By Bagdonavicius V.

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All the points lie exactly on a straight line. 5 Fig. 2 XY-plot of two perfectly correlated variables (r = 1). 5 –2 Fig. 51). 51), but not perfectly correlated. Note that the XY-plot still exhibits an upward sloping pattern, but that the points are much more widely scattered. 4 is an XY-plot of two completely uncorrelated variables (r = 0). Note that the points seem to be randomly scattered over the entire plot. Plots for negative correlation exhibit downward sloping patterns, but otherwise the same sorts of patterns noted above hold for them.

However, this strategy is usually inappropriate since it implicitly weights all companies equally to one another. Let us suppose, as their names indicate, that Megaco and Monstroco are huge companies with a large amount of stock outstanding, traded on many stock exchanges. In contrast, we suppose Minico to be a tiny company with only a small amount of stock outstanding, traded only rarely on a local stock exchange. A simple average just would add up the stock prices of these three companies and divide by three.

E. 12 Sometimes, such indices are referred to as “value-weighted”. For empirical work, it is usually acceptable to understand this 29 Basic data handling intuition and a knowledge of the precise calculations performed in calculating a valueweighted stock price index is not necessary. 1 describes these calculations in the context of our simple example. A value-weighted stock price index can be written in terms of a mathematical formula. Let P denote the price of a stock, Q denote the market capitalization and subscripts denote the company and year with Megaco being company 1, Monstroco company 2 and Minico company 3.

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Analysis of survival data with cross-effects of survival functions by Bagdonavicius V.


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