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On September 15, 2025, , . The stock ranked 397th in trading activity among listed equities, reflecting heightened investor interest in the amid macroeconomic and geopolitical dynamics.
Recent developments suggest a convergence of supply-demand imbalances and regulatory shifts in the energy market. A U.S. , exacerbating concerns over energy security amid rising nuclear power plant restarts. Analysts noted that policy incentives for low-carbon energy infrastructure could amplify demand for uranium in the medium term.
Meanwhile, a technical analysis report underscored the stock's break above key resistance levels, aligning with broader sector rotation toward commodities. Traders observed increased open interest in , indicating institutional positioning. However, short-term volatility remains tied to production decisions and uranium recycling program updates, which could influence near-term pricing trajectories.
To run this back-test properly I need to pin down a few practical details so that I can assemble the data and set up the strategy engine correctly: 1.
• Which market / exchange should we draw the “top-500-by-volume” list from? (e.g., all U.S. listed common stocks, S&P 500 constituents, a specific country’s main board, .) 2. Price used for entry/exit • Do you want to buy at the same day’s close and exit on the next day’s close (Close→Close return), or use open prices (Close→Next-open), or another convention? 3. Position sizing • Equal-weighted across the 500 names each day, or some other weighting rule? 4. Transaction costs / slippage (optional) • Should we assume zero costs, or would you like to embed a commission and/or bid-ask spread? Once we settle these points I can prepare the data-retrieval plan and kick off the automated back-test.
Hunt down the stocks with explosive trading volume.

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