After price, volatility has the greatest impact on trading, so it is worth spending time understanding how to measure it and how to use it when trading. Those methods cover a wide range. Volatility has already been discussed as part of many indicators and as a way to make stop-losses, profit-taking, and even the charting scale variable (see the discussion of point-and-figure in Chapter 5) so that the trading methods adjust automatically to changing market conditions.
Volatility can be used as a trading filter, avoiding high risk or standing aside when the volatility is too low. It is the key measure of risk and will be the dominant ingredient in structuring a portfolio, covered in Chapters 23 and 24. As systematic programs mature, there seems to be a greater, justifiable concentration on how to include and manage volatility. Here, we will look at it in more detail.
In general, the volatility of most price series, whether stocks, financial markets, commodities, or the spread between two series, is directly proportional to the increase and decrease in the price level. Higher prices translate into higher volatility. This price-volatility relationship has been described as lognormal in the stock market, and is similar to a percentage-growth relationship.
Consider Google in Figure 20.1a, a plot of the price since inception, and 1b, a semi-log plot, available on Excel under format axis/axis scale/logarithmic. In a semi-log plot, ...