{"sources": [{"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/retail.py", "quote": "            side = \"BUY\" if self._rng.random() < self._config.buy_probability else \"SELL\"\n            notional = self._rng.lognormvariate(mu_ln, sigma)"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py", "quote": "    retail_arrival_rate_min: float = 0.154\n    retail_arrival_rate_max: float = 0.352\n    retail_mean_notional_min: float = 2.64\n    retail_mean_notional_max: float = 6.336"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/market.py", "quote": "        if side is Side.SELL:\n            return min(candidates, key=lambda order: (order.price_ticks, order.sequence))\n        return max(candidates, key=lambda order: (order.price_ticks, -order.sequence))"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/process.py", "quote": "        future_variance = (\n            horizon * config.diffusion_sigma * config.diffusion_sigma\n            + n_jumps * config.jump_sigma * config.jump_sigma\n        )"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/types.py", "quote": "    competitor_best_bid_ticks: int | None\n    competitor_best_ask_ticks: int | None\n    buy_filled_quantity: float\n    sell_filled_quantity: float\n    own_orders: tuple[OwnOrderView, ...]"}, {"url": "https://api.imd.fun/artifacts/7236701c55bd1d2e0674854545ae0bbe4d4b54508c7f7a7c914261696b02e158", "quote": "Defends against the arbitrageur by knowing where p is before quoting."}, {"url": "https://www.paradigm.xyz/puzzles/api/v1/prediction-market/submissions", "quote": "\"code\":null,\"codeLength\":134648,\"strategyName\":\"KING\",\"meanEdge\":109.592145,\"meanRetailEdge\":130.771634,\"meanArbEdge\":-21.17949"}, {"url": "https://www.paradigm.xyz/puzzles/api/v1/prediction-market/submissions", "quote": "\"code\":null,\"codeLength\":59197,\"strategyName\":\"Littoral v16\",\"meanEdge\":109.427216,\"meanRetailEdge\":127.734891,\"meanArbEdge\":-18.307675"}, {"url": "https://www.paradigm.xyz/puzzles/api/v1/prediction-market/submissions", "quote": "\"code\":null,\"codeLength\":11909,\"strategyName\":\"IMD seat 1572\",\"meanEdge\":90.987078,\"meanRetailEdge\":118.866503,\"meanArbEdge\":-27.879424"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/engine.py", "quote": "                            order.notional / max(probability, self._config.retail.sell_quantity_price_floor),"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md", "quote": "The score is participant edge, not terminal PnL.\n\nFor 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)`"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/results.py", "quote": "        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"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py", "quote": "    for offset in range(count):\n        seed = seed_start + offset\n        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/config.py", "quote": "    sell_quantity_price_floor: float = 0.05"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md", "quote": "p_t =\n  sum_{n=0}^{infinity}\n    Poi(n; lambda_jump * H)\n    * Phi((Z_t + n * mu_jump) / sqrt(H * sigma^2 + n * sigma_jump^2))"}]}