In this post we would like to show how to use our two recently introduced features on our BittsAnalytics platform – automated detection of chart patterns and BittsBands – price resistance bands based on advanced analysis of vast amounts of data.
In a recent tweet:
we mentioned that the Ethereum Classic just broke through bottom pattern support and there are no strong resistance bands below 32 USD. This means a higher probability that the price will continue to fall. See both pictures below.
This is indeed what happened afterwards with price of Ethereum Classic falling through the very weak bands to 25.18 USD as of writing this post. This is another example of combining advanced technical analysis with resistance band to analyse potential future price movements of cryptocurrencies. If you want to improve your cryptocurrency trading with these analytics tools and many other, subscribe at www.bittsanalytics.com.
In this post we would like to demonstrate how to use our social media analytics combined with our advanced technical analysis on the example of Particl.
Particl had a surge in sentiment and tweets mentions around a week ago. See our tweet from that time:
By looking at the hourly data we can see sentiment and mentions surged on 28th February 8pm UTC time when the price of Particl was around 20.8 USD.
While the sentiment somewhat receded this was followed later by another surge in tweets mentions on 3rd March. Social media momentum was strong.
If we now look at the bands provided by our platform:
you can see 1) weak or white band between 30 USD and 32 USD. 2) stronger resistance band above 32 USD. From our bands we would expect a rapid rise from 30 USD to 32 USD and then consolidation or fall back to lower levels. One trading way in addition to original long position is to put a limit buy order at 30 USD and limit sell order at 32 USD. And this is indeed what happened regarding the band 30-32 eventually confirming again the valuable insight from our BittsBands (you can also see how fast was the increase from 21 to 26 USD where the resistance bands were very weak) . See updated chart below:
Total return from original levels around 70%.
If you want to start using our platform subscribe at www.bittsanalytics.com.
In this post we would like to introduce the use of our recently introduced advanced feature, Bands or BittsBands, on a concrete example. We are using deep learning on vast sets of different data to assess where could be possible price bands of resistance for cryptocurrencies, see e.g. bands for Ripple below. The more red the particular band is, the higher is the probability that the price will rebound from it when falling towards the band or that it will fall, “repelled” by the band when increasing and encountering the band from below. If the band is particularly weak, i.e. almost white, then there is a higher probability of price rapidly moving through such price band. Of course not every price movement will follow this pattern as often there are other drivers, such as a very positive news, where the price can rise or fall through such bands. But it can often work surprisingly well.
As an example of use, yesterday we mentioned in a tweet (see below) about Ripple that it would be interesting to see what happens when Ripple reached the rather strong resistance band from 1.05 USD to 1.2 USD:
And after the tweet the price first rose to the band, reached around 1.08 and then indeed fell back to 0.96 USD at the time of writing this post. See the updated chart below:
If you want to start using our BittsBands and many other advanced analytics you can by subscribing at www.bittsanalytics.com. For other examples of using BittsBands see our post about Particl:
Return on Particl 70% – example of using social media analytics combined with advanced technical analysis
or see our recent tweet about Ethereum Classic below where we analysed that due to weak resistance bands below 32 USD it can fall rapidly below 30 USD and this is indeed what happened, it is now around 25 USD.