{"sources": [{"url": "https://api.imd.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 competit"}, {"url": "https://api.imd.fun/artifacts/1905c7e39765aa4e1d0dbb2f5cb731a6cf724fc614f63987386857acc332dcb3", "quote": "Retains the base's sub-tick belief filter, one-tick-inside main quotes, marginal quote sizing, resting-order management and cheap YES i"}, {"url": "https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76", "quote": "Keeps the base (tick probes, sub-tick belief, quotes one tick inside the competitor, marginal sizing, resting orders, YES held to cover"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/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/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/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/process.py", "quote": "return true_probability(self._score, self.steps_remaining(), self.config)"}, {"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/runner.py", "quote": "config = sample_config(base, var, seed=seed)"}, {"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/orderbook_pm_challenge/market.py", "quote": "return max(candidates, key=lambda order: (order.price_ticks, -order.sequence))"}]}