Here are three questions this dataset can answer, based on its structure and the profile I ran. Each is proposed, not yet answered. **What the profile shows** - The data is 422,729 daily price rows for 152 semiconductor tickers, from 2012-01-02 to 2025-08-04. - 99,984 of those rows (about 24%) fall after the ChatGPT launch, which gives a usable "AI era" window. - The average daily high–low range is about 3.7% of price. - Average daily volume is about 8.47M shares, but the median is only 898,500. A few very liquid names dominate volume, and many small ones trade thinly. - 4,888 rows have zero volume, which are likely illiquid or halted days. **1. Did the AI surge change returns and risk, and for which companies?** Compare each company's price trajectory and daily range (volatility) before and after late 2022. The question is whether the gains were broad across the sector or concentrated in a few AI-exposed leaders. This would support overweight and underweight decisions. It is also a test of whether the sector's rise is a narrow rally. The 152-ticker breadth makes that test possible. **2. Has trading activity shifted toward a small group of names?** Volume is highly skewed (mean about 9× the median). Track how each company's share of total volume has moved over time, and whether that concentration increased after 2022. This would show whether investor attention, and so liquidity, has consolidated in a few stocks. It matters for position sizing and for judging how easily a position can be entered or exited. **3. What does an unusual-volume day predict?** Flag days where volume is far above a stock's own trailing norm, then look at price moves and range over the following days. Excluding the zero-volume rows keeps illiquid or halted days from distorting the baseline. The answer would show whether volume spikes are useful entry or exit signals, and whether that relationship changed in the AI era. **Caveats** - There is no data on fundamentals, exchange, or sector sub-segment, so the work is limited to price and volume behaviour. - The 152 tickers are the ones present now, so delisted companies may be missing, which would bias long-run comparisons upward. I can run any of these next; question 1 is the most direct starting point.