In lay terms, volatility is a measurement that tells us to what extent prices are changing over time. A market moving up or down 15 or 20 points a day is more “volatile” than the same market moving up or down in 3 or 5 point increments. Volatility can also serve as a proxy of underlying market activity.

Using the same three stock examples from earlier, Charts 2A-2C demonstrate how changes in volatility, as measured by the one period range (highest high minus lowest low over the course of one day), correspond positively with changes in volume over the same time period. This phenomenon is not unique to daily stock charts; it can be observed across virtually all markets and time frames. While the relationship between changes in volatility and changes in volume is by no means an absolute one, it is robust enough to help us understand the dynamics behind chart pattern development and the volatility component of the model. For example, if we assume that for every transaction there is both a buyer and a seller, volume can be viewed as a measure of the gross supply and demand at any point in time for a given market.

In the case of our model, volatility has been substituted for volume as a means of gauging these changes in supply and demand. We can thus begin to describe the development of a classical chart pattern in terms of volatility as follows: In the final stages of a price trend, and at the beginning of a so-called “classical” chart pattern, the market is characterized by relatively high volatility and wide price swings. Next, a gradual process of declining volatility begins, leading at last to an area of suspense that marks the “beginning of the end” of the chart pattern’s development.

This final stage immediately prior to a breakout is marked by a relative absence of price volatility versus the earlier stages of the chart pattern’s development. The market has reached a relative standstill and is positioned at the “tripwire” of an imminent breakout. Chart 3 depicts a schematic of the idealized volatility component. Various tools can be used to help us measure changes in volatility that might not otherwise be obvious through visual inspection of the chart pattern alone.

The standard deviations of closing prices, or an average of daily high-low ranges are two approaches. However, I prefer to use Welles Wilder’s Average Directional Index (ADX) which is based on an average of excesses between period-to-period ranges, and is smoother in comparison to raw measures of volatility such as standard deviation. Although ADX is normally thought of as a measure of trend strength, this does not preclude the use of ADX for our purposes. Later I will show how to utilize the ADX indicator (14 period) to gauge the changes in relative volatility that occur during chart pattern development.

THE STRUCTURE COMPONENT

The structure component of the model is not intended as a blueprint that tells us where we are within the structure and hence where we are likely to go next, such as with Elliott wave or seasonal trading patterns. Rather, the structure component represents an idealized form of cyclic behavior unique to classical chart patterns in general.

It is an attempt at making that which is important about classical chart pattern “shapes” interesting – and not vice versa. Specifically, the structure component emphasizes the tendency of chart patterns to exhibit a series of well-defined and periodic time cycles. This can be observed in most chart patterns as a series of distinct turning points marked by prominent highs or lows occurring at regular – or very nearly regular – time intervals.

One possible rational for this phenomenon is that cycle periodicity is susceptible to greater distortion from the effects of trends. Hence, cycle periodicity is noticeably more discernible in non-trending environments as represented by so-called “classical” chart patterns. In contrast, traditional chart pattern definitions focus primarily on the variation in cycle amplitude – or the “height” aspect of market time cycles as measured in dollars or points – as a means of classifying and distinguishing individual chart patterns. Traditional definitions rely on the repeatability of specific chart pattern “shapes” as formed by the combination of various cycle amplitudes.

The model however is based on the assumption that generic conditions, such as declining volatility and distinct periodicity, underlie most chart patterns regardless of their shape or their individual “classical” definition. The structure component also incorporates the tendency of classical chart patterns to exhibit noticeably overlapping cycles or “waves.”

Most chart patterns reveal this tendency by taking on a horizontal orientation along the length of the pattern. This aspect of structure highlights one of the most fundamental differences between price trends and chart patterns: During price trends cycles overlap minimally, and in the case of very strong trends cycles may not overlap at all. Chart 4 depicts the idealized structure component of the model.

By Daniel L. Chesler, CMT, CTA

Next: Screening Examples

Summary: Index