Long Stocks, Long Dollar, Short Gold | Jason Shapiro

Episode Summary

Executive Summary: Jason Shapiro explains his contrarian trading framework: trade extremes in participation, not price, using COT data, market confirmation, and tight risk controls. He argues most market participants lose money, so his edge comes from fading crowded positioning when sentiment and positioning align, then exiting as the crowd normalizes. He applies this to stocks, bonds, gold, euro, and more.

Main Topics: Jason Shapiro’s trading origin and evolution (Priority: 5/5): He began trading in Hong Kong at HSBC during a bull market, made money through leverage, then gave it back when the cycle turned. Those losses pushed him to study books, journal trades, and identify what actually worked over time. Contrarian trading vs. price-based contrarianism (Priority: 5/5): Shapiro distinguishes his approach from simply shorting what has risen or buying what has fallen. He fades participation extremes, not price trends, because price contrarianism can get traders run over. Using Commitment of Traders (COT) data (Priority: 5/5): He breaks down COT positioning into commercials, large speculators, and small speculators, using futures positioning extremes as a signal. He sees it as a sample of market behavior that helps identify crowded trades and avoid trouble. Market confirmation and news failure (Priority: 4/5): COT alone is not enough; he waits for price/news confirmation before acting. His favorite signal is news that should move the market one way but fails, indicating the crowd is trapped and a turn may be starting. Current market views: stocks, bonds, gold, euro (Priority: 4/5): He is bullish S&P and previously Nasdaq because speculators were excessively short; he is short gold and the euro because positioning is crowded on the other side. He sees bonds/fixed income as a lesson in how crowded trades can violently reverse. Risk management, stops, and trading discipline (Priority: 5/5): He emphasizes that trading is not about being right but about structured risk management. He sizes positions to a fixed risk budget, uses stops, and accepts that many trades lose as long as the winners pay more. Purpose of Crowded Market Report and trader education (Priority: 4/5): He created the service to share his process, mentor others, and teach that most public market commentary lacks edge. The goal is to help traders understand markets as discounting mechanisms driven by positioning and crowd behavior.

Key Arguments: Leverage is dangerous; early success in a bull market can create false confidence and lead to giving profits back when the cycle turns. Most traders lose money, so a practical edge is to identify what losing participants are doing and take the opposite side when positioning becomes extreme. Contrarian trading should focus on participation/positioning, not simply shorting strength or buying weakness; price-based contrarianism is often a losing strategy. COT reports are useful because they show who is crowded into a trade; extremes in speculator positioning often precede turning points. COT works best as a filter and risk-management tool, not as a standalone signal; market confirmation is required before entering. News failure is an important confirmation signal: when bearish news fails to push markets lower or bullish news fails to lift them, the crowd may already be trapped. Trend followers and CTAs can make money over time, but they tend to get hurt at turns; crowded fixed-income positioning in 2023 was a good example. Many analysts and active managers underperform because they focus on narratives and fundamentals that are already discounted rather than on positioning and crowding. Shapiro’s edge depends on exiting when the positioning normalizes; if the COT index returns to neutral, he gets out even if the market could keep moving. He believes public commentary from TV analysts often provides a useful contrary indicator because it reflects consensus thinking that is already in the market.

Data Points: Early trading lesson: Made a bunch of money in a bull market, then gave it all back - Shapiro described his first market cycle after starting to trade in Hong Kong Trading win rate: Less than 40% / about 35% to 40% - He said his trades are correct only around that share of the time Risk-reward profile: About 4-to-1 - He explained that his average winner is roughly four times larger than his average loser Per-trade risk: 70 basis points - He sizes trades so a stop-out costs around 0.70% of capital Volatility target: Around 7 - His 70 bps risk per trade is tied to a target portfolio volatility level Markets traded: 37 markets - He said he monitors and trades a broad futures universe Active trades at time of interview: 4 trades on - He noted he was only positioned in a few markets at that moment Historical trader failure rate: 95% - He used this estimate to argue most speculators lose money over time S&P bearish target example: S&P 500 to 200 - He said he could make an extremely bearish case to illustrate consensus-style narratives COT neutral threshold: 50 - He exits when his indexed positioning signal returns to neutral COT index range: 0 to 100 - He described his indexed positioning measure as a bounded scale October stock low example: CPI came in higher than expected but stocks closed up - He cited this as a news-failure signal at the stock market bottom CTA drawdown example: 10% to 12% in March - He said some large CTAs lost this much during the fixed-income squeeze Long-Term Capital Management example: Interest-rate convergence trade; highly leveraged - He used LTCM to show that correct trades can still blow up from crowding and leverage Swiss franc shock example: About 20 points in two days - He referenced the 2015 Swiss franc unpegging and squeeze Public commentary accuracy: Wrong 80% of the time - He relayed a client’s assessment of a successful but narrative-driven market commentator Market coverage focus: 4 key major indexes discussed (S&P, Nasdaq, bonds, euro) - He contrasted current positioning across assets to identify where crowding is most extreme

Pivotal Quotes: "Leverage is a bad thing. Overleverage is a bad thing would be the first lesson, clearly." — Jason Shapiro: He summarized the core lesson from losing money after early bull-market gains "I am not being contrarian price. I try to be contrarian participation." — Jason Shapiro: He explained the distinction between his approach and simple price-based contrarianism "All I want to do is make money. So if I know you and I’ve watched you for five years and you’ve put on 300 trades in those five years and you lost on 295 of them, then why would I need to do anything else ever than just go opposite of what you’re doing?" — Jason Shapiro: He defended fading losing market participants as the simplest expression of his edge

Implications: For traders, the interview argues that edge comes from crowding, confirmation, and risk control—not predictions or narratives. For the industry, it challenges analyst-driven market commentary and reinforces that positioning can matter more than fundamentals at turning points.