Nasdaq opens lower again as Alphabet spending plans spook investors

• Alphabet shares dropped over 4% in early trading after revealing 2026 capex plans of $175-185 billion, nearly double the prior year's spending and significantly above consensus forecasts
• The Nasdaq Composite declined nearly 1,000 points or 4.2% over five days to around 22,500, with Strategy and Qualcomm leading losses at over 7% each
• January Challenger job cuts reached 108,400, up from 35,550 in December and nearly triple the 43,000 expected, adding to market concerns about economic conditions

Market Summary: Tech Selloff Intensifies as Alphabet Spending Concerns Weigh

Market Performance:

US markets opened sharply lower on February 5, 2026, with the Nasdaq down 1.45%, S&P 500 falling 1.1%, and Dow Jones declining 0.8%. Over five days, the Nasdaq Composite dropped nearly 1,000 points (-4.2%) to just over 22,500. Small caps bucked the trend, with the Russell 2000 edging up 0.2%.

Key Company Movements:

Alphabet led the tech retreat, falling over 4% after announcing capital expenditure plans of $175-185 billion for 2026—nearly double last year's levels and significantly above analyst expectations. Strategy (bitcoin holder) and Qualcomm posted the steepest declines on the Nasdaq 100, both down over 7%. Advanced Micro Devices continued its selloff from the previous session.

Commodities and Currencies:

Bitcoin plunged 8.5% to $69,500, hitting levels not seen in over a year. Precious metals tumbled with silver down 13% to $76.60/oz and gold falling 3% to $4,818/oz. WTI crude oil dropped 2.3% to $63.66/barrel. The US dollar strengthened, with the DXY index up 0.2% at 97.8.

Economic Data:

January Challenger job cuts surged to 108,400 from 35,550, well above the 43,000 forecast. Markets awaited initial jobless claims, continuing claims, and the December JOLTS report.

Market Implications:

Alphabet's aggressive AI infrastructure spending plans rattled investors, triggering broader tech sector weakness and raising concerns about capital efficiency and returns in the AI investment cycle.