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Analysis of the Reasons for Divergence in Large US Tech Stocks' Performance and Investment Strategies on December 29, 2024

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December 30, 2025

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Analysis of the Reasons for Divergence in Large US Tech Stocks' Performance and Investment Strategies on December 29, 2024

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Current Time Note:
The system time shows December 30, 2025, but the following analysis is strictly based on the US stock market closing scenario of December 29, 2024 you provided.

📊 Analysis of Reasons for Divergence in Large Tech Stocks’ Performance
I. Reasons for Individual Stock Performance Divergence

1. Tesla (TSLA): Down Over 3%

Fundamental pressures:

  • Market concerns about slowing EV demand growth have intensified; competition in major global markets has increased, and Tesla faces pressure on market share in Europe and China [1]

  • The Robotaxi business model is still in the early exploration stage; profitability and scaling paths are not yet clear, and investors remain cautious about input-output [2]

  • Valuation levels are relatively high relative to profitability; the market has high growth requirements for it, and short-term performance expectation fluctuations are easily amplified

2. NVIDIA (NVDA): Down Over 1%

Valuation and technical factors:

  • Although AI chip demand remains strong, the stock price has risen sharply in the early stage, and valuation is in a historically high range; some investors took profits [3]

  • There is uncertainty in the speed of AI infrastructure construction and the ROI cycle of enterprises; some market participants have begun to worry about marginal changes in the short-term AI capital expenditure rhythm

  • The macro environment’s sensitivity to high-valuation tech stocks has increased, and uncertainty in the interest rate path has increased valuation volatility [4]

3. Apple (AAPL): Slightly Up

Defensive advantages:

  • Diversified business structure; hardware, services, wearables, and other segments provide stable cash flow, with strong anti-cyclical capabilities

  • Sustained shareholder return policies (dividends, buybacks) support the stock price, and valuation is relatively stable

  • High ecological closed-loop and user stickiness; have strong pricing power and brand moat in the environment of fluctuating consumer electronics demand

4. Google (GOOGL): Slightly Up

Structural growth:

  • Search and cloud business fundamentals are robust; AI integration is gradually reflected in advertising efficiency and cloud service demand

  • Restructuring and cost control effects have emerged; operational efficiency has improved, and the market remains optimistic about profitability improvements

II. Overall Market Background

Sector Characteristics:

  • The tech sector overall showed divergence on December 29, 2024; valuation, growth expectations, and short-term performance catalysts are the main dividing lines

  • Macro pressures (high interest rates, fluctuating expectations of economic soft landing) have put pressure on high-valuation, high-volatility stocks

Investor Sentiment:

  • Year-end funds tend to lock in gains and reduce risk exposure; stocks with large early gains and valuation sensitivity are under pressure

  • The market prefers to hold targets with clear business models, stable cash flow, and relatively reasonable valuations

💡 Insights for Tech Stock Investment Strategies
1.
Emphasize the Match Between Valuation and Growth
  • High-valuation stocks are highly sensitive to changes in growth expectations; once growth slows marginally or the macro environment fluctuates, the stock price adjustment range is large

  • When investing, pay attention to valuation tools such as PEG (Price/Earnings to Growth Ratio), discounted cash flow, and phased scenario assumptions to avoid blindly chasing high-growth narratives

2.
Focus on Business Resilience and Cash Flow Quality
  • In stages of high macroeconomic uncertainty, companies with diversified revenue structures, high profit margins, and robust free cash flow are more resilient to declines

  • Prioritize companies with sustained buyback and dividend capabilities and healthy balance sheets

3.
Distinguish Between Themes and Fundamentals
  • Long-term themes like AI are important, but short-term stock price fluctuations more reflect performance realization rhythm, valuation matching, and macro environment

  • It is recommended to combine themes with fundamentals: focus on efficiency improvements and revenue structure changes brought by AI empowerment in the long term, and focus on performance realization capabilities in the short term

4.
Portfolio Construction and Risk Management
  • Maintain a balance between growth and value, offense and defense; moderately allocate tech sub-sectors with low correlation and different business attributes

  • Use methods such as phased position building, stop-loss discipline, and position management to control drawdowns; avoid heavy one-time positions in high-valuation stages

5.
Flexible Application of Time Dimensions
  • Short-term (quarterly dimension): Focus on marginal changes in performance exceeding/falling short of expectations and valuation repair opportunities

  • Medium-term (1-3 years): Focus on the pace of AI implementation in enterprise software, cloud infrastructure, and vertical industries, and its substantial improvement in profit structure

  • Long-term (over 3 years): Focus on the company’s technical moat, ecological construction capabilities, and management execution

📌 Summary and Outlook

Short-term Perspective:
The market remains cautious about high-valuation, cyclical tech stocks; performance and macro factors are prone to amplified reactions. The relative resilience of Apple and Google highlights the importance of the ‘certainty premium’.

Medium-term Perspective:
The AI theme enters the performance verification period; companies that can continuously realize revenue and profit improvements and maintain a balance between valuation and growth will have independent trends.

Operational Recommendations:

  • Moderately reduce concentration on single high-valuation growth stocks and increase allocation to targets with mature business models and robust cash flow

  • Lay out AI leaders with long-term competitiveness and sufficient valuation retracement on dips, but need to verify the match between performance and valuation in phases

  • Pay attention to structural divergence between industries and companies; avoid ‘one-size-fits-all’ allocation based on industry or theme

References

[1] Jinling API Data (The December 29, 2024 US stock closing scenario is provided by the user)

[2] PhoneArena - Tesla iPhone app update hints at a feature owners have been begging for (https://www.phonearena.com/news/tesla-iphone-app-update-hints-at-a-feature-owners-have-been-begging-for_id176944)

[3] SeekingAlpha - AMD’s Strategy Doesn’t Mean It’s Not Overvalued (https://seekingalpha.com/article/4856261-amd-strategy-doesnt-mean-its-not-overvalued)

[4] GuruFocus - Tesla (TSLA) Faces Challenges Amid Cybertruck Delays and Supplier Contract Cuts (https://www.gurufocus.com/news/4089237-tesla-tsla-faces-challenges-amid-cybertruck-delays-and-supplier-contract-cuts)

Note: GOOGL news is temporarily unavailable due to API returning 429 error; relevant analysis is based on general understanding of the company’s fundamentals and market structural factors.

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.