4. A quant is instructed to investigate the relationship between the size of a bond issu and its trading volumes (value traded) x. Consider the data for 7 bonds: x 20 30 40 50 60 70 80 y 10 12 30 40 48 60 75 (a) (i) Construct a scatterplot of these data. (ii) What does the scatter plot suggest about the relationship between x and 3

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4. A quant is instructed to investigate the relationship between the size of a bond issue y
and its trading volumes (value traded) r. Consider the data for 7 bonds:
r 20 30 40 50 60
y 10 12 30 40 48 60 75
70 80
(a) (i) Construct a scatterplot of these data.
(ii) What does the scatter plot suggest about the relationship between x and y?
(b) A linear model of the form y = a+ Bx + e is fitted to the data, where the error
terms (e) independently follow a N(0, o²) distribution with the variance o? being
an unknown parameter.
(i) Determine the fitted line of the regression model.
(ii) Predict y when x = 250.
(c) A partially completed ANOVA table for this regression analysis is given below.
Source of
Sums of Degrees of
freedom
Мean
F-value
variation
squares
squares
Regression
3,410
A
D
E
Error
59
В
C
Total
3,469
6
(i) Determine the missing values A, B, C, D and E in the table.
(ii) Determine an estimate of the variance o? based on the above table.
(iii) Perform an F-test to test the null hypothesis that there is no linear relationship
between r and y, based on the above table.
(d) (i) Dertemine the percentage of variation in y explained by r.
Transcribed Image Text:4. A quant is instructed to investigate the relationship between the size of a bond issue y and its trading volumes (value traded) r. Consider the data for 7 bonds: r 20 30 40 50 60 y 10 12 30 40 48 60 75 70 80 (a) (i) Construct a scatterplot of these data. (ii) What does the scatter plot suggest about the relationship between x and y? (b) A linear model of the form y = a+ Bx + e is fitted to the data, where the error terms (e) independently follow a N(0, o²) distribution with the variance o? being an unknown parameter. (i) Determine the fitted line of the regression model. (ii) Predict y when x = 250. (c) A partially completed ANOVA table for this regression analysis is given below. Source of Sums of Degrees of freedom Мean F-value variation squares squares Regression 3,410 A D E Error 59 В C Total 3,469 6 (i) Determine the missing values A, B, C, D and E in the table. (ii) Determine an estimate of the variance o? based on the above table. (iii) Perform an F-test to test the null hypothesis that there is no linear relationship between r and y, based on the above table. (d) (i) Dertemine the percentage of variation in y explained by r.
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