Quantitative Models and Factors Summary Quantitative Models and Construction Methods - **Model Name**: Rotation Model **Model Construction Idea**: The model aims to allocate between micro-cap stocks and the "Mao Index" based on relative performance and timing indicators[19][27] **Model Construction Process**: 1. **Rotation Indicators**: - Use the relative net value of micro-cap stocks to the Mao Index. If the value is above the 243-day moving average, the preference is for micro-cap stocks; otherwise, the Mao Index is preferred. - Incorporate the 20-day closing price slope of both indices. When the slopes diverge and one is positive, allocate to the index with a positive slope[19][27] 2. **Timing Indicators**: - Use the 10-year government bond yield (threshold: 0.3) and micro-cap stock volatility crowding degree (threshold: 0.55). If either indicator reaches its threshold, a liquidation signal is triggered[19][27] **Model Evaluation**: The model currently signals a balanced allocation between micro-cap stocks and the Mao Index, with no systemic risk detected in the medium term[19][20][27] Quantitative Factors and Construction Methods - **Factor Name**: Value Factor **Factor Construction Idea**: Focuses on stocks with low valuation metrics, such as price-to-book and price-to-earnings ratios, to identify undervalued opportunities[55][67][70] **Factor Construction Process**: - Key metrics include: - **BP_LR**: Book value per share divided by market price - **EP_FTTM**: Forward 12-month earnings divided by market price - **SP_TTM**: Trailing 12-month sales divided by market price[67][70] **Factor Evaluation**: The value factor performed strongly in the past week, driven by market preference for cyclical and high-dividend assets amid geopolitical and inflationary concerns[55][56] - **Factor Name**: Volatility Factor **Factor Construction Idea**: Measures stock price stability and identifies opportunities in low-volatility stocks[55][67][70] **Factor Construction Process**: - Key metrics include: - **IV_CAPM**: Residual volatility from the CAPM model - **IV_FF**: Residual volatility from the Fama-French three-factor model - **Volatility_60D**: Standard deviation of 60-day returns[67][70] **Factor Evaluation**: The volatility factor showed excellent performance, reflecting market demand for stability during periods of heightened uncertainty[55][56] - **Factor Name**: Technical Factor **Factor Construction Idea**: Utilizes historical price and volume patterns to predict future stock movements[55][67][70] **Factor Construction Process**: - Key metrics include: - **Turnover_Mean_20D**: 20-day average turnover rate - **Price_Chg20D**: 20-day price change - **Skewness_240D**: Skewness of 240-day returns[67][70] **Factor Evaluation**: The technical factor also performed well, benefiting from short-term trading opportunities in a volatile market[55][56] - **Factor Name**: Growth Factor **Factor Construction Idea**: Identifies companies with strong earnings and revenue growth potential[55][67][70] **Factor Construction Process**: - Key metrics include: - **NetIncome_SQ_Chg1Y**: Year-over-year growth in quarterly net income - **OperatingIncome_SQ_Chg1Y**: Year-over-year growth in quarterly operating income - **Revenues_SQ_Chg1Y**: Year-over-year growth in quarterly revenues[67][70] **Factor Evaluation**: The growth factor underperformed due to market rotation into value and defensive sectors[55][56] - **Factor Name**: Convertible Bond Factors **Factor Construction Idea**: Combines equity and bond characteristics to identify attractive convertible bond opportunities[64][67] **Factor Construction Process**: - Key metrics include: - **Parity Premium**: Difference between the convertible bond price and its parity value - **Underlying Stock Metrics**: Factors such as growth, valuation, and quality of the underlying stock[64][67] **Factor Evaluation**: Convertible bond factors, particularly valuation and underlying stock value, achieved high IC averages last week[64][65] Backtesting Results of Models and Factors - **Rotation Model**: - Relative net value of micro-cap stocks to Mao Index: 2.49 (above the 243-day moving average of 1.97)[19][27] - 20-day closing price slope: Micro-cap stocks at 0.2%, Mao Index at -0.29%[19][27] - Volatility crowding degree: 3.37% (below the risk threshold of 55%)[19][22] - 10-year government bond yield: -2.27% (below the risk threshold of 0.3%)[19][22] - **Quantitative Factors**: - **Value Factor**: IC mean of 20.98%[55][56] - **Volatility Factor**: IC mean of 22.08%[55][56] - **Technical Factor**: IC mean of 10.07%[55][56] - **Growth Factor**: IC mean of -6.32%[55][56] - **Convertible Bond Factors**: High IC averages for valuation and underlying stock value[64][65]

Core Insights - The report highlights the strong performance of the CSI 1000 index, which achieved a return of 1.18% during the week of October 27-31, 2025, making it one of the top-performing indices [3][7]. - For the year, the CSI 1000 index has shown a return of 29.99%, outperforming the benchmark index by 3.99% [4][15]. Market Performance - In the week of October 27-31, 2025, the CSI 1000 and CSI 500 indices led in returns, with gains of 1.18% and 1.00%, respectively, while the STAR 50 and SSE 50 indices lagged with returns of -3.19% and -1.12% [3][7]. - Year-to-date, the Micro Index and ChiNext Index have performed exceptionally well, with returns of 67.31% and 48.84%, while the CSI Dividend and SSE 50 indices have underperformed, returning 0.83% and 12.17% [8]. Strategy Performance - The CSI 1000 index enhancement strategy yielded a return of 1.03% for the week, slightly underperforming the index return of 1.18%, resulting in an excess return of -0.15% [4][12]. - In October, the strategy achieved a return of 0.27%, outperforming the index, which had a return of -0.90%, leading to an excess return of 1.17% [14]. - For the year, the strategy's return stands at 29.99%, compared to the index's 26.00%, resulting in an excess return of 3.99% [15]. Investment Recommendations - The CSI 1000 index is noted for its strong performance in 2025, attributed to its strategic focus on sectors such as new energy, semiconductors, and medical devices, which are considered frontier industries [5][18]. - The index is characterized by significant valuation elasticity and policy expectations, making it a high-risk, high-volatility investment option as market risk appetite is expected to tighten towards year-end [5][18].

- The report tracks the performance of style factors, including Beta, liquidity, leverage, profitability, and market capitalization, with Beta and liquidity showing strong long positions, while leverage, profitability, and market capitalization exhibit strong short positions [2][16] - Style factors are constructed using various metrics, such as historical Beta, logarithm of total market capitalization, historical excess return averages for momentum, and a weighted combination of volatility measures for the volatility factor. For example, the volatility factor is calculated as $ 0.74 * historical excess return volatility + 0.16 * cumulative excess return deviation + 0.1 * historical residual return volatility $ [15] - Fundamental factors, including growth-related financial metrics and static financial metrics, are tested across different stock pools (e.g., CSI 300, CSI 500, CSI 1000). Growth-related financial factors generally show mixed or negative performance, while static financial factors exhibit varied results depending on the stock pool [3][4][5][6][18][20][23][25] - Technical factors, such as momentum and volatility, generally show positive performance across stock pools, with high-volatility and high-momentum stocks being dominant. For example, the 120-day momentum factor and 20-day volatility factor are highlighted for their significant contributions [3][4][5][6][18][20][23][26] - GRU factors are tested using different models (e.g., barra1d, barra5d, close1d), with performance varying across stock pools. For instance, barra1d shows strong positive performance in CSI 500 and CSI 1000 pools, while close1d experiences significant drawdowns in CSI 1000 [3][4][5][6][18][20][23][26] - Multi-factor strategies and GRU-based long portfolios are evaluated against the CSI 1000 index. GRU long portfolios show weak performance this week, with relative drawdowns of 0.11%-0.25%, while the barra5d model demonstrates strong year-to-date performance, achieving an excess return of 8.36% [7][30][31]