Risk-Reward

Minervini's batting average ranges between 35% and 65% depending on market conditions, and he often doesn't know the exact figure in real time because he's focused on execution. The number he actually cares about is average gain — because once you know it, you can mathematically derive the maximum average stop that keeps you profitable at your current win rate. The four sliders he can adjust are: what he buys, when he buys, how much he buys, and when he sells. The stock moving on its own is not a slider he controls.

Minervini distills the entire trading operation to four levers: what you buy, when you buy, how much you buy, and when you sell. Every other outcome — how far the stock moves, macro events, news, other traders' behavior — is outside your control and cannot justify exceptions to your process. Once you know your average gain and win rate, the required average stop to remain profitable is a mathematical derivation. Your system exists to maximize performance on the four levers you own; everything else is noise.

"Those are the four things that you have complete 100% control over."

Breitstein's rule: size 25% larger when the intraday and daily trends simultaneously align. When a stock breaks out on the intraday chart and is also moving on the daily, weekly, and monthly, every participant category is on your side — momentum traders, fundamental longs, and shorts who need to cover. He uses the AVGO breakout on Nvidia's AI earnings guide as the example: multiple timeframes firing together is rare, and the multiplier is how you capitalize without changing your risk management structure.

"When you identify these trends properly, you can really start to apply it into your trading with these rules."

Tito selects strikes slightly out of the money but realistically reachable by expiration, informed by a stock's average weekly range. Implied volatility determines the strategy: low IV favors naked long options with progressive scaling out at 25, 50%. High IV favors debit spreads — long a strike, short a higher one — which reduces net cost and theta decay while maintaining a clear max risk. Very high IV or rangebound markets favor credit spreads where time decay works for you. For multi-week or multi-month setups he buys LEAPs; new leveraged single-stock ETFs give additional flexibility.

"IV dictates which strategy I use. Low IV — naked long options. High IV — debit spreads. Rangebound — credit spreads. Options let you adapt in ways stocks can't."

Tito explains a key phenomenon: option premium can diverge significantly from the underlying stock's price move, particularly in choppy or rangebound markets. He conducts a year-end review specifically at the options level — mapping back which strategy would have been most efficient for each setup. Credit spreads can generate returns even on flat price when IV collapses. Understanding when premium and price decouple is what separates an options trader who adapts from one who just picks direction.

"More traders started appreciating that the option premium just exploded — and that's something you learn over time: how to see when the setup favors the option strategy."

Tito's XLE trade illustrates his credit spread approach. XLE had ranged between 100 and 120 for four years. Using an RSI-under-40 filter to time entries near support, he bought January 2027 $50 calls for $3. XLE broke out and hit roughly $58 within a month, making the calls worth a large multiple. He contrasts what a zero-dated option would have returned — a massive discrepancy that shows why studying option pricing across expirations, not just the underlying, is essential.

"XLE had been ranging 100 to 120 for four years. January 2027 $50 calls were three bucks. XLE hit 58. The option math — that's where the real edge shows up."

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?' Druckenmiller credits Soros with teaching him it is important to be a pig when the opportunity is there.

"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 argues bluntly that win rate is the least important trading metric — because trading is not baseball, and being right more often than wrong says almost nothing about profitability. The traders he has been most impressed by often win on fewer than a third of their trades, yet generate exceptional compounding because their average winner is many times larger than their average loser. Obsessing over win rate leads to premature exits to lock in gains and holding losers too long to avoid being wrong — the exact opposite of sound practice. The right question is always the magnitude of wins relative to losses, not the frequency of being right.

"The least important is batting average. It ain’t baseball."

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 don't 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, and beyond anything he would attempt again. His daughter Michelle Williams later won the same competition risking 10% per trade — a result Williams considers equally remarkable because it proves that exceptional returns are achievable at far more conservative risk levels. The 11,300% story is both a proof of concept and a warning: the same position sizing that drives extraordinary gains can drive ruin if the strategy has any weakness.

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