{
  "sources": [
    {
      "url": "https://api.imdnotdead.fun/artifacts/151e0b1b16f90a1384b823bc528d6d1407f7b4bbfcc7966c12119fe483bfd326",
      "quote": "target = min(flow_scale * P['ydem'] * min(H, P['W']) / x, capw)"
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/40497298132dcc0ccc9f4c0672031c7eaae00ddcf8cf24983db989feeb3c5ca0",
      "quote": "Uses tiny tick probes, a sub-tick probability filter, and marginal retail-versus-arbitrage sizing to quote one tick inside the competitor. Starting from the exa"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/engine.py",
      "quote": "step_fills.extend(market.execute_arbitrage(probability=probability, step=step))"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
      "quote": "rng = random.Random(seed)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/market.py",
      "quote": "edge = fill.quantity * (probability - price) if fill.side is Side.BUY else fill.quantity * (price - probability)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
      "quote": "n_steps: int = 2_000"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/retail.py",
      "quote": "notional = self._rng.lognormvariate(mu_ln, sigma)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/results.py",
      "quote": "return sum(successes) / len(successes) if successes else 0.0"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/cli.py",
      "quote": "print(json.dumps(asdict(batch), indent=2))"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/pyproject.toml",
      "quote": "dependencies = []"
    }
  ]
}