Herd-Behaviour Mispricing Hunt
Markets are mostly rational; opportunity hides in the rare moments they aren't.
Boyle's working assumption is that markets are rational most of the time — which is why edges are rare. The exception comes when something strange happens: a covenant breach, a forced delivery, a flash crash. In those moments investors fall back on instinct, herd behaviour kicks in, and prices dislocate.
The framework is to hunt for those moments deliberately. You're not predicting the future; you're cataloguing the conditions under which rational pricing breaks down and positioning for the snap-back.
It's a quant approach grounded in behaviour: the data-driven version is letting the computer find the dislocations. The behaviour-driven version is anticipating them.
- Markets are rational most of the time.
- Strange events trigger herd behaviour, and herd behaviour creates mispricing.
- Repeatable trading ideas live in repeatable kinds of dislocation.
- A computer finds dislocations you wouldn't notice; a human explains why they happen.
- Liquidity and tax efficiency determine whether a signal is tradeable.
- Catalogue strange eventsBuild a database of moments when markets did something extreme — gaps, breakdowns, forced flows, regulatory cliffs. The negative oil futures of April 2020 is a canonical example.Pro tipTag each event by its mechanism (storage, leverage, liquidity, index rebalance) so you can group future analogues.
- Find the mechanism, not just the moveNegative oil prices weren't about oil's value — they were about a storage shortage at Cushing during COVID. Identify the mechanical or structural cause, otherwise you're chasing noise.WarningIf the only explanation is 'sentiment changed' you don't have a mechanism, you have a story.
- Test for repeatabilitySearch history for the same mechanism appearing in other instruments, eras, or asset classes. A one-off is a story; a pattern is a signal.
- Filter for tradabilityApply liquidity and tax filters. Boyle prefers index futures because they're liquid enough to absorb size and tax-efficient in the US. A signal you can't trade at scale is academic.
- Define the snap-back triggerSpecify exactly what condition resolves the dislocation (storage capacity returns, forced sellers exhaust, index reconstitution completes). Without an exit, you're holding a thesis instead of a trade.
WTI futures went negative because oil had to be delivered to Cushing, Oklahoma, but tanks were full thanks to COVID-grounded planes and parked cars. The cost of storage exceeded the value of oil. Boyle made his first 'big' video explaining this.
Boyle points to a long-term MicroStrategy chart spanning the dot-com bubble through to its current incarnation as a Bitcoin-treasury vehicle. The crypto-era pump looks calmer than the original 1999-2000 spike.
Boyle tried both directions. He started with behavioural ideas — predicting how people would react in a given setup — and tested them. He also threw a computer at price data to see what dislocations it pulled out. The data-first approach worked better for him, but both flow from the same insight: edges live where rationality breaks. His video on negative oil prices in April 2020 is a vivid example of cataloguing a 'something strange just happened' moment.