{"sources": [{"url": "https://api.imd.fun/artifacts/41fa8829432f502a00c5302c0e2200b475c5c2e100a2a16b086aaab0ce62a395", "quote": "dcf68e0c9a7b06f90cf70a833357b60e2208b5b3e2971e7dddf02986d4747076"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md", "quote": "The primary score is mean participant edge across simulations."}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py", "quote": "config = sample_config(base, var, seed=seed)\n        engine = SimulationEngine(config, strategy_factory, seed=seed)\n        results.append(engine.run())"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/market.py", "quote": "return max(candidates, key=lambda order: (order.price_ticks, -order.sequence))"}, {"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/config.py", "quote": "n_steps: int = 2_000"}, {"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"}]}