What is Ethereum?

Ethereum is a decentralized, open-source blockchain platform that enables the creation of smart contracts and decentralized applications (dApps). It is the second largest cryptocurrency by market capitalization, behind only Bitcoin.

Ethereum was first proposed in 2013 by Vitalik Buterin, a young programmer and cryptocurrency enthusiast. Buterin saw the potential for blockchain technology to do more than just enable financial transactions, and he proposed using it to create a platform for building decentralized applications.

The Ethereum platform is powered by Ether, the cryptocurrency that is used to pay for the computational resources required to execute smart contracts and dApps on the network. Ether is also used as a form of currency for trading and other financial transactions.

One of the key features of Ethereum is its ability to create and execute smart contracts. A smart contract is a computer program that can automatically execute predefined actions when certain conditions are met. This allows for the creation of decentralized applications that can automate processes and reduce the need for intermediaries.

Overall, Ethereum is a powerful and versatile blockchain platform that has the potential to revolutionize a wide range of industries. With its ability to create and execute smart contracts, and its use of a virtual machine and built-in programming language, Ethereum has the potential to disrupt traditional business models and enable new forms of decentralized collaboration and commerce.

How much did ETH increase?

Methodology:

• Calculate the hourly average price of ETH using the ethereum.core.fact_hourly_token_prices table. ETH is the only token without a token address so we filter by where token_address is null and state that the date has to be between Jan 1 and Jan 16.

• We calculate the price difference using the following formula: ((avg_price_jan_16 - avg_price_jan_1)/avg_price_jan_1)*100

Findings

• The price of ETH has increase significantly between January 1st and January 16th, at about 30%.

What on-chain activity could correspond to the price increase?

In the next sections, we’ll examine numerous metrics that could correspond to the increase in the price of ETH.

• Users
• Transactions & Fees
• Transfers
• Swaps
• NFT’s

Topics Explored

Since 2023, the price of the ETH has increased significantly. This dashboard focuses on providing insight into this price increase. In this dashboard three topics will be explored:

• What on-chain activity could correspond to the recent increases in ETH price?
  • For finding metrics that could correspond to the price of ETH, we’ll use the following method:
    • plot the hourly data for the metric in bars between Jan 1 and Jan 16
    • plot a moving average of the metrics to better illustrate the trend
    • plot the price of ETH
    • judge the correspondence between the metric and price by visually examining the similarity in trend between the price of ETH and the moving average.
• What major dapps, tokens or similar have risen with or more than ETH between Jan 1 and Jan 16?
  • For this, we’ll examine the price action of other tokens on Ethereum and calculate the difference in price between Jan 1 and Jan 16.
• How has user activity, including in specific protocols, changed between Jan 1 and Jan 16?
  • For this, we’ll examine the metrics like swap volume, active users and swap transactions for the major protocols on Ethereum.

By default, all graphs are on the hourly timeframe. However this can be changed to daily and weekly above.

Transactions & Fees

Methodology:

• Number of transactions
  • Using the ethereum.core.fact_transactions table, count the number of distinct transactions using count(distinct(tx_hash)) and group by time period
• Transaction Volume
  • Using the ethereum.core.fact_transactions table, sum over the column eth_value and group by time period.
• Total transaction fee
  • Using the ethereum.core.fact_transactions table, sum over the column tx_fee and group by time period
• Average transaction fee

  • Using the ethereum.core.fact_transactions table, divide the total transaction fee by the number of transactions and group by time period

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Findings

• The number of transactions, average transaction fee and total transactions fee seem to have been relatively stable during the price increase.
• It is clear that there were some noticeable increases in the transaction volume in ETH when the price was increasing. Therefore, the transactions volume could correspond to the price increase.

Transfers

Methodology:

• Number of transfer transactions:
  • Using the ethereum.core.ez_eth_transfers table, count the number of distinct transactions using count(distinct(tx_hash)) and group by time period
• Transfer Volume:
  • Using the ethereum.core.ez_eth_transfers table, sum the total transfer volume by using sum(amount) and group by time period.

Findings

• The number of transfer transactions also remained relatively flat during the price increase.
• However, the Transfer Volume also showed spikes when the price was moving. The moving average also shows a slight increase in transfer volume around Jan 10. Therefore, the transfer volume could correspond to the price increase.

Swaps

Methodology:

• Number of swap transactions:
  • Using the table ethereum.core.ez_dex_swaps , count the number of swapping transactions using count(distinct(tx_hash)) and group by time period
• Swap Volume in USD:
• Using the table ethereum.core.ez_dex_swaps , calculate the swap volume by taking the average of the incoming and outgoing swap value: sum((amount_in_usd+amount_out_usd)/2).

Findings

• The number of swap transactions seems to have also stayed relatively flat.
• For swap volume, there were some spikes during the price increase, but the moving average shows that it did not increase as much as the price. Therefore, we can conclude that swaps did not correspond to the price of ETH.

NFT’s

Methodology:

• NFT sale transactions:
  • using the table ethereum.core.ez_nft_sales count the number of transactions using count(distinct(tx_hash)) and group by time period
• NFT sale volume
• using the table ethereum.core.ez_nft_sales calculate the sale volume in USD using sum(price_usd) and group by time period
• NFT mint transactions:
  • using the table ethereum.core.ez_nft_mint count the number of transactions using count(distinct(tx_hash)) and group by time period
• NFT mint volume
  • using the table ethereum.core.ez_nft_mint calculate the sale volume in USD using sum(mint_price_usdand group by time period

Findings

• Judging by the moving averages of all the different NFT graphs, there does not seems to be an upward trend. Only with the NFT mint volume there seems to be some volume where the price was increasing fast. Otherwise there does not seems to be any correspondence between the price increase and NFT metrics.

Users

Methodology:

• New Users
  • Using the ethereum.core.fact_transactions table, find the first transactions of each from_address and count the number of users that made their first transaction in a given time period
• Active Users
  • Using the ethereum.core.fact_transactions table, count the distinct number of users that made a transaction in a given time period using count(distinct(from_address))

Findings

• Interestingly, both the number of new and active users seems to have stayed flat during the price run. However, there was a large number of new and active users on Jan 5.
• Also, just before the second run in price on January 9, there was a period where the number of active users was high.
• There were some peaks in both the new and active users during the run, but for the most part both stayed flat. Therefore, we can conclude that new and active users did not correspond to the price increase.

Which tokens have increased more than ETH?

Methodology:

• using the table ethereum.core.fact_hourly_token_prices find the prices of all tokens on Ethereum on Jan 1 and Jan 16 and take the average price for those days.
• Then calculate the price change in % using the following formula ((avg_price_jan_16 - avg_price_jan_1)/avg_price_jan_1)*100
• Then, select the tokens that have increased more than Ethereum and list them in order based on price change.

Findings

• The token that increased the most in the period is the token BUND which increased more than 6k%
• There seem to be mostly just minor altcoins that have risen more than ETH in the given period.

User Activity on Protocols

Methodology:

• Distinct swappers
  • Using the table ethereum.core.ez_dex_swaps count the number of distinct swappers using count(distinct(origin_from_address)) and group by platform and time period.
• Number of swaps
  • Using the table ethereum.core.ez_dex_swaps count the number of swap transactions using count(distinct(tx_hash)) and group by platform and time period.
• Swap Volume
  • Using the table ethereum.core.ez_dex_swaps calculate the volume by taking the average of the in and out amount: sum((abs(amount_in_usd) + abs(amount_out_usd))/2)
• ETH Price vs Uniswap pool balance:
  • Using the table ethereum.uniswapv3.ez_pool_stats calculate the total balance of all pools using avg(token0_balance_usd+token1_balance_usd)

Findings

• The number of distinct swappers, number of swaps and the swap volume all seem to be in the same uptrend as the price of ETH.
• The Uniswap pool balances is extra interesting as it follows the increase of the price of ETH almost exactly. Therefore, we can say that the Uniswap pool balances definitely correspond the to the price of ETH.

Key Findings

• The price of ETH has increased significantly between January 1st and January 16th, at about 30%.
• Interestingly, both the number of new and active users seems to have stayed flat during the price run. However, there was a large number of new and active users on Jan 5.
• Also, just before the second run in price on January 9, there was a period where the number of active users was high.
• There were some peaks in both the new and active users during the run, but for the most part both stayed flat. Therefore, we can conclude that new and active users did not correspond to the price increase.
• The number of transactions, average transaction fee and total transactions fee seem to have been relatively stable during the price increase.
• It is clear that there were some noticeable increases in the transaction volume in ETH when the price was increasing. Therefore, the transactions volume could correspond to the price increase.
• The number of transfer transactions also remained relatively flat during the price increase.
• However, the Transfer Volume also showed spikes when the price was moving. The moving average also shows a slight increase in transfer volume around Jan 10. Therefore, the transfer volume could correspond to the price increase.
• The number of swap transactions seems to have also stayed relatively flat.
• For swap volume, there were some spikes during the price increase, but the moving average shows that it did not increase as much as the price.
• Judging by the moving averages of all the different NFT graphs, there does not seems to be an upward trend. Only with the NFT mint volume there seems to be some volume where the price was increasing fast. Otherwise there does not seems to be any correspondence between the price increase and NFT metrics.
• The token that increased the most in the period is the token BUND which increased more than 6k%
• There seem to be mostly just minor altcoins that have risen more than ETH in the given period.
• The number of distinct swappers, number of swaps and the swap volume all seem to be in the same uptrend as the price of ETH.
• The Uniswap pool balances is extra interesting as it follows the increase of the price of ETH almost exactly. Therefore, we can say that the Uniswap pool balances definitely correspond the to the price of ETH.