Extreme Values

Extreme values in any set of data are always interesting. From an investing standpoint the extreme values are especially intriguing. What trades would have been the most profitable? What trades would have been the least profitable? Would it reasonably have been possible to spot these opportunities beforehand? What can be learned for future reference?

The extreme cases presented in this chapter are from 2011. This is done for a couple of reasons. First, it is the last year in the sample and therefore is of particular interest as the most current year in the study. Second, in Chapter 3 you saw that the frequency of gaps has been increasing over the years; in Table 3.1 you saw that with 32,232 gaps, 2011 had more than any other year in the sample. With that many gaps, surely some interesting extreme examples exist.