全天候策略研究：基于境内ETF的多资产配置实践

Group 1 - The report emphasizes the increasing demand for robust allocation strategies that can navigate economic cycles and hedge against extreme risks amid heightened global macro uncertainty and geopolitical conflicts [1] - The core objective of the All Weather strategy is to achieve stable returns through diversified allocation of underlying assets and macro risks, utilizing a risk parity approach to balance risk contributions across different macro scenarios [1][6] - The performance metrics indicate that the strategy has achieved a monthly absolute return win rate of 73.88% and an annual win rate of 100% over the backtesting period, with a maximum drawdown of approximately -4.82% [3][35] Group 2 - The All Weather strategy aims to fully diversify risks and traverse macro cycles, originally proposed by Bridgewater Associates, which has gained recognition during market downturns [6][7] - The strategy employs a risk parity model to ensure equal risk contribution from various macro asset combinations, enhancing the robustness of the portfolio [10][11] - The report outlines the importance of optimizing models, asset selection, and adjusting for macro cycles as key elements influencing the performance of the All Weather strategy [12][14] Group 3 - The report details the selection of low-correlation, high-representative ETFs and indices as the foundation for the All Weather strategy, ensuring effective risk diversification [15][18] - Backtesting results show that the risk parity model effectively disperses portfolio risk, achieving an annualized return of 5.84% with a volatility of 4.46% over the period from 2015 to 2026 [22][25] - The All Weather ETF-FOF strategy has demonstrated a cumulative return of approximately 6.10% with a volatility of 2.97% and a Sharpe ratio of 1.54, indicating improved performance metrics compared to the risk parity model [33][35] Group 4 - The report suggests future optimization of the strategy through refining macro scenario classifications, expanding the range of underlying assets, and deepening alpha extraction in niche segments [56]