Value investors say they look for firms with a “moat” around them. Stated in other words, these are firms with durable competitive advantage which other firms have difficulty in challenging.
S&P Global has developed a Moat Index:
This index quantifies the moat abstraction by rating firms on three measures:
- Sustained ROIC (similar to RNOA): The average over the past five years
- Sustained gross margins: Gross margin/Revenue and its standard deviation over the past five years
- High market share: Weighted-average revenue in industry, calculated with Syntax’s Market Share Score
Your authors have not validated the effectiveness of the score but S&P report slightly higher returns to identified moat firms over the S&P 500.
See the S&P Moat Index fact sheet at file:///C:/Users/shp38/Downloads/fs-sp-500-economic-moat-index-usd.pdf
Another attempt to measure the moat is in Mauboussin, M. and D. Callahan, 2013. Measuring the Moat at http://csinvesting.org/2013/07/24/measuring-the-moat/
Data analytics and information aggregators are firms often hailed as castles with moats around them. S&P Global (or its parent company, Moody’s Corporation) is one, as are FactSet Research Systems, MSCI, Equifax, TransUnion, and Fair Isaac. There firms have proprietary data, proprietary methods of analyzing data, and supply benchmark metrics that many employ. They have sustainable revenue with subscriptions and high margins.
These firms trade at high valuations. Fair Isaac, the provider of the FICO score, traded at a forward P/E of 78 at the end of 2024, for example. That might be because of potential growth. But the value investor is cautious: Those multiples could be overpricing. Is the expected growth justified? Is it at risk? Should the P/E be discounted for that risk? Is the advent of AI to elicit and analyze information a breach of the moat?