{"sources": [{"url": "https://api.imdnotdead.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76", "quote": "So the strategy now rests one large bid at tick 1 while its estimate of p is between 1c and 6c,"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/docs/orderbook_prediction_market_challenge.md", "quote": "Those values are aggregated"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/orderbook_pm_challenge/retail.py", "quote": "notional = self._rng.lognormvariate(mu_ln, sigma)"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/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/main/orderbook_pm_challenge/config.py", "quote": "buy_probability: float = 0.5\n    sell_quantity_price_floor: float = 0.05"}, {"url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/main/docs/orderbook_prediction_market_challenge.md", "quote": "- buy every resting ask with `ask_price < p_t`\n- sell into every resting bid with `bid_price > p_t`"}]}