In this episode of the Amberdata Derivatives Podcast, Greg Magadini sits down with Euan Sinclair to break down what really drives trading success beyond models and market noise. From defining true edge and persistent risk premia to avoiding overfitting and psychological traps, the conversation offers practical insights grounded in real market experience. Click through to explore how robustness, preparation, and human behavior shape profitable trading.
In this episode of the Amberdata Derivatives Podcast, Greg Magadini, Director of Derivatives at Amberdata, sits down with Euan Sinclair, physicist, former prop trader, author, and advisor to Amberdata Derivatives, for a wide-ranging discussion on trading edge, risk premia, implementation, risk management, and psychology. Anchored around Sinclair’s “Theta Pig Letters,” the conversation strips away overly academic abstractions and reframes trading as a human, evolutionary, and behavioral endeavor. The discussion emphasizes robustness over optimization, simplicity over complexity, and self-awareness over arrogance.
Sinclair explains that the Theta Pig Letters were inspired by C.S. Lewis’s The Screwtape Letters, using fictional demons to personify common trader self-sabotages. This format allows uncomfortable truths to be expressed without sounding preachy. The letters focus on four pillars of trading success: edge, implementation, risk management, and psychology. Importantly, Sinclair views the project not as motivational content but as a practical guide to avoiding predictable mistakes traders make when dealing with uncertainty.
A core theme of the discussion is that edge is not mathematics. Instead, edge is a real-world phenomenon that exists independently of models. Mathematics is simply the tool used to measure or express it. Examples include trends, mean reversion, carry, spreads, and risk premia. Sinclair stresses that quants often make the mistake of starting with models rather than first understanding what is actually happening in the market.
He emphasizes that there are very few true sources of edge, and most strategies fall into a small number of buckets. Once an edge is understood in one market, it can often be transferred to another. This explains why many strategies that worked in traditional finance later appeared in crypto markets with a lag. Edge is about recognizing persistent phenomena, not reinventing complexity.
Sinclair frames risk premia through an evolutionary lens. Humans are naturally wired to overpay for safety and insurance because survival has asymmetric payoffs. This explains why convexity commands a premium and why selling volatility tends to be profitable over time. If convexity were fairly priced, no one would sell it.
He connects common behavioral biases, such as taking profits too quickly and letting losses run, to survival instincts from hunter gatherer life. Markets, as human systems, naturally reflect these biases. As a result, certain risk premia persist not because of inefficiency, but because they are rooted in human behavior that is unlikely to change.
Sinclair cautions that being smart is not itself an edge. Intelligence can help identify edge, but it often correlates with arrogance. Traders who are accustomed to solving problems intellectually may believe they can outthink markets, which are complex adaptive systems rather than engineered machines. This is particularly dangerous in markets with billions of participants. Self-awareness, not raw intelligence, is what prevents this trap.
Another key insight is that edge is inherently messy. Signal to noise ratios are low, and no amount of modeling can eliminate uncertainty. Traders must accept how little they truly know. Sinclair argues that instead of trying to perfect a single small edge, traders are better served by combining several modest edges. Robust combinations often outperform highly optimized but fragile strategies.
On execution, Sinclair distinguishes between good and bad hedging. Good hedging isolates the edge by removing unwanted exposures. Bad hedging attempts to reshape the return distribution simply to make it more emotionally comfortable, often destroying the original edge. Hedging for comfort, rather than survival, is a recurring mistake.
He emphasizes that profitable trading often involves providing a service others avoid, such as liquidity provision or selling insurance. Discomfort is not a bug of trading returns, it is the source of them.
Risk management, according to Sinclair, should never be improvised. Decisions must be planned in advance, when emotions are calm. Simple, pre-committed rules outperform complex optimizations, especially for individual traders. Robustness matters more than optimality because markets constantly change. Overfitting risk management frameworks is just as dangerous as overfitting strategies.
He advocates for intuitive portfolio construction, grouping correlated exposures together, and sizing positions based on what allows a trader to sleep at night. If a position causes stress, it is too large.
While skeptical of much of the trading psychology industry, Sinclair acknowledges psychology as a critical failure point when done poorly. Without edge and risk management, psychology is irrelevant. But poor psychology can easily sabotage good strategies.
He draws from cognitive behavioral therapy, emphasizing practical tools rather than abstract advice. Writing down emotional reactions, externalizing negative thoughts, and reframing events help traders recognize when they are catastrophizing. These techniques do not eliminate emotions, but they prevent emotions from dictating decisions.
The discussion also touches on structural changes in markets, including the rise of the IBIT Bitcoin ETF and increasing concentration in major equity indices. Sinclair notes that such changes alter volatility dynamics and render long historical backtests less relevant. Markets evolve, and traders must adapt rather than assume the past cleanly maps onto the present.
In periods of extreme volatility, Sinclair views dislocations as opportunities rather than threats, provided risk has been managed in advance. The real danger is not losing money during volatility, but losing so much that one cannot trade when the best opportunities appear.
This episode highlights that successful trading is less about prediction or brilliance but about humility, preparation, and robustness. Real edge is small, messy, and rooted in human behavior, while long-term success comes from robust execution, simple risk management, and self-awareness. Discomfort is often the price of returns, not a flaw in the strategy.
As markets evolve, the core principles remain the same: isolate true edge, manage risk before stress arrives, and focus on staying in the game. Traders who prioritize robustness over perfection are best positioned to succeed over the long run.