Position Sizing

He credits two mentors — an early Pittsburgh boss who taught him craft, and Soros, who taught him the single most important lesson of his career: position sizing. When he joined Soros, he expected to learn about macro. Instead, he learned that being right or wrong matters far less than how much you make when right and how little you lose when wrong. That asymmetry compounds differently than anything else.

“It's not whether you're right or wrong, it's how much you make when you're right and how much you lose when you're wrong.”

Despite having more pattern recognition and tools than ever, he admits he was a better portfolio manager in his 30s and 40s because he had the courage to size into conviction. Wisdom and capital accumulate; willingness to act on them can quietly erode. He is actively trying to regain that nerve — not for performance, but because the game is more fun when you play it fully.

You will not get triple-digit returns from a well-diversified, low-turnover portfolio or from following traditional financial advisor advice. Mark uses leverage, takes very large concentrated positions at times, and generates tremendous turnover — all while managing risk just as stringently as he would otherwise. The US Investing Championship is a real-money contest with a million-dollar minimum in Mark's division, so professionals cannot simply gamble on penny stocks to win. The key ingredients: concentration, timing to avoid dead time, and the willingness to press when the setups are there. Mark calls 2021 his second most aggressive trading year ever, after 1995 when he was up over 400%.

Mark never dives fully into the market; he starts with test positions and ramps up quickly as they begin working. This is a key difference between a pro and an amateur: amateurs need too much evidence and by the time they get the green lights, it is often late. When Mark sees the 'whites of the eyes' he moves fast. As stocks rise, he sells into strength — this keeps him at equity peaks, cutting off volatility and drawdowns entirely. By selling at the highest price, there is no downside giveback. The speed of escalation and the discipline of taking profits into strength are what produce low-drawdown, high-return compounding.

Mark answers the exposure question directly: he starts with small pilot buys — if his normal position size is 20-25%, he begins at 5-10%. If those work, he bumps to 15-20% or adds more positions, typically reaching 25-50% invested after the first two entries. If everything is working — open profits growing, buy list expanding, new stocks breaking out — he moves quickly to 75-100% invested. But if the same four positions are up yet the buy list is thin and new breakouts are failing, he pauses. There is no purely mechanical black-box rule; there is some feel developed over nearly four decades of trading.

Lance explains a central sizing principle: when a stock is trending in the same direction on the intraday, daily, weekly, and monthly charts simultaneously, he adds roughly 25% more size. The alignment of multiple timeframes dramatically increases the odds of follow-through because every constituency — day traders, swing traders, and institutions — is positioned in the same direction. The confidence to size up on these rare, high-conviction setups is what separates exceptional P&L years from average ones.

Lance explains his risk management framework: every trade needs a defined stop, but the stop serves a purpose beyond loss prevention — it tells you when the trade structure was wrong. If he is drawing down significantly on a position, that drawdown is a signal that the structure is flawed, not that he needs a wider stop. He sizes up only on A+ setups where multiple timeframes confirm the trend, and keeps position sizes calibrated so that no single trade — or cluster of trades — can take him out of the game.

Ryan currently runs 10 equal positions, allowing individual stocks to grow to 15–20% when they perform — less extreme than his championship concentration, but still deliberate. His framework for high-growth stocks: because they carry far more volatility than the general market, being 80% invested in them is the functional equivalent of 140% invested in a standard portfolio. He avoids margin specifically because of this — when high-octane growth stocks turn, they fall so fast you can't exit quickly enough, and leverage amplifies that into catastrophic losses.

Reverd's risk framework starts from the portfolio level: they typically risk no more than 50 basis points per trade, and increasingly closer to 15–25bps, determined by how many magic elixir criteria the opportunity checks and their conviction level — the more boxes a stock checks, the more risk they allocate. Position sizes are capped at 12.5% in Turbo (the aggressive fund targeting accredited investors) and 8% in Protection (skewed to retirement accounts). All three funds — Turbo, Grow, and Protection — operate from the same playbook but with different risk tolerances calibrated to the client base.

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.

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.”

After the 2022 FOMC blowup, Tito was mentally burned out. He traded a $5,000 account throughout 2023 to rebuild — not because he lacked capital, but because his mental equity curve had cratered. He learned that there are two curves to manage: the equity curve on your P&L statement, and the mental equity curve in your head. When you have a big loss, you must size way down and let yourself work back up to the confidence level needed to risk real capital again. The 2022 experience set him back months — almost a year — mentally, even though mathematically he could have sized back up faster.

Tito sizes options trades by tying dollar risk to a percentage of his net liquidation value — typically around 3% per trade. Rather than using percentage stop-losses on options (which aren't meaningful for instruments that can gap), he sets a dollar amount he's willing to lose and adjusts position size accordingly. In a forgiving, breakaway momentum market, that $5,000 risk might represent a 40-50% option stop; in a whippy, volatile market, he'll size so that same $5,000 equals a 100% stop — giving the trade more room to breathe without risking more dollars. The governing principle is always dollar risk, not option percentage.

Schwager addresses the widespread 1% risk rule and acknowledges it is sound advice for most traders most of the time — but identifies a critical exception documented repeatedly across all five books. When conviction is very high and opportunity is clear, the great traders step on the accelerator. He tells the Druckenmiller story: when Druckenmiller showed Soros a billion-dollar position in the Deutsche mark ahead of German reunification, Soros asked 'you call that a position?' Schwager also describes Soros's Plaza Accord trade — when the yen surged 700 points overnight, Soros stopped traders from taking profits: 'The Fed just told me the yen is going up for a year. Why would I sell it on the first day?'

“Soros asks him 'how big's your position?' He says a billion. Soros says 'you call that a position?' — if you're that sure, why do you only have a billion on?”

Schwager revisits some of the extraordinary track records he has encountered across five books, including a trader who made roughly 25% per month for nearly a decade — documented and real. He explains why this does not compound to an absurd fortune: short-term traders cannot let accounts grow without moving the market against themselves. Many pull capital out consistently and keep trading size flat — the account value stays in a manageable range while the withdrawals fund their actual lifestyle. The 300%-per-year trader on $50,000 is not a billionaire because they cannot deploy billions the same way they deploy thousands.

“He was making 25% a month over nearly ten years. I know a lot of people are thinking — why doesn't he have one-fifth of the GNP? Because he wasn't compounding. He kept pulling the money out.”

At larger AUM, percentage returns necessarily compress because the manager becomes a price factor. Schwager uses Bruce Kovner as an example: Kovner averaged 88% per year as an individual trader but could never approach that at $20 billion. The question is not whether a given return is possible — it is at what size it is possible. The trader who prints 300% per year on $50,000 simply cannot replicate it at $5 billion. This is not a failure of skill; it is a structural reality of markets: every strategy has a capacity constraint, and the great traders understand exactly where theirs sits.

When the COVID sell-off bottomed in mid-March 2020, Kristjan had very few positions. He didn’t believe the bounce at first — but then saw an enormous wave of setups developing simultaneously. He went from two or three positions to seven, then to fifteen, rapidly scaling up as the bull market confirmed itself. Swing trading means sitting in cash for long stretches, so when a strong multi-month trend emerges you have to press it hard. He also addresses a related principle: the vast majority of his annual gains come from a small percentage of his trades. Most trades roughly break even or produce small gains; a handful of exceptional winners — maybe 15 to 20 percent of all trades — drive the year.

Kristjan explains how he has scaled his trading as the account grew: when his account doubles, his position sizes and risk exposure eventually double too — always in percentage terms, never in fixed dollar amounts. He keeps almost all his capital in the account, allowing compounding to do its work over time, withdrawing only for taxes and living expenses. On margin: he uses it only when things are going well and he has a profit cushion — margin is something you have to earn, not a default privilege. He got burned early using leverage at the wrong time; now he deploys it selectively during strong trends. Thinking in percentages rather than dollar amounts is the single most useful frame shift he recommends for traders at any stage.

Kristjan identifies failure to scale as one reason traders don’t achieve exponential returns: many master a setup but trade the same size for a decade, capping their results regardless of edge quality. The fix is simple but psychologically difficult — always think in percentages, never in dollar amounts or index points. One percent is always one percent whether the Dow is at 5,000 or 50,000. When your account doubles, your dollar risk per trade should double too; if it doesn’t, your edge is shrinking relative to your capital. He describes traders whose accounts have grown but who are still scared to increase dollar risk, even though the percentage risk hasn’t changed — a psychological barrier that quietly caps their compounding.

Williams identifies position sizing as the most critical element of trading — more important than entry timing, exit rules, or system sophistication. He risks between five and ten percent of equity per trade, higher than most professionals because his track record and emotional tolerance support it. His recommended maximum for most traders is four percent. The key insight: position size is not a judgment call determined by conviction — it is calculated from the stop distance. If the stop is far from entry, trade fewer contracts to stay within your risk budget. If the stop is tight, size up. He walks through the arithmetic explicitly: a ten-thousand-dollar stop on a hundred-thousand-dollar account at four percent risk means exactly one contract, with no room for argument or emotional override.

“For most people, four percent should be the maximum.”

Williams describes the early days of his career when he and other traders were essentially cowboys — betting almost everything on two or three trades, experiencing enormous equity swings in both directions, and receiving margin calls as a daily occurrence. The turning point came through the work of Ralph Vince and others who demonstrated that risking a fixed percentage of equity on every trade was the key to both survival and compounding. Once Williams adopted percentage-based sizing, he has not had a single margin call in over 40 years. He also explains why he places orders at 5:30 PM and deliberately does not watch intraday price action — the more he watches, the more he second-guesses his system and the worse his results become. Stops are set on every trade because he knows every trader, at some point, will freeze and fail to exit when they should.

“I haven't had a margin call in 40 years — it used to be a daily occurrence.”

Williams recounts the 1987 Robbins World Cup campaign in which he turned $10,000 into over $1.1 million — an 11,300% return over twelve months. The number most people do not discuss is the one that made it possible: he risked approximately 30% of equity on every single trade. This is an order of magnitude beyond what he recommends today, and beyond anything he would attempt again. His daughter Michelle Williams later won the same competition risking ten percent per trade — a result Williams considers equally remarkable because it proves that exceptional returns are achievable at far more conservative risk levels. At one point the account was over two million dollars before a drawdown took it back. The 11,300% story is both a proof of concept and a warning: the same position sizing that drives extraordinary gains can destroy an account if the strategy has any weakness.

“I risked about 30 percent of my equity on every single trade.”

For Ted's intermediate-term trend-following system, the optimal entry conditions arrive after a multi-week pullback or bare market correction: stocks building symmetrical bases, RS lines near all-time highs, higher lows, right side of the base developing. The EMA stack (21 above 50 above 200, all rising) with abundant fresh breakouts signals the best entry windows. Portfolio feedback is the real-time confirmation: if you are not struggling much, your edge is in favor. In November 2024, setups are near non-existent — stocks that fell 40-50% need months of institutional accumulation to carve proper bases before new uptrends can develop. Ted will wait for base completion and the EMA stack to realign before getting aggressive again.

“Listening to your own portfolio feedback is probably the most important thing for identifying if your edge is in favor.”

Druckenmiller credits concentration as a major reason for his success — not being afraid to bet big. The other key is willingness to move across asset classes: equities, bonds, currencies, and commodities. If you're going to concentrate, it's far better to have five buckets to choose from than to be forced into one. His career evolved from equities-only to multi-asset, and the best risk-reward opportunities in bonds and currencies tend to appear during bear markets in equities — giving him a natural hedge and keeping him from forcing trades in areas without conviction.

“Concentration — not to be afraid of concentration — that's a big reason for my success. And probably the other big reason was being willing to go into other asset categories. If you're going to concentrate, it's better to have five buckets to play in than to play in one.”

Tangen asks for the best illustration of conviction sizing. Druckenmiller delivers the definitive behind-the-scenes account of his most famous trade: partner Scott Bessent called from London warning that the UK housing market and economy were collapsing. Druckenmiller realized the pound was pegged to the Deutsche Mark while the two economies had radically diverged — Germany booming and needing higher rates, Britain slumping and needing lower rates. These currencies shouldn't have been linked at the same rate. He built the short aggressively, and Soros wanted the position even bigger — $15 billion. When the peg broke, Druckenmiller sold into it overnight as other hedge funds piled in, and the position became a historic winner.

“I called and asked how much it would cost me to short the pound versus the Deutsche Mark. This one economy is booming and they need higher rates, this other economy is falling apart and they need lower rates — these two currencies shouldn't be linked.”

After the pound broke, Druckenmiller executed the concentric circles approach: short sterling, long gilts, long British stocks — the currency depreciation was good for exports so everything moved in sequence. This is how he trades: get a theme, then map the dominoes that fall because of that theme. The key lesson from Soros: when conviction is highest, the position can never be big enough, especially in liquid markets. In baseball terms, Druckenmiller had a very high batting average, but Soros had a much higher slugging percentage — the size of your wins matters more than how often you're right.

“In baseball terms, I had a very high batting average. He had a much higher slugging percentage. What I learned from Soros is when you have conviction, you should bet really big. It's not whether you're right or wrong, it's how much you make when you're right and how much you lose when you're wrong.”

Steven walks through his account-sizing evolution. For pure day trading, he finds $300K is the most comfortable account equity — enough to capture meaningful returns without fighting for fills. The maximum for single-day trading in small caps is roughly $2 million in equity, after which liquidity issues become unavoidable. He resets his trading equity to roughly flat each year, withdrawing profits and keeping a separate account for multi-day swing positions. After the 2021 ego crash — making $20M in one month then taking an $800K loss on a 'stupidest ticker' the next — he built a 'perfect trader calculator' that models what a completely robotic, emotion-free version of himself would make. He compares his actual performance against this ceiling monthly and typically operates at only 25-30% of what the perfect version could achieve. The calculator serves dual purposes: keeping ego in check after wins, and maintaining motivation by revealing how much more is possible.

“I have this one calculator that supposed to be the perfect trader. So what I'm supposed to do, what I'm supposed to make and is this loss actually necessary? That sheet that I track is pure based on robotic trading and not emotional trading. My average performance is about 25-30% compared to the perfect trader.”

Steven describes how he dynamically adjusts risk: when he's in a winning position, he uses the unrealized gains plus his original risk to amplify his position size. For example, if he risks $300K and the trade moves significantly in his favor, he may add enough that his total risk exposure reaches $600K — but crucially, only the original $300K is his capital at risk; the rest is house money. If he's down at the beginning of the day, he becomes very conservative — sometimes too conservative, missing gains he should have captured, but he's fine with that trade-off. The dynamic scaling only activates after a profit cushion exists, ensuring he never digs a deeper hole chasing a recovery. The goal: control risk to the maximum while amplifying reward to the maximum.

“If I'm down at the very beginning, then I'll be very conservative. Sometimes I'm too conservative that I didn't make the gain I'm supposed to make, but I'm okay with that.”

Steven is actively studying the point at which his own capital becomes large enough to diminish his returns. His estimate: retail traders start seeing significant diminishing returns around $100M in equity, with a hard ceiling around $200M. Beyond that, the size of the positions needed to make a meaningful return begins to move the market against you. He's excited, not frustrated, by this problem — seeing his own footprint on the ticker is proof that he's reached a scale few independent traders ever approach. At this level, the game changes: you're now competing against funds with 700K-800K share positions in the bid/ask, not just other retail traders. He's currently testing where exactly the threshold lies for different market cap ranges and volume conditions, treating it as the next frontier of his research.

Asked whether being dynamic with risk is a key component of his results, Steven confirms it absolutely is. The skill is knowing when to amplify risk — when the pattern is statistically at its best, when you're already deep in profit on the day, and when conviction is highest — and when to pull back. The amplification happens using profits from earlier trades, so the maximum you can lose is a break-even day, not a catastrophic loss. He stresses that this isn't about being more aggressive; it's about being more strategic. A 'good pattern' plus a profit cushion equals permission to scale. A mediocre pattern or a down start equals mandatory conservatism. The edge is not in the strategy alone — it's in the dynamic allocation of risk within the strategy.

“You need to know when you need to amplify your risk. When you are right and you lock the profits, if there's a good pattern, you can amplify and add that profit into your risk.”

American Tower is positioned at the intersection of wireless communication growth the same way Microsoft sat at the intersection of personal computer growth. Each new wireless generation — 1G through 5G — requires a denser network of towers, and the towers own the real estate where antennas must be placed. The marginal return on adding a new tenant to an existing tower is north of 90%: the tower is already there, the incremental cost is minimal, and nearly all the additional revenue drops to the bottom line. But the real story is the near-death experience. In 2002, loaded with 16:1 leverage after an acquisition spree, the stock fell from the $40s to $5. Chuck got on a plane to meet the CEO and understood the business was extraordinary but masked by a bad balance sheet. He bought at $0.50 and $0.80 — it became a 100+ bagger. Yet he admits he was too timid with position sizing: did he make a mistake by not putting a lot of money to work?

“The business itself was a terrific business masked by a bad balance sheet.”

Luk describes himself as a swing trader and trend follower who holds working positions for one to three weeks. He risks up to 5% of the portfolio per trade, varies that down when he is struggling and up when he has a profit cushion, and caps any single position at 35% — or 25–30% for small and micro caps because of gap-down risk. He uses a tight-stop, low-win-rate approach: stops are limited to less than 50% of a stock's average daily range and never more than about 5%, which pushes him toward fast-moving stocks with ADRs above 5%. In 2024 he had 104 winners and 319 losers, a 23% win rate, a 15% average win, a 3% average loss, and an average five-day hold on winners; his tools are the 9, 21, and 50 EMAs, dollar volume, and anchored VWAP.

“104 winners and 319 losers... average win around 15%, average loss around 3%, win rate 23%... I hold my winners for longer.”

Luk looks for a large weekly base because it adds confidence and an edge on breakouts, but he does not require one — some stocks make huge moves without a clean base. He also rarely adds to a position after the first entry: his tight stop already allows a large enough initial position, and adding after a 10–15% move would make the position too big. Most of his attempted adds have failed, so he treats the first entry as the position.

“I'm focused on finding a good base or a large base on weekly, but that's not a must... A good weekly chart really adds [to] my confidence.”

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.”

When conditions improve, Ang steps on the gas rather than staying inside a fixed risk band: from 100% cash he will start at about 2%, and if the environment and the balance of long versus short setups keep improving he will ramp toward 5% and end up fully invested. He is deliberately unsystematic about it, because mechanical ramping risks putting your largest risk on just as the market is about to stress-test you and pull back. Getting that timing right comes down to experience and judgment — reading the pieces of the puzzle early enough to take the bet that conditions have turned.

“Progressive exposure is more of an art than a science... by the time the market really has turned, you're putting your biggest risk when the market is about to stress-test you and pull back.”

Ang's A+ trades are the only ones where he will go below his normal risk band — about 1% initially — and the Ethereum trade of June–August 2025 is his example. Price action was constructive, but the edge came from stacking independent evidence: commitment-of-traders data showed large speculators at maximum short, a short position that would have to be covered; Bitcoin was setting up in the same way; the related crypto group was confirming; and the broader market had bottomed in April and was in a strong uptrend. Once the trade worked he parlayed the profits into a buffer and risked that buffer on the same idea rather than taking it off the table.

“If Ethereum does break out from here... you'd see a lot of short covering, which would add rocket fuel for that upside.”

The host frames the debate between the 1%-per-trade rule and aggressive sizing on A+ setups; Ang says the top traders he speaks with, Christian Flanders among them, do use dynamic sizing, but there is no universally correct answer. Fixed risk builds failure into the system because you always lose a predictable amount; dynamic sizing lets you press when everything aligns, but it also means some A+ setups fail and you must absorb the loss without going on tilt or revenge trading. Even with fixed risk, Mario produces outlier winners, so the decision comes back to what each trader can psychologically withstand.

“Can you withstand that psychological pressure when it doesn't work on you? Can you accept that loss?”

Ang describes how he previously found his risk ceiling by experiment: 2% per trade felt wrong, and 1% was where he was comfortable. When a trade works and sets up again, he will risk part of the unrealised profit on that same idea rather than adding fresh capital at risk. He thinks about the equity curve in order of operations: preserve capital first, then aim for consistent profitability, and only pursue superior returns once you have built a cushion — because a trader who starts the year in a hole has nothing to risk from and has to spend the good environment digging out. Right now, with the market trending lower and his own year only slightly green, he is treading water and staying patient.

“Number one, you have to preserve your capital. Once you're able to do that, number two, you try and aim for consistent profitability.”

Ang admits there is no clean answer to when you should restore normal size after cutting it, and describes what he actually did in 2025. After a 50% May he began selling winners too early — he sold Robinhood into strength expecting a pullback that never came while the stock doubled — then gave back part of the peak and cut size. Through June he stayed selective and waited for A+ setups; a gold and silver consolidation breakout justified a normal 0.3% risk, and when losses resumed later in the month he cut again and waited until Bitcoin and Ethereum set up. The lesson is that he did not rebuild size gradually on mediocre trades: he waited for the setup strong enough to take normal risk immediately.

“I was cutting my size down until I saw what I would consider an A+ setup.”

Ang says risk limits are still felt in dollars, not percentages: after an 80% year in 2024 he added capital, and a normal 0.3% risk suddenly equalled a month's salary, so he instinctively sized down while he adjusted. Moving to a fund role with a much larger AUM multiplied the effect — a losing streak felt like giving back an entire year's return — and the adjustment took time. His practical fix is to turn the account balance off, focus on the equity curve and the chart in front of him, and manage the trade rather than the money.

“If I stop out, that's the equivalent of my one month salary. And that hurt.”