ExtractAlpha provides curated alternative datasets and pre‑computed trading signals that are rigorously tested for predictive performance. Through its AlphaClub platform, institutional investors can explore, filter, and download raw data or ready‑to‑use signals with full documentation for seamless integration into quantitative strategies.
Funding
$100K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Quantitative investors often lack reliable, well‑validated alternative data and ready‑to‑use trading signals, making it difficult to generate incremental alpha and manage risk across multi‑strategy portfolios.
Solution
ExtractAlpha curates a broad set of alternative datasets and transforms them into rigorously tested alpha and risk signals. The company applies quantitative research methods and proprietary analytics to assess predictive power, providing both raw data and pre‑computed signals. Clients can access these assets through the AlphaClub data exploration platform, which supports real‑time, daily, and longer‑term frequencies across global markets. Detailed white papers, data dictionaries, and methodology documents accompany each offering, enabling seamless integration into systematic investment workflows and back‑testing pipelines.
Target Audience
Primary customers are hedge funds, asset management firms, brokerages, and fintech companies that run quantitative or quant‑amental investment strategies.
Features
- Over 30 curated alternative datasets covering earnings, NLP sentiment, digital revenue, patent innovation, and more, each validated for predictive performance
- Pre‑built short‑, medium‑, and long‑term trading signals with documented methodology and risk metrics
- AlphaClub web interface for data exploration, custom filtering, and download of raw datasets or signal time series
- Comprehensive documentation including white papers, data dictionaries, and methodology descriptions for transparent model replication
- Integration support for institutional data environments, with options for real‑time, daily, or quarterly data feeds
- Ownership and operation of Estimize, providing crowdsourced earnings estimates and consensus forecasts