Best Market Data Sources for Systematic Short Selling Research

Best Market Data Sources for Systematic Short Selling Research

Short selling strategies live or die on data quality. Here is where to find the specific datasets that matter.

The Data Demands of Short Selling

Systematic short selling has data requirements that are fundamentally different from long-only strategies. Beyond standard price data, short sellers need information about share availability (borrow data), cost of borrowing, short interest, SEC filings related to dilution and corporate distress, and real-time awareness of regulatory restrictions like short sale rules.

The challenge is that much of this data is fragmented, expensive, or buried in unstructured documents. Building a systematic short-selling operation requires assembling data from multiple specialized sources.

Price Data for Short Selling

For raw price data, the same providers that serve long strategies serve short strategies: Polygon.io for reliable U.S. equity data, or Databento for institutional-grade tick data. The difference is that short strategies often operate in less liquid names (small and micro-cap), where data quality matters more because spreads are wider and volumes are thinner.

Short Interest and Borrow Data

S3 Partners

S3 Partners provides real-time short interest data, borrow rates, and squeeze risk analytics. Their data is widely used by institutional short sellers and hedge funds. The pricing reflects the institutional audience.

Ortex

Ortex provides short interest analytics including real-time estimated short interest, cost to borrow, and utilization rates. Their platform is more accessible to individual researchers than S3 Partners, with pricing starting around $50 per month.

Fintel

Fintel provides short interest data, institutional ownership data, and insider trading information. Their short squeeze scoring system attempts to identify names at risk of forced covering. Pricing is accessible for individual researchers.

Corporate Events and Filing Data

For systematic short sellers, corporate events — particularly dilution events — are among the most predictive signals. When a company files an S-1 registration statement to issue new shares, the resulting supply increase often creates persistent downward price pressure, especially in small and micro-cap names.

Alphanume provides two datasets that are directly relevant to this workflow. Their dilution events feed processes SEC S-1 filings into structured, machine-readable events with timestamps, market cap context, and lifecycle tracking (whether the filing became effective or was withdrawn). Their corporate default events dataset provides a historical log of companies flagged as being in default status, labeled from SEC filing text. These datasets eliminate the need to manually parse thousands of dense regulatory filings and allow researchers to focus on testing systematic strategies around dilution and distress events.

Additionally, Alphanume's historical market cap dataset provides point-in-time capitalization data that is essential for size-based universe construction. Short strategies focused on micro-cap names need to know which stocks were actually micro-cap at each historical date — not which ones are micro-cap today.

Comparison Table

Assembling a Short Selling Data Stack

A practical data stack for systematic short selling combines price data (Massive or Databento) with short interest data (Ortex or Fintel for individual researchers, S3 Partners for institutions) and research-layer datasets (Alphanume for dilution events, corporate defaults, and point-in-time market cap classifications). Each layer serves a distinct function, and trying to source everything from a single provider will leave significant gaps.