Free guide
AI can explain a volatility strategy. It can't build you one.
A language model can walk you through the Greeks and summarise decades of research with real accuracy. This guide sets out exactly where AI helps, where it structurally fails, and what a properly built strategy requires that no model can provide.
- 5 things a language model structurally cannot do
- 2008/20/22 crises every Rivativ strategy is stress-tested against
- 0 live market data points available inside a chat window
The output looks like a strategy. It's a summary of ideas about strategies.
For the serious self-directed investor who's been using AI to research the VRP — and is starting to wonder how far that gets them.
- What AI gets right Genuine conceptual command of the premium — and the precise point where its usefulness ends.
- No regime assessment It knows the thresholds as concepts. It can't tell you which regime you're about to trade into.
- Sizing is a rule, not a process Why "never risk more than 1–2%" is a heuristic — and how a skew-aware book is actually sized.
- Structure isn't derived from the edge Generically sensible strikes and tenors aren't the same as structure anchored to today's surface.
- No portfolio-level Greeks, no monitoring A book that looks balanced position-by-position can hide dangerous aggregate exposure.
- What a built strategy looks like The full institutional process — story, falsification, stress tests, live monitoring — start to finish.
AI is an excellent reading companion — the vocabulary, the mechanics, a map of the landscape. It is not a strategy you should trade. Confusing the two is an expensive mistake.
