Bitcoin again falls after reaching sentiment high

We track millions of social media posts and use machine learning to determine sentiment of cryptocurrencies. Bitcoin sentiment has been quite useful recently for Bitcoin price direction. See e.g. the recent sentiment development below.

In a similar way as already happened about a month ago (see post below) after sentiment reached the levels from January 14th it again fell substantially.

Of course the drivers were predominantly fundamentally news, on regulation, but it seems that whenever sentiment reaches certain level and optimism some external developments happen to stop it. As such, sentiment can be a really useful indicator for when to reduce positions in Bitcoin and other cryptocurrencies. See also our post about a similar sentiment signal from the past:

Bitcoin on 17th February reached the sentiment level last seen on 14th January

If you want to use data like this as an additional source of information to improve your cryptocurrency trading, you can start using BittsAnalytics platform by becoming our user: https://www.bittsanalytics.com/subscribe.php

Ripple fell after encountering resistance Bittsband

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:

twitter.com/bittsanalytics/status/970466555074174976

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.

Lunyr up more than 100% in one day since social media mentions surge

We track millions of social media posts and use machine learning to determine sentiment and number of mentions for 200+ of cryptocurrencies in real-time. Below are hourly number of tweets mentions for Lunyr. The tweets mentions jumped by more than 8 times February 23 at 5 pm UTC time. For us that was a huge bullish signal.  And indeed, over the next 24 hours the price jumped by more than 100%. We often find that the social media buzz is ahead of price.

 

Since closing the sentiment gap, Bitcoin outperformed Ethereum by around 15 percentage points

As we have wrote in our past blog posts we use our comparison analytics for relative selections of coins. We are using it especially for relative allocations between major cryptocurrencies. In this blog post we revisit the relative allocation between Bitcoin and Ethereum as there were recent changes that warrant a revision.

In our previous blog post on this topic we wrote about an outperformance of 40 percentage points of Ethereum since it opened a sentiment gap on Bitcoin on 9th January:

Ethereum outperformed Bitcoin by 40 percentage points since opening a gap in sentiment – use of comparison tools in BittsAnalytics

Around a week ago there was  sharp reversal in this sentiment dynamic and Bitcoin after a few days  again closed the sentiment gap with Ethereum on 14th February. See the chart below. Since this closing of the gap Bitcoin outperformed Ethereum by 15 percentage points confirming that the sentiment comparisons can be powerful trading signals for relative selections.

The use of sentiment analytics for relative selections is just one of many ways you can improve your cryptocurrency trading with our BittsAnalytics platform. You can find more examples here: http://www.bittsanalytics.com/blog/category/bittssignals/ or you can start using BittsAnalytics platform by becoming our user: https://www.bittsanalytics.com/subscribe.php

Bitcoin on 17th February reached the sentiment level last seen on 14th January

We track millions of social media posts and use machine learning to determine sentiment of cryptocurrencies. Bitcoin sentiment has been rising since 6th February and has yesterday on 17th February reached levels last seen on 14th January. Would not be surprised if the rally stops a bit and the price consolidates for a while.

We assess this as a bit of a pause in price rally that started with a huge sentiment reversal on 6th February when the price was just 6200 USD. Read more about that bullish sentiment signal at around 6200 USD  in our blog post from that period:

http://www.bittsanalytics.com/blog/2018/02/07/trading-hourly-sentiment-reversals-in-recent-downturn-around-30-return-on-bitcoin-from-6th-to-7th-february-part-ii/

If you want to use data like this as an additional source of information to improve your cryptocurrency trading, you can start using BittsAnalytics platform by becoming our user: https://www.bittsanalytics.com/subscribe.php

Stratis Roadmap Update well received – example of using BittsAnalytics Tagclouds and Themes analytics

As an example of how we use BittsAnalytics platform to get immediate feedback about a particular initiative of a cryptocurrency let us take as an example Stratis yesterday. If you display the chart of daily sentiments on our platform and then click on the last day of the chart you get tagcloud from social media posts on that day as well as themes of similarity from the same posts. You can immediately see that the main topic dominating discussions is the roadmap update. And since the sentiment jumped we can assume that the community took the roadmap update positively and infer that it should be positive for the price of Stratis.

It is also interesting that our NLP analysis of themes discussed returns these words: buy, now, severely, undervalued, dip, want.

If you want to use this and many other kind of analytics tools and data to improve cryptocurrency trading read more about platform at  www.bittsanalytics.com.

RChain up 75% since sentiment surge on 8th February

We track millions of social media posts and use machine learning to determine sentiment for 200+ of cryptocurrencies. We can become interested in a cryptocurrency for many different reasons based on our data, three such examples are:

  • cryptocurrency had a large jump in tweets mentions
  • it had a large jump in sentiment as determined with machine learning from tweets about it
  • it had a large increase in both sentiment and tweets mentions number

We are especially interested in coins which are below the top 10 in terms of market cap but still among the top 100 (those that are below 100 have smaller number of tweets and the sentiment can thus be less statistical significant). One of the latest examples for second kind of signal was Rchain. It had a surge in sentiment on 8th February, see chart below. Since then its price increased around 75%.

We also wrote about the surge in RChain sentiment in our twitter account in recent days:

twitter.com/bittsanalytics/status/963205304233156609

If you want to use data like this as an additional source of information to improve your cryptocurrency trading, you can get it at our platform www.bittsanalytics.com.

Trading hourly sentiment reversals in recent downturn – around 30% return on Bitcoin from 6th to 7th February

We track millions of social media posts and use machine learning to determine sentiment for 200+ of cryptocurrencies in real-time. Hourly sentiment can provide opportunities for profit especially in turbulent times like the last few days. One signal we look for is a prolonged fall in hourly sentiment followed by a sharp sentiment reversal in positive direction, like seen in the chart below for Bitcoin:

It occurred on 6th February 6am UTC time. The price at the time was 6200 USD and has since then rallied to the price of 7700 USD at the time of this blog post. That is a return of almost 30% in around a day. Find out more about our data and analytics tools at www.bittsanalytics.com.

Trading hourly sentiment reversals in recent downturn – 15% in around one day on Bitcoin

We track millions of social media posts and use machine learning to determine sentiment for 200+ of cryptocurrencies in real-time. Hourly sentiment can provide opportunities for profit especially in turbulent times like the last few days. One signal we look for is a prolonged fall in hourly sentiment followed by a sharp sentiment reversal in positive direction, like seen in the chart below for Bitcoin:

It occurred on 2nd February 1pm UTC time. The price at the time was 8050 USD and then quickly rallied for the intermediate high of 9377 USD for a return of over 15%.

Ethereum outperformed Bitcoin by 40 percentage points since opening a gap in sentiment – use of comparison tools in BittsAnalytics

In this post we would like to show one way of how to use comparison tools in BittsAnalytics. In periods of sideways movement in prices or downturns, the relative outperformance or underperformance of one cryptocurrency in comparison to another becomes much more important. Any tools or data that can help you with relative selections provide potential added value.

As an example we chose the comparison between two of the biggest cryptocurrencies, Bitcoin and Ethereum. The data we are interested in are daily tweets mentions of both as well as sentiment calculated with machine learning from tweets about them. As you can see in the chart below, Ethereum has opened a gap in sentiment on 9th January and maintained it since then. Since that time Ethereum has outperformed Bitcoin by around 40 percentage points. Note that Bitcoin substantially increased the lead in tweets mentions but still lagged behind in price. So the buzz itself is not necessarily indicative of the price direction, the sentiment of buzz seems to matter though.

The use of sentiment analytics for relative selections is just one of many ways you can improve your cryptocurrency trading with our BittsAnalytics platform. You can find more examples here: http://www.bittsanalytics.com/blog/category/bittssignals/ or you can start using BittsAnalytics platform by becoming our user: https://www.bittsanalytics.com/subscribe.php