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.
5 documents
The document explains automated trading bots as programs that use market or other data to analyze conditions and place trades under a configured strategy. It describes potential benefits such as faster, more frequent execution and less emotion-driven…
This guide introduces statistical learning through an example of predicting the S&P 500 from company fundamentals. It frames the task as estimating a response from predictor features plus residual error, then distinguishes prediction, which prioritizes…
The document summarizes a study of Alpha101 factors in China’s A-share market and a method for generating additional price-volume signals with genetic programming. It says the authors assessed existing factors using Rank IC, portfolio stratification, and…
The proposed stock screen combines three conditions: membership in the metaverse sector, positive institutional activity, and overlap among several moving averages. The rationale is that sector exposure may offer growth potential, institutional buying may…
This Chinese stock-screening strategy selects companies in the metaverse sector that recorded a limit-up day in the previous 25 days. At the current market auction, it requires a positive price change and combined large and extra-large buy orders above 7…