Fast Fourier Transformation applied to the pattern recognition.
I’ve created an indicator that helps recognize repeated waves on the chart. The basic idea used for the indicator is that price changes are cyclic. Since there are a lot of “random” changes in the price we cannot just match one of the periods to another. We need somehow filter the small changes and keep only the main trend of price. I’ve used the Fast Fourier transformation (FFT) to get the main trend of price and filer the random noise.
Let’s use the FFT and try to find some pattern and predict the price moves.
This is the current H1 chart of EUR/USD.
We could see the two similar price moves. Let’s apply the FFT indicator. I’ve used the initial settings – 256 periods to analyze and no shift of waves.
Here you can see three “waves”: green, blue and red. The green wave is the representation of analyzed price movement – the last 256 periods of chart. The red wave is the copied green wave to the past, the blue one – to the future. The past wave could be shifted by a number of periods from the green wave.
After the FFT is applied we have to change the base point of the green wave to match the end of the trend.