Omaha's Equity research team is delighted to share with you its latest publication. In this double paper, we lay out some extensive answers to question “why do we do what we do?”, or equivalently “why do we think normalizing accounting on a large scale should be performed by anyone looking at valuing companies”.
​
The research was carried out thanks to an in-house point-in-time economic framework, that we managed to build after several years of software development and factorization. The software architecture delivers rule-based normalized data that is both free of legacy and with no gimmicks. This extensive decision-tree-based technology not only enabled us to scale our model and enhance its robustness, but also to test our ideas and findings in a reliable way.
​
Part II - A quantitative study
​
-
The statistical edge of Economic data over accounting ones appears clear: economic data are more stable, more robust, and potentially very different.
-
To measure the historical performances of equity investments based on normalized data, we calculated more than 200 different investment back-tests on elementary metrics (eg. valuation, profitability, etc.) with different criteria such as time frames and entry points. The back-tests of the long-only strategies show that our normalized data offer a performance potential higher than standard accounting data by an average of 2% per annum. For the Long/Short approach, it is about 7%.
Although not sufficient, we believe that the accounting normalization is particularly relevant as a basis for any analysis or selection of companies based on fundamental data. This work also prepares the ground for other publications, on other regions, different adjustments, concrete cases, etc.
​
“You have to understand accounting and you have to understand the nuances of accounting. It’s the language of business and it’s an imperfect language, but unless you are willing to put in the effort to learn accounting – how to read and interpret financial statements – you really shouldn’t select stocks yourself”. - Warren Buffett
​