In your first Bloomberg task you will have to use Altmans Z score to determine if companies Boeing is going to fail in the near future.
For more information, see: http://en.wikipedia.org/wiki/Altman_Z-score.
The following is the formula for most public companies (there are small differences for financial companies, private companies as so on)
X1 = Working Capital / Total Assets X2 = Retained Earnings / Total Assets X3 = EBIT / Total Assets X4 = Market Value of Equity /Book Value of Total Liabilities
X5 = Sales/ Total Assets
A Z score higher than 2.99 is considered a safe score; between 1.8 and 2.99 it is a grey area; below 1.8 is the danger area.
Each of you were assigned a blue chip company. You will need to find a company that is in more danger than blue chips. Bloomberg uses a system of rankings and computes the probability of default. It is under the function DRSK. The following grab shows an example. You will select companies with HY 2 and above. Those companies have higher probabilities of default.
To select such companies I suggest that you search for companies that have bonds rated CCC- to CCC+. To do so you will need to go to CORP and do a search. I suggest the following fields for your search. However, any other way you devise to select companies with a high HY is fine by me.
Once you have the second company you will have to compute the Z scores for the past three years for both companies. You will compare the scores between the blue chip and the danger zone company and determine if the Z score you computed is similar with the one that you can find for both companies in Bloomberg. In addition, you will see if the Z score you computed is correlated with the probability of default that Bloomberg computed in DRSK. As a conclusion you will need to make a prediction if the danger zone company will default in the next two years.
You will present your results in a format that will include your computations, your comments and the necessary Bloomberg grabs that show your work (mainly the DRSK grabs of your two companies and some grabs showing an example on how you extracted the relevant data.)
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