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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].