Data analysis of the four bull and bear cycles Is the team really related to the coin price?

Analyzing Four Bull and Bear Cycles Examining the Correlation Between Team Dynamics and Coin Price

Author: LUCIDA & FALCON

When we hold cryptocurrencies, “team doing things” is the confidence that “the price will take off in a bull market” and the bottom line for “continuing to hold in a bear market.”

But does “team doing things” really make the price rise more in a bull market? Is it more resistant to decline in a bear market?

This article tells you the answer using 10 years of historical data.

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The four bull and bear cycles of the crypto market

The genesis block of Bitcoin was born in 2009. Its price has gone through multiple bull and bear cycles in the following 14 years, and various industry narratives have emerged, such as the “ICO era,” “public chain boom,” “DeFi summer,” and “NFT wave.”

For analysis convenience, this article defines 2015.07-2018.01 as the first bull market, 2018.01-2020.03 as the first bear market, 2020.03-2021.05 as the second bull market, and 2021.05-present as the second bear market.

The first round of the “ICO” bull market from 2015.7 to 2018.1 is too far away, and there is too little available data to obtain rigorous results. Therefore, this article focuses on analyzing the last three cycles.

What factors can reflect “team doing things”? We have found six factors

Most 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 6 factors from GitHub as quantitative metrics to measure “team doing things,” specifically including: Star, Fork, Commit, Issues, Pull requests, Watchers. Below are the specific meanings and types of the six factors:

The specific introduction of six factors of project GitHub data

The GitHub data of all projects in this article can also be viewed on Falcon’s product, link.

Effective sample size and term explanation

The team has collected the price trends of three market cycles and their corresponding GitHub six-factor data of projects. After outlier handling, there are 81, 330, and 596 valid token samples for the three market cycles, respectively.

The following chart will explain the terms:

The first bear market (2018.1-2020.3) GitHub data has a certain anti-decline effect on the price, but its impact is limited, or it may be related to insufficient sample size

Let’s start with the first bear market:

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Descriptive statistics of the six factors of GitHub data and the price changes:

The data of the first bear market round is relatively dispersed, which is in line with the characteristics of the early stage of the crypto market. The standard deviation values of the seven statistical quantities are far from the average value, indicating that there is a large difference in the prices and GitHub data of different cryptocurrencies. In this period, well-developed tokens like bitcoin and ETH have extremely high attention to various factors on GitHub, but many emerging coins have low attention and developer contributions on GitHub.

The statistical situation of the six factors of GitHub data corresponding to the cryptocurrencies with price drops smaller than the average drop value (highlighted in bold black):

The gray cells represent tokens that oppose the market trend. We believe that these tokens have special characteristics and need to be analyzed in combination with market conditions. There is only one token, binance-exchange, in this interval. Observing its six factors of GitHub data, the values of star and fork are in the top 10 of the statistical quantities, but commit, issues, pull_requests, and watchers are extremely low. This is mainly because the token bnb only had the “platform coin” attribute before 2019 and did not have the “public chain” attribute, so the code is not open source. In the second half of 2018, the market focus was on platform coins, so bnb had a high increase and resisted the decline in this cycle. For this token, only the star and fork factors of GitHub data have some correlation with price.

Among the tokens with price drops smaller than the average value, 40% of the tokens have GitHub factors in the top 10 of the statistical quantities, while the GitHub situation of the remaining tokens is generally low. It can be inferred preliminarily that GitHub factors have a certain positive effect on reducing price drops in this cycle, but this effect is not particularly significant.

The Second Bull Market (2020.3-2021.5) Projects with more active GitHub perform better in the bull market

Descriptive statistics of the six factors of GitHub data and the price changes:

The data of the second bull market round is relatively concentrated, indicating an improvement in the maturity and prosperity of the crypto market. * The standard deviation statistical values of the seven factors in this interval are closer to the average value compared to the statistical situation from 2018 to 2020. Combining the analysis with the actual market situation, on the one hand, the token market has become more mature in 2020, and the tokens that emerged in 2018 have also had some development in this interval, with a generally significant increase in their corresponding fundamental GitHub data. On the other hand, as the market develops, the number of tokens issued in this interval has increased significantly, and with the increase in the number of reference samples, the concentration of data distribution has also further improved.

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The prices of the coins in this range that have exceeded the average increase value (highlighted in bold) and the statistical results of their corresponding GitHub data six factors are as follows:

Out of the 330 data coins, 11 have exceeded the average increase value, with 5 of them exceeding the average value of GitHub data six factors, accounting for about 45%. It can be tentatively inferred that there is a certain correlation between the increase in GitHub data and the rise in coin prices, and the specific correlation size will be analyzed in the third part of the article.

Projects that do not rise but fall in a bull market are very inactive on Github

Abnormal price situation (coin prices falling in a bull market):

Out of the 330 valid samples in this cycle, 28 tokens saw a price decline against the trend, indicating that these 28 tokens are very weak. At the same time, the GitHub data for these tokens is 90% below the average and tends to approach the minimum value.

In the third bear market (2021.5 to the present), projects with more active GitHub activity have contributed to resisting the market decline to some extent, but their impact is still not significant

Descriptive statistics of GitHub data six factors and coin price fluctuations:

The data for the top 20 tokens in terms of the star factor and the other 6 statistical measures (highlighted in bold for tokens that exceed the average value):

As the crypto market further develops, token data in the second bear market phase tends to be more dispersed, which is speculated to be related to further differentiation within the industry. * The standard deviation values of the 7 statistical measures in this range are significantly different from the average, indicating that the token data in the second bear market phase is more dispersed. In 2021, the token market is still in a vibrant stage of development, with more and more people entering the token market. People first focus on well-performing and relatively mature token projects in the market. The statistical measures with GitHub attention reaching tens of thousands are for these types of tokens. However, for emerging tokens during this period, it still takes time for them to become familiar to the public, so naturally, they receive less attention and have lower development levels.

By combining the statistics of the top 20 tokens ranked by star data, it is found that tokens that exceed the average value of GitHub data six factors have certain similarities in statistical patterns, suggesting a high correlation between the six factors. At the same time, it is noticed that the tokens with excellent rankings in GitHub data six factors are relatively mature tokens, most of which were issued between 2015 and 2018, such as bitcoin, ETH, and dogecoin.

Abnormal price situation (price increase in a bear market):

Out of 596 token data points, 28 are abnormal. Among them, there are 6 tokens with factors from GitHub that are above the average value, accounting for 28%. According to the table, it can be inferred that the increase in GitHub data has a certain contribution to resisting the decline in the bear market, but its impact is not particularly significant. Coins like these have such a strong price advantage, mainly determined by factors from other categories.

How do we quantify the correlation between the GitHub factor and price? Which coefficient will we use to determine it?

In the previous section, we found through simple statistical analysis that the effect of GitHub data varies in bull and bear cycles.

So how do we quantify the correlation between the GitHub factor and price?

Q-Q Plot uses the quantiles of a sample as the x-axis and the corresponding quantiles calculated according to a normal distribution as the y-axis, representing the sample as a scatter plot in a Cartesian coordinate system. If the dataset follows a normal distribution, the sample points form a straight line around the diagonal of the first quadrant. If the dataset does not follow a normal distribution, it is more reasonable to use the Spearman correlation coefficient for analysis.

The Q-Q plot results for the six factors in three intervals are as follows:

Based on the table, it is known that the sample points for the six factors (Star, Fork, Commit, Issues, Pull_requests, Watchers) in the three intervals do not form a distribution around the diagonal of the first quadrant, indicating that they do not follow a normal distribution. The correlation analysis between the six factors and token price will be based on the results of the Spearman coefficient.

Round 1 of the bear market (2018.1-2020.3): Limited correlation between GitHub factors and token price due to sample size

Correlation table between the six factors and token price increase:

Five factors from GitHub have a positive effect on price resistance in the bear market. From the table, the correlation coefficient values between star, fork, issues, pull_requests, watchers, and price are all around 0.260, and they all show significance at the 0.05 level, indicating that these five factors are positively correlated with token price.

The commit factor in this interval has no significant relationship with the token price increase. The correlation coefficient value between commit and token price increase is -0.032, close to 0, and the P-value is 0.776>0.05, indicating that commit and price are not correlated.

The correlation results of star, fork, issues, pull_requests, watchers with price align with our previous judgment, indicating a certain positive effect. We already know that this correlation will not be too high, but a correlation of around 0.260 is meaningful for our subsequent research on token price trends and the construction of related factor strategies. The result for commit is slightly different from the previous section, and we preliminarily conclude that it is due to limited sample data. In the second and third intervals, we will collect more token data to further examine the correlation between commit and price.

Second Bull Market (2020.3-2021.5): The more active GitHub is, the higher the coin price rises

The correlation between the six factors and the increase in coin price:

In the second bull market, as the effective sample increases from 81 to 330, the correlation between the six factors (star, fork, commit, issues, pull_requests, watchers) and the price significantly increases. The correlation is around 0.322, significantly higher than the average correlation of 0.260 in the first interval, and it is statistically significant at the 0.01 level. Among them, the factors star, commit, and watchers have a correlation as high as 0.350 with the price. In this interval, all six factors are positively correlated with the price, which seems to confirm our speculation in the first interval that commit is negatively correlated with price. This suggests that the sample data is not sufficient and is affected by individual extreme values.

Second Bear Market (2021.5-present): GitHub factors have timeliness! They are still significantly correlated with the coin price in the bear market, but not necessarily resistant to decline

The correlation between the six factors and the increase in coin price:

In the third interval, the effective sample size increased to 597 compared to the first interval. The correlation between the six factors (star, fork, commit, issues, pull_requests, watchers) and the price strengthened. Under the condition of statistical significance at the 0.01 level, 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 in the second interval.

We believe that the six factors of GitHub data are positively correlated with the increase in coin price, but they have a certain degree of timeliness!

That is, the six factors have stronger predictability and contribution to the increase and decrease in coin price during the bull market, but their utility is relatively weak in the bear market, where the coin price is more influenced by other factors (such as volume-price factors, market sentiment, etc.). GitHub data is only part of the fundamentals and plays a relatively limited role.

Conclusion

Based on the above content, Falcon summarizes the conclusions of this article:

1. With the development of the crypto market and the prosperity of the industry developer ecosystem, there is an increasingly strong correlation between GitHub data and the coin price.

2. From an investment perspective, it is advisable to invest in actively developed projects on GitHub and avoid projects with low GitHub activity.

3. In the bull market, projects with more GitHub activity have higher price increases; in the bear market, projects with more GitHub activity are more resistant to decline.

4. The correlation between GitHub and the coin price is significantly higher in the bull market than in the bear market.

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