FOURWEEKMBA TRACKER ยท PRICES AS OF 4 NOVEMBER 2026 ยท UPDATED 4 NOVEMBER 2026
Free to share with a link to this page. Market caps are our arithmetic from filed share counts and closing prices.
The short version: this page tracks what 14 of the largest AI-exposed listed companies are worth, from chip designers and chipmakers to the clouds and the software built on them. At the close on 4 November 2026, Apple led at $5.08T, ahead of Nvidia at $4.82T. Together the 14 add up to $28.76T.
Over the 30 days to 4 November 2026 they lost $2.74T, or โ8.7%; 11 of the 14 fell, and CoreWeave moved most (โ44.6%). When a headline says AI stocks dropped or rallied, this is the table to check it against.
“As of October 21, 2026, there were 5,888 million shares of Alphabetโs Class A stock outstanding, 827 million shares of Alphabet's Class B stock outstanding, and 5,579 million shares of Alphabet's Class C stock outstanding.”
“As of December 31, 2025 , 25,932,524,521 Common Shares, par value NT$10 each were outstanding.” “by each individual as to the total outstanding common shares of the Company was calculated by including both common shares and shares held in the form of ADSs (each ADS represents five (5) common shares)”
“Class Number of Shares Outstanding Class A Common Stock $0.000006 par value 2,214,472,367 shares outstanding as of October 16, 2026 Class B Common Stock $0.000006 par value 341,768,886 shares outstanding as of October 16, 2026”
“As of October 26, 2026, there were 2,306,705,341 shares of the registrantโs Class A common stock outstanding, 101,787,133 shares of the registrantโs Class B common stock outstanding, and 1,005,000 shares of the registrantโs Class F common stock outstanding.”
“As of July 31, 2026, CoreWeave, Inc. had outstanding 458,871,690 shares of Class A common stock, 92,664,912 shares of Class B common stock, and 0 shares of Class C common stock, each with a par value of $0.000005.”
Market cap, 30-day change and distance from the 52-week closing high are our arithmetic. Each row links the filing its share count comes from (open “Cover-page quote” for the sentence) and the price history its closes come from.
Who gained and who lost in the last 30 days
How we calculate it
Market cap = shares outstanding from the latest filing x the close on 4 November 2026. The share count is the one each company states on the cover page of its latest 10-Q, 10-K or 20-F at the SEC; the close is from Nasdaq.com’s historical quotes.
More than one share class. Alphabet, Meta, Palantir and CoreWeave have several classes. We count every class on the cover. Alphabet’s Class A and B are valued at the GOOGL close and Class C at the GOOG close; for the others, unlisted classes are valued at the listed Class A close.
TSMC and ASML file annual 20-F reports, so their share counts date from the end of 2025, not this quarter. TSMC is valued through its US ADR: common shares divided by five (each ADR is five shares, per the 20-F) times the TSM close.
30-day change compares the close on 4 November 2026 with the close on 5 October 2026, with the share count held fixed, so it measures the price move. vs 52-wk high compares the latest close with the highest daily close in the year before.
Share counts lag. Buybacks and new shares after the filing date are not reflected until the next filing, so our figures can differ slightly from quote pages that update share counts daily.
Not on the list yet
Samsung Electronics. No SEC filing: its share count is in Korean DART filings, and its price is in won on the Korea Exchange. Not sourced in this build, so left out rather than estimated.
SK Hynix. No SEC filing: its share count is in Korean DART filings, and its price is in won on the Korea Exchange. Not sourced in this build, so left out rather than estimated.
Updated 4 NOVEMBER 2026 with closing prices from 4 November 2026. Built by FourWeekMBA from SEC filings and Nasdaq.com price history; every share count links to its filing. This page is information, not investment advice.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
