BWX Technologies Surges 2.54% on $250M Volume, Ranks 456th in U.S. Stock Liquidity Amid Defense Backlog Growth
BWX Technologies (BWXT) closed Monday’s session with a 2.54% gain, trading on $250 million in volume—ranking 456th among U.S. stocks by liquidity. The defense contractor’s performance followed a strategic review of its contract pipeline with federal agencies, which analysts noted could influence mid-term revenue visibility.
Internal communications highlighted a 12% increase in unpriced backlog from Q2 to Q3, though no formal guidance was provided. Market participants observed that the stock’s momentum aligned with sector-wide trends in defense spending, though valuation metrics remained elevated relative to historical averages.
To run this back-test accurately I need to pin down a few practical details and make sure we set it up in a way the system can support: 1. Universe • Which market(s) and symbol universe should we draw the “top-500 by daily trading volume” from (e.g., all U.S. common stocks on NYSE + NASDAQ, only S&P 500 constituents, etc.)? 2. Trade mechanics • Entry price: open of the ranking day or close of the ranking day? • Exit price: close of the same day or next day’s open/close (i.e., exact “1-day” holding definition)? • Slippage/transaction costs: any assumption? 3. Portfolio aggregation Our built-in back-testing engine is optimized for single-ticker or event-based studies. For a 500-stock daily-rebalanced portfolio we have two workable routes: a) Event study: treat “being in the top-500 by volume” as an event for each stock, then aggregate the 1-day event returns across stocks and days. b) Custom multi-asset back-test (requires an external data export step and a separate Python engine outside this chat). Route (a) fits entirely inside this interface; route (b) would require you to run code on your side. Which route would you like to pursue? Once I have these clarifications I can fill in any remaining default assumptions and start pulling the data.


Comentarios
Aún no hay comentarios