BRU Chart, page-999

What you're outlining is the relative quantitative valuation changes over time.

This link helps explain Morningstars dark art of quantitative valuation:

https://www.morningstar.com/content/dam/marketing/shared/research/methodology/678203-QuantitativeEquityAndCreditRatings.pdf

The Philosophy of Morningstar's Quantitative Ratings
Morningstar has been producing differentiated investment research since 1984. Although our roots are
in the world of mutual funds, Morningstar research has expanded to Equity, Corporate Credit, Structured
Credit, ETFs and more. Traditionally, our approach has been to provide analyst-driven, forward-looking,
long-term insights alongside quantitative metrics for further understanding of the investment landscape.
However, we have now developed a new way of combining our quantitative and analyst-driven output
while expanding the coverage of our analysis beyond the capabilities of our analyst staff.
In general, there are two broad approaches that we could have chosen to expand our analyst-driven
rating coverage in a quantitative way: either automate the analyst thought process without regard for
output similarity, or, alternatively, replicate the analyst output as faithfully as possible without regard for
the analyst thought process.
We find that attempting to mechanically automate a thought process introduces needless complexity
without marginal benefit, so we have opted to build a model that replicates the output of an analyst as
faithfully as possible. To this end, our quantitative equity and credit ratings are empirically driven and
based on the proprietary ratings our analysts are already assigning to stocks.
Utilizing the analyst-driven ratings in our quantitative rating system strengthens both systems. The
quality of our quantitative recommendations is intertwined with the quality of our analyst-driven ratings.
Accordingly, improvements to our analyst-driven research will immediately flow through our quantitative
rating system and leaves the analyst-driven research as the internal focal point of our rating
improvement efforts.
But perhaps the most obvious benefit of developing a quantitative set of ratings is the gains to breadth
of coverage. Our quantitative coverage universe is many times the size of our analyst covered universe,
and growing. It is limited only by our access to the necessary input data. Morningstar, and indeed the
investment sector continue to grow their data collection efforts at a rapid pace.
Of course no rating system, quantitative or otherwise, is valuable without empirical evidence of its
predictive ability. Just as we regularly test and diagnose problem areas in our analyst-driven research,
we have rigorously tested the performance of our quantitative ratings. We have peppered some of these
studies throughout this document and will continue to enhance our methodologies over time to improve
performance.

Quantitative Valuation for Stocks
To an investor that thinks about stocks as a claim on the cash flows of a business, the true intrinsic value
of those cash flows is a must-have piece of information for any investment decision. As part of our
continuing effort to provide investors with better estimates of intrinsic values for stocks, we have
developed a quantitative valuation algorithm.
In essence, the quantitative valuation algorithm attempts to divine the characteristics of stocks that
most differentiate the overvalued stocks from the undervalued stocks as originally valued by our team of
human equity analysts. Once these characteristics have been found, and their impact on our analystdriven valuations has been estimated, we can apply our model beyond the universe of analyst-covered
stocks.