Free, Point-in-Time Public Data for German and Nordic Small-Cap Research: Sources, Coverage and Pitfalls

Research on small and mid-cap equities outside the United States is held back less by methods than by data: the free sources are scattered, rarely carry a trustworthy publication timestamp, and often omit the firms that disappeared. This data paper documents what a private research project learned while testing more than thirty free public sources for German-speaking and Nordic markets, with a cut-off of 1 March 2026 for all research data. For each source we report what it contains, whether availability can be dated to the moment of publication (point in time), how many firms and years it covers, what access rules apply (robots.txt, rate limits, terms, blocks), which defects spot checks against the originals revealed, and a verdict. The main findings are the following. Usable daily prices exist for about 91–99% of German index members, including most delisted ones, but for only about 30–40% of Nordic titles listed in a given year. Deutsche Börse monthly turnover statistics are an excellent, exactly reconcilable liquidity filter from 2014. The ESEF filing index covers Austria and the Nordic countries but not Germany, and its ingestion date is useless for point-in-time work. Central archives of insider transactions and regulatory news exist for the Nordic countries, Austria and (since 2016) Sweden, but Germany and Switzerland have none that can be crawled within the rules. A report-calendar pipeline built on the legally mandated pre-announcement of financial reports (AFR) covered 102 listed firms after its first day. We close with crawling etiquette, including where the project fell short of it. The appendices give an inventory of every source, a per-host access catalogue, the pitfalls found, and a rebuild-level specification of the report-acquisition funnel (stages, file schemas, parsing rules, run order, regression cases).Read next: What these data could not deliver is reported in negative results on event-driven signals. Report PDFs from these sources feed the primary-source report-analysis funnel. How to use them without leakage: see leak-resistant point-in-time backtesting.This preprint is part of an eight-paper series on retail equity research from public data by Christopher Helm, covering German and Nordic small caps, backtesting methodology, data sources and AI-assisted research. All papers in the series:How Wise Is the Crowd? Timing and Selection Skill of Retail Social-Trading PortfoliosA Leak-Resistant Point-in-Time Backtesting Protocol and Engine for Retail Equity StrategiesThree Pre-Registered Bets: A One-Shot Out-of-Sample Test of Retail Strategy CandidatesWhat Did Not Work: Negative Results on Event-Driven Signals in German and Nordic Small CapsRequirements for an Autonomous Retail Order Engine Running Unattended for a DecadeRunning an Autonomous AI Agent on Quantitative Trading Research: Protocol, Supervision and Failure ModesFrom Pre-Announcement to Verified Facts: Design of a Primary-Source Report-Analysis Funnel for Small-Cap EquitiesChristopher Helm is an entrepreneur, consultant, and researcher. More research and articles on his blog.