Financials Outperform Tech as S&P 500 Stays Flat
The S&P 500 eked out a 0.09% gain on February 17 in a volatile session where financial stocks outperformed the broader market. Technology stocks remained under pressure due to persistent fears of AI-driven disruption, which weighed on the Nasdaq. The Dow Jones Industrial Average and Russell 2000 were little changed.
- The rotation out of technology stocks is a significant reversal from prior years; as of February 17, the S&P 500 software sector has fallen roughly 17% year-to-date in 2026. This sell-off is partly linked to new AI tools from companies like Anthropic, which investors fear could disrupt the business models of established IT service and software firms. - While financials outperformed for the day, the sector has struggled for most of the year, down 5.9% year-to-date. The market leaders in 2026 have been resource stocks, with the Energy and Materials sectors up 21.3% and 16.6%, respectively. - The underlying market strength is broader than the headline index suggests; the S&P 500 equal-weighted index has outperformed the market-cap-weighted version in 2026, indicating positive performance in smaller companies and non-tech sectors. - Recent economic data includes a stronger-than-expected January jobs report, which added 130,000 payrolls (double the consensus estimate), and an unemployment rate that ticked down to 4.3%. At the same time, the annual inflation rate cooled to 2.4%. - Tech giants are funding their AI ambitions through massive debt issuance; Alphabet recently raised nearly $32 billion in bond sales, and the top five AI infrastructure firms are projected to spend over $500 billion by the end of 2026. This level of capital expenditure has created investor anxiety around future profitability. - For students targeting Summer 2026 internships, recruiting for many large finance and tech firms began in the fall of 2025. Some boutique investment banks, like Evercore and Houlihan Lokey, opened applications as early as January 2025. - Finance interviews for technical roles typically test knowledge of the three financial statements and financial modeling techniques like discounted cash flow (DCF) analysis. Data analytics interviews often involve case studies and technical questions on Excel, SQL, and Python.