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At a Glance: Quant IP Patent and Innovation Metrics

This dataset combines smart algorithms, artificial intelligence, and Quant IP's deep experience in patent law and patent state to evaluate the quality of creativity for thousands of companies worldwide.

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Quant IP brings together experts from various fields to extract unique value from information contained within over 120 million patent documents. Deep experience in patent law and patent state is combined with smart algorithms and artificial intelligence (AI)-powered software to produce a comprehensive dataset. The Quant IP Patent and Innovation Metrics dataset enables users to evaluate the quality of creativity for thousands of companies worldwide, revealing their true innovation power in one simple indicator: The Quant IP Innovation Score.

This aggregated indicator, which measures the consistency, quality, and efficiency of a company's innovation process, makes it possible to rank listed companies according to their origination power and to construct portfolios to outperform regular equity indices.

Quant IP offers three packages of datasets with different universes. The first data package covers approximately 5,000 active large cap-listed organizations from developed markets. The second data package uses a standardized company name and covers small cap and non-listed entities, aggregating to over 850,000 global companies. A third data package is available as a combination of the first and second. All data is point-in-time and suitable for rigorous backtesting with history commencing from 1995.

Data Overview

Asset Class: Public and Private Companies

Data Frequency: Monthly

Delivery Frequency: Daily

History: Data available back to 1995

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Data Methodology

There are three main raw data inputs for the Quant IP innovation score: Fundamental Data, Patent Data, and Corporate Trees. Patent Data is sourced from IFI Claims while Fundamental Data and Corporate Trees are collected from Bloomberg.

IFI Claims is a high-quality aggregator of raw patent data from more than 40 offices around the world. This comprehensive network allows for frequent updates and language translations, which further enhance the overall quality of Quant IP’s datasets.

All processing of data is rule based without human judgement, and Quant IP applies sanity and quality checks at various points during the data processing lifecycle. 

The Quant IP dataset includes several patent indicators that are calculated on a monthly or quarterly basis. The factors are constructed with information that is available prior to the indicator calculation data. The literature adds an additional investment lag of six months to avoid backtesting bias and rebalancing frequencies of three to 12 months are common.

A summary of the indicators is listed below:




Invention Count

Number of inventions over a rolling 12-month period

Quantitative measure for innovation process output (e.g., Count/R&D Expenses)

Grant Count

Number of grants over a rolling 12-month period

Based on document publication dates (i.e., typically three to five years after publication)

Tech Footprint

Distribution of inventions by technical classifications

Used to identify shifts in activity over time


Measuring the age of citations

The younger the age, the higher probability of future growth 


How many different fields have been used in prior art

The more variation in origin, the higher probability of significant field gains

Market Coverage

GDP-weighted exposure of jurisdictions covered

The more important markets, the better

Tech Share

Share of inventions within a tech field held by entity

The higher the share, the more competitive the entity

Quant IP Quality Score

Machine-learning trained score using quality indicators and legal robustness

The higher the score, the better

Quant IP Innovation Score

Industry-relative benchmark score for equities based on six innovation metrics

The higher the score, the better

Use Cases


  • The quality indicators make it possible to benchmark the patent portfolios of thousands of companies. Point-in-time data makes it possible to benchmark over time and detect significant changes.

Stock Picking

  • Patent and innovation metrics are suited well for stock selection. Point-in-time data starting in 1995 makes it possible to backtest strategies based on filing activity, patent grants, quality indicators or the Quant IP Innovation Score. Several backtests show significant risk adjusted outperformance for strategies for many industries and markets.

Deal Sourcing

  • Private Equity & Venture Capital institutions use Quant IP’s extensive private company coverage to create focused target lists using a proprietary classification system. This aids in the identification of those entities that lead their peer group through quality innovation and therefore act as a leading investment candidate.

The details provided above are as of August 2020.

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