Stock Screening with Turnover, Order Flow, and Prior-Day Leaderboard Status

Summary

This post outlines a stock-selection screen using turnover between 3% and 12%, a positive product of price change and net volume from very large orders, and prior-day appearance on a market leaderboard. Its accompanying discussion frames turnover as an activity measure, order flow as a sentiment or trading-pressure signal, and leaderboard membership as a measure of recent market attention. The examples also include additional liquidity, price, and volume conditions and rank candidates by a score.

No backtest results or evidence of predictive performance are supplied. The post notes that the rules may exclude less-active opportunities, that leaderboard appearances do not establish investment merit, and that emphasis on market attention can overlook fundamentals. Its Python example does not explicitly encode the leaderboard condition and uses a different turnover range for a previous day, so the written screen and implementation are not fully consistent. The author suggests adding other data and reviewing the filters as conditions change.

Key ideas

• The stated screen combines a turnover range, positive price-change and large-order-flow product, and previous-day leaderboard inclusion.
• The examples add liquidity, price, and volume filters and rank qualifying candidates.
• Leaderboard attention and order flow can fail to reflect a stock’s underlying value.
• The post supplies no performance results, and its code differs from its stated selection conditions.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.