Stock market forecast in the week of 3 August = Trend
- Average directional index: Neutral
- Institutional activity: Trend
- On balance volume: Trend
ANALYSIS
The outlook of the stock market remains in an upward trend for US shares, although the sale of a lot of volume and Bearish bias shifts are warning signs.
The S&P500 ($ Spx) fell 2.4%. The index is ~ 2% above the 50-day advancing average and ~ 6% above the 200-day advancing average.
The ADX-Directional indicators are about to a cross-over (ie neutral), but the other two signals keep coming in the week.
SPX price and volume card before August 3, 2025
Performance comparisons
The utilities sector ($ XLU) Was the only win last week; Materials ($ XLB) led to the disadvantage. Consumer discretionary, energy and financial data ($ Xly, $ XLE, $ XLF) Link -gone to neutral bias, while staples, health care, materials and real estate ($ XLP, $ XLV, $ XLB, $ XLB) All cases to bearish.

S&P sector performance from week 31 of 2025
All sector styles were lower last week; Momentum ($ Mtum) escaped with the least damage, while the small cap value value ($ IWN) Was the hardest hit. Low beta, small/medium dop value and high dividend ($ SPLV, $ IWN, $ IJJ, $ IWX, $ SPHD) fell on neutral bias.

Sector style performance from week 31 of 2025
Oil ($ Use) Outrophy other assets and Bitcoin ($ 4) underperformed. Oil, gold and bonds ($ Uso, $ gld, $ eaf) All returned to Bullish bias and the US dollar ($ Dxy) Improved to neutral.

Acti -class performance of week 31 2025
COMMENTARY
US shares were not a fan of the macro data dump. June Job Opening (Jolts) fell slightly and missed expectations, but not much. The first GDP estimate was 3%, which is unchanged year after year, but above expectations and considerably better than the reading of previous quarter.
So it is not everything so surprising that the FOMC rates has kept stable, with reference to a low unemployment rate, somewhat increased inflation and persistent uncertainty about the economic outlook (ie impact of rates).
The subsequent PCE data data issue showed inflation in June (a year on an annual basis), and that is after an upward adjustment of 0.2% at the head of May and key figures.
| PCE (J/Y) | Really | Prior | Expected |
| Head | +2.6% | +2.4%* | +2.5% |
| Core | +2.8% | +2.8%* | +2.7% |
We continue to see a pattern of earlier core and headline PCE data that reveals higher the following month … Not enough to influence the policy, but certainly enough to ask questions.
Enter non-farming letter letters in July. The NFP data of Friday showed an increase of 73,000 jobs in July, well below the expectations of 110,000. Not great, but not terrible either. Also revise the report also in June and July figures:
- June -won data were lowered from 147k to 14k ( -90% ))
- May Payroll data were lowered from 144K to 19K ( -87% ))
These are enormous revisions and points to a weaker labor market than the one used to determine the policy. Admittedly, NFP is only a directorally correct estimate, derived from small surveys and models every month. But even the higher accuracy, lower speed data (three -month census of employment and wages or QCEW) shows a growing gap with NFP estimatesWhat all suggests that even “directionally correct” can be a piece.
So what should a safe investor do? View the prices of assets and use fundamental/macro data as confirmation. The outbreak in bonds (ie rates fall) and the US dollar is a deflationary signal, but stock indexes are still bullish.
In the meantime, when sectors, styles or activa classes switch back to Bearish bias, it is time to adjust their respective position sizes. At least, dropping the position to your minimum size is justified, while leaving the position together is a safer game, especially if the ticker among other category (eg $ XLP and $ SPLV).
The best for your week!
PS If you find this research useful, tell a friend.
If you don’t, tell an enemy.
Sources: Bloomberg, CNBC, Federal Reserve Bank or St. Louis, HedeGeye, Stockcharts.com, Tradingconomics.com, US Bureau or Economic Analysis, US Bureau or Labor Statistics
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