Linear Regression Analysis of BAE System Data

Quantitative Methods for Accountants
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Question 4
The BAE system data were obtained from the website: https://uk.investing.com/equities/bae-
systems-historical-data, for which they were available as from 01-04-2004 to-date. On the
monthly 3-month treasury bill rates, I used the end of the End month level of the discount
rate, 3-month Treasury bills, Sterling. The following variables were computed as per the
instructions. That is; Market returns → Rmt = ln(ABS(Pmt/ Pmt-1))*100, an absolute was used
since the logarithmic could not be found for the negative values. BAE system returns → Rt =
ln(ABS(Pt/ Pt-1))*100. The 3-month treasury bills were also converted from the annual rate of
return to monthly using the function RMrf = RArf/12.
A linear regression model was fitted to the data, to obtain a linear model of the form,
Rt =α + β (Rmt −Rft )
The results of the analysis are as follows.
Table 1: Model summary
Regression Analysis
r² 0.470 n 157
r -0.686 k 1
Std. Error 71.147 Dep. Var. Rt
Table 2: ANOVA summary of the regression model
ANOVA
table
Source SS df MS F p-value
Regression 696,735.9831 1
696,735.983
1 137.64 3.77E-23
Residual 784,604.1302 155 5,061.9621
Total
1,481,340.113
3 156
Table 3: Regression coefficient summary
Regression output confidence interval
Variables coefficients std. error t (df=155) p-value
95%
lower
95%
upper
Intercept 366.8531 11.0691 33.142 3.04E-72 344.9873 388.7189
Rmt-Rft -0.5076 0.0433 -11.732 3.77E-23 -0.5931 -0.4222
The fitted linear regression model is Rt = 366.8531 – 0.5076(Rmt-Rft).