Core Viewpoint - The article discusses the "Leading Stock Diffusion Effect" as a mechanism driving sector trends, emphasizing the importance of stock selection to enhance returns from industry rotation strategies. The report presents various stock selection strategies and their performance metrics, highlighting the effectiveness of the "Alpha Dual-Drive Preferred Combination" strategy, which has achieved an annualized return of 33.6% since 2013, outperforming the CSI 500 index by 28.3% [1][68]. Group 1: Research Background - The demand for industry-level beta timing has increased with the development of flexible allocation funds and FOF products, making industry rotation a core asset allocation need [3]. - The article notes that the return dispersion between industries is often greater than that among individual stocks within the same industry, indicating that selecting the right industry is more beneficial than selecting individual stocks [3]. - Challenges in extracting industry rotation factors include limited sample sizes and the heterogeneous nature of industries, which complicates the universality of factor logic [3][4]. Group 2: Mechanism of the Leading Stock Diffusion Effect - The diffusion effect is described as the process where stock price increases in leading stocks spread to related stocks, leading to a broader industry uptrend [12]. - The process includes several stages: policy triggers leading to the activation of leading stocks, active capital inflow driving sector resonance, and cognitive dissemination leading to widespread price increases across related stocks [12][13]. - The article outlines different migration methods of capital during the diffusion process, including vertical and horizontal diffusion, market capitalization descent, and valuation arbitrage [15]. Group 3: Stock Selection Strategies - The report evaluates various stock selection strategies to replicate or enhance industry rotation returns, including full replication, half-weighted combinations, and top 10 equal-weighted combinations [30][31]. - The full replication strategy achieved an annualized return of 24.9% since 2013, while the half-weighted and top 10 equal-weighted strategies yielded returns of 24.5% and 23.5%, respectively, with reduced trading complexity [34][46]. - The "Alpha Dual-Drive Preferred Combination" strategy, which selects stocks based on both industry and individual stock factors, has shown superior performance with an annualized return of 33.6% [52][59]. Group 4: Performance Metrics - The "Alpha Dual-Drive Preferred Combination" strategy has an information ratio (IR) of 2.07 and a maximum drawdown of 27.8%, indicating strong risk-adjusted performance [68]. - The article provides detailed annual performance data for the preferred industry combination, showing significant absolute and excess returns across various years [29][66]. - The report emphasizes that the improved SUE and active large order factors contribute to the strong performance of the preferred industry combination, achieving annualized excess returns of 8.3% and 10.1%, respectively [18][23].

Core Viewpoint - The report discusses the "Leading Stock Diffusion Effect" as a mechanism driving sector trends in the A-share market, emphasizing the importance of constructing optimal investment portfolios based on improved factors like economic conditions and capital flows [1][2][3]. Research Background - The demand for industry-level beta timing has increased due to the development of flexible allocation funds and the growing industry ETF system, making sector rotation a core asset allocation need [6]. - The A-share market has seen accelerated sector rotation, which poses challenges to traditional rotation models, necessitating a reevaluation and improvement of these models [7]. Mechanism of Diffusion Effect - The diffusion effect in the A-share market typically involves capital migrating from core leading stocks to related targets, driven by policy triggers, active capital inflows, cognitive dissemination, and expectation overshoot leading to differentiation [2][16]. - The process includes vertical and horizontal expansions within the industry, market capitalization descent, and valuation arbitrage, ultimately leading to a broader sector rally [17]. Performance of Improved Factors - The report presents improved factors based on the previous discussion, showing significant performance enhancements in the revised SUE and active large order factors, with annualized excess returns of 7.9% and 10.3% respectively [21][22]. - The improved factors demonstrate better stability and lower volatility compared to traditional models, particularly in recent years [64]. Optimal Industry Portfolio - The optimal industry portfolio, constructed using a common condition screening method based on component factors, has shown superior historical performance with an annualized return of 26.0% and an annualized excess return of 19.1% since 2013 [3][64]. - The portfolio has maintained stable excess growth since 2022, with an annualized excess return of 11.7% and a maximum drawdown of 9.2% [74]. Comparison of Multi-Headed Construction Methods - The report compares two multi-headed construction methods: composite factor multi-headed and component factor common condition screening, concluding that the latter offers lower volatility and more stable excess returns [42][64]. - The composite factor multi-headed approach has shown stagnation in excess returns in recent years, while the optimal industry portfolio continues to outperform [53][64].