Library / Investment Tools
Date of review: March 2020
Book author: Heather Brilliant and Elizabeth Collins
Вook published: 2014
Book author: Heather Brilliant and Elizabeth Collins
Вook published: 2014
Why Moats Matter. The Morningstar Approach to Stock Investing by Heather Brilliant and Elizabeth Collins (2014)
The book discusses the crucial elements that are, in my view, necessary for successful investing - namely, factors that allow companies to achieve durable competitive advantages ('Moats' in the language of investment guru Mr Buffett).
Morningstar's valuation methodology
Surprisingly, the book is not widely advertised and does not pop up at the top of most reading lists on investing. I was lucky to get a free copy of this book when I attended a London Value investor conference back in 2017 where Morningstar representatives had a stand.
While Morningstar was founded as a service to rank mutual funds, it later developed a robust framework to identify stocks on the back of Buffett's approach, thanks to the efforts of its former head of research, Pat Dorsey. Pat published his own books on Moats and, more importantly, launched his own investment company (Dorsey Asset Management).
The book has two main parts. In the first section, the authors discuss the concept of Moats, including its five sources, as well as how to incorporate management's qualities and capital allocation into the analysis. The key sources of Moats, according to Morningstar's research team, include 1) Intangible assets (brands, patents, licences); 2) Cost advantages; 3) Switching costs; 4) Network effects; and 5) Efficient scale.
Morningstar's valuation approach is based on discounting future cash flows, but it differs from many simple versions of this method by incorporating the concept of Return on invested capital (ROIC) and Return on New invested capital (RONIC). The authors point out that they expect a normal company to see its RONIC converge with WACC, which is often missed by new analysts trying to evaluate the stock. Moreover, the firm also takes into account the industry cycle by trying to understand at what stage of the cycle does its cash flow forecast end. What I particularly like about such an investment approach is that it also assigns the level of uncertainty (conviction level) for its valuation work. For example, using the most reasonable set of assumptions leads one to estimate that an oil company's fair value is around $50. However, realistically each assumption (on oil price, geology, regulation, execution) can vary dramatically, which would lead to very different valuation outcomes. Hence, even if the math is correct, the certainty about the inputs is so low that we can hardly rely on this valuation estimate.
What I also like about the book is that in addition to a clear methodology, the authors provide a long list of companies from practically all sectors as examples of businesses with strong and average Moats. Importantly, certain sectors have naturally fewer conditions to establish and maintain long-term competitive advantages (e.g. commodity sectors) which may explain why certain investors tend to focus on consumer goods or media, for example.
While Morningstar was founded as a service to rank mutual funds, it later developed a robust framework to identify stocks on the back of Buffett's approach, thanks to the efforts of its former head of research, Pat Dorsey. Pat published his own books on Moats and, more importantly, launched his own investment company (Dorsey Asset Management).
The book has two main parts. In the first section, the authors discuss the concept of Moats, including its five sources, as well as how to incorporate management's qualities and capital allocation into the analysis. The key sources of Moats, according to Morningstar's research team, include 1) Intangible assets (brands, patents, licences); 2) Cost advantages; 3) Switching costs; 4) Network effects; and 5) Efficient scale.
Morningstar's valuation approach is based on discounting future cash flows, but it differs from many simple versions of this method by incorporating the concept of Return on invested capital (ROIC) and Return on New invested capital (RONIC). The authors point out that they expect a normal company to see its RONIC converge with WACC, which is often missed by new analysts trying to evaluate the stock. Moreover, the firm also takes into account the industry cycle by trying to understand at what stage of the cycle does its cash flow forecast end. What I particularly like about such an investment approach is that it also assigns the level of uncertainty (conviction level) for its valuation work. For example, using the most reasonable set of assumptions leads one to estimate that an oil company's fair value is around $50. However, realistically each assumption (on oil price, geology, regulation, execution) can vary dramatically, which would lead to very different valuation outcomes. Hence, even if the math is correct, the certainty about the inputs is so low that we can hardly rely on this valuation estimate.
What I also like about the book is that in addition to a clear methodology, the authors provide a long list of companies from practically all sectors as examples of businesses with strong and average Moats. Importantly, certain sectors have naturally fewer conditions to establish and maintain long-term competitive advantages (e.g. commodity sectors) which may explain why certain investors tend to focus on consumer goods or media, for example.