十二月配置建议：主权CDS上行提示风险

Quantitative Models and Construction Methods 1. Model Name: ERP and DRP Standardized Equal-Weight Model for A-Share Odds - Model Construction Idea: The model calculates A-share odds using standardized values of ERP (Equity Risk Premium) and DRP (Default Risk Premium) with equal weighting[12] - Model Construction Process: - Standardized values of ERP and DRP are calculated - These values are equally weighted to derive the A-share odds - As of the end of November, the A-share odds declined to near the zero axis, indicating a neutral level[12] - Model Evaluation: The model reflects a neutral positioning for A-shares, with odds returning to a balanced state[12] 2. Model Name: Bond Odds Indicator - Model Construction Idea: The model uses the expected return difference between long-term and short-term bonds to construct a bond odds indicator[19] - Model Construction Process: - The expected return difference between long-term and short-term bonds is calculated - This difference is standardized to derive the bond odds indicator - Recently, the bond odds indicator has significantly rebounded but remains at a low level of -0.9 standard deviations[19] - Model Evaluation: The model effectively captures the rebound in bond odds, though it remains at a relatively low level[19] 3. Model Name: AIAE Indicator for US Stocks - Model Construction Idea: The AIAE (Asset Implied Allocation Efficiency) indicator measures the historical positioning of US stocks to assess risk and return[20] - Model Construction Process: - The AIAE indicator is calculated based on historical data - Currently, the AIAE indicator is at 55%, the highest point in its history, corresponding to 2.4 standard deviations above the mean - Historical analysis shows that when the AIAE indicator exceeded 50% in 2000 and 2022, the S&P 500 experienced significant corrections of 46% and 25%, respectively[20] - Model Evaluation: The model highlights elevated risks for US stocks, with the AIAE indicator at a historically high level[20] 4. Model Name: Federal Reserve Liquidity Index - Model Construction Idea: Combines quantity and price dimensions to construct a liquidity index for asset allocation[20] - Model Construction Process: - The index incorporates multiple factors, including net liquidity, Federal Reserve credit support, market expectations, and announcement surprises - After the October FOMC meeting, the announcement surprise signal turned negative, and net liquidity continued to decline - Other indicators showed easing signals, and the liquidity index returned to a moderately high level of 20%[20] - Model Evaluation: The model provides a comprehensive view of liquidity conditions, highlighting mixed signals in the current environment[20] --- Model Backtesting Results 1. ERP and DRP Standardized Equal-Weight Model for A-Share Odds - Odds: Neutral (near zero axis)[12] - Win Rate: 16%[12] 2. Bond Odds Indicator - Odds: -0.9 standard deviations (low level)[19] - Win Rate: -4% (medium level)[19] 3. AIAE Indicator for US Stocks - Odds: 2.4 standard deviations (historically high level)[20] - Win Rate: Not explicitly mentioned[20] 4. Federal Reserve Liquidity Index - Liquidity Index: 20% (moderately high level)[20] --- Quantitative Factors and Construction Methods 1. Factor Name: Small-Cap Factor - Factor Construction Idea: Evaluates small-cap stocks based on odds, trends, and crowding levels[21] - Factor Construction Process: - Odds: 0.2 standard deviations (neutral level) - Trend: 1.2 standard deviations (high level) - Crowding: -1.4 standard deviations (low level) - Comprehensive score: 4[21] - Factor Evaluation: The factor shows strong trends and low crowding, making it attractive for allocation[21] 2. Factor Name: Value Factor - Factor Construction Idea: Assesses value stocks using odds, trends, and crowding levels[23] - Factor Construction Process: - Odds: 0.8 standard deviations (moderately high level) - Trend: 0.1 standard deviations (neutral level) - Crowding: -1.3 standard deviations (low level) - Comprehensive score: 3[23] - Factor Evaluation: The factor ranks high among others, suggesting it is worth focusing on[23] 3. Factor Name: Quality Factor - Factor Construction Idea: Evaluates quality stocks based on odds, trends, and crowding levels[26] - Factor Construction Process: - Odds: 1.2 standard deviations (high level) - Trend: -0.6 standard deviations (low level) - Crowding: 0.1 standard deviations (medium level) - Comprehensive score: 0[26] - Factor Evaluation: The factor's weak trend reduces its allocation value, requiring confirmation of a right-side trend[26] 4. Factor Name: Growth Factor - Factor Construction Idea: Analyzes growth stocks using odds, trends, and crowding levels[29] - Factor Construction Process: - Odds: 0.1 standard deviations (neutral level) - Trend: 0.5 standard deviations (moderately high level) - Crowding: 1.5 standard deviations (high level) - Comprehensive score: -1.2[29] - Factor Evaluation: The factor's high crowding level indicates elevated trading risks[29] --- Factor Backtesting Results 1. Small-Cap Factor - Odds: 0.2 standard deviations[21] - Trend: 1.2 standard deviations[21] - Crowding: -1.4 standard deviations[21] - Comprehensive Score: 4[21] 2. Value Factor - Odds: 0.8 standard deviations[23] - Trend: 0.1 standard deviations[23] - Crowding: -1.3 standard deviations[23] - Comprehensive Score: 3[23] 3. Quality Factor - Odds: 1.2 standard deviations[26] - Trend: -0.6 standard deviations[26] - Crowding: 0.1 standard deviations[26] - Comprehensive Score: 0[26] 4. Growth Factor - Odds: 0.1 standard deviations[29] - Trend: 0.5 standard deviations[29] - Crowding: 1.5 standard deviations[29] - Comprehensive Score: -1.2[29]