A Daily A-Share Timing Model Built from Prior-Day Data

Summary

The post outlines a low-frequency model for timing Chinese A-share exposure and selecting trading targets. It describes using daily Wind data and a large set of predetermined spreadsheet formulas to generate bullish or bearish signals and identify an instrument for the day. The stated process uses information available at the previous close, which the author says avoids look-ahead data. The model was developed over several years and received some refinement before 2022.

The evidence described consists of backtest charts in an attached document, but those charts and the model’s formulas are not reproduced in the post. No numerical performance statistics, benchmark comparison, transaction-cost assumptions, or out-of-sample results are supplied here. The description therefore communicates the model’s data frequency and workflow, but is insufficient to assess robustness, implementation details, or whether its reported historical behavior would persist in live trading.

Key ideas

• The model uses daily Wind data to time A-share exposure and select trading targets.
• Hundreds of spreadsheet formulas generate daily directional signals from prior-close information.
• The author says the model avoids look-ahead data and refers to backtest charts in an attachment.
• The post provides no detailed formulas or performance statistics for independently evaluating the results.

Tags

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