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Weekly NewsletterOctober 21, 2024

This Week on Wall Street – Week of October 21st

We kicked off the week with a rebound in stocks, fueled by dip-buying after last week’s sell-off.

This Week on Wall Street – Week of October 21st

Market Commentary

Stocks began the week taking a breather after 2024’s longest weekly rally, while Fixed Income faced renewed pressure. This comes as markets scaled back expectations for aggressive rate cuts, with the looming government debt debate weighing on bond investors’ minds.

Nearly 20% of S&P 500 companies are set to report earnings this week. According to Factset, the “Magnificent 7” names are projected to post year-over-year earnings growth of 18.1% for Q3. Excluding these seven companies, the blended earnings growth rate for the remaining S&P 500 firms is a modest 0.1%. Overall, the blended earnings growth rate for the full S&P 500 stands at 3.4% for the third quarter. Notably, companies exceeding Q3 earnings or revenue expectations have seen an average one-day excess return of 2.1%, 2.3%, and 2.6% — more than double the long-term averages for entire earnings seasons. Meanwhile, earnings misses have led to sharper selloffs of 3.8%, 2%, and 3.7%, respectively.

This week is also filled with a flurry of Fed speeches, and investors will be closely watching for any shifts in the outlook on rate cuts in the coming months. Volatility remains elevated, driven by upcoming U.S. elections just two weeks away, heightened geopolitical tensions between Israel and Iran, and technically overbought risk-on markets. The elevated volatility index indicates investors are slightly hedging against potential negative shocks in these areas.

Newton models last week recommended rotating back to domestic markets over international ones, a theme that persists this week. Energy, once a bright spot just a few weeks ago, now ranks as the worst-performing sector and the only one with a score below 12. Leading the pack are Financials, Consumer Discretionary, and Industrials. 

Economic Releases This Week

Tuesday: Philadelphia Fed President Harker Speaks

Wednesday: Fed Governor Bowman Speaks, Existing Home Sales, Fed Beige Book

Thursday: Initial Jobless Claims, S&P Flash Manufacturing & Services PMI, New Home Sales

Friday: Durable Goods, Consumer Sentiment

Stories to Start the Week

Boeing and its machinists’ union have reached a new contract proposal that could end a more than monthlong strike. 

The New York Liberty survived OT to win their first WNBA title

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What is Newton?

Our Newton model attempts to determine the highest probability of future price direction by using advanced algorithmic and high-order mathematical techniques on the current market environment to identify trends in underlying security prices. The Newton model scores securities over multiple time periods on a scale of 0-20 with 0 being the worst and 20 being the best possible score.

Trend & level both matter. For example, a name that moves from an 18 to a 16 would signal a strong level yet slight exhaustion in the trend.

Newton Score
This Week / Last Week
EQUITIES
THISLAST
Large Cap
1918
Small Cap
1812
Mid Cap
1812
Emerging Markets
1411
Foreign Developed
1111
FIXED INCOME
THISLAST
Floating Rate Bond
129
Corporate Bond
126
High Yield Bond
1110
Long-Term Bond
115
Intermediate Term Bond
105
Short Term Bond
105
SECTORS
THISLAST
Financials
1913
Consumer Cyclical
1818
Industrials
1715
Technology
1517
Utilities
157
Communications
1414
Real Estate
1410
Materials
145
Health Care
1312
Consumer Defensive
129
Energy
18
MARKET SEGMENTS
THISLAST
Mid-Cap Growth
2017
Mid-Cap Value
1910
Small Growth
1815
Large Value
1712
Small Value
1711
Large Growth
1416

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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