The Zhongjie Fund stated in its article that the trading sentiment in the A-share market remained in the rising range last week. From a fundamental perspective, domestic demand is still weak, and policy expectations are at a high level. From a fund perspective, the market continues to expand. Margin trading data remains high, but the continuous net outflow of ETF data for two consecutive weeks reflects differences in the market. Overall, the current overall economy is still weak, with data showing slight improvement but the sustainability still needs to be verified. The social and economic operation remains stable, making it currently difficult to make a smooth linear extrapolation of fundamental improvement. Therefore, it is believed that pro-cyclical related assets will cause market divisions, but the likelihood of competing for the main line position is low. The current technology market is more likely to fluctuate upwards, and its trading indicators have not yet reached historical extremes, leading to further development under strong narratives and continuing to be the focus of structural market trends. The Zhongjie Fund stated that the AI market continues to deepen, with funds focusing on "seven big technology companies and six emerging technology companies" and showing some divergence, but overall maintaining an upward trend, driving structural bull market. Looking ahead, factors supporting the AI market include: the current AI empowerment narrative in China cannot be falsified, and relevant catalysts are still emerging, although it has not yet reached the stage of commercial application and fundamental verification, the continuous development of AI could still be linearly extrapolated until achieving grand goals such as AGI and A-share tech stock valuation revaluation. Drag factors include: unstable international situations, exchange rate and geopolitical pressures still exist, important domestic meetings are approaching, when AI assets reach high levels, funds diverge, with some funds switching to relatively low-cycle assets in anticipation of economic catalysis. In terms of industries, the allocation proportion of defensive dividend-related industries can be moderately reduced in the short term, with timing for replenishment based on market fluctuations and the trends of main line sectors. The low interest rate environment provides medium to long-term liquidity support for the dividend style, still maintaining high stability. It is recommended to allocate catalytic dividend-related assets (convertible bonds, market value management, two new and two heavy related catalysts are more intensive, and there is another small thematic theme like the reconstruction of Ukraine, short-term allocation of more profitable beaten-down state-owned enterprises), low valuation stable cash flow public utilities, financial, precious metal and other industries. As for most offensive assets, continue to focus on A-share technology (with the highest certainty of catalysts, relatively less affected by economic policies, theme opportunities continue to emerge, and the related narrative and intensity of catalysts are increasing without decreasing, market expectations for economic conferences are rising, earning effects and momentum are still sufficient, and the adjustment amplitude is expected to be not significant. Also continue to pay attention to Hong Kong-listed internet, controllable and autonomous, robotics, low altitude, smart driving, etc.), business support and overseas expansion (as the earnings season approaches, manufacturing with performance support and sustained expectations have the advantage of relatively small fluctuations, performance and expectations, such as power equipment, consumer electronics, home appliances and other high-quality assets. The pre-pricing of Trump's trade deal may bring opportunities for the valuation recovery of oversold overseas assets, but it is difficult to select stocks and timing, requiring judgment on oversold at the fundamental level) related assets, pro-cyclical assets (which have high elasticity of policy and fundamental expectations, but have a lower win rate compared to technology and other sectors during the policy verification period. Allocate based on risk preferences and catalysts, with consumption-related assets in the lead).