{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/79af781a0f1882f2a291e045f803714b52128f9938480d54fb43360417b381ac",
      "quote": "ON = dict(cancel=(2, 3, 4), cut=(1, 4), postjump=(1,), premium=(), deadband=(3,))"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
      "quote": "    competitor = replace(\n        base_config.competitor,\n        quote_notional=rng.uniform(\n            variance.competitor_quote_notional_min,\n            variance.competitor_quote_notional_max,\n        ),\n        spread_ticks=rng.randint(\n            variance.competitor_spread_ticks_min,\n            variance.competitor_spread_ticks_max,\n        ),\n    )"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/engine.py",
      "quote": "    def run(self) -> SimulationResult:\n        strategy = self._strategy_factory()\n        process = JumpDiffusionScoreProcess(self._config.process, seed=self._seed)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/loader.py",
      "quote": "    module = importlib.util.module_from_spec(spec)\n    assert isinstance(module, types.ModuleType)\n    spec.loader.exec_module(module)"
    }
  ]
}