Moving Average Is More Than What You Think – Part 2
We now know that moving average can be measured more effectively when average bar range is used as the yardstick. How do we utilitize this information?
If You Like Channel
If you like using channel, it is obvious that our understanding of the distribution of the emini S&P 45-minute bars, is giving us a perfect case for a new channel style indicator.
I call this indicator Average Range Channel.
In short, the indicator can be described wth the formulas below,
Average Range = Average range of data over 9 period
Middle Line = Average of data over 9 period
Upper Channel = Middle Line + Previous value of the average range * factor
Lower Channel = Middle Line – Previous value of the average range * factor
The actual indicator code is much more readable,
$arange := avgrange (1, data1, param1) * param2;
plot1 := average (data1, param1);
plot2 := plot1 + $arange;
plot3 := plot1 – $arange;
You can download the indicator Average Range Channel here.
The trickiest part of using a channel indicator is picking the correct period for the middle line and selecting a correct parameter to calculate the channel width. In our case, it becomes a very easy task due to the fact that we start from analyzing the behaviour of the 9 period SMA. It is obvious that our channel will use that as the middle line. The factor is also very easy to choose because we already discover that the price distribution relative to the midpoint is very stable based on average range. I will pick 2 as the factor because visually it is clear that it covers most of the data in the various distribution charts in Part 1.
Here is a chart with period = 9, factor = 2
Take a look at the various points on the chart that penetrated the channel and then reversing back to the middle line. The stability is very remarkable, especially when the average range we’ve used is the one calculated from the previous bars, thus the average range value used in the formulas is independent from the current bar’s price range.
A Similar Indicator – Keltner Channel
The average range channel is very similar to the Keltner Channel because both of them are based on the price range.
Keltner Channel is based on exponential moving average and the average true range.
For exponential moving average, a longer seasoning period is needed for the indicator value to stablize. In order words, exponential moving average will give you different results for the same data bar if the length of leading data varies. Its advantage is that it is less choppy due to its smoothing process.
A comparison between average true range and average range is a good topic by itself and is available in a separate article.
In short, when exponential moving average is combined with average true range, you will get a smooth channel easier for visual inspection, but not necessarily having the same statistical significance like the average range channel.
It will be a good exercise for you to plot the Keltner Channel’s price distribution as a comparison. I can give you a hint – there is indeed bias towards the upside, that is, there are more price points sitting above the exponential moving average.
What Should We Do Now
By using the distribution plot technique in Part 1, you will be able to identify the proper moving average period and average range combination that results in extremely stable distribution. That in turn can be used in the average range channel that you will have more confidence in your choice of parameters.
This technique of exploring the data characteristics can be applied to any instruments, not just the emini.