行业轮动全景观察：市场整体情绪修复，传统行业走强而科技承压

• The report introduces the Industry Basic Tracking Model, which monitors industry fundamentals and identifies the top-performing industries based on their sentiment and activity levels. The model highlights transportation, food & beverage, and coal as the industries with the highest sentiment, while media, communication, and banking show lower sentiment levels[3][8][9] - The Crowding Factor is introduced to measure the disparity between leading and lagging stocks within an industry across three dimensions: volatility, liquidity, and systemic risk. Higher crowding factors indicate elevated risks such as high volatility, active trading turnover, or increased beta exposure. For example, the food & beverage industry shows historically high crowding factors, while industries like agriculture, pharmaceuticals, machinery, consumer services, and coal exhibit historically low crowding factors[3][17][18] - The Crowding Factor is calculated using metrics such as stock volatility, liquidity, and beta exposure. It reflects the degree of market concentration and trading activity within an industry. Higher values suggest speculative trading and heightened systemic risk, while lower values indicate reduced market activity and risk exposure[17][18][28] - The pharmaceutical industry demonstrates a divergence between sentiment and crowding factors, with sentiment decreasing by 0.06 and crowding factors increasing by 0.28. This is attributed to short-term policy benefits, event-driven catalysts, and market sentiment, despite the lack of comprehensive recovery in industry fundamentals[12][15][17] - The report emphasizes that industries with high crowding factors, such as food & beverage, may face risks of speculative trading and systemic volatility. Conversely, industries with low crowding factors, such as agriculture, pharmaceuticals, machinery, consumer services, and coal, may present opportunities for stable investment due to reduced speculative activity[17][18][28]