从逆风开局到领涨市场，兴银富利兴易智享量化实现40%净值跃升

Core Insights - The article highlights the impressive performance of the "Xingyin Wealth Fuli Xingyi Smart Quantitative Index Growth" product, which achieved a net value increase of 40.42% since its inception, significantly outperforming its benchmark [1][4]. Group 1: Product Performance - As of November 24, 2025, the average net value growth of mixed public wealth management products with a 1-3 month investment period was 4.34%, with the top products coming from four wealth management companies, including Xingyin Wealth [1]. - The "Fuli Xingyi Smart Quantitative Index Growth 3-Month Minimum Holding Period No. 1 Mixed Wealth Management Product A" achieved a net value growth rate of 41.97% over the past two years, ranking first in performance [1][2]. - The product's annualized return since inception reached 19.65%, showcasing its strong performance in a challenging market environment [4]. Group 2: Investment Strategy - The product employs a combination of quantitative stock selection and derivatives, aiming to exceed the returns of a specific index through diversified holdings and flexible trading [2]. - The investment strategy is based on a performance benchmark that combines the returns of the CSI 1000 Index (45%), CSI 500 Index (45%), and the People's Bank of China 7-day notice deposit rate (10%) [2]. - The management team utilizes a multi-factor model to identify stocks with high growth potential and reasonable valuations, optimizing the investment portfolio while controlling style and sector deviations [4]. Group 3: Market Context - The product was launched during a period of market volatility, with the A-share market experiencing a recovery phase, particularly in the technology sector, which later led to a structural bull market [4]. - Following a shift in U.S. Federal Reserve monetary policy and unexpected domestic policy support, market enthusiasm surged, contributing to the product's strong performance [4]. - The management anticipates that the market will maintain high trading volumes and volatility, which will favor the quantitative models adept at capturing short-term mispricing opportunities [4].