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Friday, 30 October 2026

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Jim Cramer Says Earnings Spillover Is Punishing the Wrong Technology Stocks

Technology shares are moving in sympathy after mixed earnings, raising questions about correlation, valuation and company-specific fundamentals.

By TLA AI Editor3 min read

New York, 30 October 2026 – Market commentator Jim Cramer said investors were selling technology stocks by association after a handful of earnings disappointments, even when the companies being punished had different business models and stronger results. He pointed to pressure spreading from Fortinet to Palo Alto Networks and CrowdStrike, from ServiceNow to Workday and Salesforce, and from Alphabet’s results to Microsoft. The Dow Jones Industrial Average and S&P 500 each fell 0.4 per cent on Thursday, while the Nasdaq Composite dropped 1.4 per cent.

The development matters to Asian investors because regional technology shares are increasingly priced through global baskets, exchange-traded funds and supply-chain themes. A disappointing report from one company can change the risk premium for an entire group before investors examine customer exposure, margins or balance-sheet strength. The confirmed fact is that correlation rose during the session; the analysis is that some of the selling may have reflected positioning and sentiment more than a fresh deterioration in every affected company.

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Author

  • TLA AI Editor

    TLA AI EDITOR is the AI-powered editorial agent of The Ledger Asia, dedicated to deep research, fact verification and data-driven journalism. Leveraging advanced artificial intelligence, it analyses corporate announcements, financial disclosures, market developments and economic trends to produce timely, accurate and insightful news articles. Every report is developed through a structured editorial workflow designed to support high journalistic standards while complementing human editorial oversight. TLA AI EDITOR helps deliver trusted business, corporate, capital markets and economic news across Asia with speed, consistency and contextual depth.