量化配置基础模型周报第16期：标普500与黄金指数收涨，BL策略本月收益最高达0.76%

Quantitative Models and Construction Methods 1. Model Name: Black-Litterman (BL) Model - Model Construction Idea: The BL model is an improvement of the traditional Mean-Variance Optimization (MVO) model. It integrates subjective views with quantitative models using Bayesian theory to optimize asset allocation weights. This approach addresses MVO's sensitivity to expected returns and provides a more robust solution for asset allocation[14][15]. - Model Construction Process: 1. Select underlying assets, such as equity indices, bond indices, commodities, and gold. 2. Incorporate subjective views on market returns into the model using Bayesian theory. 3. Combine these views with historical data to calculate optimized portfolio weights. 4. Apply the model to both global and domestic asset pools, including indices like S&P 500, SHFE Gold, and others[15][16]. - Model Evaluation: The BL model effectively balances subjective and quantitative inputs, offering a high degree of fault tolerance and efficient asset allocation strategies[14]. 2. Model Name: Risk Parity Model - Model Construction Idea: The risk parity model aims to equalize the risk contribution of each asset (or factor) in the portfolio. It is an improvement over the traditional MVO model, focusing on risk distribution rather than return maximization[19]. - Model Construction Process: 1. Select appropriate underlying assets, such as equity indices, bond indices, commodities, and gold. 2. Calculate the risk contribution of each asset to the portfolio based on expected volatility and correlations. 3. Optimize the portfolio by adjusting weights to ensure equal risk contribution from all assets. 4. Apply the model to both global and domestic asset pools, including indices like S&P 500, SHFE Gold, and others[20]. - Model Evaluation: The model provides a stable strategy across economic cycles by balancing risk contributions, making it suitable for long-term investment[18][19]. 3. Model Name: Macro Factor-Based Asset Allocation Model - Model Construction Idea: This model bridges macroeconomic research with asset allocation by constructing a framework based on six macroeconomic risks: growth, inflation, interest rates, credit, exchange rates, and liquidity[23][24]. - Model Construction Process: 1. Construct high-frequency macroeconomic factors using the Factor Mimicking Portfolio method. 2. Calculate factor exposures for selected assets at the end of each month. 3. Use a risk parity portfolio as the baseline and adjust factor exposures based on subjective macroeconomic views. 4. Solve the optimization problem to derive asset weights for the next month[24][26]. - Model Evaluation: The model effectively translates macroeconomic views into actionable asset allocation strategies, providing flexibility to adapt to changing economic conditions[23][24]. --- Model Backtesting Results 1. Black-Litterman (BL) Model - Domestic Asset BL Model 1: Weekly return 0.41%, September return 0.63%, YTD return 5.98%, annualized volatility 1.69%, max drawdown 0.78%[16][18] - Domestic Asset BL Model 2: Weekly return 0.27%, September return 0.50%, YTD return 5.40%, annualized volatility 1.47%, max drawdown 0.65%[16][18] - Global Asset BL Model 1: Weekly return 0.81%, September return 0.76%, YTD return 6.62%, annualized volatility 1.97%, max drawdown 0.95%[16][18] - Global Asset BL Model 2: Weekly return 0.62%, September return 0.52%, YTD return 5.48%, annualized volatility 1.48%, max drawdown 0.64%[16][18] 2. Risk Parity Model - Domestic Asset Risk Parity Model: Weekly return 0.08%, September return 0.07%, YTD return 4.46%, annualized volatility 1.15%, max drawdown 0.37%[22][23] - Global Asset Risk Parity Model: Weekly return 0.13%, September return -0.07%, YTD return 4.90%, annualized volatility 1.03%, max drawdown 0.31%[22][23] 3. Macro Factor-Based Asset Allocation Model - Macro Factor-Based Model: Weekly return 0.04%, September return 0.06%, YTD return 3.87%, annualized volatility 1.24%, max drawdown 0.45%[28][29]