OK, here it is. Moving averages aren’t that great – and you **can** do better!

In short, here are a couple of reasons why moving averages aren’t great:

- Moving averages assume the market is either going up or down. They are either rising or falling. But the market isn’t that simple – there aren’t just 2 states. In fact there are 3 states: the market is either rising, falling or in congestion. A moving average can’t help you determine this third congestion phase.
- There are literally millions of different moving averages. Simple, exponential, weighted, etc. etc. Then 9 bar, 13 bar, 21 bar, 50 bar, etc. etc. Then displaced, or not. Add all those combinations together and you almost have an infinite number of combinations. And so which one is “right”?

But there is a better way. Let me explain. But first a little history.

## Exponential Moving Average first published in 1956

1956 was the year Robert Brown and his co-creator Charles Holt published a book on the Exponential Moving Average. They both worked for the U.S. Navy, although independently, and had been using the Exponential Moving Average to track the location of submarines for some years previously.

The beauty of the Exponential Moving Average was that you only need two numbers to make the calculation. So here’s the little formula for an Exponential Moving Average: it is yesterday’s (or the previous bar’s ) value of the Exponential Moving Average times some factor, alpha, plus 1 minus alpha times today’s (or the current bars’) value.

So as an example, if alpha was 0.8, you multiply the current value of the Exponential Moving Average, say 100, by 0.8 then add 1 minus 0.8, which is 0.2, times the current data point, which might be 110. Add those two numbers together and you get 102.

If you’re using a 10 or a 25 period Simple Moving Average, you’d have to add together 10 or 25 different numbers and then divide by 25 or 10 or whatever it might be. With an Exponential Moving Average, you only needed two numbers. And then in the days before the first pocket calculators were available, this was a godsend. Beautiful.

So 1956 was an important year. Prior to that, technical analysis has been very chart-based. It was all about trend and support resistance lines and things that you could draw on a chart. After 1956, technical analysis was far more computationally-based, where we’re calculating moving averages and we’re using computer power to analyze charts.

## The search for the BEST moving average

Now, the problem is this increased computer power we’ve had ever since 1956 has led us down the wrong path – the search for the ultimate moving average, one that smoothes out periods of consolidation.

Here’s a 4,500 tick bar chart of the Emini continuous contract day and night session going back 7 or 8 days. I’ve just overlaid a Simple Moving Average – it doesn’t matter the length of this particular moving average – but if it’s falling it’s colored white and if it’s rising it’s colored red.

You can see the trending moves quite nicely marked. But in between we have periods of consolidation, where the market is trying to determine which way it’s going to go. And our Simple Moving Average is all over the place. I’ve marked these areas of consolidation and false signals with red boxes.

During these periods of uncertainty or congestion, the moving average does not do very well at signaling direction. You don’t know whether the market’s going up or going down. So, all the activity that’s gone on in developing moving averages since 1956 has been about trying to find this “ultimate” moving average that smoothes out those periods of consolidation.

And the result is we literally have thousands of different moving averages:

- Simple Moving Average
- Exponential Moving Average
- Weighted Moving Average
- Hull Moving Average
- Jurik Moving Average
- Multiple Moving Averages
- Moving Average Differences

- Linear regressions
- TEMA (Triple EMA)
- MAMA and FAMA
- Zero-lag Filters
- Laguerre Filter
- Median
- T3, etc.

So, as you can see, there are dozens of different types of moving averages. Then, on top of that, you’ve got to choose the length, or the smoothing factor, for each. And then you could also be displacing these moving averages. So, put all of that together, and you’ve got a myriad of different choices of moving averages to use.

And all they’re trying to do is smooth out these periods of consolidation and limit the number of false signals you get.

## The solution requires looking at market activity

Rather than trying to find this ultimate moving average, we should be looking for an indicator that tells us what kind of activity the market is going through. If the market is trending, a moving average will be fantastic. But when a market is not trending, but is consolidating, then the moving average will be horrible.

You need an indicator that will tell you which kind of activity the market is going through right now. One that can tell is the market is trending or in consolidation. And the secret is **calculating support and resistance levels adaptively**. Because once you break out of a support or resistance level, that’s when you move into a trending period. And if you keep within the support and resistance levels you’re in consolidation.

John Ehlers to the rescue. He developed a beautiful piece of code called the Hilbert Sine Wave. I’ve improved on that algorithm, added the support and resistance levels and called it the Better Sine Wave. I gives this alternate view of adaptive support and resistance levels.

So going back to our 4,500 tick bar chart you can see that during periods of consolidation the Emini just bounces between support and resistance levels. But when a resistance level is broken to the upside we break into an uptrend. And when a support level is broken to the downside we break into a downtrend.

The trending periods are also market with PB and END text. These show when a trending period is likely to stop with “Pull Back” and “End of Trend” signals. After we get an end of trend signal, we’re going to go through some consolidation with adaptive support and resistance levels being plotted.

The Better Sine Wave indicator is showing you periods of consolidation and periods of trending. And so what you need to do is to figure out what the market is doing and to play it accordingly. If the market is going through a consolidation phase, having been a strong trend, you need to be playing the support and resistance levels. And then waiting for the next breakout into a trend and you can ride along.

## Benefits of using an adaptive indicator

Now the beauty of using this Better Sine Wave approach is that, first of all, there are no inputs to tweak. You just load this indicator onto a chart and it dynamically calculates the support and resistance levels. There are no inputs. Nothing to optimize.

The second thing is, because these levels are dynamically calculated, it’s an improvement on the traditional support and resistance view of the world. When traders with charting the market the support and resistance levels were actually fixed values – which isn’t realistic.

So, that’s my pitch for the Better Sine Wave indicator and why you should be ditching your moving averages. Moving averages will always be giving you false signals through all these consolidation periods. Great during the trending periods. Lousy during consolidation.

## How to use moving averages (alternative approach)

Now, having trashed moving averages there is one instance where I think they are of tremendous value!

I have found moving averages great for smoothing incoming price data or “pre-processing” it in order to eliminate the noise. Then feeding that pre-processed or noise-reduced data into your other indicators. But you use a very short “window” or short period for these moving averages. No more than 5 bars and something between 2 and 4 bars is ideal.

In fact, one of the simplest ways to pre-process, or smooth, input data is to use a 3-bar or 5-bar median of the price data. This will get rid of the “noise”. So that is using moving averages in a totally different way. Very short term in order to pre-process data and reduce the noise.

So, there we go, just a quick video and article explaining my pitch for why I think you should ditch your moving averages. Forget the search for the ultimate moving average and instead understand the psychology of the market and try and figure out when it’s trying to break support or resistance.