An analysis of the correlation of stock volume and stock price in index funds using OLS regression

The relationship between stock trading volume and stock price has been widely debated, with prior research reporting both positive and negative correlations. Understanding this relationship is essential for identifying potential arbitrage opportunities and anticipating market movements. This study examines the correlation between trading volume and price by applying an Ordinary Least Squares (OLS) regression model specifically to index fund data. The analysis reveals a modest correlation of 3.25%, with an adjusted value of 3.22%, suggesting that while the relationship is weak, the variables are not statistically independent. Additionally, the results indicate that, for the given dataset, the Laplacian error metric offers a better fit than the Gaussian metric. These findings provide a nuanced perspective on volume–price dynamics and highlight the potential benefits of alternative error modeling approaches in financial time series analysis.