Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
4 documents
This document presents a QuantStats tear sheet for an automated strategy labeled “orb-plain,” compared with SPY over January 4–9, 2026. It reports return and risk statistics, including a 0% total return for the strategy, a 0.67% maximum drawdown, a 0.55…
This document outlines an intraday opening range breakout strategy implemented as a two-agent trading bot. It tracks the high and low during the first 15 minutes for a universe of liquid stocks and ETFs, then ranks symbols that move above the range high.…
This strategy scans a fixed universe of large, liquid US-listed stocks for breaks above the high established during the first 15 minutes of the regular session. A research agent identifies and ranks stocks that have since closed above that level; a separate…
This example describes an equity opening-range breakout system split between two agents. A research agent scans a configured universe and ranks breakouts using completed regular-session bars beginning at the market open. A separate trading and risk agent…