Bitcoin's total on-chain transaction volume nearly reached $4 trillion in 2019, with "whales" entering a dormant phase | Review of Bitcoin's on-chain data in 2019 (Part 1)

Between the fluctuations in cryptocurrency prices, what stories unfolded for regular users, "whales," exchanges, and miners? Let's review the data on the Bitcoin blockchain in 2019. This is part one of the series.

"Bitcoin has been the best performing asset in the past decade," according to Merrill Lynch and Bloomberg.

In terms of price increase, this is true. Bitcoin went from $1 to nearly $20,000 in just 6 years. However, it cannot be ignored that Bitcoin also dropped from $20,000 back to $3,000 in just 1 year. The roller-coaster trend of Bitcoin continued in 2019.

According to CoinMetrics' adjusted price data, Bitcoin reached its low point at $3,358.87 on February 7, 2019. Subsequently, hot topics such as IEO, DeFi, Staking, Libra, DE/CP emerged, injecting vitality into the market. By June 26, Bitcoin had risen to $12,863.46, a 282.97% increase from the low point. However, after hovering around the $10,000 mark for three months, Bitcoin entered a phase of oscillating decline, closing at $7,167.40 on December 31, with a drop of 44.28% from its peak.

Amidst the fluctuations in price, what stories unfolded for regular users, "whales," exchanges, and miners? PAData, together with Chain.info, a one-stop data service platform focusing on blockchain transactions, reviewed the Bitcoin chain data of 2019 and released the 2019 Bitcoin Chain Data Rankings, offering a glimpse into the real picture of the Bitcoin network through data.

This article is the first part of the review of the Bitcoin chain data in 2019.

PAData Insights:

Most Active Users in Q2; Number of Addresses Weakly Correlated with Price

The number of active addresses on the chain is considered to be roughly equivalent to the number of active users, with a high likelihood of similar trends between the two.

Statistics show that the total number of Bitcoin chain addresses showed a moderate upward trend in 2019, growing by 24.72% for the whole year. In the second quarter, the number of chain addresses exceeded 62 million, including 35.0398 million active addresses (addresses that had transaction activities on that day, excluding addresses with first-time transactions) and 27.8514 million new addresses (addresses with first-time transaction activities), marking the most active period for users throughout the year, while Bitcoin's price was rapidly climbing.

May saw the highest number of new addresses for the whole year, reaching 12.2304 million. However, due to Bitcoin's unique UTXO model, the change balance of transactions automatically enters a new address, so only a portion of the new addresses may represent new users. June, on the other hand, had the highest number of active addresses for the entire year, reaching 9.9234 million, which can be considered the most active month for existing hodlers.

By comparing the monthly price trends, it can be observed that July, August, and September, which had higher average prices, did not correspond to higher numbers of active addresses and new addresses on the chain. Instead, as the average monthly price gradually increased, the numbers of active addresses and new addresses decreased month by month.

What kind of relationship exists between the secondary market price and the number of chain addresses?

PAData calculated the Pearson correlation coefficients between the total number of active addresses, new addresses, total addresses, and the average daily prices of the past 7 days (excluding the current day), the past 3 days (excluding the current day), the current day, the next 3 days (excluding the current day), and the next 7 days (excluding the current day) for the whole year. The higher the absolute value of the coefficient, the higher the potential correlation between the two.

From the statistical results, none of the correlations reached a significant level. However, the correlation between the number of active addresses and the price was slightly higher than that of new addresses. Throughout the year, new addresses showed little correlation with the price. As for active addresses, they showed a weak correlation with the average price of the previous 7 days, with a coefficient close to 0.4, indicating that a higher average price in the previous 7 days may slightly incentivize transactions for existing hodlers. The correlation coefficients between the number of active addresses and the average price of the next 3 days and the next 7 days were only around 0.31, indicating that, overall, the on-chain transactions of existing hodlers had little impact on the price. This may be related to whales holding more Bitcoin chips, the weaker influence of regular users, and the asynchronous settlement of exchanges off-chain.

Furthermore, the correlation between the total number of addresses, including active and new addresses, and the current day's price, the price of the next 3 days, and the price of the next 7 days was slightly higher than the correlation between the number of active addresses, new addresses, and different periods of prices during the same period. This may imply that the growth in the total user base represented by a portion of new addresses and the existing hodlers represented by active addresses had a slight impact on the subsequent price increase.

PAData's further analysis found that the research on price and on-chain addresses was greatly influenced by different statistical time ranges. For example, in May, the correlation coefficient between the number of active addresses and the average price of the previous 7 days reached 0.57, and the correlation with the average price of the previous 3 days reached 0.64. This demonstrates a scenario where, after a clear upward trend in late April, the rising price stimulated the trading behavior of existing hodlers. In July, the correlation coefficient between active addresses and the average price of the next 3 days reached 0.52, and with the average price of the next 7 days reached 0.54, indicating that after Bitcoin surpassed the $10,000 mark at the end of June, more hodlers started trading, leading to the price running at a high level.

Total On-Chain Transaction Volume Approaching $4 Trillion; Transaction Count Misaligned with Price

Compared to the intense fluctuations in price, the number of on-chain Bitcoin transactions tended to be stable. The total number of on-chain transactions in 2019 exceeded 1.19 billion for the whole year, with monthly transactions averaging around 10 million. May had the highest number of transactions for the whole year, totaling 11.5055 million, followed by April with 11.003 million transactions, and the months of June, July, and August also saw transaction numbers exceeding 10 million.

Combining the monthly price trends, it can be observed that the distribution of total on-chain transactions per month was misaligned with the average monthly price. The months with the highest number of on-chain transactions were April, May, and June, while the months with the highest average price were June, July, and August. In other words, the frequency of on-chain transactions initiated before the price, and the price level did not significantly affect the frequency of on-chain transactions.

According to the cumulative total on-chain transaction amount for the whole year, the actual global market size of Bitcoin in 2019 reached $3.93 trillion, approximately ¥27.23 trillion converted at the January 9 exchange rate. According to data from Oriental Wealth Choice, the trading volume of A-shares in 2019 was about ¥121.60 trillion (excluding new listings that year), making the total on-chain transaction volume of Bitcoin around a quarter of that. China's largest A-share trading company, Ping An, had a trading volume of only ¥12.4 trillion, making Bitcoin's total on-chain transaction volume more than 20 times that. It can be said that as an asset target, Bitcoin's market size is still relatively small, but when compared to specific stock targets, the market size is significant.

In August, which had the highest on-chain transaction volume this year, the transaction volume reached $790.423 billion, especially on August 21, 22, and 23, where daily transaction volumes reached $105.208 billion, $248.891 billion, and $118.573 billion, respectively, while on regular days, it was only $62.311 billion at its highest. However, there is currently no consensus on the reasons for the abnormal transaction volumes on these three days, which may be influenced by factors such as over-the-counter trading, dark web transactions, and institutional fund inflows.

Overall, the total monthly on-chain transaction volume showed a certain consistency with the price, with June, July, and August having higher on-chain transaction volumes and also higher prices.

"Hibernating Whales": Inactive Large Transactions by Whales Unrelated to Transaction Frequency and Amount

If addresses with balances exceeding 2,000 bitcoins outside of exchanges are defined as "whale" addresses, these addresses account for roughly 0.01% of the total active Bitcoin addresses. According to statistics, in 2019, non-exchange "whale" addresses averaged about 1,097 single large transfers exceeding 50 bitcoins per month, or approximately 3 times a day. The second quarter was the period with the most frequent large transfers by non-exchange "whales," with a total of 3,910 large transfers in April, May, and June, reaching a peak of 1,474 large transfers in April.

Despite the total number of large transfers by non-exchange "whales" reaching 13,200 for the whole year, involving a total of 1,614 "whale" addresses, 780 of these addresses were only involved in one large transfer, and 671 "whale" addresses had fewer than 10 large transfers, or less than one per month. These two categories of "whale" addresses with inactive large transfers accounted for 89.90% of the total, with only 1.55% of "whale" addresses having more than 100 large transfers for the whole year. Overall, large transfers by non-exchange "whales" were not active in 2019. The "whales" were essentially in a "hibernation period."

The most active non-exchange "whale" in large transfers in 2019 was "3Gh8v," with a total of 682 large transfers for the year, equivalent to 13 large transfers per week (7 days), showing high activity. Additionally, "392LK," "3CfRK," "3EaWc," and "14BWH" had more than 450 large transfers for the year, equivalent to 8 large transfers per week (7 days).

When combined with the monthly price trends, the activity of large transfers by non-exchange "whales" was most active in the second quarter, rather than during the high points of the year in July and August. The activity of non-exchange "whales" aligned with the total monthly on-chain transaction volume, moving before the price did. Is there a relationship between "whale" activities and price? PAData calculated the Pearson correlation coefficients between the total number of large transfers and the transfer amounts of non-exchange "whales" and the average price of the past 7 days (excluding the current day), the past 3 days (excluding the current day), the current day, the next 3 days (excluding the current day), and the next 7 days (excluding the current day) for the whole year. The higher the absolute value of the coefficient, the higher the potential correlation between the two.

According to the statistical results, there was no correlation between the number of large transfers and the amount of large transfers and different periods of prices, even when the observation time range was narrowed down to each month. The correlation coefficients between any two were not above 0.3, indicating that the activity of non-exchange "whales" was not directly related to the secondary market price.

Data Explanation: [1] The statistics of large transfers by "whales" here are determined based on either the sender or recipient being identified as a "whale." If both parties in the transaction are "whales," it will be recorded as 2 large transfers. [2] The statistics of the large transfer amount by "whales" here are determined based on either the sender or recipient being identified as a "whale." If both parties in the transaction are "whales," only 1 large transfer amount is recorded.

This article is from our partner PANEWS

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