1Sample and description statistics
You should end up with more than 4,000 bonds; thus, you will need to download the data to Excel in batches (e.g., first, download small bond issues, then medium, and lastly with large bond issues). From the remaining issues, drop the convertible bonds.
Discuss briefly your sample, including the number of observations, outliers. Provide the descriptive statistics of the sample. How you choose to do this is entirely at your discretion. However, it is recommended that you consider using both summary statistic and graphical methods (this task should include at least one properly formatted table, one pie chart, one histogram, and one scatter plot) while also noting any peculiarities within the data set. You should put more emphasis on variables that are the dependent variables in the regressions estimated in other tasks.
Which bonds are more likely to include “a call” feature?
A bond issuer can repurchase its bonds before their maturity if they include a call feature. Firstly, identify statistically significant characteristics of callable bonds.
You may consider, issue size, maturity, industry, credit rating, and other variables available in Eikon. Secondly, compute the average of the individual marginal effects of the amount outstanding on the probability that a bond includes a call feature.
Thirdly, estimate the probability that a bond with the following characteristics includes a call feature:
· maturity: 10 years
· coupon: 2.5%
· amount: $750,000,000
· currency: US dollars
· seniority: senior unsecured
· Moody^s (Issue) credit rating: Aa2
· sector: Electronics
· domicile: USA
· convertible: no
· market of issue: global
· puttable: no.
Do the results suggest that this bond is callable or not?
In this task, you are expected to use a logit regression analysis. To ensure that the results are robust, estimate at least two regression models (e.g., in the first regression model, one includes amount in $ and in the second model, one uses the natural logarithm of amount in $).
Which bonds are more likely to be issued in the domestic and foreign markets?
^Market of Issue55 can take the following values:
· Domestic: a bond is issued in the US
#
• Global: a bond is issued in the US and foreign markets
· Eurobond: a bond denominated in USD is issued in the foreign market.
You need to estimate the probabilities that a bond with the following characteristics is issued in each market:
· maturity: 10 years
· coupon: 2.5%
· amount: $750,000,000
· currency: US dollars
· seniority: senior unsecured
· Moody^s (Issue) credit rating: Aa2
· sector: Electronics
· domicile: USA
· convertible: no
· callable: yes
· puttable: no.
In the analysis, estimate multinomial logit regression model and briefly discuss the determinants of ^Market of Issue/5 According to the analysis, what is the most likely market of issue of this bond?
Estimating yield for a hypothetical bond
Lastly, you need to estimate the yield for a bond with the following characteristics:
· maturity: 10 years
· coupon: 2.5%
· amount: $750,000,000
· currency: US dollars
· seniority: senior unsecured
· Moody^s (Issue) credit rating: Aa2
· sector: Electronics
· domicile: USA
· convertible: no
· callable: yes
· puttable: no
· market of issue: global.
To ensure that the results are robust, estimate at least 3 regression models (e.g., in the first regression model, one includes amount in $, in the second model, one uses the natural logarithm of amount in $, and the third model features something else). Briefly discuss the determinants of yield.
Using one of the regression models, compute two additional yields:
1. the amount is $1,000,000,000, other bond characteristics the same as above
2. Moody^s (Issue) credit rating is A2, other bond characteristics the same as above (i.e., amount: $750,000,000 etc.).
Are the results the same as the main estimate? Why?
#