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Skewness, Price Extensions, and Trade Entries

Skewness, Price Extensions, and Trade Entries        Click the file link to Download.

When looking at price action, there are several different ways to interpret the data. One of the most popular is to look at moving averages. Moving averages have definite drawbacks, such as lag and determination, but make up for these with ease of use. Using the concept of skewness, a trader can better determine entry points by understanding how the current bar relates to the overall trend.

Skewness is a simple concept used to understand the distribution of a range of data. For instance, if the closing data is normally distributed, you will have a relatively equal range of closing prices above the mean as you do below the mean. Skewed data would mean that the balance is off, or there is more data above or below the mean. The following charts show examples of all three kinds of distribution.

This explanation may be simplistic, and entire books have been written about the subject, but for our purposes, simply remember that in skewed data, more data points lie below or above the mean, and that price action is not normally evenly distributed.

Another concern is that we are generally working with numbers that are relatively small. Considering the fact that most currency pairs are quoted out to four, sometimes five, decimal places, when we finally get around to charting the skewness, it will appear that much of the time that price action is evenly distributed.

I used the following definition of skewness to calculate this indicator: n is the number of bars in the study, xbar is the average of the n bars, and s is the standard deviation.

I used the following code to calculate the above function.

Local sd = STDEV( Close , 10 )
Local avg = SMA[0](Close, 10)
Local sum = Close[0]
Local sum = SMA[0](Close, 10)
Local ptskw = ((sum-avg)/sd*sd*sd))
Local num = 10
Local skw = (1/(num - 1))* (ptskw*ptskw*ptskw)
//Indicator Skewness
Indicator Skewness
Skewness.Thickness= 1
Skewness.Value= skw

There are a few things that need to be said about the above code: first, the local variable designation was chosen so that the value of the indicator was not passed. Second, the majority of the mathematical lifting was done by the variables because IntelliScript does not have the ability to use exponents. Without doing it this way, the script's function would be very long, and making changes would be more difficult.

What does all this show us about price action though? Keep in mind that this skewness test only describes the current bar compared against the average of the others, so it should keep us from entering a trade when it is highly extended, allowing us to find entries at better levels.

Here is an example of what the skewness test offers.

Enlarge Chart

As the trader begins to look for trade entries, entering the trade when price action is more balanced keeps the trader from enduring immediate draw downs on the way to possible profits. The more balanced entry level is where the indicator is closer to zero.

There are also setups where entering in the opposite direction of the out of balance setup would also be beneficial. The key idea is that when price is away from the zero line, price is extended and out of balance. Keep this in mind, do lots of testing, and never trade without really understanding the indicator.

Good luck, and send us any questions you may have.