How Do Auto-Adaptive Indicators Work?

One of the first challenges that every trader has to face in the beginning is setting up the period of indicators. Almost every indicator is calculated from the last several bars in the chart and the indicator period defines how many bars should be used for the calculation. For every period value, the indicator looks different. What is the right approach? And can auto-adaptive indicators help us?

First, let me tell you something about the period setup of indicators.

Basically, there isn’t any general, universal, recommended value (neither it is the value 14 that is used as a default value for many indicators). The optimal period for each parameter depends on many factors, like timeframe, expected length of trades (scalping, short-term, medium-term, long-term trades,… ), or even the computer optimization of the period. Generally speaking, we can say that for short-term trades the optimal period is approximately 2-20, the medium-term 21-50 and for long-term trades it is at about 51-200. But it really depends on the specific situation, indicator, system and the timeframe. Often it can be beneficial to combine different periods in one system – for example when one indicator is used with one lower and one higher period – to get the short-term, medium-term and long-term view on the market. In general, you need to remember that the lower is the period, the more market noise you will get – you can filter this out by looking at the higher period (or timeframe) to get a more complex view on the market situation (e.g. power and direction of a trend).

There is quite an interesting theory about the best period published by Perry Kaufman in 1995, who observed following:


  1. When the market trends, it is mostly strong and clean move (I disagree with him on this point as it also depends on the timeframe and other circumstances), which doesn’t contain too much noise. In that case, we can work with lower periods of indicators.
  2. When the market doesn’t trend (it is choppy), charts contain a lot of noise and it is much better to use a higher period of indicators. level switch manufacturer


Perry Kaufman also advanced from theory into practice (as one of few) and created an indicator (which I consider to be one of the first, or maybe even the very first auto-adaptive indicator), called Adaptive Moving Average (abbreviated to AMA or also KAMA), which solves the issue of the optimal period in a new, original, way – it dynamically changes the period and adapts to the situation in the market – depending on if the market is trending or not. Creating such indicator isn’t complicated and AMA (or also KAMA) is a standard part of many trading platforms.

Auto-adaptive indicator construction

When constructing auto-adaptive indicator, you need to add to the “standard” indicator one additional component – the part that will tell you if the markets are in trending or non-trending phase. There are many indicators that can provide this information, but Perry Kaufman decided to use another from his own indicators, the one that he calls Efficiency Ratio (ER). This indicator fluctuates between 0 and 1. The closer it is to number 1, the more the market trends, the closer it is to number 0, the less the market trends.The second step is quite simple – we use any of the moving averages (Kaufman uses modified EMA) and choose the range of the values that should be used for the period – let’s say from 2 to 50. When connected with ER indicator, the auto-adaptive version of the moving average uses higher values of the pre-defined range (in our case values close to 50), whenever ER indicator gets closer to 0 (when it reaches 0, the EMA period will be 50). This is because there is too much market noise and low period values are not suitable. On the other side, the lower periods will be automatically used for EMA every time ER gets closer to value 1 (when it reaches value 1, the EMA period will be 2).

Leave a Reply

Your email address will not be published.