LUCIDA: A 10-Year Data Observation, Is There Really a Connection Between "Teams Doing Things" and Coin Prices?
"Does 'the team is working' really make the price of the coin rise more in a bull market? Is it more resistant to declines in a bear market?"Written by: LUCIDA
When we hold crypto assets, "the team is working" is the confidence that "the coin price will take off in a bull market" and also the bottom line for "continuing to hold during a bear market."
But does "the team is working" really lead to higher coin prices in a bull market? Is it more resilient in a bear market?
This article uses 10 years of historical data to provide you with the answer.
Four Bull and Bear Cycles in the Crypto Market
Bitcoin's genesis block was born in 2009, and its price has shown multiple alternating bull and bear cycles over the subsequent 14 years, along with the emergence of industry narratives such as the "ICO era," "public chain explosion," "DeFi Summer," and "NFT wave."
For the sake of analysis, this article defines the period from July 2015 to January 2018 as the first bull market, from January 2018 to March 2020 as the first bear market, from March 2020 to May 2021 as the second bull market, and from May 2021 to the present as the second bear market.
The first "ICO" bull market from July 2015 to January 2018 is too far in the past, and the available data is too limited 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 working"? We found six factors!
The vast majority of projects in the industry are based on blockchain technology, and their code is open source on GitHub (GitHub is a platform for code hosting and sharing).
Therefore, Falcon uses six factors from GitHub as quantitative standards to measure "the team is working," specifically including: Star, Fork, Commit, Issues, Pull requests, Watchers. Below are the specific meanings and types of the six factors.
Specific introduction of the six GitHub data factors for projects
The GitHub data for all projects in this article can also be seen on Falcon's product, visit the link: https://falcon.lucida.fund/ch/asset_tracker/73/github?uid=
Product page screenshot
Effective Sample Size and Terminology Explanation
The team has compiled the price trends of coins during the three market cycles and their corresponding project GitHub six-factor data. After processing outliers, the three market cycles retained 81, 330, and 596 effective token samples, respectively.
The following charts will include terminology explanations:
Specific explanations of terms
First Bear Market (2018.1-2020.3): GitHub data has a certain anti-dip effect on coin prices, but the effect is limited, possibly due to the small sample size.
Let's start with the first bear market:
Descriptive statistics of GitHub data six factors and price fluctuations during the bear market:
The token data during the first bear market is relatively dispersed, reflecting the characteristics of the early stage of the crypto market's rise. The standard deviation values of the seven statistics during this period are far from the average, indicating significant differences in price and GitHub data among different coins. Tokens that were more mature during this stage, such as Bitcoin and ETH, had extremely high attention on their GitHub factors, while many emerging coins had relatively low attention and developer contributions on GitHub.
The statistical situation of coin prices that fell less than the average decline (bold black) and their corresponding GitHub data six factors:
The gray boxes represent tokens that move against the market trend, which we believe have a special nature and need to be analyzed comprehensively in conjunction with market conditions. During this period, only Binance Exchange was observed; its GitHub data six factors show that the star and fork values are in the top 10 of statistics, but commit, issues, pull requests, and watchers are extremely low, mainly because the BNB token only had "platform token" attributes before 2019 and no "public chain" attributes, thus the code was not open source. In the second half of 2018, the market focus shifted to the platform token sector, leading to a high increase in BNB, which was resilient during this cycle. For this token, only the star and fork factors of the GitHub data have a certain correlation with price.
Among the tokens with price declines less than the average, 40% of the tokens have GitHub factors in the top 10 of statistics, while the remaining tokens generally have low GitHub conditions. It is preliminarily inferred that during this cycle, GitHub factors have a certain positive effect on reducing price declines, but this effect is not particularly large.
Second Bull Market (2020.3-2021.5): Projects with more active GitHub presence rise more in a bull market.
Descriptive statistics of GitHub data six factors and price fluctuations during the bull market:
The token data during the second bull market is relatively concentrated, indicating an increase in the maturity and prosperity of the crypto market. The standard deviation statistics of the seven statistics during this period are closer to the average, and compared to the 2018-2020 statistics, the sample data distribution during this period is more concentrated. Analyzing in conjunction with the actual market situation, on one hand, the token market has developed relatively maturely by 2020, and tokens that emerged in 2018 have all seen some development during this period, with their corresponding fundamental GitHub data generally showing significant increases. On the other hand, as the market developed, the number of tokens issued during this period increased significantly, and with the increase in the number of reference samples, the concentration of data distribution further increased.
The statistical situation of coin prices that rose more than the average increase (bold black) and their corresponding GitHub data six factors:
Among the 330 data, 11 tokens had price increases exceeding the average, of which 5 had GitHub data six factors exceeding the average, accounting for about 45%. It is preliminarily inferred that the increase in GitHub data has a certain correlation with the rise in coin prices, and the specific size of the correlation will be analyzed in the third part of the article.
Projects that fell instead of rising in a bull market are all very inactive in GitHub development.
Price anomaly situation (price decline in a bull market):
Among the 330 effective samples in this cycle, 28 tokens experienced price declines against the trend, reflecting the extreme weakness of these 28 tokens. At the same time, 90% of the GitHub data corresponding to these tokens is below the average and overall close to the minimum value.
Second Bear Market (2021.5 to Present): More active GitHub projects contribute to resilience in the bear market, but their effect is still not significant.
Descriptive statistics of GitHub data six factors and price fluctuations during the bear market:
Ranking the top 20 tokens by star factor and their other six statistical data (bold black indicates tokens exceeding the average):
As the crypto market further develops, the token data during the second bear market has become more dispersed, which is speculated to be related to the further differentiation within the industry. The standard deviation values of the seven statistics during this period differ significantly from the average, indicating that the token data during the second bear market is more dispersed. The token market in 2021 is still in a booming development phase, with more and more people entering the token market, and people first targeting tokens that are performing well and are relatively mature in the market. The GitHub attention for such tokens reaches statistical values of tens of thousands, but for emerging tokens during this period, it still takes time for the public to become familiar with them, resulting in relatively low attention and development levels.
Combining the statistical situation of the top 20 tokens ranked by star data, it is found that tokens with GitHub data six factors ranking above the average have certain similarities in statistical patterns, indicating a high correlation among the six factors. It is also found that those with particularly high rankings in GitHub data six factors are all relatively mature tokens, with issuance periods mainly between 2015 and 2018, such as Bitcoin, ETH, and Dogecoin.
Price anomaly situation (price increase in a bear market):
Among the 596 token data, there are 28 anomalies, of which 6 tokens have one or more GitHub data factors exceeding the average, accounting for 28%. Based on the table, it is inferred that the increase in GitHub data has a certain contribution to resilience in the bear market, but its effect is not particularly large. The strong price advantage of such tokens is mainly determined by other categories of factors.
How to quantify the correlation between GitHub factors and price? What coefficient will we use to judge?
In the above text, we found that the role of GitHub data during bull and bear cycles is different through simple statistical analysis.
So how should we quantify the correlation between GitHub factors and price?
Q-Q Plot uses the quantiles of the samples as the horizontal axis and the corresponding quantiles calculated according to the normal distribution as the vertical axis, representing the samples as scatter points in a Cartesian coordinate system. If the dataset follows a normal distribution, the sample points will form a straight line around the diagonal of the first quadrant. For datasets that follow a normal distribution, it is more reasonable to analyze using the Pearson correlation coefficient, while for datasets that do not follow a normal distribution, it is more reasonable to analyze using the Spearman correlation coefficient.
The Q-Q plot results of the six factors for the three intervals are as follows:
As can be seen from the table, the sample points of the six factors Star, Fork, Commit, Issues, Pull_requests, and Watchers do not cluster around the diagonal line of the first interval, indicating that they do not follow a normal distribution. The correlation analysis of the six factors with token prices will be based on the results of the Spearman coefficient.
First Bear Market (2018.1-2020.3): Limited correlation between GitHub factors and coin prices due to sample size
Correlation table of six factors with price increases:
Five factors of GitHub data have a positive effect on the anti-dip of coin prices during the bear market. From the table, it can be seen that the correlation coefficients of star, fork, issues, pull_requests, and watchers with price are all around 0.260, and all show significance at the 0.05 level, statistically indicating that the five factors are positively correlated with price.
The commit factor in this interval shows no significant relationship with price increases. The correlation coefficient between commit and price fluctuations is -0.032, close to 0, and the P value is 0.776 > 0.05, indicating no correlation between commit and price.
The correlation results of star, fork, issues, pull_requests, and watchers with price align with our previous judgment, indicating a certain positive effect. We know that this correlation will not be too high, but a correlation of 0.260 is meaningful for our subsequent research on token price trends and constructing related factor strategies. The result for commit slightly contradicts our previous findings, and we preliminarily attribute this to the limited sample data. In the second and third intervals, we collected more token data and will further examine the correlation between commit and price.
Second Bull Market (2020.3-2021.5): The more active GitHub is, the more the price rises
Correlation table of six factors with price increases:
In the second bull market, the effective sample size increased from 81 to 330, the correlation of the six factors star, fork, commit, issues, pull_requests, and watchers with price significantly strengthened, with a correlation around 0.322, significantly higher than the average correlation of 0.260 in the first interval, and showing significance at the 0.01 level. Among them, the correlation of star, commit, and watchers with price reaches as high as 0.350. All six factors are positively correlated with price in this interval, which seems to confirm our speculation that commit and price are negatively correlated in the first interval, indicating that the sample data was insufficient and influenced by individual extreme values.
Second Bear Market (2021.5 to Present): GitHub factors are time-sensitive! They are still significantly correlated with price in the bear market, but not necessarily anti-dip.
Correlation table of six factors with price increases:
In the third interval, the effective sample size increased to 597, and compared to the first interval, the correlation of star, fork, commit, issues, pull_requests, and watchers with price has strengthened. Under the significance condition of 0.01, the average correlation is 0.216, slightly higher than the 0.205 in the first bear market, but significantly weaker than the correlation of 0.322 found in the second interval.
We believe that all six factors of GitHub data are positively correlated with price increases, but they have a certain time sensitivity!
That is, the six factors have stronger predictive and contributory effects on price fluctuations in a bull market, but their utility is relatively weak in a bear market. In a bear market, coin prices are more influenced by other categories of factors (such as volume-price factors, market sentiment, and alternative factors), and GitHub data serves only as a part of the fundamentals, playing a relatively limited role.
Conclusion of the Article
Based on the above content, Falcon summarizes the conclusions of this article:
With the development of the crypto market and the prosperity of the industry developer ecosystem, GitHub data increasingly shows a strong correlation with coin prices.
From an investment perspective, it is advisable to invest in projects with active GitHub development and avoid those with inactive GitHub development.
In a bull market, projects with more active GitHub development see higher price increases; in a bear market, projects with more active GitHub development are more resilient.
The correlation between GitHub and coin prices is significantly higher in a bull market than in a bear market.
