Objective: This assignment asks you to prepare a financial report for a real U.S. firm using data from Yahoo! Finance and the methods presented in the module. The report has to be of professional standards and easy to read.
Task description: You are employed as a quantitative analyst by a big hedge fund. You have been asked to perform a financial analysis and produce a report. In order to prepare your report you will need to collect data on monthly dividend- adjusted closing prices for the firm assigned to you and for the period from January 1990 to December 2015 (you can check your firm in the “FIRM_STUDENT.xls” file in the Assignment 2 folder on the Bb).
In addition you will have to use monthly data on the following variables: (i) the return on the S&P500 index, (ii) the CPI inflation rate (as a percentage), (iii) the credit spread of US corporate bonds and finally, (iv) the monthly return of crude oil. You can find the latter data in the “Economic_Data.xls” file on the Bb. You should include the following components in your report:
Calculate the mean, the median, the range, the variance and the standard deviation for the monthly returns of your firm and for those of the S&P500.
a) Briefly explain both the statistical and financial meaning of these statistics.
b) Report the monthly covariance as well as the correlation between the returns of the S&P500 and those of your firm. Discuss the kind of relationship between the two series including the appropriate plot. (5 marks)
You are trying to build a model to explain the monthly returns of your firm using the above four economic variables. To this end, you need to regress the returns of your firm’s stock on these four variables using the “Data Analysis Tool” of Excel. Then:
a) Discuss the interpretation of the regression coefficients. (5 marks)
b) Examine the significance of the above regression coefficients both at the 5%
and 10% significance levels (use both the p-value and t-statistic). (10 marks)
c) Report the 90% and 95% confidence intervals for each of the four coefficients and briefly discuss their meaning. (10 marks)
d) Discuss how well the model fits the data using the appropriate statistic and discuss how to test for the significance of this statistic. (5 marks)
(Total: 30 marks)
Suppose you want to build a model to predict the monthly returns of your firm. To do this, you need to perform the following tasks:
a) Estimate a regression to examine if the returns of crude oil for the previous four months can predict the current month returns on your firm’s stock. Plot the actual and predicted values of your firm’s returns on the same graph. Discuss the predictive ability of the model. (10 marks)
b) Now estimate the above regression replacing the past four month returns of crude oil with the past four month returns of your firm. Calculate the mean absolute error of the two models in (a) and (b) and say which of the two has better forecasting performance. (10 marks)
c) Use the regression in (b) to predict the return of January 2016. (5 marks) (Total: 25 marks)
4.Valuation of Bonds
a) Your company has recently decided to issue new bonds. Compute the fair value of your firm’s bond knowing that it pays semi-annual coupons with an annual coupon rate of 6%, it has a par value of $1,000 and a maturity of 15 years (you can assume the current date as the settlement date). The yield to maturity of the bond is 4.5%. Also, using the appropriate graph show how the value of this bond changes as a function of maturity (Hint: consider a range of possible maturities from 1 to 20 years). Based on the above graph, discuss the relationship between the value of a bond and its maturity. (15 marks)
b) Consider the bond of your company as described above. Perform and discuss the following: (i) Compute the percentage of the bond price that comes from the coupon payments, and: (ii) If the bond is callable at $1,150 after the first 6 years of its life compute its yield-to-call. (15 marks)
(Total: 30 marks)
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