{
 "sources": [
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/docs/orderbook_prediction_market_challenge.md",
   "quote": "5. Let the arbitrageur sweep stale quotes against `p_t`.\n6. Generate retail market orders and match them against the book."
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/orderbook_pm_challenge/market.py",
   "quote": "fills.extend(self._execute_buy_quantity(best_ask.remaining_quantity, aggressor=ARB, step=step))"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/orderbook_pm_challenge/config.py",
   "quote": "retail_arrival_rate_min: float = 0.154\n    retail_arrival_rate_max: float = 0.352\n    retail_mean_notional_min: float = 2.64\n    retail_mean_notional_max: float = 6.336"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76",
   "quote": "P = dict(lam_r=0.25, m=5.0, sig_n=1.2"
  }
 ]
}