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This Week on Wall Street |
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| Markets head into a heavy week of earnings with the artificial intelligence trade under pressure. The Nasdaq Composite fell 4.5% last week, its worst stretch since June, as semiconductor shares led the retreat and attention turned to the borrowing behind the data-center buildout. The selling was narrower than the index suggests. Roughly seven in ten S&P 500 members finished the week higher, health care and defensive groups took in what left technology, and the Dow closed up for a second week. Energy supplied the other thread. Brent crude settled Friday at its highest level since May, after attacks on tankers cut traffic through the Strait of Hormuz, then gave back part of that move this morning when Washington waived certain sanctions on Russian fuel exports. Crude has swung between the high $90s and the $110 area this month, and shipping through the strait remains the variable that sets the range. |
| The Federal Reserve is in its blackout period before the October 27 and 28 meeting, so the rates question gets no help from officials this week. The backdrop has pulled in two directions all autumn. Hiring has slowed to a crawl, with September payrolls barely moving and the unemployment rate drifting up, while consumer prices rose 3.7% in the year through September, the fastest pace since spring. That mix briefly made a second straight increase look like a coin flip once the inflation report landed, before futures and prediction markets settled back toward a hold. The calendar offers little to resolve it, with housing data early and jobless claims Thursday. Friday carries the week's weight: the first October read from purchasing managers, and the final consumer sentiment survey, where the preliminary reading put year-ahead inflation expectations at 4.7% and marked a second straight monthly increase. |
| The quarter's defining earnings stretch opens this week, and the question it carries is no longer whether artificial intelligence spending produces revenue. It is how the spending is paid for. Meta reports Wednesday after the close as the first of the hyperscalers, with full-year capital spending guided to a range of $130 billion to $145 billion, and Tesla follows about an hour later. Netflix opens the slate Tuesday. What separates this round from the last several is the audience. Concern about the debt financing the buildout sat at the center of last week's selling, which puts capital spending guidance to double duty: a revenue outlook for chipmakers and equipment suppliers, and a signal of how much borrowing the next phase requires. Alphabet, Microsoft and Amazon report over the two weeks that follow, so this week frames the question rather than answering it. |
Tech Capex Against the Internet Era |
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| Measured as the change in information technology capital spending as a share of GDP across rolling ten-year windows, the series shows how much of the economy has been redirected toward technology. The current reading of roughly 1.9 percentage points sits level with the 2000 peak and above the personal computer era, against a trough near negative 0.9 points in the years after the financial crisis. The latest point ticks lower, the first downward move in the current climb. |
| Source: U.S. Bureau of Economic Analysis. Values read from the supplied chart and approximate. |
Economic Releases This Week |
| Monday | Housing Market Index | | Tuesday | Housing Starts, Building Permits,
Pending Home Sales | | Wednesday | None | | Thursday | Initial Jobless Claims | | Friday | Manufacturing PMI (Flash),
Services PMI (Flash),
Consumer Sentiment (Final) |
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Stories to Start the Week |
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What is Newton? |
| Our Newton model determines the highest probability of future price direction using advanced algorithmic and high-order mathematical techniques on the current market environment. It scores securities over multiple time periods on a 0–20 scale (0 worst, 20 best). Trend and level both matter. A name moving from 18 to 16 still signals a strong level, with slight exhaustion in the trend. ▼ 0–8 declining ▬ 9–13 neutral ▲ 14–20 strong |
| Equities | Trend | This Wk | Last Wk | | Foreign Developed | ▬ | 13 | 9 | | Large Cap | ▬ | 10 | 16 | | Mid Cap | ▬ | 10 | 12 | | Small Cap | ▼ | 5 | 7 | | Emerging Markets | ▼ | 3 | 7 |
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| Fixed Income | Trend | This Wk | Last Wk | | Floating Rate Bond | ▬ | 12 | 7 | | Long-Term Bond | ▬ | 10 | 7 | | Corporate Bond | ▬ | 10 | 7 | | Intermediate Term Bond | ▬ | 10 | 5 | | High Yield Bond | ▬ | 9 | 7 | | Short Term Bond | ▼ | 8 | 6 |
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| Sectors | Trend | This Wk | Last Wk | | Health Care | ▲ | 18 | 11 | | Communications | ▲ | 17 | 17 | | Financials | ▲ | 17 | 11 | | Consumer Defensive | ▲ | 15 | 11 | | Energy | ▲ | 14 | 14 | | Consumer Cyclical | ▬ | 12 | 14 | | Real Estate | ▬ | 11 | 3 | | Technology | ▬ | 9 | 13 | | Materials | ▬ | 9 | 5 | | Utilities | ▼ | 8 | 9 | | Industrials | ▼ | 5 | 10 |
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| Market Segments | Trend | This Wk | Last Wk | | Large Value | ▲ | 16 | 12 | | Mid-Cap Value | ▲ | 14 | 12 | | Small Value | ▬ | 12 | 9 | | Large Growth | ▬ | 9 | 14 | | Mid-Cap Growth | ▼ | 5 | 10 | | Small Growth | ▼ | 5 | 8 |
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Notable Newton Moves This Week: Scores improved across most of the board. Health Care jumped from 11 to 18 for the top read, Financials followed at 11 to 17, and Consumer Defensive moved into the strong band at 11 to 15, while Real Estate posted the largest single move at 3 to 11 without leaving neutral. The declines were concentrated in growth, where Technology slipped 13 to 9, Industrials 10 to 5, Large Growth 14 to 9 and Mid-Cap Growth 10 to 5. Value held the firmer reads at 16 for Large Value and 14 for Mid-Cap Value, and fixed income strengthened across the board, Intermediate Term Bond rising 5 to 10. |
Technical trading models are mathematically driven based upon historical data and trends of domestic and foreign market trading activity, including various industry and sector trading statistics within such markets. Technical trading models, through mathematical algorithms, attempt to identify when markets are likely to increase or decrease and identify appropriate entry and exit points. The primary risk of technical trading models is that historical trends and past performance cannot predict future trends and there is no assurance that the mathematical algorithms employed are designed properly, updated with new data, and can accurately predict future market, industry and sector performance.
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