全天候策略再思考：多资产及权益内部的应用实践——数说资产配置系列之十二

Group 1 - The core idea of the article revolves around the All-Weather Strategy, which is favored by investors for its robust performance and ability to withstand cyclical fluctuations [1][3] - The All-Weather ETF launched by Bridgewater and State Street in March 2025 has a scale of approximately $204 million as of the end of May, with a leverage level of about 1.8 times [1] - The asset allocation of the All-Weather ETF as of March includes approximately 25% in stocks, 20% in commodities, and 55% in bonds, which is similar to the target allocation of the risk parity product RPAR [3][4] Group 2 - The All-Weather ETF has shown characteristics of a Beta strategy, primarily holding long positions, and has experienced significant fluctuations in the market, with a maximum drawdown of 8.78% shortly after its launch [3][4] - The maximum drawdown of the risk parity ETF RPAR with a leverage level of 1.2 times was about 8%, while the UPAR with a leverage level of 1.7 times had a maximum drawdown of approximately 11% [3] - The All-Weather ETF's drawdown is between the two risk parity ETFs, indicating a strong correlation with similar strategy products [3] Group 3 - The report explores various construction methods for the All-Weather Strategy, starting from the basic risk parity strategy and considering the application of All-Weather thinking within high-correlation equity assets [4][12] - The core idea of risk parity is to equalize the risk contribution of each asset in the portfolio, with a focus on achieving a balanced risk exposure across different macroeconomic scenarios [4][12] Group 4 - The article discusses the concept of "Scenario Parity," which involves identifying asset combinations that benefit from different macroeconomic conditions and allocating them based on risk parity [12][14] - The asset allocation for different macro scenarios includes stocks and commodities during economic growth, nominal bonds and gold during economic downturns, and inflation-protected bonds during rising inflation [12][13] Group 5 - The performance of the "Scenario Parity" strategy has been superior to traditional risk parity, with a static scenario parity combination yielding an annualized return of 5.01% compared to 4.00% for risk parity [17][18] - Dynamic combinations based on macroeconomic factors have shown even better performance, with the dynamic scenario parity strategy achieving an annualized return of 6.57% [17][18] Group 6 - The article emphasizes the importance of macro sensitivity in constructing portfolios, suggesting that using sensitivity measures can lead to more effective asset allocation compared to traditional regression methods [23][24] - The results indicate that portfolios constructed using macro sensitivity measures have better explanatory power and stability compared to those based solely on regression analysis [25][36] Group 7 - The All-Weather strategy can also be applied internally within equity assets, similar to a "barbell strategy," by calculating the exposure of sectors and stocks to various macroeconomic variables [28][29] - The performance of sector-based All-Weather combinations has shown significant improvement, with the scenario parity approach yielding higher returns and lower drawdowns compared to traditional risk parity [34][50]