The Average Directional Index or ADX was originally developed by J. Welles Wilder who wrote about it in his book: “New Concepts in Technical Trading Systems.” This popular technical indicator helps traders determine if a trend exists and if so, how strong it is and in what direction it is heading.
The ADX indicator is most commonly run over a 14 period time frame and consists of the following three lines used in combination:
Trading signals are generated using the ADX based on crossovers among the +DI and –DI lines and their direction. The ADX is a lagging indicator relative to the price and ranges between 0 and 100. ADX levels under 20 tend to indicate a weak trend, while levels over 40 indicate a strong trend.
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Traders often observe several things about the Average Directional Movement indicator when using it in practice. First, they will see whether +DI or –DI is on top. An uptrend is indicated by +DI being in the superior position, while a downtrend is indicated by –DI being plotted higher.
Then, traders using the ADX will observe the magnitude of any separation between –DI and +DI. The size of their deviation will indicate the strength of the trend in progress, if any.
When using the ADX to generate trading signals, perhaps the simplest method involves looking for crossover points between +DI and –DI. For example, if –DI crosses upwards above –DI, then a sell signal would be generated as the market turns downward. Alternatively, if +DI crosses above –DI, then a buy signal would be indicated as an up trend starts to take over.
Some traders add greater complexity to these simple signals by increasing the divergence criteria for a trend to exist and a position to be established. Wilder, on the other hand, suggested using “points of extremeum” that were the high for an uptrend crossover day and the low for a crossover day indicating a downtrend. Once the market price exceeded those points, the signal to trade in the direction of the indicated trend would be triggered.
The calculation method illustrated below can be varied by using different time periods or by substituting several alternative types of moving averages that might include: simple, weighted and adaptive moving averages, for the exponential moving averages.
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