基金持仓与基准偏离视角下的行业潜在冲击研究

• The report defines a formula for calculating the benchmark allocation scale of a specific index across all sample funds, expressed as: $bmAsset_{i}=\sum_{j=1}^{N}fundAsset_{j}\times weight_{i,j}$ Here, $bmAsset_{i}$ represents the benchmark allocation scale of index $i$, $fundAsset_{j}$ is the fund scale of fund $j$, and $weight_{i,j}$ is the weight of index $i$ in fund $j$ [10][11] - Another formula calculates the industry benchmark allocation scale as the sum of the benchmark allocation scales of all constituent stocks within an industry: $bmInduAsset_{k}=\sum_{s=1}^{S}bmStkAsset_{s}$ Here, $bmInduAsset_{k}$ represents the benchmark allocation scale of industry $k$, $bmStkAsset_{s}$ is the benchmark allocation scale of stock $s$, and $S$ is the total number of constituent stocks in industry $k$ [15][16] - The benchmark allocation scale of a stock is calculated as: $bmStkAsset_{s}=\sum_{i=1}^{L}bmAsset_{i}\times stkWeight_{s,i}$ Here, $bmStkAsset_{s}$ represents the benchmark allocation scale of stock $s$, $bmAsset_{i}$ is the benchmark allocation scale of index $i$, $stkWeight_{s,i}$ is the weight of stock $s$ in index $i$, and $L$ is the total number of indices containing stock $s$ [17] - The formula for estimating the industry allocation scale based on fund holdings is: $fundInduAsset_{k,T}=\sum_{s=1}^{S}\sum_{j=1}^{J}\frac{stkMv_{j,s,T-1}}{totalStkMv_{j,T-1}}\times totalStkMv_{j,T}$ Here, $fundInduAsset_{k,T}$ represents the fund allocation scale of industry $k$ at time $T$, $stkMv_{j,s,T-1}$ is the holding scale of stock $s$ by fund $j$ at time $T-1$, $totalStkMv_{j,T-1}$ is the total stock holding scale of fund $j$ at time $T-1$, and $totalStkMv_{j,T}$ is the total stock holding scale of fund $j$ at time $T$ [18] - The report introduces the concept of "potential impact" by standardizing industry under-allocation using free-float market capitalization as a proxy for industry capacity. The formula is: $PotentialImpact = \frac{IndustryUnderAllocation}{IndustryFreeFloatMarketCap}$ This metric reflects the potential inflow or outflow impact on industries based on their under-allocation relative to free-float market capitalization [23][25][29] - Using the unified benchmark framework, the report analyzes industry deviations under two major indices: - CSI 300: Industries with the largest over-allocation are electronics (1647 billion RMB), machinery (1070 billion RMB), and chemicals (807 billion RMB). Industries with the largest under-allocation are banking (2381 billion RMB), non-banking finance (2149 billion RMB), and food & beverages (568 billion RMB) [26][27][28] - CSI A500: Industries with the largest over-allocation are electronics (1291 billion RMB), machinery (911 billion RMB), and chemicals (442 billion RMB). Industries with the largest under-allocation are banking (1286 billion RMB), non-banking finance (1033 billion RMB), and utilities (329 billion RMB) [32][33][35] - The report concludes that regardless of benchmark type, the industries with the highest potential inflow impact are banking and non-banking finance, while the industries with the highest potential outflow impact are light manufacturing and textiles & apparel [5][23][34]