Core Viewpoint - The recent phenomenon of "beta rising while alpha falls" in the A-share market is attributed to structural market differentiation and the characteristics of quantitative investment strategies, where a few large-cap stocks drive index gains while most stocks lag behind [3][4][5]. Group 1: Market Environment and Performance - Since August, the A-share market has experienced accelerated gains, with trading volumes reaching historical highs, but there is significant differentiation between large-cap and small-cap stocks [2]. - The strong performance of large-cap stocks has raised concerns among investors regarding the allocation to small-cap index-enhanced products [2][9]. - The market's overall upward momentum is primarily driven by a small number of stocks, leading to a decrease in pricing efficiency for individual stocks and making it harder for quantitative models to capture alpha [3][4][5]. Group 2: Challenges for Quantitative Strategies - The concentration of funds into a few large-cap stocks has resulted in a weak performance for the majority of stocks, complicating the ability of quantitative strategies to generate excess returns [4][5][6]. - The recent market structure has led to a situation where the alpha capture becomes more challenging due to the high degree of style concentration [4][5][6]. - Historical experience suggests that extreme structural market conditions are typically unsustainable, and the market will eventually revert to a more balanced state, allowing quantitative strategies to recover their alpha [5][6]. Group 3: Investor Concerns and Strategy Adjustments - Investors are currently worried about the risks associated with style switching, particularly regarding small-cap index-enhanced products [9]. - To mitigate risks, companies suggest diversifying portfolios and focusing on high-quality small-cap stocks with strong earnings capabilities [10][11]. - The emphasis is placed on maintaining a balanced approach to investment, ensuring that strategies are adaptable to changing market conditions [12][13]. Group 4: AI Integration in Investment Strategies - Companies have increasingly integrated AI technologies into their investment processes, enhancing data processing capabilities and improving the efficiency of information extraction [22][24]. - AI is utilized for various functions, including data cleaning, feature extraction, and optimizing investment strategies, which helps in capturing potential signals more effectively [22][23][25]. - The application of AI in investment strategies is seen as a critical factor in enhancing predictive capabilities and optimizing decision-making processes [25][26]. Group 5: Long-term Investment Perspectives - The focus is on long-term investment strategies rather than short-term timing, with an emphasis on building resilient portfolios that can withstand market fluctuations [27][28][29]. - Companies advocate for a diversified approach to asset allocation, which can help mitigate the emotional impact of market volatility on investment decisions [35][36]. - The importance of identifying undervalued assets with high certainty for long-term gains is highlighted as a key strategy for investors [31][32].

Core Viewpoint - The article highlights the significant outperformance of quantitative index enhancement products in 2025, driven by increased market activity, structural opportunities in small-cap stocks, and advancements in AI technology within quantitative strategies [2][29]. Group 1: Performance of Quantitative Index Enhancement Products - As of May 2025, quantitative index enhancement products have shown an average excess return of 24.48% over the past year, with 93.91% of the products reporting positive excess returns [2]. - The performance of various strategies is detailed, with the "Other Index Enhancement" category leading at an average excess return of 34.74% over the past year [2]. - The market environment has favored small-cap stocks, which have outperformed due to increased liquidity and risk appetite among investors [3][8]. Group 2: Drivers Behind Performance - The active trading environment and increased stock price volatility have provided ample trading opportunities for quantitative managers, facilitating the generation of excess returns [3][29]. - The introduction of the CSI A500 index has opened new avenues for quantitative strategies, prompting institutions to accelerate their product offerings [8]. - The application of AI in quantitative investment has enhanced the resilience and effectiveness of strategies, allowing for better data processing and risk management [8][29]. Group 3: Trends in Quantitative Strategy Layout - Private equity firms are diversifying their quantitative strategies, with a focus on machine learning and AI to meet varying investor needs [4][9]. - There is a noticeable trend towards multi-category and finely-tuned product lines, particularly in index enhancement products, to cater to different client demands [9][20]. - The market is witnessing a shift towards thematic strategies, such as dividend enhancement and industry-specific strategies, to provide investors with more targeted investment options [25][20]. Group 4: Small-Cap Index Enhancement Products - Small-cap index enhancement products are expected to continue showing potential for excess returns due to their inherent volatility and liquidity advantages [11][21]. - The current market environment has led to increased interest in small-cap stocks, which are perceived to have higher growth potential, although they also carry higher risks [21][26]. - Investors are advised to balance their portfolios according to their risk tolerance, especially given the potential for significant price fluctuations in small-cap stocks [17][27].