Pages 116-130
Year 2024
Issue 2
Volume 13


Jinzhi Zhang

Doi: 10.7508/aiem.02.2024.116.130

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited


The market attention is high for popular industries, with more closely tracked fundamental information, higher crowdedness, and relatively higher stock price volatility. In recent years, the Chinese A-share market has been dominated by structural trends, with frequent shifts in hotspots. Most investors prefer to chase popular industries, but the returns of popular industries are pretty volatile and the long-term return is not ideal. Moreover, many industry rotation models focus on macroeconomic data and industry analysis to study investment strategies, which can capture medium and long-term market trends but fail to seize shortterm opportunities. To address the above issues, this paper focus on unpopular industries and combine momentum factors with resistance level indicators to construct an industry rotation strategy. This approach will result in smaller fluctuations in portfolio returns and increased sensitivity to short-term investment opportunities, which is beneficial for capturing short-term market opportunities. The main approach is to use momentum factors to capture industries with strong momentum effects, and then use resistance level indicators to eliminate some industries that face high short-term downside risks. The strategy is applied in unpopular industries and all industries to build models, analyzing the performance of the models and the generalization effect of the strategy. In addition, this paper provides a method to translate the industry rotation model into practical investment plans through ETFs. The industry rotation strategy proposed in this paper has good performance and high generalization ability. Both industry rotation Model 1 and Model 2 achieve good performance, with stable returns both in and out of sample.

Industry rotation, momentum factor, resistance level, backtesting, ETF