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Western (WDC) closed on September 19, 2025, , , . equities by liquidity. The move followed a strategic shift in its cloud storage division, which prioritized long-term margin expansion over short-term market share growth. Analysts noted that the company’s decision to phase out lower-margin consumer SSDs by Q1 2026 aligned with broader industry trends toward enterprise-grade solutions, potentially stabilizing pricing power in a sector facing persistent supply overhang.
Shareholder sentiment appeared to hinge on Western’s ability to execute its dual-brand strategy under the
and umbrellas. , , signaling improved cost discipline and client retention. However, mixed signals emerged from the front, .To run this rigorously I need to pin down a few implementation details and be sure the set-up fits within the current back-testing engine’s capabilities. Key points to confirm: 1. Universe • Do you want every U.S. listed common share (≈ 4,000+ names), only the S&P 1500, or another universe? 2. Trade-day
• Ranking by yesterday’s total $-volume, then buy the top 500 at today’s open and liquidate at today’s close (one-day hold), equal-weight? 3. Practical settings • Include transaction costs/slippage? If yes, what assumptions? 4. Engine constraints • The built-in engine handles one instrument per run. To replicate a 500-stock portfolio we need to build the trade list and aggregate externally. I can: a) Export daily open/close returns per security, compute the equal-weighted portfolio return, then feed the portfolio series into the engine, or b) Sample a representative subset / proxy ETF if you prefer a quicker approximation. Let me know your preferences on (1)–(3) and whether you’re comfortable with approach (a) (full portfolio aggregation) or would like an approximation first.
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