Although the universe of trading strategies is as wide and varied as the number of traders, orthodox technical analysis can be summarized simply as the forecasting of markets through the study and analysis of data generated exclusively from the buying and selling of financial instruments. The most obvious piece of data under this definition is price. Yet, there are many other types of data besides price that are also generated exclusively from the buying and selling process and that are no less important to the astute technician.

Besides price, some other examples of such data include volume, open interest, realized and implied option volatility, the relative performance between markets and asset classes, large trader position data, seasonal patterns and quantitative measures of price strength, intensity and momentum.

A brief bit of technical analysis history is useful for context. Technical analysis is perhaps the oldest form of financial market analysis, with origins spanning back at least to the mid-1700s. One of the most popular modern texts on the subject is Technical Analysis of Stock Trends, first published in 1948 and written by Robert Edwards and John Magee.

Edwards' and Magee's work, which is often referred to as "classical charting", was inspired by even earlier writings on the subject of charting, namely Stock Market Theory and Practice, published in 1930 and written by Richard Schabacker.

Going back to the late 1800s, before the advent of "open-high-low-close" bar charts, traders and analysts used point-and-figure charts to forecast the price direction of stocks and commodities. Classical charting has survived the test of time and continues to hold a prominent place in the arsenal of even the most seasoned traders.

Today, of course, traders have access to the speed and convenience of advanced, feature-rich software platforms to help them organize and study technical data. Perhaps the most valuable feature of such platforms is the availability of accurate market data. It is essential, for example, for technicians to work with reliable price data, reflective of the precise prices transmitted by the exchanges.

Let's take a look at some charts and see how the application of Wilder's Average Directional Index (ADX) can help improve the timing of classical chart pattern breakouts and breakdowns.

It is helpful to understand that classical chart patterns are not just a means of forecasting price direction. Classical chart patterns are more properly viewed as a method for identifying and cordoning off specific market conditions that precede price trends. The interpretation of classical chart patterns can be enhanced, however, by using the ADX indicator in an unconventional manner.

ADX was originally designed to evaluate trend strength. For example, rising or falling prices, accompanied by rising ADX values, are normally viewed as supportive of further directional price movement. However, for the classical chartist interested in getting an early lead on a price breakout or breakdown, we can flip this traditional ADX approach on its head.

Instead of looking for rising ADX values to confirm a price trend already underway, chartists can look for low and declining ADX values in tandem with developing chart patterns as a means of identifying markets that are ready to move outside the bounds of their respective chart pattern.

Some chart examples (using eSignal's FutureSource Workstation) follow.

Note the low and declining ADX values just prior to chart pattern breakouts (and breakdowns from topping patterns). This is a technique that combines the time-honored tradition of classical charting and modern technical indicators with reliable price data (as previously mentioned). It can be applied to all freely traded exchange markets and is just as valid on intraday and weekly time frames as it is on daily charts.

*Reprinted (and modified) with permission from Daniel Chesler