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The Distribution of
Stock Prices
Much of the work that has been done in statistics and related areas regarding the
stock market has made the assumption that stock prices are distributed normally, or
more specifically, lognonnally. In actual practice, this is usually an incorrect assump­
tion. For the option strategist, this means that some of the things one might believe
about certain option strategies having an advantage over certain other option strate­
gies might be incorrect. In this chapter, a number of facts concerning stock price dis­
tribution will be brought to light, including how it might affect the option strategist.
MISCONCEPTIONS ABOUT VOLATILITY
Statistics are used to estimate stock price movement (and futures and indices as well)
in many areas of financial analysis. Many authors have written extensively about the
use of probabilities to aid in choosing viable option strategies. Stock mutual fund
managers often use volatility estimates to help them determine how risky their port­
folios are. The uses are myriad. Unfortunately, almost all of these applications are
wrong! Perhaps wrong is too strong a word, but almost all estimates of stock price
movement are overly conservative. This can be very dangerous if one is using such
estimates for the purposes of, say, writing naked options or engaging in some other
such strategy in which volatile stock price movement is undesirable.
As a review for those not familiar with mathematical distributions, the lognor­
mal distribution is what's commonly used to describe stock prices because its shape
is intuitively similar to the way stocks behave - they can't go below zero, they can rise
to infinity, and most of the time they don't go much of anywhere. On top of that, the
distribution's shape is based on the historical volatility of the underlying instrument.
In a lognormal distribution (and normal distribution, too), stocks remain within 3
standard deviations of their current price 99. 7 4% of the time. A standard deviation
783