Bartels (1982) illustrated the RVN test for randomness using data on annual changes in stock levels...

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Bartels (1982) illustrated the RVN test for randomness using data on annual changes in stock levels of corporate trading enterprises in Australia for 1968-1969 to 1977-1978. The values (in $A million) deflated by the Australian GDP are 528, 348, 264, -20, -167, 575, 410, -4, 430, -122. He tested randomness against the alternative of autocorrela- tion. Random stock-level changes occur when companies are well man- aged because future demands are accurately anticipated. "Negative autocorrelation constitutes evidence for a tendency to overreact to short- falls or excesses in stock levels, whereas positive autocorrelation suggests there is a long delay in reaching desired stock levels." The test statistic is NM = 169, which is not significant. Compare this result with that of (a) runs up and down, and (b) runs above and below the sample median. Bartels (1982) illustrated the RVN test for randomness using data on annual changes in stock levels of corporate trading enterprises in Australia for 1968-1969 to 1977-1978. The values (in $A million) deflated by the Australian GDP are 528, 348, 264, -20, -167, 575, 410, -4, 430, -122. He tested randomness against the alternative of autocorrela- tion. Random stock-level changes occur when companies are well man- aged because future demands are accurately anticipated. "Negative autocorrelation constitutes evidence for a tendency to overreact to short- falls or excesses in stock levels, whereas positive autocorrelation suggests there is a long delay in reaching desired stock levels." The test statistic is NM = 169, which is not significant. Compare this result with that of (a) runs up and down, and (b) runs above and below the sample median.

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The RVN Runs Versus Normality test is a test of randomness that examines the runs of positive and negative values in a data set In Bartels study he us... View the full answer