Onchain Ethereum Fees Remain Low Ahead of the Merge, 4 L2 Networks Offer Transfers Below a Nickel

newsbtcОпубликовано 2022-08-29Обновлено 2022-08-29

Введение

Ethereum’s Onchain Transfer Cost Remains Low, L2 Transfer and Swap Fees Are Still Cheaper

With just over two weeks until The Merge, Ethereum network fees have reduced significantly as the average ethereum transfer fee has dropped to 0.00092 ether or $1.37 per transaction on August 28. Median-sized fees have slid to 0.00036 ether or $0.544 per transfer, and etherscan.io’s gas tracking tool notes a priority fee will cost 11 gwei or $0.34 to get a transaction confirmed in roughly 30 seconds.

Ethereum’s Onchain Transfer Cost Remains Low, L2 Transfer and Swap Fees Are Still Cheaper

On August 16, the Ethereum Foundation updated a previously published blog post in order to make it clear that The Merge would not reduce gas fees and improve throughput. While The Merge is a little more than two weeks away, Ethereum gas fees have been far less expensive than they were before mid-June.

At that time, in the middle of June, Ethereum’s average gas fees started to drop lower from $3.86 per transaction to 0.00086 ether or $1.46 per transfer during the first week of August. Gas fees are even lower today, as the average fee is currently 0.00092 ether or $1.37 per transaction, according to bitinfocharts.com data.

The average Ethereum network fee on August 28, 2022. The current fee is 0.00092 ether or $1.37 per transaction.

Bitinfocharts.com metrics further show that the median sized Ethereum fee on Sunday is 0.00036 ether or $0.544 per transaction. Etherscan.io data shows gas prices are lower, according to the website’s dedicated gas tracking tool.

The median-sized Ethereum network fee on August 28, 2022. The current fee is is 0.00036 ether or $0.544 per transaction.

Presently, at 4:30 p.m. (EST) on August 28, 2022, the highest “priority” gas fee according to etherscan.io is 11 gwei or $0.34 per transfer. An Opensea settlement will cost $1.17 per transaction, a Uniswap trade will cost a user $3.03 using the priority transfer setting, and to send an ERC20 token like tether (USDT), etherscan.io estimates the cost is around $0.89 per transaction.

While ETH fees are lower, they are two times the size of bitcoin’s (BTC) average transfer fees, which are 0.000039 BTC or $0.785 per transaction on Sunday. Median-sized fees on the Bitcoin blockchain are 0.000013 BTC or $0.258 per transaction, which is also lower than ETH’s median-sized transfer fees.

In terms of 24-hour rewards, ETH miners obtained $41,107,170 in block rewards, while BTC miners acquired $35,976,600 in block rewards plus transaction fees. As onchain Ethereum data fees have dropped a great deal, it is still much cheaper to transact via Ethereum-compatible layer two (L2) payment rails.

Metis Network is the cheapest transfer fee today as l2fees.info indicates the estimated cost to transfer ether via Metis is $0.01 per transfer, and to swap coins via Metis it is around $0.06 per transaction. A Loopring ether transaction will cost an estimated $0.03 per transfer; to trade via Loopring the L2 estimated cost is $0.37 per transaction.

L2 fees via Zksync, Arbitrum, Boba Network, Optimism, Aztec Network, and Polygon Hermez are all lower than onchain transfer fees. Swap fees via these networks are also less expensive than onchain swap fees via a traditional trade on a decentralized exchange (dex) like Uniswap.

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Analysis of Bitcoin Trading Strategies: Why Celebrity Forecasts and Classic Models Fail, Leaving Only These Four Reliable Indicators This analysis examines the failure of common Bitcoin prediction methods and identifies four reliable indicators for constructing a trading strategy. The author reviewed all major BTC prediction approaches from 2017-2025, categorizing them into three groups: celebrity price targets (consistently over-optimistic), analytical models like Stock-to-Flow (broken post-2022), and on-chain signals. The key finding is that more data often creates confusion, not clarity. The strategy discards unreliable elements: celebrity predictions (incentivized to be extreme), pure models (invalidated by post-ETF market changes), and the Fear & Greed Index used alone (too many false signals). Four reliable indicators were selected: 1. **MVRV Z-Score:** Accurately identifies cycle bottoms when entering its green zone (e.g., 2018, 2020, 2022). Note: Its ability to call tops is now ineffective post-2024. 2. **SOPR (28-day MA):** Consistently signals bottoms when below 1.0, indicating holders are selling at a loss. 3. **ETF Net Flow:** A crucial post-2024 metric showing institutional momentum (e.g., sustained inflows = buying). 4. **Macro Liquidity (Fed policy & M2):** Sets the overall directional bias (e.g., bullish during easing cycles). The core strategy involves waiting for a multi-signal共振 (resonance). For example, a bottom signal requires MVRV in the green zone + SOPR < 1.0. A top signal requires overheated on-chain data + sustained ETF outflows. Macro policy sets the overall direction. The Fear & Greed Index is only used as a weighted confirmatory signal, never alone. Action is only taken when three or more indicators align. The author automated this into a monitoring system that sends Telegram alerts only when signals trigger. As of the article's date (April 15, 2026), the system showed a strong bottom signal: extreme fear (F&G=12), MVRV in the buy zone, and SOPR < 1.0. The only contrary signal was weak ETF flows. Historically, such triple on-chain共振 has preceded 100%+ returns. The conclusion emphasizes building a personal framework over relying on external predictions, allowing for iterative improvement and customization based on individual risk tolerance.

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