Metaverse Stock Screening with Turnover and Trading-Value Filters

Summary

This stock-selection screen targets companies classified in the metaverse theme. It requires the actual turnover rate from two trading days earlier to fall between 3% and 28%, and the prior day’s trading value to exceed 60 million yuan. The document gives corresponding screening expressions and a Python example that filters stock data by industry, turnover, and trading value, then returns matching stock identifiers and names.

The rationale offered is that turnover may indicate market interest and trading value may indicate activity, but the text provides no backtest, return data, benchmark, or evidence that these conditions predict gains. It also warns that the liquidity filter can admit speculative names and that restrictive criteria may produce few candidates. The example relies on a particular data source and a fixed historical date, and its industry classification may not capture all metaverse-related firms. The screen is therefore a candidate-generation rule, not a complete portfolio or risk-management method.

Key ideas

• The screen selects metaverse-themed stocks using a prior-day trading-value threshold.
• It filters for a turnover range measured two trading days earlier.
• The document provides formula and Python examples for implementing the conditions.
• The stated rationale is not supported by reported performance testing.
• The screen may select speculative stocks or produce a small candidate set.

Tags

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