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.
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
We track millions of social media posts and use machine learning to determine sentiment for 200+ of cryptocurrencies. Our platform allows many analysis including comparisons and in the chart below you can find the sentiment comparison between Bitcoin and Ethereum. It is quite interesting to see how during the latest downturn it seems that the Bitcoin was mostly mentioned in the negative posts and thus bared the brunt of negative comments. On the other hand it got a lot of free publicity as well.
If you want to know how you can improve cryptocurrency trading with sentiment and other data from social media read our blog posts:
We track millions of social media posts and use machine learning to determine sentiment for 200+ of cryptocurrencies in real-time. An interesting happened yesterday regarding the sentiment of cryptocurrencies, most had their sentiment fall.
See examples, first Bitcoin:
Sentiment is often ahead of the price and you can start using sentiment data like this to improve your cryptocurrency trading by using our platform www.bittsanalytics.com.
We track millions of social media posts and use machine learning to determine sentiment for hundreds of cryptocurrencies in real-time. With Bitcoin and Ethereum as the largest cryptocurrencies it is interesting to track relative trends about them in social media. Below you can find the chart showing sentiment and number of tweets with mentions of Bitcoin or Ethereum. We find it fascinating that Ethereum has not only closed the gap to Bitcoin in terms of number of tweets and also took a lead in sentiment a couple of days ago. This should be a bullish signal for Ethereum. If you want to track comparisons like that, set up tracking portfolios, get real-time sentiment trading signals, ICO analytics and much more subscribe at www.bittsanalytics.com.
We track millions of social media posts and use machine learning to determine sentiment for hundreds of cryptocurrencies in real-time. Below is real-time sentiment of tweets for Ethereum over the last few days. The real-time sentiment of Ethereum made a major sentiment spike reversal on 8am 11th December (UTC time). As we have already posted in other such cases in the past this means a major bullish signal for the price and indeed the price of Ethereum has since then rallied by more than 30%.
Ethereum had a great sentiment reversal on 2. November at 11h (UTC). +6% in a day to make some money in ETH as well which is not in a bull trend for months now. So the potential for profit is mostly in some short-term trading.