Following the Trend With the Adaptive Moving Average.
Creating a New Strategy on the Adaptive Moving Average.
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Adaptive moving averages offer the opportunity to take into account multiple variables in order to reflect better the current conditions and to avoid whipsaws. This article discusses a certain type of strategies to be applied on adaptive moving averages.
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The Adaptive Moving Average
Moving averages help us confirm and ride the trend. They are the most known technical indicator and this is because of their simplicity and their proven track record of adding value to the analyses. We can use them to find support and resistance levels, stops and targets, and to understand the underlying trend. This versatility makes them an indispensable tool in our trading arsenal.
As the name suggests, this is your plain simple mean that is used everywhere in statistics and basically any other part in our lives. It is simply the total values of the observations divided by the number of observations. Mathematically speaking, it can be written down as:
We can see that the moving average is providing decent dynamic support and resistance levels from where we can place our orders in case the market goes down there. The code for the moving average can be written down as the following:
def ma(Data, lookback, what, where):
for i in range(len(Data)):try:Data[i, where] = (Data[i - lookback + 1:i + 1, what].mean())…
