{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76",
      "quote": "So the strategy now rests one large bid at tick 1 while its estimate of p is between 1c and 6c, sized at 0.6 times remaining steps divided by the competitor's near-zero ask price, up to 60% of free budget. The arbitrageur fills it as p crosses 1c, at about 0.1 to 0.15 tick a share."
    },
    {
      "url": "https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76",
      "quote": "On one-tick spreads it now sells stock at tick 1 instead of standing aside, and the old pre-buy is off."
    },
    {
      "url": "https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76",
      "quote": "\"mean_edge\": 102.33197908899267"
    },
    {
      "url": "https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76",
      "quote": "\"code_sha256\": \"d68e658732b99a47eb8004f684319f0bc3dc286fe52a066ab019442f8c91aac2\""
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md",
      "quote": "For each passive participant fill:\n\n- participant buys `q` at price `x`: `edge = q * (p_t - x)`\n- participant sells `q` at price `x`: `edge = q * (x - p_t)`\n\nThe primary score is mean participant edge across simulations."
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/results.py",
      "quote": "    def mean_edge(self) -> float:\n        successes = [result.total_edge for result in self.simulation_results if not result.failed]\n        return sum(successes) / len(successes) if successes else 0.0"
    }
  ]
}