Metaverse Stock Screen Using the Ten-Day Average and Large-Order Flow

Summary

This note proposes screening metaverse-related stocks whose opening price is near the ten-day moving average, then ranking candidates by large-order net flow. Its stated rationale combines a sector filter, a basic price-location condition, and an indicator of trading activity. The document provides formula and Python examples, although their implementation details differ: the formula uses moving-average crossover conditions and a circulation-value rank, while the prose describes large-order net quantity; the Python sketch instead uses a price proximity threshold and positive net amount.

The author cautions that the screen relies heavily on technical and flow measures, which may omit company value, industry conditions, and other relevant factors. The note recommends combining market, sector, and financial data, but provides no backtest or evidence that the conditions predict returns. The screen's inconsistent definitions and ranking fields also make careful verification necessary before implementation.

Key ideas

• The proposed universe is metaverse-related stocks.\nCandidates are selected for an opening price near the ten-day moving average.\nThe screen also uses a ranking related to large-order activity.\nThe formula and Python examples use differing definitions of price proximity and ranking.\nThe document provides no empirical evidence of strategy performance.

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