Using the CCK Model to Detect Herding in Chinese Equities

Summary

The study applies the CCK approach to detect herding among the constituents of Chinese equity indices. It treats herding as a period when constituent returns move more alike: their co-movement increases while the dispersion of returns falls. The authors also incorporate the broad A-share market’s daily return to capture market-wide context, then use the resulting signal as an index timing strategy.

The summary reports that results depend on market direction, index capitalization and style characteristics, and industry. The strategy is described as more effective in rising markets, with stronger historical results for large-cap, style-pure broad indices and for some non-growth industries; growth industries are reported as weaker. It gives selected average return and win-rate figures for the Shanghai 50 and financial-sector indices during rising markets. These are reported backtest outcomes, not evidence of live performance, and the excerpt does not specify the sample, trading rules, costs, or statistical uncertainty.

Key ideas

• The CCK approach detects herding through lower constituent return dispersion and stronger co-movement.
• The study adds broad A-share daily returns to its herding analysis.
• The resulting signal is used to time exposure to broad and industry indices.
• Reported strategy performance varies with market trend, index size and style, and industry type.
• The excerpt reports selected rising-market backtest results but omits methodology and cost details.

Tags

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