prediction_market_engine

The Breeden-Litzenberger theorem is a classical result in options pricing: the second derivative of the call price with respect to strike recovers the risk-neutral probability density. Applying it to prediction markets is a legitimate and under-explored idea — prediction-market contracts are effectively binary options, and if a market has enough strike granularity or related instruments (multi-outcome events, conditional markets), you can attempt to recover an implied density and compare it to a model density for mispricings. Whether the author has actually implemented this or is only gesturing at it is unclear from an 11KB repo. At this size, there's no engine — there's a folder structure and maybe a couple of modules. No stars, no forks, one-week-old account activity. The concept is worth tracking because a real implementation would be genuinely differentiated versus the sea of 'BTC 5-min momentum' bots. Do not clone yet; revisit in 30-60 days when the codebase is either fleshed out or abandoned.