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. 8, , ranking 299th in market activity. , . , citing reduced leverage risks. , , citing improved gas transport volumes from recent expansions. .
, . The transaction occurred under a pre-arranged established in May. Post-sale, . Analyst ratings remained mixed, . , .
To run this back-test rigorously I’ll need to clarify a few details and assumptions first: 1. Universe – Should the “top 500” be selected from all U.S. listed common stocks, another specific market (e.g., Europe, China), or a custom universe you have in mind? 2. Ranking price & execution convention – Do we rank stocks by their dollar trading volume using that day’s close? Should we assume we buy those names at the next day’s open and exit at the same day’s close (one trading-day holding period), or buy at today’s close and exit at tomorrow’s close? 3. Portfolio construction – Equal-weight each of the 500 names every day? Or value-weight by traded volume / market-cap / something else? 4. Transaction costs – Should we include any commission or slippage assumptions? (Default is zero if you don’t specify.) Once those points are clear I can generate the daily buy/sell lists, run the portfolio back-test from 2022-01-03 through today, and present key performance metrics (CAGR, annualized volatility, max drawdown, Sharpe ratio,
.) along with an equity-curve chart.Hunt down the stocks with explosive trading volume.

Dec.24 2025

Dec.24 2025

Dec.24 2025

Dec.24 2025

Dec.24 2025
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