The privateMetrics® database is extensive, encompassing a wide range of private company data and valuation metrics. Here’s a breakdown of its magnitude and scale:

Database Size and Coverage:

• Number of Companies: The database includes data on over 1 million private companies globally. As of September 2024, the Broad Private Market Universe (BMU) comprises 937,000 uniquely identified private companies.
• Geographic Coverage: The database spans over 150 countries, representing the entire investable universe. The flagship indices focus on the most attractive 30 countries for private equity and venture capital investors.
• Prices Computed: Over 75 million prices have been computed. The privateMetrics asset pricing model is used to shadow price a universe of hundreds of thousands of potential index constituents.
• Track Record: The database has a 10-year track record.
• Data Points: The database contains over 6 million accessible data points (equity).
• Monthly Updates: The data is updated monthly.

Breakdown by Universe:

privateMetrics employs a three-tiered universe structure:

1. Broad Private Market Universe (BMU): Comprises a wide range of private companies.
   • As of September 2024, it included 937,000 uniquely identified private companies.
   • Spans across 150+ countries and more than 60 industrial activity sectors.
   • Represents over USD 59 trillion in market capitalization.
2. PE-Backed Universe (PEU): Focuses on firms exhibiting a “PE-backed” profile.
   • Approximately 175,000 firms.
   • Represents approximately USD 17 trillion in market capitalization.
3. Market Index Universe (MIU): Selects companies from the PE-Backed Universe to represent the private equity market in key countries.
   • Consists of 2,000 companies.

Granularity and Segmentation:

• PECCS® Taxonomy: The database utilizes the PECCS® (PrivatE Company Classification Standard) taxonomy to classify companies across five objective and independent pillars:
  • Activity (Industry).
  • Lifecycle Phase.
  • Revenue Model.
  • Customer Model.
  • Value Chain.
• Activity Sectors: Covers more than 60 sectors as defined by PECCS.
• PECCS Segment Combinations: Offers over 1,000 PECCS® segment combinations.
• Custom Benchmarks: With over 300 combinations of PECCS® segments available, privateMetrics benchmarks offer significant granularity and a wide range of customisations based on segment, industry, geography, revenue model, lifecycle stage.

Valuation Metrics:

• Metrics Available: Offers over 80 metrics.
• Valuation Metrics: Includes various valuation multiples and financial metrics such as:
  • Price-to-Sales.
  • Price-to-Earnings.
  • EV/EBITDA.
  • EV-to-Sales.
  • Price-to-Book.
  • EBITDA-to-Sales.
  • EBIT-to-Sales.
  • Net Income-to-Sales.
  • Net Debt-to-Assets.

Data Sources and Processing:

• Transaction Data: A representative set of 10,000 private market transactions (entries and exits) since 2013 are collected from PitchBook, Capital IQ, and fund manager annual reports.
• Company Characteristics Data: Data used to shadow price firms in the universe comes from audited accounts, public markets, deal characteristics, and the PECCS segments to which each firm belongs.
• Data Aggregation: Data is aggregated from multiple sources, including Orbis, PitchBook, and annual company accounts, and processed via artificial intelligence.

Robustness and Accuracy:

• Shadow Pricing: The privateMetrics asset pricing model allows the computation of numerous shadow prices. As of May 2024, the model allows computation for hundreds of thousands of assets and totals over 40 million monthly prices for more than 900,000 unique private companies since June 2013.
• Model Calibration: The asset pricing model is re-calibrated monthly as new transaction information becomes available.
• Factor Model: privateMetrics employs a factor model that leverages actual equity transactions in private companies to estimate valuations.

The privateMetrics database is designed to provide a representative and robust view of the risk and performance of the private (unlisted) equities market. It addresses the lack of raw market data in private markets by relying on realized transaction prices and a sophisticated asset pricing model.