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Practice · graded on a filing
Build it from GOOGL’s latest annual filing. Every line you enter is checked by code against the filing.
Work the arithmetic of a stated all-stock deal: derive the acquirer's standalone diluted EPS from its filed net income and diluted share count (and check it against the filed EPS you are given), add the stated target income, add the stated new shares, and compute the pro-forma EPS. The last cell is the change as a percentage of standalone EPS — positive is accretive, negative is dilutive. Every filer runs the SAME stated deal, so the difference in the result is entirely the acquirer's own filed figures: the sign is a property of the pair, not of the deal, and the walk stops at the EPS delta. Every figure you are given comes from GOOGL’s latest annual filing and is cited below; the assumptions are handed to you and are never graded. Nothing here is a view on the company.
Match the AI
An AI model worked this exact drill and got 5 of 5 lines right. Match it.
Claude Sonnet 5, given the same filed figures and stated assumptions you see, scored by the same grader. One run, on 2026-09-28, not retried. It does arithmetic on this filing only and never forms a view on the company.
Reconcile GOOGL's model from the filed figures below (as of 2025-12-31). Derive each linked line in the unit its label names — the model must reconcile end to end.
Alphabet Inc. 10-K (FY2025, period ended 2025-12-31), accession 0001652044-26-000018, via SEC EDGAR
Educational use only — not investment advice.
Compare the buyer's EPS before and after. Pro-forma EPS is combined net income over the combined share count, including any new shares issued to pay. If pro-forma EPS is higher, the deal is accretive; if lower, dilutive. In an all-stock deal it comes down to whether the target adds a larger slice of combined earnings than the slice of the company the buyer issues.
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Net income, weighted-average diluted shares outstanding, and diluted EPS, as filed in the latest annual report — plus the stated deal (a target income set at a fixed fraction of the filed net income, and a fixed share issue), which is handed to you and never graded. Each cell is checked against the value the same pipeline derives from that filing, inside a small tolerance band, and the model has to reconcile end to end. There is no language model in the grade — it is arithmetic over filed figures, so it returns the same verdict every time. The correct values are not in this page: they are recomputed on the server when you submit, and your entries are read as a submission, never as the answer.
Every attempt ends in a review. Each line is marked Best, Inaccuracy, Mistake or Blunder by how far it is off, and the first line that went wrong is flagged, so an error carried through the rest of the model is fixed once, where it started.
Signed out, nothing is recorded: work it as many times as you like. Signed in, each graded attempt is saved to your account so your dashboard can track it.
Each one is built from that company's own annual filing and graded the same way.
Educational use only — not investment advice. Figures come from public SEC filings; Echelon teaches you to analyze data, it never recommends buying or selling any security.