【广发宏观陈礼清】用宏观因子穿透资产

Core Viewpoint - The article emphasizes the importance of effectively controlling risks and reducing volatility in asset management, advocating for a "macro factor" risk parity strategy that adapts to changing macroeconomic environments, contrasting it with traditional asset risk parity models [1][13][15]. Group 1: Macro Factor Risk Parity Framework - The construction of a macro factor risk parity framework involves four steps: selecting factors, calculating risk exposure, determining target risk exposure, and matching target risk exposure to asset weights [2][16][17]. - The mainstream methods for constructing macro factors include using low-frequency economic data, principal component analysis (PCA), and regression methods to fit higher-frequency macro factors [3][18][19]. Group 2: Factor Construction and High-Frequency Transformation - The article outlines a refined approach to factor construction, summarizing it as "defining dimensions, screening assets, and high-frequency transformation," which combines the advantages of various methods [3][18][19]. - The transformation of low-frequency macro factors into high-frequency factors is achieved through factor mimicking, which involves regression analysis to identify strong correlations with asset prices [5][29][31]. Group 3: Risk Exposure and Asset Sensitivity - A risk exposure matrix is created to show the sensitivity of assets to different macro variables, using robust OLS regression to capture dynamic features [6][33][34]. - The analysis reveals that large-cap stocks are more sensitive to economic growth, while mid-cap stocks are more sensitive to liquidity conditions [6][35][38]. Group 4: Performance of Different Strategies - The "lightweight" strategy, focusing on growth and inflation factors, has shown an annualized return of 7.7% with a volatility of 5.4% since 2016, outperforming traditional asset risk parity strategies [7][40][41]. - The "three-dimensional" strategy, incorporating M1, BCI, and PPI, has yielded an annualized return of 9.0% with a volatility of 7.8%, indicating a more diversified asset allocation [8][9]. - The "broad-spectrum" strategy, which includes multiple macro factors, has achieved an annualized return of 7.5% with a lower volatility of 4.0%, demonstrating a higher Sharpe ratio compared to simpler models [9][10].