Alternative data datasets
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This solution is a quantum annealing based deep learning model capable of training on transactions data to identify anomalous transactions.
Visual quantitative research workspace that blends sentiment, social, and web-traffic feeds into customizable backtesting strategies.
Analytics derived from space assets that merge image and signal intelligence to track defense, infrastructure and commercial activity.
Archive of past performance ratings and related documentation for every skilled nursing facility.
A multilingual collection comprising over one million Italian dialogue exchanges, ten thousand audio clips, six thousand images, and roughly two thousand five hundred verified retail purchases, refreshed each month.
Bitcoin and Ethereum exchange flow indicators and miner activity metrics for market positioning.
Complete filing metadata & URLs for institutional holdings, insider trades, etc
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Papers published in arXiv/quant-ph between 2012-2016 with number of Scites
Patent_FR_US_Merge_Radix_65536 is a Hugging Face dataset by publisher PhysiQuanty that merges French and US patent documents into a single text corpus. It is distributed in Parquet format and is tagged with an Apache-2.0 license, though the README provides no further description.
A real-time stream of submissions and engagement metrics from the WallStreetBets forum curated by Quiver Quantitative and distributed through BattleFin, used to gauge retail investor mood toward stocks.
Quantitative insider trading records intended to support alpha-generating investment strategies.
Structured Form 144 filings used to track insider transactions and inform quantitative trading approaches.
A sharded Parquet archive of NSE equities and index prices from India spanning 2000 to 2026, covering more than 2,500 tickers and organized into roughly 1.5 GB files for efficient streaming.
Subscription research service delivering executive-level briefings, quantitative models and curated datasets authored by seasoned former leaders in technology, automotive and consumer sectors.
Risk and compliance intelligence derived from official audit and supervisory examination records applied across regulated organizations.
Deloitte’s ESG Financial Reporting Agent is an AI-driven solution that automates the end-to-end process of ESG (Environmental, Social, and Governance) financial reporting. The agent streamlines data collection, standardizes metrics across frameworks, and quantifies the financial impact of ESG initiatives and risks. With advanced automation, real-time validation, and predictive analytics, it empowe
Projected gains and token quantities along individual arbitrage routes for a specific point on the blockchain.
Weekly purchase quantities of over 800 products over 52 weeks
Quantitative financial fundamentals along with associated key performance indicators.
Sustainability metrics spanning general and sector-specific ESG themes across three tiers, 334 subjects, and more than 700 explanatory measures.
Sustainability information organized into general and industry-focused ESG categories with three layers, 334 subjects, and over 700 supporting indicators.
Computed metrics include news-based sentiment scores and the degree to which individual companies track commodity futures performance.
Aggregated hiring information from Chinese firms, including vacancy counts and associated pay bands.
Tone indicators extracted from onshore research publications originating in China.
Non-traditional Chinese financial datasets include capital movement patterns and broader macroeconomic signals.
Information that guides drug indication selection by quantifying addressable market size and opportunity.
A proprietary mood metric extracted from transcripts of US corporate earnings calls.
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FINRA Short Interest, last 12 months Shares sold short for every exchange-listed and OTC security, twice a month, for the last 12 months (522,296 rows): short shares, change from the prior report, average daily volume and days to cover. import pandas as pd df = pd.read_parquet("hf://datasets/FinzData/finra-short-interest/data/short_interest.parquet") df[df.ticker == "GME"] In the full FinzData dat
Indian equity market price history covering NSE-listed stocks and indices from 2000 through 2026, offered in Parquet shards of roughly 1.5GB each for efficient streaming on the Hugging Face hub. The collection draws on more than 2,500 tickers and supports both minute-level and end-of-day intervals.
Confirmed location records demonstrating when devices were physically present at specific venues, enabling advertisers and analysts to evaluate in-store traffic and quantify the impact of marketing campaigns on visits.
🇮🇳 Indian Stock Market Data: Minute & Daily (2000 - 2026) 📌 Overview This is a high-performance financial dataset containing the historical price history of 2,500+ NSE Stocks and Indices. The dataset has been sharded and optimized for high-speed training. Instead of thousands of tiny files, it is grouped into large ~1.5GB Parquet shards, making it ideal for fast streaming with the Hugging Face dat
Movement intelligence gathered from mobile devices that quantifies customer flow, time spent and trade areas for retailers, property firms and financial institutions operating throughout Europe and North America.
Quantitative climate indicators and reference values for businesses, segmented by location and industry.
🇮🇳 Indian Stock Market Data: Minute & Daily (2000 - 2026) 📌 Overview This is a high-performance financial dataset containing the historical price history of 2,500+ NSE Stocks and Indices. The dataset has been sharded and optimized for high-speed training. Instead of thousands of tiny files, it is grouped into large ~1.5GB Parquet shards, making it ideal for fast streaming with the Hugging Face dat
Specialized measurements track corporate media presence, flagging atypical surges in coverage and quantifying alignment across sources.
Automated satellite-image analysis that quantifies construction, industrial-site activity, mining and energy infrastructure.
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
Analytics product that links weather conditions to changes in category-level and regional sales demand.
Consumer panels in China quantifying monthly active users, usage duration and behavior across multiple applications.
Minute- and daily-resolution price histories for more than 2,500 National Stock Exchange securities and indices from 2000 through 2026 are consolidated into roughly 1.5 gigabyte Parquet shards to enable rapid streaming on Hugging Face infrastructure.
Panjiva-derived trade records from shipping manifests that map corporate import and export links and quantify global commerce volumes.
Indian stock market price history spanning 2000 to 2026 for over 2,500 NSE-listed stocks and indices, packaged in large Parquet shards around 1.5 GB each for efficient streaming.
Daily ticker-level web-traffic engagement for over 25,000 listed companies worldwide, with visits, demographics and ranks plus point-in-time ticker mapping, packaged for quantitative funds.
Movement quantification across roads, zones and points of interest calculated from location-based services data, widely used in transport and land-use economics.
Countrywide mobile telemetry from China quantifying device penetration and in-app activity levels.
Cleaned, quality-flagged insider transactions and buying clusters, Jan 2024
Minute-level open-high-low-close-volume bars for Indian equities, hundreds of millions of rows in Parquet under MIT. Gives high-frequency microstructure across the Indian cash market for intraday and market-on-close strategies.
Essential energy sector fundamentals suited for quantitative analysis and modeling work.