Visualization Reveals: Giant Bitcoin Whales Exchange Usage

Jan 16 · 6 min read

Tracking bitcoin mining addresses and transactions can help to monitor the dynamics of large holders and institutions (aka “whales”) and make better decisions. Tracking also helps to crack down on criminal activity, cryptocurrency laundering, and dark web transactions. The results of transaction tracking typically include a large amount of complex data, which is difficult for ordinary users to understand, and even more difficult to use.

In response to this data complexity problem, recently developed a product for easy to understand visual display of mining and transactions that visualizes the history and context of large transfers and capital flows at popular addresses. Although this product is still in beta, we hope to show readers the power of address mining and tracking combined with visualization technology through the following examples of recent whale activity.

Graphics Description

In the transaction tracking visualization, the color and size of the node (circle) and transaction inputs (line) represent different values. Because the value of each transaction is very different, different colors and sizes indicate the distribution of values within a particular transaction.

Color: indicates the number of transactions included in the node or line.

Size: indicates the amount of Bitcoin contained in the node or line. The larger the circle or thicker the line, the higher the number.

Transaction tracking

— 01 —

37Xu … SKUs is the fourth-ranked address on the rich list. The address received a huge transfer of 94,504 BTC on September 4, 2019, which was worth about 1 billion US dollars at that time, causing lots of shock in cryptocurrency circles.

From the visual graph of transaction tracking, the transaction has 7 large inputs (each greater than 200 BTC) addresses, of which 1JCe … x2Sy address has 3 inputs, the total transfer of this address is about 53,000 BTC which is the main source of funds. The transaction amount of the remaining input addresses is distributed between 200–15,000 BTC. As shown in the figure, this rich list address has not been transferred coins out.

Chart source:

We can carefully analyze the address 1JCe … x2Sy as the main source of funds. From the visual graph, it can be seen that the funds of this address mainly come from 11 addresses, of which 1L9e … 3d3Q is the main source of funds, and the total remittance is 37,426 BTC. Continuing to track the above address, you can find that its upstream address contains multiple transactions with Huobi. From the tracking of these related exchanges, some clues about the giant whale may be found.

Chart source:

— 02 —

183h … gahM is the 6th address on the rich list ( It can be seen from the transaction tracking visualization that the total 82,773 BTC of this address comes from the address 1Kat … fjx7, which is gathered by 138 large fund transfers (50 BTC or more, the same below). The source of funds for the 1Kat … fjx7 address is very extensive. There are 12 entities from which it has direct large capital transactions. One of them, Huobi Exchange, transferred 23,028 BTC to the address. The remaining addresses are relatively decentralized, and the exchanges eventually tracked include mainstream exchanges such as Binance, Bitstamp, Bitflyer, OKEx, Coinbase, and

Chart source:

— 03 —

3Gh8 … SG1j is an address with frequent on-chain transactions. Since its creation on July 31, 2019, a total of 12,978 transactions have occurred. It can be seen from the transaction tracking visualization that the main funds of the address ultimately come from different exchanges. From where the funds go, it can be seen that the address first transfers the amount to 7 addresses, most of which are 3,000 BTC per transaction, and then the coins of these addresses are scattered to more ordinary addresses, each amount in the range 100- 500 BTC. This kind of behavior of gathering funds first and then breaking them up for several times is typical of money laundering and deserves further monitoring.

Chart source:

— 04 —

3Kzh … NLNS is located at the 26th place on the rich list. According to the visual graph of transaction tracking, it can be seen that the funding source of this address is very broad. After multi-level transaction tracking, it involves more than a hundred addresses and more than 10 exchanges. The address of the main source of funds for this address is 3Cg3 … iuCo, a total of 61,541 BTC. The funds at this address mainly flowed to 1J37 …. sdCn (137,509 BTC) and bc1q …. 89l2 (66,601 BTC), and then eventually flowed to Bitstamp, Bittrex, Kraken, OKEx, Coinbase, Xapo and other exchanges and custodian institutions.

Chart source:

— 05 —

3R1h … jg4B is the 55th address on the rich list, with a total of 260 transactions and a total transaction amount of 435,900 BTC. As can be seen from the visual graph of transaction tracking, the main source of large funds (220,018 BTC) and destinations (211,500 BTC) of this address are Xapo custodians. Although other sources of funds are numerous, and all are associated with Bitfinex transactions, but the transfers are relatively small. It can be inferred that the address should be an address within the Xapo system, but it needs continuous observation and verification.

Chart source:

Circulation Between Exchanges

From the inflow and outflow chart of Huobi Exchange in the past month (December 9 to January 9), we can see that:

  • During this period, Huobi Exchange had a total inflow of 46,315 BTC and a total outflow of 98,420 BTC. The overall state of net outflow was 52,105 BTC.
Inflow and outflow chart of Huobi Exchange in the past month (December 9 — January 9), Chart source:

In the future, will continue to optimize its products, and strive to provide users with the most accurate and concise address transaction tracking and various visualization services. Also, we will track the current popular large-value transactions and special addresses, from our professional perspective of on-chain transaction data, and we welcome your attention!

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A blockchain transaction-focused data service platform

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