Metaverse Stock Selection with Institutional Flows and Large-Order Activity

Summary

This post proposes screening metaverse-related stocks using positive institutional activity and a ranking based on large-order net volume. It presents these flow measures as indicators of investor attention and concentrated buying, then describes selecting stocks near the top of the large-order ranking. The post also supplies a formula reference and a lengthy sample data workflow that combines sector identification, flow data, turnover, financial fields, and ranking operations.

The author cautions that large-order data may be delayed or biased, institutional flows do not represent the entire market, and a sector-focused screen may miss broader conditions or liquidity concerns. Suggested refinements include adding market, technical, and fundamental information or trying other flow measures. The post reports no backtest or trading results, and its sample workflow includes several filters beyond the stated core logic. The exact relationship between the ranking condition and the code should therefore be checked before interpreting or reproducing the screen.

Key ideas

• The core screen targets metaverse-related stocks with positive institutional activity and strong large-order net volume ranking.
• The post treats flow measures as clues about attention and concentrated market activity.
• Flow data can be delayed or incomplete, and institutional activity alone does not capture market conditions or liquidity.
• The sample workflow adds filters beyond the main selection rule and provides no performance evidence.

Tags

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