- Model Name: Short-term Quantitative Timing Model; Model Construction Idea: The model is based on market sentiment indicators, valuation, macro liquidity, and macro fundamentals to generate timing signals; Model Construction Process: The model uses various indicators such as manufacturing PMI, long-term loan balance growth rate, M1 growth rate, PE and PB valuation percentiles, Beta dispersion, volume sentiment score, volatility, monetary rate, exchange rate expectation, and net financing amount to generate signals. For example, the formula for the volume sentiment score is: $$ \text{Volume Sentiment Score} = \frac{\text{Current Volume} - \text{Mean Volume}}{\text{Standard Deviation of Volume}} $$ where the current volume is the trading volume of the current period, the mean volume is the average trading volume over a specified period, and the standard deviation of volume is the standard deviation of trading volumes over the same period. The model evaluates these indicators to determine the overall market sentiment and generates a timing signal accordingly[9][14][15]; Model Evaluation: The model is highly sensitive to market sentiment indicators, which can lead to frequent signal changes[9] - Model Name: Growth-Value Style Rotation Model; Model Construction Idea: The model uses economic cycle analysis to determine the allocation between growth and value styles; Model Construction Process: The model evaluates the slope of the profit cycle, the level of the interest rate cycle, and the changes in the credit cycle. For example, the formula for the profit cycle slope is: $$ \text{Profit Cycle Slope} = \frac{\text{Current Profit} - \text{Previous Profit}}{\text{Previous Profit}} $$ where the current profit is the profit of the current period, and the previous profit is the profit of the previous period. The model also considers PE and PB valuation differences and turnover and volatility differences between growth and value styles to generate allocation signals[25][26]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[25][26] - Model Name: Small-Cap vs. Large-Cap Style Rotation Model; Model Construction Idea: The model uses economic cycle analysis to determine the allocation between small-cap and large-cap styles; Model Construction Process: The model evaluates the slope of the profit cycle, the level of the interest rate cycle, and the changes in the credit cycle. For example, the formula for the interest rate cycle level is: $$ \text{Interest Rate Cycle Level} = \frac{\text{Current Interest Rate} - \text{Mean Interest Rate}}{\text{Standard Deviation of Interest Rate}} $$ where the current interest rate is the interest rate of the current period, the mean interest rate is the average interest rate over a specified period, and the standard deviation of interest rate is the standard deviation of interest rates over the same period. The model also considers PE and PB valuation differences and turnover and volatility differences between small-cap and large-cap styles to generate allocation signals[30][31][32]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[30][31][32] - Model Name: Four-Style Rotation Model; Model Construction Idea: The model combines the conclusions of the growth-value and small-cap vs. large-cap rotation models to determine the allocation among four styles: small-cap growth, small-cap value, large-cap growth, and large-cap value; Model Construction Process: The model uses the signals generated by the growth-value and small-cap vs. large-cap rotation models to allocate the portfolio among the four styles. For example, if the growth-value model suggests overweighting value and the small-cap vs. large-cap model suggests overweighting large-cap, the allocation would be adjusted accordingly[33][34]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[33][34] Model Backtest Results - Short-term Quantitative Timing Model: Annualized Return 16.24%, Annualized Volatility 14.70%, Maximum Drawdown 27.70%, Sharpe Ratio 0.9613, IR 0.5862, Monthly Win Rate 68.21%, Quarterly Win Rate 68.63%, Annual Win Rate 85.71%[16][19][22] - Growth-Value Style Rotation Model: Annualized Return 11.51%, Annualized Volatility 20.85%, Maximum Drawdown 43.07%, Sharpe Ratio 0.5316, IR 0.2672, Monthly Win Rate 58.00%, Quarterly Win Rate 60.00%, Annual Win Rate 85.71%[27][29] - Small-Cap vs. Large-Cap Style Rotation Model: Annualized Return 11.92%, Annualized Volatility 22.75%, Maximum Drawdown 50.65%, Sharpe Ratio 0.5283, IR 0.2386, Monthly Win Rate 60.67%, Quarterly Win Rate 56.00%, Annual Win Rate 85.71%[32] - Four-Style Rotation Model: Annualized Return 13.03%, Annualized Volatility 21.60%, Maximum Drawdown 47.91%, Sharpe Ratio 0.5834, IR 0.2719, Monthly Win Rate 59.33%, Quarterly Win Rate 62.00%, Annual Win Rate 85.71%[34][35]

Market Overview - In March 2025, the equity market entered a correction phase, while the commodity market continued to experience fluctuations. Early March saw a continuation of optimistic risk appetite, but by mid-March, the market became more cautious due to earnings season and various disturbances following Trump's administration, leading to a market decline. The market style shifted from small-cap growth to large-cap value, with trading focus diversifying towards sectors like non-ferrous metals, consumer services, and defense [3][14]. Equity Market Performance - The public quantitative strategy performance showed varied results across different indices. For the CSI 300 index, the monthly return was -0.07%, with strict constraint strategies yielding an excess return of 0.57%, SmartBeta strategies at 0.85%, and rotation strategies at 0.70%. The CSI 500 index had a monthly return of -0.04%, with excess returns of 1.39% for strict constraint strategies, 1.82% for SmartBeta, and 1.64% for rotation strategies. The CSI 1000 index saw a monthly return of -0.70%, with excess returns of 1.58%, 2.02%, and 2.45% for the respective strategies [4][17][25]. Private Fund Strategy Performance - In March 2025, the best-performing private fund strategy was the CSI 1000 index strategy with an annualized return of 26.20%. The quantitative stock selection strategy followed with a return of 20.50%, while the CSI 500 index strategy achieved 16.24%. The CSI 300 index strategy lagged with a return of only 0.17%. In the relative value strategy, the convertible bond strategy performed well with a return of 22.67%, while the market-neutral strategy returned 10.22% and the ETF arbitrage strategy returned 3.66%. In the managed futures strategy, the options arbitrage strategy led with a return of 9.31% [5][29][32]. Market Environment Factors - The equity market in March experienced a style shift towards large-cap value, which increased the difficulty for quantitative strategies to achieve excess returns. The volatility in value-growth styles also heightened market instability, impacting the performance of quantitative strategies. Despite a decrease in market volatility and turnover rate, trading volume remained within a "comfortable zone" for quantitative strategies, suggesting a lower likelihood of significant declines in excess returns in the short term [6][30][34]. Commodity Market Analysis - The commodity market in March showed mixed performance influenced by overseas disturbances. The energy sector saw oil prices rise due to new production cuts from OPEC+ and increased sanctions on Iran and Venezuela. Conversely, the black metal prices declined due to unmet domestic demand. Gold prices surged significantly as a safe-haven asset amid uncertainties regarding international trade and economic outlooks [14][36]. Conclusion - Overall, the report indicates a complex market environment with shifting styles and varied performance across different strategies. The quantitative strategies face challenges due to increased volatility and changing market dynamics, while certain sectors within the commodity market present potential opportunities for investors [30][34][36].