Group 1 - The macro timing strategy has an annualized return of 7.08% and a Sharpe ratio of 1.34 as of August 29, 2025, with the latest portfolio including various ETFs such as the CSI 500 ETF (8.35%) and government bond ETFs (38.21%) [2][4][8] - The momentum strategy has an annualized return of 20.22% since 2020, with a recent portfolio allocation including the CSI Digital Economy Theme ETF (19.51%) and the Shanghai Stock Exchange Sci-Tech Innovation Board Chip ETF (20.37%) [10][14] - The industry rotation strategy has achieved an annualized return of 9.34% since 2020, with the latest holdings including non-ferrous metals ETFs and green power ETFs [19][16] Group 2 - The Copula-based second-order stochastic dominance strategy has an annualized return of 15.52% since 2020, with the latest portfolio including the Huaxia CSI Agricultural Theme ETF (6.71%) and the Guangfa CSI Major Consumption ETF (69.79%) [21][24] - The technology ETF allocation strategy based on quantile random forests has an annualized return of 12.33% since 2020, with a significant portion allocated to the Guangfa CSI All-Index Information Technology ETF (4.78%) and the Huatai-PineBridge CSI Photovoltaic Industry ETF (76.51%) [27][31]

- The macro timing strategy model suggests a recommended equity position of 45% for June, with signal strengths of 50% for economic growth and 40% for monetary liquidity[3][26][27] - The micro-cap stock rotation and timing signals remain strong, with the micro-cap/Chow index relative net value rising to 1.93 times, above its 243-day moving average of 1.41 times[4][29] - The micro-cap stock's 20-day price slope is 0.00257, indicating stronger upward momentum compared to the Chow index's -0.00019[4][29] - The risk warning has been lifted, with volatility congestion at -0.415%, well below the warning threshold of 0.55%, and the 10-year government bond yield at -0.27%, below the risk control line of 0.30%[4][29] - The market's recent rise has favored small-cap growth styles, leading to strong performance in market cap, consensus expectations, and growth factors, while technical and low-volatility factors have underperformed[4][40] - The market cap factor had the highest IC in the CSI 300 pool at 0.2241, while the growth factor had a weak signal in the CSI 500 pool with an IC of -0.0305[39] - The market cap factor also performed well in the entire A-share pool with an IC of 0.2347[39] - The weekly performance of multi-factor strategies showed the market cap factor leading with a gain of approximately +2.21% in the CSI 300 pool, while the growth factor rose by about +0.17%[39] - The consensus expectations factor and growth factor are expected to continue performing well, while technical and low-volatility factors may see a rebound as market sentiment slows down[40] - The convertible bond selection factors showed the stock growth factor leading with a gain of about 0.72%, followed by the stock consensus expectations factor with a return of about 0.63%[45] - The stock quality factor fell by about 0.26%, the stock value factor retreated by about 0.66%, and the convertible bond valuation factor had the largest decline of about 1.70%[45] Model Backtest Results - Macro timing strategy model, equity position: 45%[3][26][27] - Micro-cap stock/Chow index relative net value: 1.93 times[4][29] - Micro-cap stock 20-day price slope: 0.00257[4][29] - Volatility congestion: -0.415%[4][29] - 10-year government bond yield: -0.27%[4][29] - Market cap factor IC in CSI 300 pool: 0.2241[39] - Growth factor IC in CSI 500 pool: -0.0305[39] - Market cap factor IC in entire A-share pool: 0.2347[39] - Market cap factor weekly gain in CSI 300 pool: +2.21%[39] - Growth factor weekly gain in CSI 300 pool: +0.17%[39] - Stock growth factor weekly gain: 0.72%[45] - Stock consensus expectations factor weekly return: 0.63%[45] - Stock quality factor weekly decline: -0.26%[45] - Stock value factor weekly decline: -0.66%[45] - Convertible bond valuation factor weekly decline: -1.70%[45]

Quantitative Models and Construction Methods 1. Model Name: Macro Timing Strategy - **Model Construction Idea**: The model aims to provide signals for equity allocation based on macroeconomic growth and monetary liquidity indicators[26] - **Model Construction Process**: The model uses dynamic macro event factors to construct a stock-bond rotation strategy. The signal strength for economic growth and monetary liquidity is calculated monthly. For April, the signal strength for economic growth is 0%, and for monetary liquidity is 50%[26][27] - **Model Evaluation**: The model has shown a return of 1.06% from the beginning of 2025 to the present, compared to a 1.90% return for the Wind All A index during the same period[26] 2. Model Name: Micro Cap Timing Model - **Model Construction Idea**: The model focuses on timing and rotation signals for micro-cap stocks based on volatility and interest rate indicators[30] - **Model Construction Process**: The model uses two mid-term risk warning indicators: 1) Ten-year government bond yield YoY indicator and 2) Volatility congestion YoY indicator. On October 15, 2024, the volatility congestion indicator fell below the threshold, lifting the risk warning signal. The interest rate YoY indicator was -20.45%, not triggering the risk control threshold of 0.3[30] - **Model Evaluation**: The model has not triggered risk control, suggesting investors continue holding micro-cap stocks[30] Model Backtest Results 1. Macro Timing Strategy - **Economic Growth Signal Strength**: 0%[27] - **Monetary Liquidity Signal Strength**: 50%[27] - **Equity Allocation Recommendation**: 25%[27] - **Return from 2025 to Present**: 1.06%[26] 2. Micro Cap Timing Model - **Ten-year Government Bond Yield YoY**: -28.69%[31] - **Volatility Congestion YoY**: -50.09%[31] Quantitative Factors and Construction Methods 1. Factor Name: Value Factor - **Factor Construction Idea**: The factor aims to capture the value characteristics of stocks based on fundamental metrics[37] - **Factor Construction Process**: The value factor includes metrics such as the latest annual report book value to market value (BP_LR), future 12-month consensus expected net profit to market value (EP_FTTM), and past 12-month operating income to market value (SP_TTM)[47] - **Factor Evaluation**: The value factor performed best in the CSI 300 stock pool last week[37] 2. Factor Name: Size Factor - **Factor Construction Idea**: The factor aims to capture the size characteristics of stocks based on market capitalization[37] - **Factor Construction Process**: The size factor includes metrics such as the logarithm of circulating market capitalization (LN_MktCap)[47] - **Factor Evaluation**: The size factor showed strong positive returns in the CSI 1000 stock pool last week[37] Factor Backtest Results 1. Value Factor - **IC Mean (CSI 300)**: 25.88%[38] - **IC Mean (CSI 500)**: 10.56%[38] - **IC Mean (CSI 1000)**: 6.32%[38] - **Multi-Long Return (CSI 300)**: 10.84%[38] - **Multi-Long Return (CSI 500)**: 10.56%[38] - **Multi-Long Return (CSI 1000)**: 6.32%[38] 2. Size Factor - **IC Mean (CSI 300)**: 3.33%[38] - **IC Mean (CSI 500)**: -3.23%[38] - **IC Mean (CSI 1000)**: -1.84%[38] - **Multi-Long Return (CSI 300)**: 3.33%[38] - **Multi-Long Return (CSI 500)**: -3.23%[38] - **Multi-Long Return (CSI 1000)**: -1.84%[38]

Quantitative Models and Factor Analysis Quantitative Models and Construction - **Model Name**: Macro Timing Strategy **Construction Idea**: This model evaluates macroeconomic signals to determine equity allocation recommendations. It incorporates economic growth and monetary liquidity signals to generate timing signals for equity investments[4][27]. **Construction Process**: 1. The model assigns weights to two dimensions: economic growth and monetary liquidity. 2. Signal strength is calculated for each dimension. For April, the economic growth signal strength was 0%, while the monetary liquidity signal strength was 50%[27]. 3. Based on these signals, the recommended equity allocation for April was 25%[27]. **Evaluation**: The model provides a systematic approach to macro timing, but its performance is subject to changes in macroeconomic conditions[27]. - **Model Name**: Micro-Cap Timing and Rotation Model **Construction Idea**: This model uses indicators related to market sentiment and fundamentals to monitor micro-cap stock performance and rotation opportunities[31]. **Construction Process**: 1. **Rotation Signal**: The model tracks the relative net value of the Micro-Cap Index and the "Mao Index" (a benchmark index). A signal was triggered on October 14, 2024, when the Micro-Cap Index crossed above its annual moving average[31]. 2. **Risk Warning Indicators**: - **Volatility Congestion**: This indicator reflects market sentiment. On October 15, 2024, the indicator fell below its threshold, deactivating the risk warning[31]. - **10-Year Treasury Yield YoY**: This fundamental indicator remained at -20.45%, below the risk control threshold of 0.3[31]. **Evaluation**: The model effectively combines sentiment and fundamental indicators to guide micro-cap stock investments[31]. Model Backtesting Results - **Macro Timing Strategy**: - Year-to-date return: 1.06% - Benchmark (Wind All A Index) return: 1.90%[27] - **Micro-Cap Timing and Rotation Model**: - Volatility Congestion YoY: -50.09% - 10-Year Treasury Yield YoY: -28.69%[31][32] --- Quantitative Factors and Construction - **Factor Name**: Volume-Price Factors **Construction Idea**: These factors capture market dynamics by analyzing trading volume and price volatility[5]. **Construction Process**: - **Low Trading Volume**: Measures stocks with lower trading activity. - **Low Volatility**: Identifies stocks with stable price movements[5]. **Evaluation**: These factors performed well in a low-risk appetite environment, benefiting from market stability[5]. - **Factor Name**: Consensus Expectation Factor **Construction Idea**: This factor reflects market expectations for stocks with strong earnings forecasts[5]. **Construction Process**: - Derived from analysts' earnings forecasts and target prices. - Tracks changes in consensus expectations over time[5]. **Evaluation**: The factor performed well due to investors' preference for certainty in volatile markets[5]. - **Factor Name**: Convertible Bond Selection Factors **Construction Idea**: These factors predict convertible bond performance based on their relationship with underlying stocks and valuation metrics[46]. **Construction Process**: - **Equity Factors**: Derived from the underlying stock's consensus expectations, growth, financial quality, and valuation. - **Valuation Factor**: Based on the premium rate between the convertible bond's parity and floor price[46]. **Evaluation**: The factors achieved positive returns, indicating their effectiveness in identifying outperforming convertible bonds[46]. Factor Backtesting Results - **Volume-Price Factors**: - Low Trading Volume: Positive performance in a low-risk appetite environment[5]. - Low Volatility: Positive performance in stable market conditions[5]. - **Consensus Expectation Factor**: - Positive performance due to strong earnings forecast alignment[5]. - **Convertible Bond Selection Factors**: - Positive multi-long-short returns for equity consensus expectation, equity valuation, and convertible bond valuation factors[46].