ACF5320 Business Analytics Corporate Bonds

Order Description Fin" rel="nofollow">inish Task group Submission: You are required to submit BOTH hardcopy and softcopy of your work. Hardcopy (prin" rel="nofollow">inted copy) of your work can be submitted through the Assignment Drop Box on Level 3, Department of Accountin" rel="nofollow">ing, Buildin" rel="nofollow">ing H, Caulfield campus. A redundant, softcopy submission should be made through Moodle. If the (default) hardcopy submission does not exist, then the softcopy submission will be marked. The receipt of the softcopy is absolutely necessary for your assignment to be marked. So, please ensure you submit the correct version of your work – both in" rel="nofollow">in hardcopy and softcopy; and that the hardcopy is not submitted late (passin" rel="nofollow">ing deadlin" rel="nofollow">ine). It is imperative for students to do both submissions (hardcopy and softcopy) to avoid missin" rel="nofollow">ing submission. By havin" rel="nofollow">ing a redundant system, we are preventin" rel="nofollow">ing possible dispute with regards to lost submission. Students who only rely on one mode of submission are takin" rel="nofollow">ing the risk of their assignment bein" rel="nofollow">ing lost in" rel="nofollow">in the system. Fin" rel="nofollow">inally, please ensure that the softcopy of your submission (both Excel file(s) and Word (or PDF) file) is not password protected. For the softcopy submission, zip all your files (in" rel="nofollow">includin" rel="nofollow">ing the excel file and the cover sheet) and submit it via Moodle. You must use Win" rel="nofollow">inZip to compress your files (please do not use any alternative software to compress your files). Attach the signed cover sheet with your hardcopy submission. This signed cover sheet is a declaration that your submission is your own work. Any attempt of plagiarism will be heavily penalized. If deemed necessary, Lecturer/Tutor/Marker may opt ACF5320 Busin" rel="nofollow">iness Analytics, Individual Assignment Prepared by Dr. Kristian Rotaru, September 2016 2 to in" rel="nofollow">interview students on their submissions and this may be reflected on student’s mark. Namin" rel="nofollow">ing File: The zip file should be named X_Y_A2.zip where X is up to 5 characters is your SURNAME. Y is up to 3 characters is your FIRSTNAME. Part B. Problem Description Instruction: This assignment consists of three cases (Case 1: Plannin" rel="nofollow">ing the Sales Territory, Case 2: Audit Delay, and Case 3: Corporate Bonds) and three sets of tasks. It is important that you read and understand the topics and have acquired skills to successfully develop spreadsheet models before carryin" rel="nofollow">ing out the assignment. Please note that these cases are not optional. You need to attempt three cases in" rel="nofollow">in this assignment and all associated questions/tasks. Case 3: Corporate Bonds Problem Statement A sample contain" rel="nofollow">inin" rel="nofollow">ing years to maturity and yield (percent) for 40 corporate bonds is presented in" rel="nofollow">in the data file named Corporate_bonds.xlsx. The data file can be located in" rel="nofollow">in the Assignment 2 folder on Moodle. Task group 3 (6.5 marks) (3.1) Develop a scatter chart of the data usin" rel="nofollow">ing years to maturity as the in" rel="nofollow">independent variable. Does a simple lin" rel="nofollow">inear regression model appear to be appropriate? Explain" rel="nofollow">in your answer. (3.2) Develop an estimated quadratic regression equation with years to maturity and squared values of years to maturity as the in" rel="nofollow">independent variables. How much variation in" rel="nofollow">in the sample values of yield does this regression model explain" rel="nofollow">in? Is the overall regression relationship significant at a 0.05 level of significance? If not, explain" rel="nofollow">in why it is the case. If yes, then test the relationship between each of the in" rel="nofollow">independent variables and the dependent variable at a 0.05 level of significance. How would you in" rel="nofollow">interpret this model? (3.3) Create a plot of the lin" rel="nofollow">inear quadratic regression lin" rel="nofollow">ines overlaid on the scatter chart of years to maturity and yield. Does this help you better understand the difference in" rel="nofollow">in how the quadratic regression model and a simple lin" rel="nofollow">inear regression model fit the sample data? Which model reflected on this chart provides a superior fit to the sample data? Why? (3.4) What other in" rel="nofollow">independent variables could you in" rel="nofollow">include in" rel="nofollow">in your regression model to explain" rel="nofollow">in more variation in" rel="nofollow">in the yield? Explain" rel="nofollow">in your answer.