存储周期上行，数据看清新一轮炒作的龙头

Group 1 - The core viewpoint of the article highlights that memory prices are expected to rise by 80%-90% quarter-on-quarter by Q1 2026, driven primarily by demand for general server DRAM, with DRAM, NAND, and HBM reaching historical highs [1] - Domestic securities firms validate the long-term bullish logic of the storage industry, with Aijian Securities suggesting that the high demand for AI servers and continuous upgrades in terminal storage parameters will extend the storage price increase cycle into 2026 [1] - Financial Street Securities points out that the combination of supply contraction and high-end demand creates a clear growth logic for domestic storage manufacturers to expand production and upgrade processes [1] Group 2 - The current market is characterized by a "long adjustment cycle and short upward cycle," stemming from a regulatory-driven slow bull market, which effectively suppresses large fluctuations [3] - Ordinary investors often confuse market trends with trading behavior, but trends are merely external manifestations of trading actions, and institutional funds can obscure their true trading intentions through fluctuating trends [3] - An example illustrates that from September 2024, a specific stock only saw price increases on a few trading days, while remaining in a fluctuating state for over 40 days, indicating that ordinary investors might exit prematurely due to impatience [3] Group 3 - Institutional inventory data reflects the active trading level of institutional funds, showing that even during periods of price fluctuation, institutions may still be actively participating in trading rather than passively holding [5] - In Q2 2024, a leading consumer stock saw an increase in state-level funding, but its price continued to adjust, which can be explained by the disappearance of institutional inventory data, indicating a lack of active trading support [5] - Another popular stock in 2025 demonstrated that institutional inventory had been present months before price increases, suggesting that institutional positioning occurred prior to visible market movements [7] Group 4 - In uncertain market conditions, the misleading nature of fluctuating trends can obscure risks, and institutional inventory data serves as a key verification indicator [9] - A specific stock that entered a horizontal phase after continuous adjustments in 2025 appeared to be at a price adjustment point, but the disappearance of institutional inventory indicated a lack of active trading support, leading to subsequent price declines [9] - The core value of quantitative data lies in its objectivity, as it does not reflect fund inflows or outflows but indicates whether institutional funds are actively trading [5] Group 5 - The core role of quantitative big data is to replace subjective judgment with objective data, breaking the cognitive biases associated with market trends [11] - In a slow bull market, the oscillatory behavior of institutional funds is essentially a process of selection and testing of stocks, allowing for strategic adjustments based on trading behavior [11] - Establishing a quantitative mindset involves understanding that "behavior determines results," shifting focus from short-term trends to the objective characteristics of trading behavior, which can enhance investment decision-making [11]