EOS up 25% in a day after encountering weak BittsBands

We are using deep learning on vast sets of different data to assess where could be possible price bands of resistance for cryptocurrencies. For more detailed explanation of BittsBands please see e.g. our blog post:

Our deep learned BittsBands have proven excellent for trading in recent Bitcoin price developments

 

In this blog post we discuss EOS BittsBands. As you can see in the BittsBands chart below EOS was approaching prices ranges with very weak BittsBands above 12 USD. That means a high probability of rapid rise of EOS and this is indeed what happened next with the price now over 15 USD for a quick 25% return in around a day.

 

If you want to include these deep learned analysis in your cryptocurrency trading you can find it at our BittsAnalytics platform: www.bittsanalytics.com.. Platform also has a lot of other advanced data such as social media analytics and  chart patterns automatically detected with AI as well as sophisticated analytical tools.

Aeternity up 20% on encountering weak BittsBands

We are using deep learning on vast sets of different data to assess where could be possible price bands of resistance for cryptocurrencies. Let us explain how users of our platform can use our BittsBands for better anticipating possible price paths. We will use Aeternity price movements in the last days as an example.

The more red the particular band is (see picture below) , the higher is the probability that:

1. the price will consolidate within the band or rebound from it when falling towards the band from above (see e.g. point 3 below)

2. or that it will be “repelled” by the band downwards when approaching the band from below or consolidate within the band afterwards (see point 2).

If the band is particularly weak, i.e. almost white, then there is a higher probability of price rapidly moving through such price band. This has indeed happened in the last few days (see point 4 in the chart). There were very weak bands above 2.1 USD and the price then quickly rallied for a return of more than 20%. Of course not every price movement will follow this pattern as often there are other drivers, e.g.. fundamental ones but even in those cases we often see effects as described above. We regard BittsBands as one the best analytical tools on our platform.

If you want to include these deep learned data in your cryptocurrency analysis you can find it at our BittsAnalytics platform: www.bittsanalytics.com.. Platform also has a lot of other advanced data such as social media analytics and  chart patterns automatically detected with AI as well as sophisticated analytical tools.

Storm up 20% after mentions and sentiment surge on 20th April and positive BittsBands picture

We track millions of social media posts and use machine learning to determine sentiment for 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

One of the latest examples for third kind of signal was Storm. It had a surge in sentiment on 20th April, see chart below. The price was around 0.047 USD at the time.

Another important factor was also that the BittsBands were weaker from 0.04 USD up so one could expect a fast move up (for explanation of BittsBands see our blog post: http://www.bittsanalytics.com/blog/2018/04/19/our-deep-learned-bittsbands-has-proven-excellent-for-trading-in-recent-bitcoin-price-developments).

This is has indeed what happened as we got a rally from 0.047 USD to 0.058 USD for a return of 20% in a couple of days.

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

 

 

Our deep learned BittsBands have proven excellent for trading in recent Bitcoin price developments

We are using deep learning on vast sets of different data to assess where could be possible price bands of resistance for cryptocurrencies. Let us explain how users of our platform can use our BittsBands for better anticipating possible price paths. We will use Bitcoin price movements in the last days as an example.

The more red the particular band is (see picture below) , the higher is the probability that:

1. the price will consolidate within the band or rebound from it when falling towards the band from above (see e.g. point 3 below)

2. or that it will be “repelled” by the band downwards when approaching the band from below or consolidate within the band afterwards (see point 5).

If the band is particularly weak, i.e. almost white, then there is a higher probability of price rapidly moving through such price band. This has indeed happened as you can see in points 2 and 4 .  Of course not every price movement will follow this pattern as often there are other drivers, e.g.. fundamental ones but even in those cases we often see effects as described above. We regard BittsBands as one the best analytical tools on our platform.

If you want to include these deep learned data in your cryptocurrency analysis you can find it at our BittsAnalytics platform: www.bittsanalytics.com.. Platform also has a lot of other advanced data such as social media analytics and  chart patterns automatically detected with AI as well as sophisticated analytical tools.

End of Wild West in cryptocurrencies occurred in January – the tale of correlations, Part 1

In 2017 the cryptocurrencies had emerged as a new asset class with full force, never before has an entirely new asset class been established in such a short period of time. The year 2017 was also peculiar in that the individual cryptocurrencies were still very much different from each other in terms of relative returns or performance. There were some huge winners, also some losers and they were all correlated to Bitcoin to greater or lesser degree but the correlations were still lower than what is typical in other classes, for example stocks.

See for example rolling 20-day correlations with Bitcoin 5 months ago (on 6th November) for main cryptocurrencies:

A lot of them were actually inverse correlated with Bitcoin. In December of 2017  (data on 6th December) correlations increased but were still lower than typical in other classess:

Now contrast those correlations with values in April 2018:

So when was the regime change or phase transition to borrow from physics? Clues can be find in the following chart showing rolling 20-day correlation between Ethereum returns and Bitcoin returns:

As you can see there was a drastic change in correlations both in magnitude as well as in persistence in month of January. While the chart is shown for Ethereum other cryptocurrencies display almost the same evolution. While we would not like to speculate about the possible causes for this phenomenon one explanation could be emergence of new large financial players who employ arbitrage or some other classes of quant strategies.

So how does one adapt to these new times? Well, the bar has certainly been raised and simple approaches will work less well in achieving superior relative returns. But as we have shown in many blog posts in last months and that you can read by yourself, there are still possibilities for substantial performance but it requires better data and more sophisticated tools. One of the reasons we built our platform BittsAnalytics (learn more about it at www.bittsanalytics.com) was just to prepare for these kind of times. It was inevitable that they would eventually come. Perhaps it was just surprising how long it took for that happen.

 

 

Lisk up 40% after rebounding on bottom pattern and our BittsBands

Our BittsAnalytics platform uses artificial intelligence to provide its users with automated recognition of technical chart patterns for the cryptocurrency market. We also use deep learning to generate our BittsBands that show price bands with increased probability of resistance. In this post we would like to demonstrate how use of both features can lead to high returns.

As you can see in the following picture Lisk had a bottom pattern already formed through dips in December and End of March. And what happened recently is that it had indeed bounced on that bottom support line of 6.9 USD to deliver a return of 40%.

Note that our BittsBands also indicated a strong resistance in the area around 7 USD indicating a higher probability of the price bouncing on this level. You can also see that it has already bounced on this level several times in December. And that has indeed happened confirming the value of our BittsBands framework yet again.

If you want to use automated detection of chart patterns with artificial intelligence and our advanced BittsBands (as well as many other advanced tools) to improve your cryptocurrency trading it is easy – subscribe and become one of the many users of our platform BittsAnalytics at www.bittsanalytics.com.

Over 170% cumulative return of Verge from sentiment and mentions analytics signals over the last ten days

We track millions of social media posts and use machine learning to determine sentiment of cryptocurrencies in real-time. Hourly sentiment can provide opportunities for profit especially in turbulent times like the last week. One signal we look for are surges in either hourly sentiment or tweets mentions like seen in the chart below for Verge which we regard as bullish signals (when occurring in a consolidating or downward price trend):

As you can see there was a sentiment and mentions surge (signal 1) and (signal 2) and sentiment surge (signal 3). We plotted these signals on the price chart of Verge:

As you can see after the first and third signal, price rallies were especially big. The total compounded return from these signals was around 170% and occurring in time when most other cryptocurrencies actually fell. If you want to improve your trading in cryptocurrencies you can start using our platform BittsAnalytics – just subscribe at www.bittsanalytics.com.

Sentiment analytics trading signal hit the Bitcoin low point almost to the hour resulting in 15% return on Bitcoin

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

It occurred on 1st April 5 pm UTC time. The price at the time was 6500 USD and it was literally the low point of this latest correction. While this kind of sentiment signal was correct in many past cases as you can read in numerous posts on our blog, this time it hit the low point practically within an hour. The price has then rallied from 6500 to of 7500 USD at the time of this blog post. That is a return of almost 15% in just a couple of days on the main cryptocurrency. If you want to improve your trading in cryptocurrencies you can start using our platform BittsAnalytics – just subscribe at www.bittsanalytics.com.

Bitcoin again falls after reaching sentiment high – for the fourth time the warning was correct

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.

We have noticed in the past that after sentiment and optimism for Bitcoin reach a certain level, the optimism cannot sustain itself for long and the sentiment and price soon fall afterwards. This has happened in several cases in the past, see the picture below.

It has also happened in the latest instance when the sentiment went over the warning line on 24th March continued for a while but subsequently fell, with price also following. It is down around 12% from price levels of 24th March. For the statistics of previous cases see the table below and the chart.

As such, sentiment can be a really useful indicator for when to reduce positions in Bitcoin and other cryptocurrencies. See also our previous posts on these sentiment signals from the past:

Bitcoin again falls after reaching sentiment high

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

Tron up 85% since social media surge on 18th March

We track millions of social media posts and use machine learning to determine sentiment of cryptocurrencies. Below is hourly sentiment of tweets mentioning Tron over the last period.  We often look for any surges in tweets mentions because buzz is often ahead of price. As you can see in the chart below, the tweets mentions surged on 18 March 7 am UTC time when the price was around 0.265 USD and so has the sentiment associated with the tweets. As we have already posted in other such cases in the past this means a major bullish signal and Tron has indeed rallied since then for a gain of 85% in just one week.

A similar surge can also be observed with tweets mentions aggregated on daily basis:

We also do NLP analysis of themes discussed and generate tagclouds. As you can see in the following picture below, one of the main topics is the upcoming launch of Tron test net:

Tweets mentions is also like sentiment often ahead of the price and you can start using sentiment and tweets mentions data like this to improve your cryptocurrency trading by subscribing to our platform www.bittsanalytics.com.