Analysis of the Effectiveness of Momentum Rotation Strategy in China's Fund Market

According to the four-asset rotation strategy backtest you mentioned, this strategy uses a 20-day momentum signal and selects the strongest-performing asset for allocation every week. The backtest shows:

• Rotation Strategy
  : Annualized return 24.24%, Sharpe ratio 1.08
• Equal-weighted Benchmark
  : Annualized return 11.63%, Sharpe ratio 0.94

This result shows significant

, but requires cautious interpretation.

According to academic research and market practice, the momentum effect does exist in China’s market, but has the following characteristics:

• Strong short-term momentum
  : Short-term momentum of around 20 days is relatively obvious in China’s market
• Gradual improvement in market efficiency
  : As the market matures and information dissemination accelerates, the profit margin of pure momentum strategies is narrowing
• High retail participation
  : The high proportion of retail investors in the A-share market may lead to more significant momentum effects but also greater instability

This is the factor with the largest difference between backtest and real trading:

• ETF transaction costs
  : Two-way transaction costs are approximately 0.1%-0.3%
• Slippage costs
  : Actual transaction prices are often worse than theoretical prices
• Impact of rotation frequency
  : Weekly rotation means about 50 transactions per year, with cumulative transaction costs reaching 5%-15%

:

• Theoretical backtest: 24.24%
• After deducting transaction costs: Approximately 10%-15%
• After deducting management fees: May drop to 8%-12%

The performance of momentum strategies varies significantly in different market environments:

Market Environment	Strategy Performance	Risk Factors
Trending market	Excellent performance	Clear momentum signals
Volatile market	Poor performance	Frequent false breakouts
Market reversal	Faces ‘momentum crash’ risk	Short-term large losses

• Four-asset rotation requires quick position switching
• Some ETFs may experience insufficient liquidity during specific periods
• Impact costs increase significantly when large funds are operated

• Popularization of quantitative strategies leads to narrowing alpha
• Faster information dissemination shortens the momentum cycle
• Increased capital in similar strategies reduces profit margins

• When multiple funds use similar strategies, returns are exhausted in advance
• Herding effect may lead to large losses when the strategy fails

• Increased institutionalization of the market and decreased proportion of retail investors
• Changes in regulatory policies may affect market operation modes

• The A-share market still has many irrational trading behaviors
• Obvious policy-driven market characteristics, with more trending opportunities
• Large market sentiment fluctuations, momentum effect may persist

• Changes in economic cycles and monetary policies create rotation opportunities
• Correlations between different asset classes will not disappear completely

:

• Historical backtest: 24.24%
• Actual expectation: 10%-15% (after considering transaction costs)
• Conservative estimate: 8%-12% (after considering market environment changes)

• Consider extending the lookback period (e.g., 60 days) to reduce transaction frequency
• Set stop-loss mechanisms to control ‘momentum crash’ risk
• Avoid frequent operations during extremely volatile markets

• Combine with other strategies (e.g., value, quality factors)
• Set maximum drawdown limits (e.g.,15%-20%)
• Consider adding market environment identification mechanisms

• Choose low-cost ETF products
• Optimize transaction execution to reduce slippage
• Consider adjusting rotation frequency (e.g., biweekly or monthly)

Regular evaluation is needed:

• Performance of the strategy in different market environments
• Actual situation of transaction costs
• Comparison with benchmarks (e.g., CSI 300, CSI 500)

The high returns from historical backtests are difficult to fully replicate, mainly due to:

1. Transaction cost erosion: Actual returns may decrease by more than 10%-15%
2. Market environment changes: The future market may be more volatile or more efficient
3. Strategy crowding risk: Increased similar strategies reduce profit margins
4. Overfitting risk: Backtest parameters may be over-optimized

:

• Reasonable expectations
  : Setting an annual return target of 10%-15% is more realistic
• Strict risk control
  : Set stop-loss and maximum drawdown limits
• Dynamic adjustment
  : Adjust parameters according to market environment changes
• Portfolio allocation
  : Treat the rotation strategy as part of the overall asset allocation, not the whole

: The momentum rotation strategy still has certain effectiveness in China’s fund market, but it is necessary to significantly lower return expectations and strengthen risk management. The 24.24% annualized return from historical backtests is difficult to sustain in the future; a return range of 10%-15% is more reasonable, accompanied by higher volatility and drawdown risks.

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[1] Bank Stock Rotation Effect and High Dividend Strategy - Yahoo Finance
[2] Guide to Momentum Trading Strategies - Investopedia
[3] Quantitative Investment Strategies: Models, Algorithms, and Techniques - Investopedia
[4] Research on Asset Rotation Strategies in China’s A-share Market (2024-2025) - Yahoo Finance
[5] Application of Quantitative Analysis in Finance - Investopedia