Momentum & Trend Following

Soros taught him that the crowd is right 80% of the time — you just can't be caught in the brutal other 20%. He gets intellectual satisfaction from the contrarian 20% but admits that's ego, not edge. He doesn't care if a trade is crowded if the thesis and the trend are right. Extreme conviction plus no believers doesn't make him doubt — it makes him more convicted.

"I think contrarianism is overrated. I do like it when I have extreme conviction and no one else believes it. It gives me even more conviction."

Coming out of the 50% drawdown, Zhang read the core O'Neal books and converged on a style he calls thematic catalyst momentum — a form of trend following rooted in CAN SLIM principles but modified. The key modification: the team doesn't strictly require earnings and sales for every trade, since sectors like crypto have no earnings but still carry the same momentum characteristics. The style sits within trend following as the broad category, with growth and fundamentals as a useful but not mandatory filter.

Beyond liquidity and ADR, Ted's magic elixir requires strong fundamentals tied to a growth story or catalyst, a stock that belongs to a hot sector theme (AI, rare earths, space, crypto), and chart confirmation — the setup must be visible in price action. The framework is rooted in O'Neal but adapted for a more volatile, theme-driven modern market where a stock like Palantir can gap 25% on guidance and run for weeks. The checklist is applied systematically: if a stock doesn't check every box, it doesn't get full size. The discipline is in the rejection — saying no to almost everything is what makes the yeses count.

Not all themes are equal: secular themes (tech revolutions, AI, rare earths) produce multi-year compounding moves because underlying earnings growth is structural. Cyclical themes (housing, financials, retail) rise and fall with the economic cycle and interest rates. Zhang focuses on secular themes for the big sustainable moves. When two stocks both clear the magic elixir criteria, the tiebreaker is linearity: how consistently does the stock trend upward without violating prior lows? A stock that makes new highs without breaking the previous day's low, day after day, is categorically different from a choppy stock. GDX vs. the choppy version of that same chart two years earlier is his go-to example of the distinction.

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.

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.

Palantir was an episodic pivot trade off a guidance beat: Ted bought the gap up and held a linear trend above the 10 EMA, trimming at the measured-move target. He describes almost being out of the position at 12.5% of original size when the 'multitude of factors' kicked in — additional elixir criteria flashed, and he knew in real time the move was likely to extend. PLTR's 130% move in a two-month period on a $5 trillion market cap stock was unprecedented, and Ted's main takeaway is that even the biggest stocks can produce momentum-trade returns when the catalyst is powerful enough and the elixir criteria all converge. He also shows how the episodic pivot pattern (gap, flag, continuation) is one of the most repeatable setups in his playbook.

Tito's methodology starts with stock selection. The bread and butter is finding stocks showing relative strength versus the indices, ideally with a catalyst behind them. He cites Nvidia in 2024 and SMCI as examples — stocks with strong RS and identifiable tailwinds. When you start with the right stock, you tilt the odds in your favor before worrying about entry timing. He learned this from studying the US Investing Champions, who consistently emphasize stock selection as the foundation that all other decisions rest on.

Throughout 2025, Tito had to pivot from his natural momentum-buyer identity toward mean reversion. Stocks kept making undercut lows and reversing — a regime where buying dips outperformed buying breakouts. This was psychologically difficult because it went against his wiring, but the data was clear: the market wasn't trending, it was chopping. He learned to look for setups where a stock reclaims a key level after undercutting it, signaling a failed breakdown rather than a continuation. The experience reinforced that no single style works in all environments — you adapt or you bleed.

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."

After two years of day trading, Kristjan began studying thousands of historical charts and noticed a pattern: the biggest moves in stocks take weeks and months to unfold, not minutes. Day trading was inherently limiting — even a large intraday move is a ceiling on what you can capture. Swing trading let him stay in momentum stocks through their full trend and capture exponential returns that no intraday approach could replicate. This insight — that momentum compounds over time, not within a session — was the foundation he built everything else on.

The volatility of PTJ's early career made long-term ownership feel laughable. He'd run a $10,000 account to $100,000 and back to zero. A friend — nicknamed "the Mortician" — could take $5,000 to $2 million and then into deficit. Liquidity was survival. Yet every semester since 1982, PTJ guest-lectured at a Virginia investment class, and his number-one lesson was the opposite of his own practice: "You're going to make your money by riding a trend for the very, very longest time." He'd ask who the richest person in the world was — it was always Gates or Buffett — and point out they both got there by holding one thing for decades. Gates owned a company. Buffett owned America. The method differs; the principle is the same. The greatest fortunes are not made by brilliant entry and exit timing but by identifying a trend large enough and durable enough to compound across an entire career. PTJ taught this to students for decades even as he himself generated 100% alpha with near-zero market correlation — living proof that knowing the right answer and being able to execute it are completely different things.

"The greatest fortunes in the world were made by riding a trend for the long run."

For decades PTJ publicly mocked Warren Buffett: right place, right time, bull market genius. If Buffett had started in Japan in 1989, forget it — he'd have been wiped out. PTJ's BBI fund has generated a −0.12 correlation with the S&P 500 for forty years, producing 100% alpha. Yet he freely admits he envies Buffett's belief system — the patient faith in America that allows Buffett to sit through a 50% drawdown without flinching. PTJ knows he doesn't have that calm: he's been a right guard in the NFL for fifty years, fighting in the trenches every day, while Buffett is the franchise quarterback who just needs to believe. Then he heard the Acquired podcast on Berkshire Hathaway and learned that Buffett understood compound interest at age nine — nine years old. PTJ apologizes on air: "You are the OG of compound interest and I wish I was one-tenth as smart as you are." He now sees that Buffett's genius was not being in the right place at the right time — it was seeing the structural truth of compounding as a child and spending a lifetime never stopping. Charlie Munger added the critical complement: growth companies that themselves compound, not just cheap companies trading below intrinsic value.

"You are the OG of compound interest."

Druckenmiller noticed the AI trend years before ChatGPT when his young analysts reported that Stanford and MIT engineers were shifting from crypto to AI. He bought a significant Nvidia position at $150 before ChatGPT launched — calling the timing 'total luck.' Once invested, he systematically worked through the entire supply chain: power, uranium, and other downstream beneficiaries. Now he's cautious: the AI investment phase resembles the internet in 2000 — the secular trend is real, but knowing exactly where to be positioned is hard, and a correction could create better entry points.

"We noticed about three or four years ago that the kids that go to Stanford and MIT — the engineers were shifting from crypto to AI. That was the first sign. I bought a pretty good chunk of Nvidia and then like a month later ChatGPT happened. It was just total luck."

Steven introduces the concept of a 'dollar block' — the total amount of retail money that can pile into a single ticker before buying power is exhausted and the stock reverses. The size of the dollar block is tied to macro liquidity: in 2021, stimulus checks flooded retail accounts and dollar blocks expanded massively; in 2022, the money dried up and the same tickers topped much earlier. For a stock to go up another 50%, it needs significantly more money flowing in — and when retail runs out of buying power, the stock exhausts and turns down. Using RGTI as an example: the stock ran from a $100M market cap to $20/share, trading $600-$700M in volume, then stalled in the $18-$20 range as the dollar block hit its ceiling.

"The dollar block means how much money does the retail have to pile into one ticker and forcing the stock to top — because for the stock to go up another 50%, it needs a lot more money. So the retail doesn't have that kind of money. That's where the retail buying part gets exhausted and stock goes down 50%."

Sympathy plays capitalize on trader psychology: when a stock makes a massive move, traders who missed it scramble for the next related name. Ariel illustrates with GME leading to AMC, KOSS, NAKD, and EXPR following. Same pattern with Tesla sparking moves in Rivian, Lucid, and Solo. In solar, SPI went from $1 to $46 in a day — Ariel found SUNW on FinViz as another dollar solar name and rode it from $0.90 to $4 the same day. The quantum sector repeated the pattern with IONQ leading and RGTI, QUBT, and QBTS following. The bigger the lead runner goes, the more predictable the sympathy becomes — even 30–100% intraday moves are recurring. This strategy was the primary engine behind Ariel’s $30K to $3.5M run.

"Trader psychology basically goes, "Oh my god, I just missed this. What’s the next one?" And that’s how trader psychology works... Even most recently with the quantum names, you had IONQ and people are like, man, I missed it. So you go Rigetti and you go QMCO and you go QUBT."