量化点评报告：一月配置建议：看多大盘质量

Quantitative Models and Construction Methods 1. Model Name: GK Model - Model Construction Idea: The GK model is used to estimate the expected returns of broad-based indices over the next year, incorporating factors such as dividend yield, equity dilution, earnings growth, and valuation changes [8][9][12] - Model Construction Process: The expected return of an index is calculated as: $ Expected\ Return = Dividend\ Yield + Equity\ Dilution + Earnings\ Growth + Valuation\ Change $ - Dividend Yield: Represents the expected dividend income relative to the index price - Equity Dilution: Accounts for changes in the number of shares outstanding - Earnings Growth: Reflects the projected growth in corporate earnings - Valuation Change: Captures the expected change in valuation multiples (e.g., P/E ratio) [9][12] - Model Evaluation: The model demonstrates strong predictive accuracy over long cycles, particularly for valuation-driven indices like the CSI 300 [12] 2. Model Name: ERP-Based Valuation Model - Model Construction Idea: This model uses the equity risk premium (ERP) to assess the valuation and expected returns of indices, identifying potential valuation expansion opportunities [12] - Model Construction Process: ERP is calculated as: $ ERP = Earnings\ Yield - Risk-Free\ Rate $ - Earnings Yield: Inverse of the P/E ratio - Risk-Free Rate: Typically represented by the yield on government bonds The model evaluates the relative attractiveness of equities versus bonds based on ERP levels [12] - Model Evaluation: The model shows robust long-term predictive power, with current ERP levels indicating room for valuation expansion [12] 3. Model Name: Credit Bond Pricing Model (CCB Model) - Model Construction Idea: The CCB model evaluates convertible bond (CB) pricing errors to determine the relative attractiveness of CBs as an asset class [24] - Model Construction Process: The model calculates pricing errors by comparing market prices with theoretical values derived from CB pricing formulas. These errors are then standardized to assess relative valuation levels [24] - Model Evaluation: The model identifies CBs as a medium-high odds but low-probability asset class, with recent pricing errors at 1.1 standard deviations above the mean [24] --- Model Backtesting Results 1. GK Model - CSI 300: Expected return of 14.2% - CSI 500: Expected return of -28.2% - SSE 50: Expected return of 9.2% [9][12][20] 2. ERP-Based Valuation Model - CSI 300: ERP remains at historically high levels, indicating potential for valuation expansion [12] 3. Credit Bond Pricing Model (CCB Model) - Convertible Bonds: Expected return of -0.7%, with pricing errors at 1.1 standard deviations above the mean [13][24] --- Quantitative Factors and Construction Methods 1. Factor Name: Quality Factor (ROE) - Factor Construction Idea: The quality factor is based on return on equity (ROE) and aims to identify high-quality stocks with strong profitability and low crowding [31] - Factor Construction Process: - Odds: ROE is standardized to assess relative valuation levels (1.3 standard deviations above the mean) - Trend: Positive trend signal since May 31, 2024 - Crowding: Low crowding level at -1.1 standard deviations [31][33] - Factor Evaluation: The factor exhibits high odds, strong trends, and low crowding, making it the top-ranked style factor [31] 2. Factor Name: Growth Factor - Factor Construction Idea: The growth factor focuses on earnings growth and is sensitive to credit expansion [34] - Factor Construction Process: - Odds: Standardized at -0.1 standard deviations (neutral) - Trend: Positive trend at 0.8 standard deviations - Crowding: Low crowding at -0.3 standard deviations [34][36] - Factor Evaluation: The factor is characterized by medium-low odds, strong trends, and low crowding, with a confirmed breakout signal [34] 3. Factor Name: Dividend Factor - Factor Construction Idea: The dividend factor targets high-dividend-yield stocks but currently faces valuation and trend challenges [38] - Factor Construction Process: - Odds: Standardized at -0.8 standard deviations (low) - Trend: Negative trend at -0.4 standard deviations - Crowding: Low crowding at -0.6 standard deviations [38][39] - Factor Evaluation: The factor's low odds and weak trends reduce its attractiveness [38] 4. Factor Name: Small-Cap Factor - Factor Construction Idea: The small-cap factor captures the performance of smaller companies but is currently constrained by high crowding and weak trends [41] - Factor Construction Process: - Odds: Standardized at 0.02 standard deviations (neutral) - Trend: Negative trend at -1.0 standard deviations - Crowding: Medium-high crowding at 0.1 standard deviations [41][43] - Factor Evaluation: The factor's weak trends and high crowding make it less favorable for allocation [41] --- Factor Backtesting Results 1. Quality Factor - Odds: 1.3 standard deviations - Trend: Positive - Crowding: -1.1 standard deviations [31][33] 2. Growth Factor - Odds: -0.1 standard deviations - Trend: 0.8 standard deviations - Crowding: -0.3 standard deviations [34][36] 3. Dividend Factor - Odds: -0.8 standard deviations - Trend: -0.4 standard deviations - Crowding: -0.6 standard deviations [38][39] 4. Small-Cap Factor - Odds: 0.02 standard deviations - Trend: -1.0 standard deviations - Crowding: 0.1 standard deviations [41][43] --- Composite Strategies and Construction Methods 1. Strategy Name: Odds-Enhanced Strategy - Strategy Construction Idea: Focuses on overweighting high-odds assets while underweighting low-odds assets under a volatility constraint [56] - Strategy Construction Process: - Asset allocation: 16.6% equities, 5.0% gold, 78.4% bonds - Backtesting results: - Annualized return: 6.9% (2011-2024) - Maximum drawdown: 3.0% [56][58] 2. Strategy Name: Probability-Enhanced Strategy - Strategy Construction Idea: Allocates based on macro probability scores derived from five factors: currency, credit, growth, inflation, and overseas markets [59] - Strategy Construction Process: - Asset allocation: 7.4% equities, 4.1% gold, 88.5% bonds - Backtesting results: - Annualized return: 7.0% (2011-2024) - Maximum drawdown: 2.8% [59][61] 3. Strategy Name: Odds + Probability Strategy - Strategy Construction Idea: Combines the risk budgets of the odds and probability strategies to achieve a balanced allocation [62] - Strategy Construction Process: - Asset allocation: 12.9% equities, 5.0% gold, 82.1% bonds - Backtesting results: - Annualized return: 7.0% (2011-2024) - Maximum drawdown: 2.8% [62][64] --- Strategy Backtesting Results 1. Odds-Enhanced Strategy - Annualized return: 6.9% - Maximum drawdown: 3.0% - Sharpe ratio: 2.96 [56][58] 2. Probability-Enhanced Strategy - Annualized return: 7.0% - Maximum drawdown: 2.8% - Sharpe ratio: 3.09 [59][61] 3. Odds + Probability Strategy - Annualized return: 7.0% - Maximum drawdown: 2.8% - Sharpe ratio: 3.07 [62][64]