均衡配置应对市场波动与风格切换

• A-share multi-dimensional timing model: The model evaluates the overall directional judgment of the A-share market using four dimensions: valuation, sentiment, funds, and technical indicators. Each dimension provides daily signals with values of 0, ±1, representing neutral, bullish, or bearish views. Valuation and sentiment dimensions adopt a mean-reversion logic, while funds and technical dimensions use trend-following logic. The final market view is determined by the sum of the scores across all dimensions [9][15][16] - Style timing model for dividend style: The model uses three indicators to time the dividend style relative to the CSI Dividend Index and CSI All Share Index. The indicators include relative momentum, 10Y-1Y term spread, and interbank pledged repo transaction volume. Each indicator provides daily signals with values of 0, ±1, representing neutral, bullish, or bearish views. The final view is based on the sum of the scores across all dimensions. When the model favors the dividend style, it fully allocates to the CSI Dividend Index; otherwise, it allocates to the CSI All Share Index [17][21] - Style timing model for large-cap and small-cap styles: The model uses momentum difference and turnover ratio difference between the CSI 300 Index and Wind Micro Cap Index to calculate the crowding scores for large-cap and small-cap styles. The model operates in two crowding zones: high crowding and low crowding. In high crowding zones, it uses a small-parameter dual moving average model to address potential style reversals. In low crowding zones, it uses a large-parameter dual moving average model to capture medium- to long-term trends [22][24][26] - Sector rotation model: The genetic programming-based sector rotation model selects the top five sectors with the highest multi-factor composite scores from 32 CITIC industry indices for equal-weight allocation. The model updates its factor library quarterly and rebalances weekly. The factors are derived using NSGA-II algorithm, which evaluates factor monotonicity and performance of long positions using |IC| and NDCG@5 metrics. The model combines multiple factors with weak collinearity into sector scores using greedy strategy and variance inflation factor [29][32][33][36] - China domestic all-weather enhanced portfolio: The portfolio is constructed using a macro factor risk parity framework, which emphasizes risk diversification across underlying macro risk sources rather than asset classes. The strategy involves three steps: macro quadrant classification and asset selection, quadrant portfolio construction and risk measurement, and risk budgeting to determine quadrant weights. The active allocation is based on macro expectation momentum indicators, which consider buy-side expectation momentum and sell-side expectation deviation momentum [38][41] --- Model Backtesting Results - A-share multi-dimensional timing model: Annualized return 24.97%, maximum drawdown -28.46%, Sharpe ratio 1.16, Calmar ratio 0.88, YTD return 37.73%, weekly return 0.00% [14] - Dividend style timing model: Annualized return 15.71%, maximum drawdown -25.52%, Sharpe ratio 0.85, Calmar ratio 0.62, YTD return 19.53%, weekly return -3.43% [20] - Large-cap vs. small-cap style timing model: Annualized return 26.01%, maximum drawdown -30.86%, Sharpe ratio 1.08, Calmar ratio 0.84, YTD return 64.58%, weekly return -2.22% [27] - Sector rotation model: Annualized return 33.33%, annualized volatility 17.89%, Sharpe ratio 1.86, maximum drawdown -19.63%, Calmar ratio 1.70, weekly return 0.14%, YTD return 39.41% [32] - China domestic all-weather enhanced portfolio: Annualized return 11.66%, annualized volatility 6.18%, Sharpe ratio 1.89, maximum drawdown -6.30%, Calmar ratio 1.85, weekly return 0.38%, YTD return 10.74% [42]