Study on the Explanatory Power of Weighted Constituents on the Performance of the STAR 50 ETF - Lai, Xuekai (Exploring Science Academic Conference Series, 2026)
With the deepening of China's science and technology innovation strategy, the STAR 50 ETF has seen its trading volume increase day by day. The study aims to explore whether a small number of high-weight assets can effectively explain and predict the overall performance of the ETF. The study employs empirical methods such as descriptive statistics, correlation analysis, and multiple linear regression, based on daily trading data for 2025. The results show that there is an extremely high positive correlation between the top-weighted constituents and the STAR 50 ETF, with all correlation coefficients exceeding 0.9. Moreover, the price movements of these five stocks can explain more than 99% of the ETF’s price fluctuations(R²=0.998). This finding not only verifies the effectiveness of partial replication strategies on the STAR 50 ETF, but also provides market participants with a simple and feasible prediction tool — that is, by tracking the performance of a few leading stocks, one can roughly determine the direction of the ETF.