In our search for new knowledge about Bitcoin, data analysis can serve us well. In this article we will do a little data analysis together. The focus is on the relationship between the Bitcoin rate and the transaction volume.
Do your own research is a popular motto in the Crypto Legacy field. Both here at BTC-ECHO and in the BTC-ACADEMY, we strive to equip our readers with the necessary tools and to allow them to share our insights. As a starting point for the BTC-ECHO community, our Discord is also a source for such research.
To own research but also includes the sober look at the raw data
The responsible crypto citizen should always be a little data analyst. In the last articlewe have taken a first step in this regard: In the first part of this series, I explained how interested parties can download course data and work with it. With TradingView and APIs like Coingecko’s, investors and analysts have come a long way. You can view Bitcoin & Co. courses according to the current rules of technical course analysis and study new metrics and indicators. You can also study investment strategies such as dollar cost averaging (regular investments in smaller, fixed dollar amounts) and the use of seasonality or create a portfolio based on several cryptocurrencies.
However, the course does not take into account a special feature of cryptocurrencies: Thanks to the public nature of the blockchains, every analyst can take a look on-chain himself. How many transactions were there on the blockchain? How full are the blocks? Analysts can clarify such questions on-chain at a glance. In this article we would like to explain a few ways in which you can get such data using APIs. As explained in the last article in the series, we use R.
A second goal of this article is to do a little exploratory data analysis together. We therefore start with the data acquisition and play together with the corresponding data. Let’s see what we find out.
Sophisticated Bitcoin data from Coinmetrics
Coinmetrics is a good service for a first look at data beyond the mere price events. Coinmetrics is a company that focuses on crypto-relevant analyzes. Their analyzes have been discussed in various articles in the past. In addition to these insights, Coinmetrics offers the community a large amount of data that can be the first step for many analyzes.
Even those who don’t want to get started with R right away can get started on their platform. At this link Interested parties can reach a frontend in which various data can be viewed with regard to their development over time:
As you can see, a wide variety of other cryptocurrencies can be examined in addition to Bitcoin. The above illustration shows the development of the Bitcoin exchange rate. However, sizes such as the realized capitalization, the NVT ratio or the current block size can also be selected. If that is not enough for you, you can use “Formula” to create combinations of the sizes mentioned and plot them graphically. The future Bitcoin analyst can go very far here and model simple trend forecasts , for example.
But what if you want to use other models or look at the Coinmetrics data together with others? Or if data should not simply be analyzed in terms of its time dependency? Let’s say that we want to analyze the relationship between Bitcoin’s number of transactions and its rate in more detail. We are not interested in the temporal context, but what an influence the number of transactions has on the Bitcoin rate .