committed, he had no other job and still hasn’t had one since. He put in 10–12 hours a day — at his desk 90 minutes before the open, an hour or two after the close, sometimes at night — buying courses, joining chat rooms, studying successful traders on FinTwit. The core discipline was simple: focused on not losing money, buying dips, cutting quickly if wrong, and compounding the frequency of small wins. He got kicked off his broker for exploiting midpoint fills with too many market orders.

"My P&L some days was like three bucks, five bucks, lose eight, lose 10 because I wasn’t trying to risk anything. I was just trying to figure out what the heck was going on in the markets. What is VWAP? How do I even put a moving average on my chart?"

Ariel started swing trading with a basic setup: move up, move sideways, surf the moving averages, breakout. But not every chart is picture-perfect, so as he gained experience he added specific setups to his playbook — undercut and rally from Gil Morales, the VCP from Mark Minervini, the flat base breakout from Pat Walker. Market environment and the stock’s industry group determine which setups work and when. For short selling, his trick is simple: put a minus sign in front of the ticker to flip the chart upside down — if it looks bullish inverted, you short it. The philosophy: "I’m just a trader and that’s just a setup. In real time, I’m just a risk manager." Price is the only thing that pays — not news, not earnings, not CNBC. Master one setup, go to the next, and play both sides of the market.

"I’m just a trader and that’s just a setup. And in real time, I’m just a risk manager. Nothing else matters — not news, not what Trump said, not what CNBC is saying, not what the earnings are saying. None of it matters. Price is the only thing that’s going to pay you."

Ariel knows what he’s going to lose before he ever enters a trade — if a position is 10% of his portfolio and he’s risking a 2% stop to the low of day, the max loss is 0.2% of the portfolio. As a swing trader, you’re wrong roughly 60% of the time. The most common trades are small green, small red, and flat. There is never a big red trade because the stop is defined before entry — unless an overnight gap creates an anomaly. The home runs like HIMS or Nvidia take care of themselves: trim some into strength, trail the moving average, and let the rest ride. The best stocks in the world hold up best when the market goes down, and the weakest stocks act relatively weak even when the market is strong — this asymmetry is the core filter. Journaling is essential early on to build the data set that validates what works, but becomes less necessary once the patterns are internalized.

"As a swing trader, you’re going to be wrong like 60% of the time. The most common trades you take are small green, small red, flat trades. We never take big red. Why? Because we know exactly where we’re wrong before we even get in."

Day trading is extremely difficult — you need to come up with a new, bright idea every single day in a market that may not be offering any good setups. Swing trading flips this: your homework is done at night when the market is closed. Ariel’s scanning process starts on FinViz with industry group relative strength over one, three, and six months to identify where institutional money is flowing. Then he filters for stocks above the 200-day and 50-day moving averages, adds fundamental criteria (good earnings and sales quarter-over-quarter), and checks which individual names are holding up best. "Now your universe of stocks just went from everything to the best stocks in the best groups in the market." Limit orders with stops at prior day lows mean a trade can trigger while you’re at a 9-to-5 job. Even your aunt "can slow down in the evening with a glass of wine and say, ‘What are the best groups? Which ones have good earnings and sales?’"

"I don’t think I’m some kind of an anomaly... Swing trading is one of those things where your homework is done at night when the market is closed. I know exactly where I want to be with the four, five or six names on watch for tomorrow, the night before."

Transitioning from day trading was psychologically difficult — Ariel was used to making good money every single day. The mental hurdle was asking: "Who cares about a seven-figure trade if it’s going to take four months? I can make $50,000 a day and do it in 20 days." But the reality of day trading is down days, changing markets, and heart-rate spikes. Swing trading lowers the tempo: he holds Rocket Lab from under $6 to $30 over five months, Nvidia for multiple months. Moving averages dictate trend strength — as long as the stock is above them, he doesn’t think about it. "I can hang out with my dogs. I can go get my haircut — and I still have positions working for me." The goal is to be in the best companies making the biggest moves: "Who doesn’t want to be in Nvidia from 200 to 1,000?"

"I can hang out with my dogs. I can go get my haircut, right? And I still have positions working for me whether they’re coming up or down. As long as they’re above those moving averages, I don’t think about it. I don’t really care."

Mental capital consumption is much higher in day trading because shorter timeframe moves require oversized positions to move the needle — a 2% move with a 5% position barely registers. In swing trading, time pays you: a 30–40% move on a 10% position meaningfully compounds the portfolio. P&L swings are less violent because you’re not adding money until existing positions show traction. Ariel uses the TOAST trade as a case study in what he could have done better: he bought in September and got stopped out weeks before the interview, giving back a substantial amount of the gains. He could have sold more into strength when it broke the 50-day moving average. The saving grace: "In the back of my mind, if I get stopped out of TOAST and I get stopped out of my longs, I’m getting really paid on my shorts" — hedging turns losers into a portfolio-level trade.

"As a swing trader, you let time be the thing that pays you versus position size. The P&L swings aren’t as violent. You’re not putting more money to work until you’ve seen traction on the other things that you’ve gotten yourself into."

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 pillar list tracks mega-caps because they drive the indexes. When Microsoft gapped down in early February and failed to reclaim its moving averages while the QQQ still looked fine, he read it as a warning that the market was not acting right and that he should not be aggressive on the long side. His tier-two list holds growth and micro-cap names, separated into stocks with more than $100 million average dollar volume and less liquid names; he prefers trading the liquid ones because illiquid small caps carry more gap-down risk.

"If Microsoft is bouncing towards the declining 9 and 21 EMA, it is not a good sign for being too aggressive in longs."

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."

Newer traders prioritise the setup over the environment, Ang says; the longer you trade and the more winners you study against an index chart, the clearer it becomes that the market sets the odds. When the NASDAQ is above a rising 10-day and 20-day moving average, breakouts follow through more easily; when the index is below all its relevant moving averages, he treats almost any breakout as likely to fail. That makes market environment the first filter on how much risk he is willing to take, before he looks at a single stock.

"When the index is trending below all the relevant moving averages, you can almost guarantee that any breakout you find will fail."

Ang walks through the April 2025 Liberation Day low as a case study in reading the market rather than predicting it. The first signal was technical: leaders began breaking their 20-day exponential moving averages in February, so short-term momentum was gone. Through the selloff he screened for relative strength and found growth names holding above their moving averages while the NASDAQ sat below all of its own, and sentiment on X was universally bearish. The turn came on a Monday gap-down that immediately snapped back — an undercut and rally — with the NASDAQ testing its February 2021 breakout level, which turned into support, and the strongest leaders breaking out first. No single indicator called the bottom; it was the sum of the evidence.

"There's no one indicator that will tell you the market has bottomed. It's more like the sum of the evidence, putting the puzzles together."

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."

To learn market environment, Ang adopted Qullamaggie's exercise wholesale: chart every big winner of 2023 and ask where he would have bought, where he would have placed his stop, how he would have managed the trade, and whether the stock respected its 10-day or 20-day moving average on the way out. He repeated it until the patterns became obvious, then overlaid the index on his entries and exits and saw that when the QQQ was extended, breakouts tended to fail — so he became more selective and bought pullbacks instead of breakouts. Rereading the first 100 charts in O'Neil's How to Make Money in Stocks produced the aha moment: the biggest winners come after market corrections, which made him more patient in the current decline.

"The biggest opportunities, the biggest winners, happen after market corrections. Why didn't I get it until now?"

Ang separates the mechanical part of his process from the discretionary part. His screen looks for Stage 2 uptrends: price above a rising 50-day and 200-day moving average, ideally above the 20-day exponential moving average where he engages; market environment must be favorable or the win rate collapses. He then demands relative strength — the RS line above its own 21-day moving average, or simply a stock moving sideways or up while the market falls, as Fastly did on its earnings gap while the market was selling off — followed by a volatility contraction on low volume that shows supply has dried up. Finally he checks extension: he prefers the stock less than four ATRs from its 50-day, because beyond that the meat is off the bone.

"When there's low volume as a stock is consolidating, there's not a lot of supply... it just takes a little bit of demand to push the price higher."

Ang runs his universe through DeepVue, using preset scans plus custom ones — for example, when the market is down 2% for the week, he scans for stocks up 10%. During the week he moves names through three lists: a wide list covering the universe for the next couple of weeks, an almost-ready list for stocks showing relative strength and tightening price and volume, and an execution list of his top five to ten names for the session. A fourth list collects breakdowns: he does not scan for shorts, he lets the market tell him when to look, demoting stocks that lose the 20-day exponential moving average onto the short candidates list. He repeats the process every day because it builds a feel for the quality and quantity of setups on both sides.

"I don't exactly scan for shorts. I let the market tell me it's time to look for shorts."

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."