{"sources": [{"url": "https://api.imd.fun/artifacts/7236701c55bd1d2e0674854545ae0bbe4d4b54508c7f7a7c914261696b02e158", "quote": "{\n \"approach\": \"Defends against the arbitrageur by knowing where p is before quoting. Each step it rests 0.01-share two-sided probes around its estimate: the arbitrageur removes every order on the wrong side of p, so the surviving and eaten probes, plus the competitor's best quotes and sudden jumps "}, {"url": "https://www.paradigm.xyz/puzzles/api/prediction-market/submissions/cfe113fd-d470-4569-84b1-e65023d83d86", "quote": "\"meanEdge\":90.987078,\"meanRetailEdge\":118.866503,\"meanArbEdge\":-27.879424,\"meanFinalWealth\":1060.16299,\"successCount\":200,\"failureCount\":0,\"createdAt\":\"2026-11-05T19:37:08.809813Z\""}, {"url": "https://www.paradigm.xyz/puzzles/api/prediction-market/submissions/6852415b-a699-431b-bb83-8c874053c01f", "quote": "\"meanEdge\":-6.504278,\"meanRetailEdge\":0.945833,\"meanArbEdge\":-7.450112,\"meanFinalWealth\":994.152248,\"successCount\":200,\"failureCount\":0,\"createdAt\":\"2026-07-07T01:19:16.990591Z\",\"d"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/.python-version", "quote": "3.11"}, {"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": "        seed = seed_start + offset"}, {"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/process.py", "quote": "    total = sum(weights)"}, {"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://docs.python.org/3.12/whatsnew/3.12.html", "quote": "now uses Neumaier summation to improve accuracy and commutativity"}, {"url": "https://www.paradigm.xyz/puzzles/prediction-market-challenge/about", "quote": "Each simulation runs 2,000 steps."}, {"url": "https://www.paradigm.xyz/puzzles/_next/static/chunks/2qj-htyse-w10.js", "quote": "    quote_size = 5\n\n    def on_step(self, state: StepState):"}]}