Metaverse Stock Screening with Institutional Flows and Auction Buying

Summary

This Chinese stock-selection post describes a screen for metaverse-related equities that combines positive institutional-flow readings with buying activity from large and extra-large orders during the opening auction. It also filters for a price-move threshold, treating order flow as a proxy for institutional intent and price change as a sign of market demand.

The post gives example indicator definitions and a formula, then outlines a Python workflow using stock, flow, and tick data. These examples are implementation references rather than reported performance evidence; the article provides no backtest or measured returns. It cautions that price moves can be volatile, large orders can be misleading, and sudden activity can cause false signals. Suggested improvements include adding technical and fundamental measures, refining order-flow thresholds, limiting the number of picks, and using dynamic stops. The described screen is therefore a candidate selection rule, not evidence of a validated trading strategy.

Key ideas

• The screen targets metaverse stocks with positive institutional-flow readings.
• It uses large and extra-large order buying during the auction as a selection input.
• A price-change threshold is combined with order flow to identify candidate stocks.
• The post supplies formula and code examples but reports no strategy performance.
• It recommends additional analysis and risk controls to address false signals and volatility.

Tags

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