台光電
NT$21.53B
Historical data for 2026-09, compared with 2026-08. This is not a current investment thesis or demo. Current research industries are CPO, Physical AI, and space infrastructure. Check the registry for approved Packs.
The July revenue data for EquityLayer's tracked Taiwan AI-materials slice does not show broad near-term deterioration relative to June.
investment view effect: insufficient evidence — The 2026-09 Pack contains new evidence. It does not reuse the registered 2026-07 tests. Review the new evidence before changing the view.
Unknowns: Reported revenue does not identify shipment volume, mix, margin, or customer concentration. A three-company slice is not evidence for the full Taiwan market or an entire industry. Issuer notes remain management statements and do not establish causality.
Falsifier: A later official MOPS release that shows broad deterioration in the tracked names, or a company disclosure that contradicts the revenue read-through, falsifies the current continuation view.
Next trigger: Refresh when the official MOPS 2026-10 monthly-revenue dataset is published; preserve this snapshot and append a new diff.
Follow it from your agent: create_research_follow {"pack_id":"tw-monthly-revenue"}. Your agent checks again on 2026-11-10 and tells you when a new version is out. Connect your agent
Cite as: EquityLayer Research. "Taiwan AI Compute monthly revenue." 2026-09, as of 2026-09. https://equitylayer.io/research/monthly-revenue
NT$21.53B
NT$18.65B
NT$5.59B
Reported facts: Monthly-revenue fields are issuer-reported. Changes are deterministic comparisons against the preserved prior snapshot.
Management claims: Issuer notes are company statements reproduced from the official dataset. They do not establish demand causality or a research conclusion.
Inference: These are deliberately narrow operating read-throughs derived from reported fields. They are not causal, valuation, or investment inferences.
Taiwan Stock Exchange (臺灣證券交易所) 2026 上市公司每月營業收入彙總表, dataset t187ap05_L, as published. The Open Data is made available to the public under the Open Government Data License. Open Government Data License: https://data.gov.tw/license
Recommended workflow: discover_theses → test_thesis → get_thesis_update.
Remote MCP: https://equitylayer.io/mcp
JSON: /api/research/monthly-revenue?symbols=2383,3037,8046
Research Pack JSON: /api/research/pack?symbols=2383,3037,8046
Changes JSON: /api/research/changes?since=2026-06&symbols=2383,3037,8046
Research Update JSON: /api/research/update?pack_id=tw-monthly-revenue&since_version=taiwan-monthly-revenue:2026-06&symbols=2383,3037,8046
Backward-compatible tools: get_taiwan_monthly_revenue, get_taiwan_monthly_research_pack, get_research_changes_since
Add it to Claude Code:
claude mcp add --transport http equitylayer https://equitylayer.io/mcpOr paste into any MCP client config:
{ "mcpServers": { "equitylayer": { "url": "https://equitylayer.io/mcp" } } }Pack version: taiwan-monthly-revenue:2026-09 · Snapshot hash: 64dea69a5c27579cda94295dda593f5871bc9e96373f24526039efc1b9c9748e
Prior snapshot hash: 8cf5b9818d5c28a79a188c569164e6eb6984e7d3ab9462757ad02ae2eb78fa01
Each query returns the same dated snapshot, source attribution, and limitations. User-specific interpretation stays inside the caller's own agent, so EquityLayer incurs no per-question model cost.