Add training workflow, datasets, and runbook
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Chapter 38: The Distribution of Stock Prices 187
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Lest you think that this example was biased by the fact that it was taken during
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a strong run in the NASDAQ market, here's another example, conducted with a dif
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ferent set of data- using stock prices between June 1 and July 18, 1999 (also 30 trad
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ing days in length). At that time, there were fewer large moves; about 250 stocks out
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of 2,500 or so had moves of more than three standard deviations. However, that's still
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one out of ten - way more than you've been led to expect if you believe in the nor
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mal distribution. The results are shown in Table 38-3.
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TABLE 38-3.
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More stock price movements.
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Total Stocks: 2,447 Dates: 6/1 /99-7 /18/99
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Upside Moves:
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Downside Moves:
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3cr
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104
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54
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4cr
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28
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19
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Scr
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13
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7
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>6cr
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12
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14
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Total number of stocks moving >=3cr: 251 ( 10% of the stocks studied)
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Total
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157
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94
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Finally, one more example was conducted, using the least volatile period that
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we had in our database - July of 1993. Those results are in Table 38-4.
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TABLE 38-4.
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Stock price movements during a nonvolatile period.
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Total Stocks: 588 Dates: 7 /1 /93-8/17 /93
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3cr 4cr Scr >6cr Total
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Upside Moves: 14 5 1 1 21
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Downside Moves: 28 5 3 4 40
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Total number of stocks moving >=3cr: 61 ( 10% of the stocks studied)
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At first glance, it appears that the number of large stock moves diminished dra
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matically during this less volatile period in the market - until you realize that it still
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represents 10% of the stocks in the study. There were just a lot fewer stocks with list
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ed options in 1993 than there were in 1999, so the database is smaller (it tracks only
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stocks with listed options). Once again, this means that there is a far greater chance
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for large standard deviations moves - about one in ten - than the nearly zero percent
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chance that the lognormal distribution would indicate.
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VOLATILITY BUYER'S RULE!
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The point of the previous discussion is that stocks move a lot farther than you might
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expect. Moreover, when they make these moves, it tends to be with rapidity, gener-
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