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Apple (AAPL) closed 0.04% lower on Sept. 5, , ranking fifth in market activity. The stock’s performance precedes its highly anticipated product launch event on Sept. 9, where the iPhone 17 is expected to debut with significant design upgrades after five years of incremental changes. Analysts suggest the redesign could boost consumer demand and temporarily shift focus from Apple’s perceived lag in , potentially revitalizing investor sentiment.
Goldman Sachs has positioned the iPhone 17 as a potential catalyst for renewed growth, citing supply chain improvements and global rollout plans. , , and emphasized hardware upgrades, carrier promotions, and as key drivers. However, caution persists. , highlighting concerns over margins pressured by discounts in China and the limited impact of . The broader market consensus reflects a muted outlook, .
Recent earnings data underscores mixed signals. , , , . , Apple’s stock has underperformed in 2025, . Competitive pressures remain, , . The iPhone 17’s success in premium markets and expansion will be critical to sustaining margins and market leadership.
To run this back-test rigorously I need to nail down a few practical details first: 1. Market universe • Do you have a particular exchange or index in mind (e.g., all primary-listed US equities, only S&P 500 constituents,
.)? • If it is “all US listed stocks”, the daily count can exceed 4 000, so ranking the top-500 by volume each day is feasible but data-intensive. 2. Price & execution convention • Open at today’s close and exit at tomorrow’s close (T + 1 holding period) – is that what you had in mind? • Equal-weight each of the 500 names, or weight by dollar volume? 3. Benchmarks / risk controls • Should we compare the strategy against something (e.g., SPY) and/or apply any stop-loss / max-drawdown limits, or are we strictly measuring raw returns? Once I have those points, I can lay out the exact data retrieval plan and run the back-test.
Hunt down the stocks with explosive trading volume.

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