Bankruptcy Prediction Modeling
EyePredictor.com uses Bayes' theorem to conduct bankruptcy prediction modeling. One can find a good discussion of this concept at Wikiperia, The Free Encyclopedia:
http://en.wikipedia.org/wiki/Bayes%27_theorem. In addition, Bayes' original essay, An Essay towards solving a Problem in the Doctrine of Chances. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M. A. and F. R. S. This is found in the above reference. Basically, Bayes' theorem is a pure probability that is different from frequentist methodology in that Bayes' theorem uses unobservable prior and observable current knowledge to determine posterior knowledge based on the prior knowledge. In essence, it uses the prior knowledge to revise current knowledge or likelihoods to determine the revised probabilities.
A major advantage of Bayes' theorem is its ability to use the full spectrum of observable and unobservable event probabilities to accurately map the posterior probabilities. An example is drawn from the above Wikipedia website.
Suppose there is a co-ed school having 60% boys and 40% girls as students. The girl students wear trousers or skirts in equal numbers; the boys all wear trousers. An observer sees a (random) student from a distance; all they can see is that this student is wearing trousers. What is the probability this student is a girl?
It is clear that the probability is less than 40%, but by how much? Is it half that, since only half the girls are wearing trousers? The correct answer can be computed using Bayes' theorem.
The event A is that the student observed is a girl, and the event B is that the student observed is wearing trousers. To compute P(A|B), we first need to know:
Given all this information, the probability of the observer having spotted a girl given that he got is wearing trousers can be computed by substituting these values in the formula:
P(A|B) = P(B|A)P(A) / P(B) = 0.5*0.4/0.8 = 0.25.
As expected, it is less than 40%, but more than half that.
Instead of finding the probability that it is a girl, EyePredictor.com finds the probability of a firm entering into Chapter 11 bankruptcy.
http://en.wikipedia.org/wiki/Bayes%27_theorem. In addition, Bayes' original essay, An Essay towards solving a Problem in the Doctrine of Chances. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M. A. and F. R. S. This is found in the above reference. Basically, Bayes' theorem is a pure probability that is different from frequentist methodology in that Bayes' theorem uses unobservable prior and observable current knowledge to determine posterior knowledge based on the prior knowledge. In essence, it uses the prior knowledge to revise current knowledge or likelihoods to determine the revised probabilities.
A major advantage of Bayes' theorem is its ability to use the full spectrum of observable and unobservable event probabilities to accurately map the posterior probabilities. An example is drawn from the above Wikipedia website.
Suppose there is a co-ed school having 60% boys and 40% girls as students. The girl students wear trousers or skirts in equal numbers; the boys all wear trousers. An observer sees a (random) student from a distance; all they can see is that this student is wearing trousers. What is the probability this student is a girl?
It is clear that the probability is less than 40%, but by how much? Is it half that, since only half the girls are wearing trousers? The correct answer can be computed using Bayes' theorem.
The event A is that the student observed is a girl, and the event B is that the student observed is wearing trousers. To compute P(A|B), we first need to know:
- P(A), or the probability that the student is a girl regardless of any other information. Since the observers sees a random student, meaning that all students have the same probability of being observed, and the fraction of girls among the students is 40%, this probability equals 0.4.
- P(A'), or the probability that the student is a boy regardless of any other information (A' is the complementary event to A). This is 60%, or 0.6.
- P(B|A), or the probability of the student wearing trousers given that the student is a girl. As they are as likely to wear skirts as trousers, this is 0.5.
- P(B|A'), or the probability of the student wearing trousers given that the student is a boy. This is given as 1.
- P(B), or the probability of a (randomly selected) student wearing trousers regardless of any other information. Since P(B) = P(B|A)P(A) + P(B|A')P(A'), this is 0.5x0.4 + 1x0.6 = 0.8.
Given all this information, the probability of the observer having spotted a girl given that he got is wearing trousers can be computed by substituting these values in the formula:
P(A|B) = P(B|A)P(A) / P(B) = 0.5*0.4/0.8 = 0.25.
As expected, it is less than 40%, but more than half that.
Instead of finding the probability that it is a girl, EyePredictor.com finds the probability of a firm entering into Chapter 11 bankruptcy.
Recent Bankruptcy Filings
Bankrupcy Data
EyePredictor.com has two types of bankruptcy data for resell: PACER F-5 and PACER Chapter 11 Bankruptcy Data. We obtain both of these data from the Administrative Office of the U.S. Courts PACER Service center. The PACER F-5 data reports the number of personal and corporate Chapter 7, 9, 11, 12, and 13 bankruptcy filings on a quarterly basis for all United States counties. The PACER Chapter 11 Bankruptcy Data drills down the PACER F-5 data and reports Chapter 11 bankruptcy case data to include company name, aliases, employee identification number; bankruptcy circuit, district, state, county, and office: This is the divisional office for the Chapter 11 case, filing address and ZIP Code, debtors first, middle, and last name, county court code, case numbers, bankruptcy type; type of firm, public or private, date filed, closed, converted, dismissed, entered, and closed; PACER identification number, previous bankruptcies, disposition code, bankruptcy trustee, judge, county, and office; fees paid, assets, and disposition of the case. Contact EyePredictor.com for a cost estimate. Generally, our cost consists of the PACER retrieval cost plus a cost per case. Contact EyePredictor.com for an estimate.
