The United States Patent and Trade­mark Office awarded us patent #7,752,090, titled: Sys­tem and Method For Revers­ing Account­ing Dis­tor­tions and Cal­cu­lat­ing A True Value of a Busi­ness.

This patent is for the automa­tion of the process of

1. read­ing and ana­lyz­ing the entire annual report, includ­ing the Notes to the Finan­cial State­ments and the Man­age­ment Dis­cus­sion & Analy­sis and
2. mod­el­ing all of that data in a stan­dard and objec­tive manner.

In my opin­ion, the best, most sophis­ti­cated mod­el­ing is stan­dard and objec­tive because Cash Is a Fact, Earn­ings Are An Opin­ion, as War­ren Buf­fett has often said. There is long-standing con­tro­versy sur­round­ing account­ing prof­itabil­ity met­rics and com­pa­nies’ abil­ity to “man­age” earn­ings; there is no con­tro­versy sur­round­ing the cash eco­nomic prof­itabil­ity of a busi­ness as long as the eco­nomic model takes into account all rel­e­vant infor­ma­tion, which our model does as described in Eco­nomic Ver­sus Account­ing Earn­ings. That is why we read the Finan­cial Footnotes!

This patent is fur­ther evi­dence of the unique sophis­ti­ca­tion of our stock invest­ment research. The depth and breadth of New Con­structs’ research rep­re­sents a Par­a­digm Shift in the qual­ity of equity research. No one gets more data to make more dili­gent invest­ment rat­ings than we do.

This patent is for cre­at­ing a sys­tem to do what every good investor (not Spec­u­la­tor) should do. I was more than a lit­tle sur­prised that no one else had already patented this process. I am cer­tainly not the first to pro­pose that equity investors reverse account­ing dis­tor­tions when ana­lyz­ing stocks. Adam Smith was the first in the 1800’s in Wealth of Nations. How­ever, we are the first to build a sys­tem to reverse account­ing dis­tor­tion– which means we are the first to scale what is a VERY time con­sum­ing and dif­fi­cult task to per­form manually.

Per my bio, my first job on Wall Street (in 1996) was to fig­ure out how to reverse account­ing dis­tor­tion to build more sophis­ti­cated earn­ings mod­els for Value-based Analy­sis (VBA), aka Eco­nomic Value Added (“EVA”) analy­sis, for the thou­sands of com­pa­nies cov­ered by Credit Suisse. Like my prior job with Arthur Ander­son in Hous­ton, my Wall Street job required spend­ing enor­mous amounts of time read­ing annual reports and build­ing mod­els. Revers­ing account­ing dis­tor­tion requires ana­lyz­ing the Finan­cial Foot­notes (“the Notes”) in annual reports, 10Ks, 10K/As, 8-Ks, etc. As a for­mer accoun­tant, I can attest that the Notes are where the most impor­tant finan­cial infor­ma­tion on com­pa­nies is often dis­closed. Ana­lyz­ing the Notes requires read­ing hun­dred of pages for often obscure details on items like off-balance sheet debt, hid­den charges, false rev­enues, option lia­bil­i­ties, pen­sion lia­bil­i­ties and asset dis­pos­als. Every com­pany reports dif­fer­ently, which makes ana­lyz­ing the Notes even harder. Ana­lyz­ing the Notes and putting all the data into a model takes a lot of time.  Even after build­ing sev­eral hun­dred mod­els, it still took me at least 1 hour to model a sin­gle annual report. I spent thou­sands of hours read­ing annual reports because my job depended on my exper­tise of finan­cial report­ing for the 3000+ com­pa­nies that Credit Suisse cov­ered glob­ally. Read­ing annual reports for so many dif­fer­ent com­pa­nies around the world taught me a great deal about account­ing and finance in a rel­a­tively short amount of time.

After I left Credit Suisse, I con­tin­ued to apply the rig­or­ous form of analy­sis I had brought to the firm as a more tra­di­tional sell-side ana­lyst. While cov­er­ing only 2 –3 com­pa­nies, I found it increas­ingly dif­fi­cult to do all the work required to under­stand the true prof­itabil­ity and val­u­a­tion of com­pa­nies along with other equity research respon­si­bil­i­ties. I had to get faster at read­ing the annual reports and quar­terly reports and mod­el­ing the data or I would not be able to meet the stan­dards of qual­ity I demanded of my research pub­li­ca­tions. So, I focused on devel­op­ing tech­niques that increased my speed and effi­ciency. After all, I had an enor­mous job and the faster I was the bet­ter I was.

Over time I devel­oped so many tech­niques that I began to think that a computer/machine could per­form many of my tech­niques auto­mat­i­cally, which would increase my speed and effi­ciency. Turns out I was right. As long as my instruc­tions were explicit enough, the machine could per­form them. That is what New Con­structs was orig­i­nally cre­ated to do: develop the tech­nol­ogy to scale my annual-report read­ing and mod­el­ing skills. See our Research Plat­form for more detail.

As stated above and in Eco­nomic Ver­sus Account­ing Earn­ings, the stan­dard eco­nomic model is best because: though account­ing rules may change from com­pany to com­pany or coun­try to coun­try, the basic eco­nom­ics of busi­ness are always the same. The basic eco­nom­ics of a busi­ness are: (1) how much real cash flow does the busi­ness gen­er­ate rel­a­tive to (2) how much cap­i­tal has gone into the busi­ness over its life.

The chal­lenge is that the eco­nomic model works only if it incor­po­rates all avail­able and rel­e­vant finan­cial infor­ma­tion. More­over, the eco­nomic model is infi­nitely more use­ful to investors when it is avail­able for all com­pa­nies, not just a pre­cious few.

Our patented sys­tem and pro­pri­etary tech­nol­ogy enabled us to build a Research Plat­form that, for the first time, allows investors to rely on a com­pre­hen­sive eco­nomic model when mak­ing invest­ment deci­sions. No longer must investors rely on the account­ing data that Cor­po­rate Amer­ica and Wall Street pub­lish. Now, investors have, via New Con­structs, an alter­na­tive source of unbi­ased, com­plete infor­ma­tion on the eco­nomic prof­itabil­ity and val­u­a­tion of companies.

We have devel­oped unpar­al­leled exper­tise in inter­pret­ing account­ing data and apply­ing that to under­stand­ing the eco­nom­ics of busi­nesses. We have unri­valed expe­ri­ence inter­pret­ing account­ing data as we have parsed over 50,000  fil­ings into New Con­structs’ data­base over the past 7 years. Click here for more infor­ma­tion on our Research Plat­form, which shows how we man­i­fest the patent into a sys­tem that enables us to ana­lyze the Notes for 3000+ companies.

NOTE that this patent is assigned to New Con­structs. I am the inven­tor, and I assigned own­er­ship of the patent to New Con­structs in August of 2003. See assig­na­tion let­ter here.

Click here for a copy of the Offi­cial Patent.

To learn more about how well our sys­tem works for investors, see our Stock-Picking Acco­lades.