Questions were raised over what was labelled a “flash crash” in Bitcoin hash rate last week. Data from Blockchain.com shows the hash rate dropping from 98 EH/s to 67 EH/s. Other data sources such as Coin.Dance report an even more pronounced drop with the figure moving from 98 EH/s to 58 EH/s over the course of a day.
With hash rate used to secure proof-of-work networks, the drop has sparked concern among some analysts. Larry Cermak, Director of Research for The Block, posted a tweet looking for potential explanations for the drop.
Emin Gün Sirer called for businesses to increase the number of confirmations they require for payment in lights of the drops.
Hash Rate Is Unknown
Several researchers have stepped in to point out that the drop may not be as concerning as it first appears. Firstly, hash rate is an unknown metric. The metric displayed on websites such as BTC.com, Blockchain.com, and bitinfocharts.com is inferred from both the interval between blocks and the difficulty level. If block intervals increase, it is inferred that the hash rate has dropped and vice-versa.
Block times are Poisson distributed which means that we know the average block time is ten minutes but the interval between one block and the next is random. It could be one minute but it also it could be over one hour. On average, it will be ten minutes but a series of blocks found in quick succession will infer a high hash rate whereas longer-than usual intervals between blocks will infer a lower hash rate. This is why when we observe raw values for inferred hash rate figures, the graph consists of large spikes up and down to reflect the variance in block time intervals. The seven-day moving average is commonly used instead as an estimate of how much hash rate is deployed.
“herein lies the essence of the problem. If the measurement interval is too short, the estimate becomes vulnerable to the inherent variance in block times.”
Chris Bendiksen, Head of Research at CoinShares
Just Variance?
Chris Bendiksen has noted the drop to be likely just variance. A number of analysts did a deeper dive on the numbers. Nic Carter, co-founder of CoinMetrics, graphed the time interval of the 144-block moving average with block height. He found that there has only been a slight increase in the 144-moving average of block time.
James Prestwich noted the outsized impact of long-block intervals compared to short block intervals when estimating the hash rate. Hash rate has since recovered indicating that the most likely explanation for the observed drop in hash rate was a number of statistical outlier blocks which had highly unlikely long interval times. A number of these outliers can be observed on the graph which Nic Carter shared with one block interval being over 70 minutes.
It is also worth noting that rainy season in Sichuan province is drawing towards an end. Sichuan’s rainy season takes place from April to October each year resulting in abundant energy consumption. As rainy season draws to an end, mining farms operating in the region have informed MinerUpdate that energy production drops by roughly 66% and energy prices rise as a result of this. With Sichuan estimated to account for roughly 50% of Bitcoin hash rate, it is feasible that miners coming offline in the region can contribute to a reduction in the hash rate. However, when it comes to hash rate flash crashes, variance in block intervals is the highly likely answer.
