Alternative data datasets
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Visual quantitative research workspace that blends sentiment, social, and web-traffic feeds into customizable backtesting strategies.
Stocks Quarterly Earnings This dataset includes quarterly earnings report data for various stocks. 355,371 rows over 6,406 symbols, 8 columns, covering 1996-01-31 to 2026-07-31. Refreshed monthly. Strategies Built on This Data 490 papers in the Papers With Backtest catalogue declare this dataset as an input. 456 of them have been coded and run over their own full history. The median replicated Sha
Stocks Weekly Earnings Surprise Weekly earnings surprise probabilities and outcomes for publicly traded companies. 2,204,032 rows over 6,067 symbols, 8 columns, covering 2016-12-30 to 2026-07-03. Refreshed monthly. Why It Matters This dataset supplies high-frequency earnings-surprise context for equity strategies by: Pre-event positioning: Surprise probabilities guide sizing and hedging ahead of e
Cleaned, quality-flagged insider transactions and buying clusters, Jan 2024
ZipLime US Insider Trading Disclosures (PIT) [!CAUTION] Use knowledge_date, not transaction_date, when backtesting. transaction_date says when a trade occurred; knowledge_date says when the filing became observable through EDGAR. Using the former as the signal date introduces look-ahead bias. visible = trades.filter(pl.col("knowledge_date") <= simulation_time) This dataset normalizes corporate-ins