{
    "action": "final",
    "content": "**Short answer:** the four price columns (open, high, low, close) are almost perfectly correlated with one another. Volume and date are essentially unrelated to everything else.\n\nThe correlations come from one pass over all 422,729 rows (the result of my last correlation query, step-2).\n\n**1. Price columns move together (r ≈ 0.9998–0.9999)**\n- high–close: 0.99989\n- open–low: 0.99989\n- open–high: 0.99987\n- low–close: 0.99988\n- high–low: 0.99984\n- open–close: 0.99976\n\nThis is expected. Open, high, low and close are all quotes of the same stock on the same day, so they sit at almost the same price level. The raw correlation is also inflated because the pooled data mixes about 149 companies with very different price levels. Most of the variation is between companies, not within a day. The pooled figure therefore says little about daily moves. Correlating daily returns per stock would be a better test of that, and I did not run it.\n\n**2. Volume is essentially uncorrelated with price (r ≈ -0.008)**\n- volume vs. open: -0.00807\n- volume vs. high: -0.00807\n- volume vs. low: -0.00806\n- volume vs. close: -0.00806\n\nThis is a slightly negative but negligible linear relationship. Pooled across companies, higher-priced stocks do not trade more shares. Volume seems to be driven by other factors, such as share count and investor interest.\n\n**3. Time has little linear relationship with either measure**\n- date vs. close: 0.088, a weak positive drift. Prices rose over 2012–2025, but the pooled linear trend is small because company levels differ so much.\n- date vs. volume: 0.003, effectively zero.\n\n**Takeaways**\n- The open, high, low and close columns are largely redundant for modelling. Using all four in a regression would cause severe multicollinearity.\n- Volume carries independent information, so it is worth keeping as a separate signal.\n- For useful relationships, such as volatility against volume or the effect of the AI surge, analyse per company or use returns and high–low range rather than pooled price levels."
}