334 The Basics of financial economeTrics
FiGuRe A.1 Scatter Plot: Extreme 1—No Relationship of Component Variables x and y
xywhether the variation of one component variable somehow affects the vari-
ation of the other. If, for example, the points in the scatter plot are dispersed
all over in no discernible pattern, the variability of each component may be
unaffected by the other. This is visualized in Figure A.1.
The other extreme is given if there is a functional relationship between
the two variables. Here, two cases are depicted. In Figure A.2, the relation-
ship is linear whereas in Figure A.3, the relationship is of some higher order.^6
When two (or more) variables are observed at a certain point in time, one
speaks of cross-sectional analysis. In contrast, analyzing one and the same
variable at different points in time, one refers to it as time series analysis. We
will come back to the analysis of various aspects of joint behavior in more
detail later.
Figure A.4 shows bivariate monthly return data of the S&P 500 stock
index and the GE stock for the period January 1996 to December 2003 (96
observation pairs). We plot the pairs of returns such that the GE returns
are the horizontal components while the index returns are the vertical com-
ponents. By observing the plot, we can roughly assess, at first, that there
(^6) As a matter of fact, in Figure A.2, we have y = 0.3 + 1.2x. In Figure A.3, we have
y = 0.2 + x3.