Research: Miners sent 57K Bitcoin to exchanges in 2022; selling pressure decreasing

cryptoslateОпубліковано о 2022-12-19Востаннє оновлено о 2022-12-19

Анотація

On-chain data shows miners have been capitulating en masse throughout the year. However, this doesn't mean that they have been selling all of their BTC.

This year hasn’t been kind to Bitcoin miners as the invasion of Ukraine in February 2022 triggered a global energy crisis, pushing mining costs through the roof.

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In addition, the collapse of Luna in June tanked Bitcoin’s price to a two-year low, wiping out the little profitability miners had left.

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After a challenging summer with skyrocketing electricity prices, miners welcomed winter scarred by the FTX fallout and even more uncertain prices.

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The 2022 crisis hit both large and small mining operations. Large, publicly-listed mining companies were the ones hit the worst, as a hugely profitable 2021 led many to take on debt and embark on expensive expansion projects.

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The struggle miners have been through isn’t anecdotal – on-chain data shows an incredibly stressful year, according to CryptoSlate’s analysis.

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Miner revenue per Exahash has been dropping sharply since the beginning of the year. Revenue denominated in USD has seen significantly more volatility, spelling trouble for those that decided to sell their BTC holdings.

bitcoin miner revenue per exahash

Graph showing miner revenue per Exahash (Source: Glassnode)

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Looking at hash ribbons further confirms this trend. The metric analyzes the 30-day moving average and the 60-day moving average of the Bitcoin hash rate to determine when miners capitulate. When the 30-day MA drops below the 60-day MA, capitulation begins as Bitcoin becomes too expensive to mine. When the trend reverses, Bitcoin mining returns to being profitable.

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Since the beginning of the year, the market has seen three instances of these moving averages crossing — in June, July, and August. And now, the beginning of December saw the fourth reversal of moving averages, indicating another capitulation has begun.

bitcoin hash ribbons

Graph showing Bitcoin hash ribbons in 2022 (Source: Glassnode)

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On-chain data clearly shows miners have been capitulating en masse throughout the year. However, this doesn’t mean that they have been selling all their BTC.

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Data analyzed by CryptoSlate shows that there has actually been a notable decrease in the amount of BTC miners have been selling since the beginning of the year.

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Looking at the number of outgoing transactions from miner wallets in 2022 reveals a decreasing selling pressure. Outside of a short-lived spike in outgoing transfers in mid-November, the trend has been steadily declining.

outgoing transfers from miner wallets

Graph showing the number of outgoing transfers from miner wallets in 2022 (Source: Glassnode)

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Transfers from miner wallets to exchanges further confirm this trend.

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Since the beginning of the year, miner transfers to all exchanges have been decreasing. Miners sent a total of around 57,000 BTC to exchanges in 2022, with 18,500 going to Binance and around 12,500 going to Coinbase.

miner transfers to exchanges

Graph showing transfers from miner wallets to exchanges in 2022 (Source: Glassnode)

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Diving deeper into Bitcoin’s hash rate reveals that the strength of the network hasn’t been compromised. The selling pressure driven up by rising electricity prices and skyrocketing hardware costs hasn’t affected the hash rate. In fact, Bitcoin’s hash rate is currently climbing back to the yearly high it recorded in mid-November — in spite of Bitcoin’s dropping price.

bitcoin price hash rate

Graph showing Bitcoin’s price and hash rate in 2022 (Source: Glassnode)

Пов'язані матеріали

Bitcoin Trading Strategy Breakdown: Celebrity Predictions and Classic Models All Fail, Only These Four Indicators Remain

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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