Group 1 - The core viewpoint of the report emphasizes the need for a stop-loss strategy to optimize the basic deviation recovery model due to the unsatisfactory performance of the strategy across various industries [15][17][28] - The basic deviation recovery model involves calculating the relative closing price of individual industry indices against the CSI 300 and determining effective drawdown values through iterative methods [3][15] - The report highlights that many industries, such as steel, retail, and real estate, did not meet the conditions for strategy application, indicating potential limitations in the model's effectiveness [6][9] Group 2 - The stop-loss strategy is designed to activate when the closing price exceeds a certain threshold, allowing for dynamic adjustment of stop-loss positions based on market movements [18][19] - The report indicates that the stop-loss strategy has not significantly improved performance in most industries, with some experiencing reduced returns compared to the original strategy [20][28] - Notably, industries like agriculture, electronics, and pharmaceuticals have shown improved drawdown metrics under the stop-loss strategy, suggesting selective benefits [25][68][72] Group 3 - The report discusses various stop-loss strategies, including multi-parameter and pullback types, which aim to enhance entry and exit points based on market conditions [31][62][79] - It is noted that while some industries benefited from specific stop-loss models, the overall performance of the original strategy remains competitive [79][80] - The findings suggest that the choice of parameters in stop-loss strategies can influence outcomes, with a preference for values around 5 or 6 for broader applicability [80]