When we hold crypto assets, the team is working is the firm confidence that the currency price will take off in the bull market and is also the bottom line for continuing to hold when the bear market is trapped.
But will the team doing the work really make the currency price rise more in the bull market? Is it more resilient in a bear market?
This article uses 10 years of historical data to tell you the answer.
Four bull and bear cycles in the Crypto market
The genesis block of Bitcoin was born in 2009. Its currency price has experienced multiple bull and bear cycles in the following 14 years, and there have been ICO era, public chain explosion, Defi Summer, Industry narratives such as the “NFT wave”.
For the convenience of analysis, this article defines 2015.07-2018.01 as the first round of bull market, 2018.01-2020.03 as the first round of bear market, 2020.03-2021.05 as the second round of bull market, and 2021.05-present as the second round of bear market.
The first round of the “ICO” bull market from 2015.7 to 2018.1 is a long time ago, and there is too little data available to obtain rigorous results. Therefore, this article focuses on analyzing the last three cycles.
Four bull and bear cycles in the Crypto market
What factors can reflect the team is doing something? We found six factors!
The vast majority of projects in the industry are based on blockchain technology, and the code is open source on Github (GitHub is a platform for code hosting and sharing).
Therefore, **Falcon uses GitHubs 6 factors as a quantitative standard to measure the team is doing something, including: Star, Fork, Commit, Issues, Pull requests, and Watchers. **The following are the specific meanings and types of the six factors
A detailed introduction to the six factors of project GitHub data
The Github data of all projects in this article can also be seen on Falcon’s products,Visit link:https://falcon.lucida.fund/ch/asset_tracker/73/github?uid=
Product page screenshot
Effective sample size and terminology explanation
The team counted the currency price trends of the three market cycles and the corresponding project GitHub six-factor data. After outlier processing, 81, 330, and 596 valid token samples were retained in the three market cycles respectively.
Explanations of terms that will appear in the chart below:
detailed explanation of noun
The first round of bear market (2018.1-2020.3) GitHub data has a certain anti-falling effect on currency prices, but the effect is limited, or it is related to the small sample size
Let’s start with the first round of bear market:
Descriptive statistics of the six factors of GitHub data and currency price increases and decreases:
**The first round of bear market token data is scattered, which is in line with the characteristics of the early rise of the crypto market. **The standard deviation values of the seven statistics during this period are far away from the average, indicating that the previous prices of different currencies and their GitHub data are quite different. At this stage, the relatively mature tokens such as Bitcoin and ETH have extremely high attention on GitHub. However, many emerging currencies have low attention on GitHub and low developer contributions.
The statistics of the currency prices in this range whose currency price decline is less than the average decline value (black bold) and the corresponding six factors of GitHub data:
**The gray grid represents tokens that are contrary to the market trend. We believe that such tokens are of special nature and require comprehensive analysis based on market conditions. **There is only one binance-exchange in this range. Observing the six factors of its GitHub data, the star and fork values are in the top 10 of the statistics, but the commit, issues, pull_requests, and watchers are all extremely low, mainly because the bnb token was in the top 10 before 2019. It only has the attribute of platform currency and no public chain attribute, so the code is not open source. In the second half of 2018, the market hot spots focused on the platform currency sector, with bnb rising at a high rate and resisting the decline in this cycle. For this currency, among the six factors in GitHub data, only the star and fork factors have a certain correlation with price.
Among the tokens whose currency prices have fallen less than the average, 40% of the tokens have GitHub factors in the top 10 of the statistics. The GitHub factors of the remaining tokens are generally low. Preliminary inference is that during this cycle, the GitHub factor is The reduction in currency price decline has a certain positive effect, but the effect will not be particularly large.
The 2nd Bull Market (2020.3-2021.5) Github’s more active projects rose more in the bull market
Descriptive statistics of the six factors of GitHub data and currency price increases and decreases:
**The second round of bull market token data is relatively concentrated, and the maturity and prosperity of the crypto market have increased. **The standard deviation statistics of the seven statistics in this interval are closer to the average. Compared with the statistics from 2018 to 2020, the sample data distribution in this interval is more concentrated. Based on the analysis of the actual market situation, on the one hand, the token market has developed relatively maturely in the 2020s. The tokens that emerged in 2018 have all achieved certain development in this range, and their corresponding fundamental GitHub data conditions are also generally relatively large. increase. On the other hand, with the development of the market, the number of tokens issued in this range has increased significantly. As the number of reference samples increases, the concentration of data distribution has also further improved.
The statistics of the currency prices in this range that exceed the average price increase (black bold) and the corresponding six factors of GitHub data:
Among the 330 data coins, 11 have price increases exceeding the average. Among them, the six factors of GitHub data exceed the average for 5, accounting for about 45%. It is preliminarily inferred that the increase in GitHub data has a certain correlation with the increase in currency prices. The specific correlation will be analyzed in the third part of the article.
Projects that do not rise but fall in the bull market are all projects whose development on Github is very inactive.
Currency price outliers (currency price drops in bull market):
Among the 330 valid samples in this cycle, the prices of 28 tokens fell against the trend, reflecting that these 28 tokens were very weak. At the same time, 90% of the GitHub data corresponding to these tokens is below the average and overall approaches the minimum value.
The 2nd round of bear market (2021.5 to present) GitHub’s more active projects have made a certain contribution to resisting the bear market, but its effect is still not very big
Descriptive statistics of the six factors of GitHub data and currency price increases and decreases:
Sorted by star factor, the data of the top 20 tokens and their other 6 statistics (black and bold are tokens that exceed the average value:
**With the further development of the crypto market, the second round of bear market token data is more scattered, which is speculated to be related to the further differentiation of industry gaps. **The standard deviation values of the seven statistics in this interval are quite different from the average, indicating that the token data in the second bear market stage is more dispersed. In 2021, the token market is still in a booming period of development. More and more people are pouring into the token market. People first target the better-developed and more mature token projects in the market. The corresponding GitHub attention of such tokens There are tens of thousands of statistics, but for the emerging tokens of this period, it still takes time for the public to become familiar with them, and the degree of attention and development they receive is naturally much lower.
Combining the statistics of the top 20 tokens in star data,** it was found that tokens whose six-factor ranking exceeds the average in GitHub data have certain similarities in statistical patterns, and it is inferred that there is a high correlation between the six factors. **At the same time, it was found that the six factors ranked particularly high in the GitHub data are all relatively mature tokens, and their issuance periods were basically between 2015 and 2018, such as Bitcoin, ETH, and dogecoin.
Outliers in currency prices (currency prices rise in bear market):
There are 28 anomalies in the 596 token data. Among them, the GitHub data has more than one factor exceeding the average token, accounting for 28%. According to the table, it is inferred that the increase in GitHub data will have a certain contribution to fighting the bear market, but its effect will not be particularly large. The ability of this type of currency to have such a strong price advantage is mainly determined by factors in other categories.
How to quantify the correlation between GitHub factors and price? Which coefficient will we choose to judge?
In the above, through simple statistical analysis, we found that Github data plays different roles in the bull and bear cycles.
So how do we quantify the correlation between the Github factor and price?
QQ chartTaking the quantile of the sample as the abscissa and the corresponding quantile calculated according to the normal distribution as the ordinate, the sample is represented as a scatter point in the Cartesian coordinate system. If the data set follows a normal distribution, the sample points form a straight line around the diagonal of the first quadrant.It is more reasonable to use Pearson correlation coefficient analysis for data sets that obey normal distribution, and use Pearson correlation coefficient for data sets that do not obey normal distribution.Spearman correlation coefficient analysis is more reasonable.
The results of the six-factor QQ plot in three intervals are as follows:
As can be seen from the table, the sample points of the six factors of the three intervals Star, Fork, Commit, Issues, Pull_requests, and Watchers are not distributed around the diagonal of the first interval, that is, they do not obey the normal distribution.The correlation analysis between the six factors and token prices will be judged based on the results of the Spearman coefficient.
The first round of bear market (2018.1-2020.3): Affected by sample size, the correlation between GitHub factor and currency price is limited
Correlation table between six factors and currency price increase:
The five factors of GitHub data have a positive effect on the resistance of currency prices in bear markets.From the table, it can be seen that the correlation coefficient values of star, fork, issues, pull_requests, watchers and price are all around 0.260, and all show significance at the 0.05 level. Statistically, it shows that the five factors have a positive correlation with the currency price. sex.
**There is no significant relationship between the commit factor and the currency price increase in this range. **The correlation coefficient between commit and currency price increase or decrease is -0.032, close to 0, and the P value is 0.776>0.05, indicating that there is no correlation between commit and price.
The correlation results of star, fork, issues, pull_requests, watchers and price are in line with our previous judgment, that is, they have a certain positive effect. We know that the correlation will not be too high, but a correlation of 0.260 is not enough for us. It is meaningful to follow up on the trend of token prices and construct related factor strategies. **The results of commit are slightly inconsistent with the previous article. **We initially concluded that this is due to limited sample data. **In the second and third intervals, we have collected more token data and will further examine the correlation between commit and price.
The 2nd round of bull market (2020.3-2021.5): The more active GitHub is, the more the currency price will rise
Correlation table between six factors and currency price increase:
In the second round of the bull market, due to the increase in the validity sample from 81 to 330,The correlation between the six factors of star, fork, commit, issues, pull_requests, and watchers and price is significantly enhanced. The correlation is around 0.322, which is significantly higher than the mean correlation value of 0.260 in the first interval, and is significant at the 0.01 level. Among them, the correlation between star, commit, watchers factors and price is as high as 0.350.All six factors in this interval are positively correlated with price, which seems to confirm our speculation that commit and price in the first interval are negatively correlated, that is, there is not enough sample data and is affected by individual extreme values.
The 2nd round of bear market (2021.5 to present) GitHub factor is timely! In a bear market, it is still significantly related to the currency price, but it is not necessarily resistant to decline.
Correlation table between six factors and currency price increase:
For the third interval, the number of effective samples increases to 597. **Compared with the first interval, the correlation between the six factors star, fork, commit, issues, pull_requests, and watchers and price is enhanced, **at the 0.01 level. Under the significance condition, the average correlation value is 0.216, which is slightly higher than the 0.205 in the first bear market, but significantly weaker than the correlation 0.322 required in the second interval.
We believe that the six factors of GitHub data are positively correlated with currency price increases, but they have a certain timeliness!
That is to say, the six factors are more predictive and contribute to the rise and fall of currency prices in a bull market, but are less effective in a bear market. The currency price in a bear market is more affected by other factors (such as volume). Price factors, market sentiment and other alternative factors, etc.), GitHub data only serves as a part of fundamentals and plays a relatively limited role.
Article conclusion
Through the above content, Falcon makes a summary of the conclusion of this article:
1. With the development of the Crypto market and the prosperity of the industry developer ecosystem, Github data and currency prices have become increasingly strongly correlated.
2. From an investment perspective, invest in projects with active Github development and avoid projects with inactive Github development.
3. In a bull market, the more active a project on Github is, the higher the price will rise; in a bear market, the more active a project on Github is, the more resistant it is to falling.
4. The correlation between Github and currency prices is significantly higher in bull markets than in bear markets.
