Metcalfe’s Law in Bitcoin Network
All data in this report were captured or processed by Huobi Research; please cite the source “Huobi Blockchain Big Data” when quote.
Huobi Research is proud to introduce the Huobi Blockchain Big Data Product — aiming to become the most comprehensive blockchain database. We provide useful data to investors, traders, researchers and other participants in blockchain and crypto market. Data retrieved in this article has been categorized into 3 categories: Bitcoin Data, Social Media data, and Market Trading Data.
With regard to Bitcoin Data, we found that the Metcalfe’s Law nearly perfectly applies in BTC network, which means that the price of Bitcoin is proportional to the square of the number of active users in the Bitcoin network. Since the beginning of May, the number of active users in the Bitcoin network has reduced from 3.51 million to 3.14 million, which is partly because of the slowing down in new addresses adding to the Bitcoin network.
With regard to Social Media Data, our market sentiment index shows that community members of 8tc.com hold polarized opposite opinions towards the market, with 25.4% of participators reported being “very pessimistic” and 21.9% of participators reported being “very optimistic”. However, our individual investor sentiment survey suggests that 39% responders are bullish with only 9% responders remaining bearish. We believe that this is because compared to investors, community members tend to be more emotional and easily influenced by market.
Statistic shows that since 2013, the continuous falling period of Bitcoin price were typically within 6 days — with the longest period of 8 days, and there were a 72.6% chance for bounce after 6 days of continuous price falling. In terms of Cryptocurrency Price Correlations, IOTA/BCH, ADA/XRP, and ADA/IOTA were the trade pairs with the highest correlation. LTC/EOS, XRP/EOS, and BTC/EOS had lowest correlations.
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1.2 Data Category
Data retrieved in this article has been grouped into 3 categories: On- Blockchain Data, Social Media Data, and Market Data.
On-Blockchain Data includes trading data and address information. Trading data includes the number of confirmed transactions on the blockchain network, trading volume and turnover rate. Address information has 15 data sets, including number of active addresses, number of churned addresses, number of re-activated addresses, and addresses distribution. We will keep updating and adding new data sets to this list.
Social Media Data
Social Media Data is retrieved from online communities such as GitHub, 8tbc.com, Facebook, Twitter and so on. For example, we will look at GitHub statistics such as “star” and “fork”, and followers number on social networking websites such as facebook and twitter.
Market Trading Data
Market Data comes from major exchanges, including price information and trading volume of certain crypto assets. For example, we will look at price volatility, trading volume, and turnover rates.
2. Bitcoin Data
2.1 Metcalfe’s Law in Bitcoin Network
Metcalfe’s Law states the value of a telecommunications network is proportional to the square of the number of connected users of the network. We studied Bitcoin price and user number, and found that the Bitcoin network highly applies Metcalfe’s Law.
Figure below shows the relation between Bitcoin price and square of number of active addresses on the Bitcoin network between May 1, 2017 and May 31, 2018.
From the figure shown above, it is clear that these two factors have a correlation. Then we conduct deeper correlation analysis on these two factors.
Chart above indicates that, 1) Bitcoin Price and n2 are correlated, with the correlation coefficient between the two factors reaching 0.7, and the correlation coefficient between the logarithm of two factors reaching a whopping 0.96; 2) The longer the moving average (MA) of Bitcoin Prices, the larger correlation coefficients. When we take it a step further by performing a regression analysis on the log of both factors, the result is shown as figure below.
From the result, it is evident that there is a positive linear relation between the 10 days moving average of Bitcoin Price and the square of the 10 days moving average of number of Bitcoin active addresses, with the relation predicting Bitcoin price with a 91.4% accuracy.
2.2 Bitcoin Address Activity
Since the beginning of May, we have detected a steady decline in number of active Bitcoin addresses, from 3.51 million to 3.14 million.
We divide the number of active address each week into three components, with active address this week = persistent active address from last week + new active address this week + reactivated address this week. As the figure shown below, we believe that the overall decrease in number of active address in the Bitcoin is in a large sense contributed by the slowing down of new address adding into the Bitcoin network.
Figure above shows that the number of new bitcoin address each week reduced to 1.67 million from 1.93 million.
3. Social Media Data
3.1 Community Sentiment
With the help of SnowNLP, a python-powered software for processing Chinese text, we analyzed the overall community sentiment in 8btc.com (China’s largest internet community for Blockchain and crypto asset) between May 19 and May 25, 2018. The result in the figure below shows that 25.4% of the community members are “very pessimistic” toward the market, while 21.9% are “very optimistic”, and the average sentiment is neutral with a bit tilt to pessimistic.
However, the results of our individual investors sentiment survey have shown a drastically different result. In our individual investors sentiment survey, 39% responders were “very bullish” toward the future market performance with only 9% being “very bearish”. We believe that this is because compared to investors, community members tend to be more emotional and easily influenced by market sentiments.
4. Market Trading Data
4.1 Analysis of Bitcoin price continuous falling period
We analyzed previous Bitcoin price continuous falling period based on data on Coinmarketcap from 2013/5/1 to 2018/6/3. Below is the definition of certain terms that will be used in our analysis:
- Opening Price: the Bitcoin Price at UTC-0:00 of any given day
- Closing Price: the Bitcoin Price at UTC-24:00 of any given day
- Continuous falling period: the closing price is lower than the opening price for 3 or more consecutive days; individual days not counted as a Bounce right after the downtrend are all considered part of a downtrend.
- Bounce: a daily increase of more than 3% in Bitcoin price, or increase in Bitcoin price for two consecutive days regardless of the percentage.
- Probability for a Bounce: the probability for a bounce in price right after the conclusion of a downtrend.
The result is shown in the chart below.
Since 2013/5/1, there has been 105 occasions of continuous falling in Bitcoin price, with the longest period lasting for 8 days and 97.1% of times being within 6 days. For a continuous falling period lasting over 6 days, the probability for a bounce in Bitcoin price is 72.6%.
4.2 Cryptocurrency Price Correlations
We performed Pearson Correlations Analysis on the TOP 10 popular crypto assets in overall market cap and retrieved their respective price information from Coinmarketcap from 2018/1/1 to 2018/5/25. The correlation coefficient is defined as the function below:
Investing in multiple crypto assets with low correlations is conducive to risk diversification. From the result shown above, we can see that pairs with the highest correlations are IOTA/BCH, ADA/XRP, and ADA/IOTA; the pairs with the lowest correlations in their respective prices are LTC/EOS, XRP/EOS, and BTC/EOS.
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