Alternative data datasets
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A weekly dataset tracking positions held by commercial and non-commercial participants across futures, provided in legacy, disaggregated, and financial-futures formats for agricultural, energy, metals, and financial contracts.
Supply-chain and demand assessments based on on-the-ground retail and distribution checks within Chinese markets.
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The kl3m-index-edgar-filings-8-k dataset is an indexed catalog of Form 8-K filings from the SEC's EDGAR system, published by the ALEA Institute. It provides structured metadata for over 1.8 million corporate event reports distributed in Parquet format.
Track release dates and times for hundreds of market-moving activities around the world. We cover the historic and projected dates for over 500 economic events in 44 countries. Type of economic events include Government debt auctions, Monetary policy announcements, Energy market reports, Economic indicators and PMIs.
Utilize AI to analyze complex financial data sets, identify trends, and generate insightful visualizations. This can include creating interactive dashboards, predictive models, and automated reports to aid in financial decision-making and strategy...
A reconstructed EDGAR corpus of company filings in English (Apache 2.0): a large sample of annual and quarterly reports and exhibits, hundreds of thousands of records. Comparable to other public SEC text sets and a solid starting point for filings-based research.
Machine-readable XBRL filings covering 10-K and 10-Q reports, cleaned and standardized so financial figures can be extracted reliably.
Millions of consumer complaints about financial products, mortgages, credit cards, debt collection and loans, with product, issue, company response and ZIP-level geography, together with HMDA mortgage disclosures.
Aggregated holdings information parsed from quarterly 10-Q financial reports.
Clean Risk Factors, MD&A and market-risk text from annual and quarterly reports
Over twenty million adverse event reports covering drugs and medical devices are consolidated, refreshed daily, and structured for analysis.
Normalized extracts from the FDA FAERS system enable evaluation of drug adverse event reports and related safety signals.
Structured records of FDA medical device adverse event reports, formatted to support safety monitoring and risk evaluation workflows.
A corpus of SEC EDGAR filings in English (Apache 2.0), roughly a few hundred thousand company documents including annual and quarterly reports and exhibits. The filings text is organized for model pretraining and retrieval, but the same documents are the raw material for filings-based and disclosure signals.
Facility-level environmental records from the US EPA, toxic release inventories, greenhouse-gas reports, air permits and regulated-facility lists, queryable by geography or company for compliance and ESG screening.
Custom sourcing research for alternative datasets: structured briefs that map the available feeds to a specific investment thesis, rather than raw data sales.
Rapid routing of intellectual property misuse reports to the appropriate parties for prompt remediation.
Entertainment industry datasets, music-streaming subscriber counts, video, gaming and creator-economy metrics, assembled from disclosures and web measurement.
FDA-regulated products and events exposed as structured JSON: adverse drug-event reports, device recalls and registrations, labels, the NDC directory and food enforcement, used for pharmacovigilance and regulatory-risk screens.
Crowd-sourced mobile speed and connectivity test results reflecting user experience across networks.
Complete textual SEC 10-K annual filings from 2021, suited for studying corporate disclosures and natural language processing tasks.
Recreational-vehicle industry data: monthly shipments by manufacturers, wholesale values, ownership demographics and outlook projections.
Container-shipping schedule reliability, vessel delays and capacity-deployment analysis from Sea-Intelligence's reports and custom data services. Scope and delivery depend on the selected product.
Text of SEC filings pulled from EDGAR spanning millions of records in English (Apache 2.0): 10-K, 10-Q, 8-K, annual reports and exhibits, tagged for text-generation and classification. A practical base corpus for earnings- and filings-driven signals, from risk factors and MD&A to management commentary.
SEC 10-K Filings Embeddings Chunked text from 49 SEC 10-K annual reports for seven large US companies, with a 1536-dimensional dense embedding per chunk. Built for the Pinecone 101 workshop as a ready-to-import vector dataset. Records 15,244 chunks Filings 49 (10-K) Companies AAPL, AMZN, GOOGL, META, MSFT, NVDA, TSLA Fiscal years 2018–2025 (7 per company) Vector 1536-dim float32, intended for cosi