春晚成了比拼舞台，上市公司谁能胜出？

Group 1 - The core idea is that data-driven approaches, similar to how Kuaishou utilizes big data for the Spring Festival Gala, can transform investment decision-making by focusing on the behavior of institutional funds rather than just stock price fluctuations [1][2][14] - The concept of "institutional inventory" is highlighted as a key indicator in quantitative big data, reflecting the activity level of institutional funds; its presence indicates active participation, while its absence suggests a decline in participation willingness [2][6] - The relationship between stock price movements and institutional fund participation is emphasized, where a lack of institutional support leads to downward price trends, akin to a Spring Festival Gala losing audience interaction [6][10] Group 2 - Quantitative models have the ability to separate different trading behaviors, allowing for precise identification of fund behavior patterns, which traditional investment methods struggle to achieve [8][10] - The importance of capturing behavioral signals early is discussed, as it enables investors to make more informed decisions, similar to how Kuaishou anticipates user content needs for the Spring Festival [8][13] - The value of quantitative big data lies in its ability to convert abstract fund intentions into visible behavioral characteristics, helping investors establish stable decision-making logic without relying on subjective guesses [10][14] Group 3 - The article illustrates that maintaining awareness of institutional fund behavior can help investors remain composed during market fluctuations, as demonstrated by cases where active institutional participation led to price recoveries despite apparent volatility [13][14] - The overarching trend is the shift towards data-driven investment strategies, which allows ordinary investors to move away from anxiety over price predictions and develop a more objective understanding of market dynamics [14]