How to use misvaluation formula

I have to do following estimation for firm's misvaluation. I have gathered the data to Excel (market value of equity, book value of equity, Net Income and leverage ratio) for all the firms. I know that based on the below formulas I would have to do following: Estimate equation 10 for each industry and year separately. Then average the coefficients from these regressions over time and plug them into equation 11, but I don't know how I should do these in R.

In below picture is the formulas, and the table 2 is the output I would like to achieve.
I would be very grateful for any help, thank you.

A recent paper walks through what appears to be a similar analysis although possibly with a different methodology. Its plots and tables appear to have been produced in R; however the authors do not provide their code.

In principle, Equation 10 can be implemented in R; doing so is not trivial, however, and may require a sophisticated understanding of several different statistical tools.

Without a citation to the paper shown, it's not possible to make any more concrete suggestion than to run searches on rseek, an R-tuned Google front-end portal against the author(s)'s names and keywords. Someone may already have implemented the algorithm in R.

Thank you for the answer!

Here's a paper that has used this similar method: https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4156&context=lkcsb_research

And here's the original paper where this method is first implemented: http://people.duke.edu/~viswanat/mergers_jfe_r3_2.pdf

Does these help to make some concrete suggestion to how should I start?

Take a look at this post, which is the only R-related result for a search of rhodes-kropf. Dirk Eddelbuettel, a very well respected expert in R and finance, has a CRAN taskview for finance that will provide many packages with functions that will likely prove useful.

After I read the paper, I'll come back with a suggested approach for developing a workflow for this.

has a very clear roadmap, well summarized in table 5, giving the components of the decomposed market-to-book ratio. The accompanying text gives an step-by-step explanation of all the calculations. There are many discrete components, and putting them all together will require care.

However, replicating and updating the paper's analysis is going to be very labor intensive. It involved 100K firms over 23 years. It used two proprietary services, SDC mergers and acquisitions database and CRS/Compustat and one ofKen French's data sets. This is not my field, but my impression is that this is a dissertation or post-doc project.

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