- The Black-Litterman (BL) model is an improved version of the mean-variance optimization (MVO) model developed by Fisher Black and Robert Litterman in 1990. It combines Bayesian theory with quantitative asset allocation models, allowing investors to incorporate subjective views into asset return forecasts and optimize portfolio weights. This model addresses MVO's sensitivity to expected returns and provides a more robust framework for efficient asset allocation[12][13][14] - The BL model was implemented for both global and domestic assets. For global assets, it utilized indices such as the S&P 500, Hang Seng Index, and COMEX Gold. For domestic assets, it included indices like CSI 300, CSI 1000, and SHFE Gold. Two variations of the BL model were constructed for each asset category[13][14][18] - The Risk Parity model, introduced by Bridgewater in 2005, aims to equalize risk contributions across asset classes in a portfolio. It calculates initial asset weights based on expected volatility and correlation, then optimizes deviations between actual and expected risk contributions to determine final portfolio weights[17][18][20] - The Risk Parity model was applied to both global and domestic assets. Global assets included indices such as CSI 300, S&P 500, and COMEX Gold, while domestic assets incorporated CSI 300, CSI 1000, and SHFE Gold. The model followed a three-step process: selecting assets, calculating risk contributions, and solving optimization problems for portfolio weights[18][20][21] - The Macro Factor-based Asset Allocation model constructs a framework using six macroeconomic risk factors: growth, inflation, interest rates, credit, exchange rates, and liquidity. It employs Factor Mimicking Portfolio methods to calculate high-frequency macro factors and integrates subjective views on macroeconomic conditions into asset allocation decisions[22][24][25] - The Macro Factor-based model involves four steps: calculating factor exposures for assets, determining benchmark factor exposures using a Risk Parity portfolio, incorporating subjective factor deviations based on macroeconomic forecasts, and solving for asset weights that align with target factor exposures[22][24][25] Model Performance Metrics - Domestic BL Model 1: Weekly return -0.11%, September return -0.14%, 2025 YTD return 3.23%, annualized volatility 2.19%, maximum drawdown 1.31%[14][17] - Domestic BL Model 2: Weekly return -0.11%, September return -0.13%, 2025 YTD return 2.84%, annualized volatility 1.99%, maximum drawdown 1.06%[14][17] - Global BL Model 1: Weekly return 0.04%, September return 0.11%, 2025 YTD return 0.84%, annualized volatility 1.99%, maximum drawdown 1.64%[14][17] - Global BL Model 2: Weekly return 0.00%, September return 0.03%, 2025 YTD return 1.84%, annualized volatility 1.63%, maximum drawdown 1.28%[14][17] - Domestic Risk Parity Model: Weekly return -0.06%, September return 0.05%, 2025 YTD return 2.99%, annualized volatility 1.35%, maximum drawdown 0.76%[20][21] - Global Risk Parity Model: Weekly return -0.07%, September return 0.13%, 2025 YTD return 2.50%, annualized volatility 1.48%, maximum drawdown 1.20%[20][21] - Macro Factor-based Model: Weekly return 0.04%, September return 0.26%, 2025 YTD return 3.29%, annualized volatility 1.32%, maximum drawdown 0.64%[26][27]

- Model Name: Domestic Asset BL Model 1; Model Construction Idea: The BL model is an improvement of the traditional mean-variance model, combining subjective views with quantitative models using Bayesian theory; Model Construction Process: The model optimizes asset allocation weights based on investor market analysis and asset return forecasts, effectively addressing the sensitivity of the mean-variance model to expected returns; Model Evaluation: The BL model provides a higher fault tolerance compared to purely subjective investments, offering efficient asset allocation solutions[14][15] - Model Name: Domestic Asset BL Model 2; Model Construction Idea: Similar to Domestic Asset BL Model 1; Model Construction Process: The model is built on the same principles as Domestic Asset BL Model 1 but with different asset selections; Model Evaluation: Similar to Domestic Asset BL Model 1[14][15] - Model Name: Global Asset BL Model 1; Model Construction Idea: Similar to Domestic Asset BL Model 1; Model Construction Process: The model is built on the same principles as Domestic Asset BL Model 1 but targets global assets; Model Evaluation: Similar to Domestic Asset BL Model 1[14][15] - Model Name: Global Asset BL Model 2; Model Construction Idea: Similar to Global Asset BL Model 1; Model Construction Process: The model is built on the same principles as Global Asset BL Model 1 but with different asset selections; Model Evaluation: Similar to Global Asset BL Model 1[14][15] - Model Name: Domestic Asset Risk Parity Model; Model Construction Idea: The risk parity model aims to equalize the risk contribution of each asset in the portfolio; Model Construction Process: The model calculates the risk contribution of each asset and optimizes the deviation between actual and expected risk contributions to determine final asset weights; Model Evaluation: The model provides stable returns across different economic cycles[20][21] - Model Name: Global Asset Risk Parity Model; Model Construction Idea: Similar to Domestic Asset Risk Parity Model; Model Construction Process: The model is built on the same principles as Domestic Asset Risk Parity Model but targets global assets; Model Evaluation: Similar to Domestic Asset Risk Parity Model[20][21] - Model Name: Macro Factor-Based Asset Allocation Model; Model Construction Idea: The model constructs a macro factor system covering growth, inflation, interest rates, credit, exchange rates, and liquidity; Model Construction Process: The model uses the Factor Mimicking Portfolio method to construct high-frequency macro factors and optimizes asset weights based on subjective macro views; Model Evaluation: The model bridges macro research and asset allocation, reflecting subjective macro judgments in asset allocation[23][24][27] - Domestic Asset BL Model 1, Weekly Return: 0.02%, July Return: 0.61%, 2025 YTD Return: 2.46%, Annualized Volatility: 2.16%, Maximum Drawdown: 1.31%[17][19] - Domestic Asset BL Model 2, Weekly Return: -0.06%, July Return: 0.48%, 2025 YTD Return: 2.41%, Annualized Volatility: 1.93%, Maximum Drawdown: 1.06%[17][19] - Global Asset BL Model 1, Weekly Return: -0.09%, July Return: 0.56%, 2025 YTD Return: 0.95%, Annualized Volatility: 1.95%, Maximum Drawdown: 1.64%[17][19] - Global Asset BL Model 2, Weekly Return: -0.07%, July Return: 0.51%, 2025 YTD Return: 1.59%, Annualized Volatility: 1.7%, Maximum Drawdown: 1.28%[17][19] - Domestic Asset Risk Parity Model, Weekly Return: -0.02%, July Return: 0.36%, 2025 YTD Return: 2.7%, Annualized Volatility: 1.46%, Maximum Drawdown: 0.76%[22][23] - Global Asset Risk Parity Model, Weekly Return: -0.03%, July Return: 0.3%, 2025 YTD Return: 2.16%, Annualized Volatility: 1.66%, Maximum Drawdown: 1.2%[22][23] - Macro Factor-Based Asset Allocation Model, Weekly Return: -0.03%, July Return: 0.38%, 2025 YTD Return: 2.76%, Annualized Volatility: 1.36%, Maximum Drawdown: 0.64%[28][29]