There has been a lot of fuss lately about alleged seasonal mining swings on the Bitcoin network.

The story goes that, like the rainy season in China comes to a halt every year around the time frame from August to October, the cheap and abundant hydropower drying up. This forces many inefficient late-model miners to close their doors or move elsewhere to find more affordable, accessible energy – by creating migrant or nomadic miners, if you will.

The story also claims that the network is seeing a significant drop in hash rate and difficulty every year, roughly consistent with this seasonal decline in Chinese hydroelectric power generation. This certainly appears to be the case now, in the fall of 2020, as many speculate that the recent loss of about 48 exahashes per second (Eh / s) (30 percent of the network’s total hash rate) is solely due to this phenomenon. is due. But does the data support this for other years?

And what about the recent Bitcoin block height difficulty adjustment 655,200, one of the biggest declines in Bitcoin’s history? Clark MoodyThe dashboard shows that the block’s difficulty has dropped 16 percent based on the aforementioned loss of network hash speed.

Bitcoin block production speed, difficulty adjustment and hash rate

The Bitcoin protocol is fine-tuned and optimized for certain predictable results. The way in which the network achieves these desired results is through a set of carefully designed system rules and guidelines that were incorporated into the free and open-source software at its creation.

The Bitcoin time chain is a series of blocks that verify, group and order transactions based on a preset set of rules. One such rule is the fact that blocks are added to the chain at a programmatic rate of about once every 10 minutes, six blocks per hour, and about 144 blocks per day.

The difficulty of the block is generally proportional to the amount of math miners have to generate to produce a block. The Bitcoin Genesis block had a difficulty of 1. Yesterday the block’s difficulty was 19,997,335,994,446. And at the time of writing, the difficulty is 16,787,779,609,932. This means that today it is about 16.7 trillion times more difficult to discover a block compared to the first block. Blocking issues are a unitless Bitcoin network metric.

To maintain block production speeds of 10 minutes with an ever-changing number of miners and hash rate produced on the network, the software programmatically adapts block difficulty blocks every 2016, or about once every two weeks, commonly referred to as a “Bitcoin block difficulty period.” This difficulty adjustment algorithm elegantly maintains an average block production speed, even at widely fluctuating network hash rates. Over time, as more miners have tried their luck on the network, the difficulty of blocks has been automatically adjusted upwards to compensate and stabilize block production rates.

Bitcoin network hash rate and difficulty, linear

In the graph above, it is seen that difficulty decreases occasionally after a decrease in hash rate, and increases as the hash rate increases. If blocks are hit faster (or slower) on average than every 10 minutes, that would mean more (or less) computing power is being directed to Bitcoin than the difficulty threshold can handle. As more or less miners work towards the chain of blocks, the difficulty of the block becomes targetnumber is changed to compensate so that blocks are created at a rate of approximately one every ten minutes.

While we can clearly see the difficulty decreasing on the linear graph, the above logarithmic graph makes the hash rate and degrees of difficulty less observable. Historically, on the Bitcoin network, the difficulty of blocks has risen upward and block problem reductions are rare. This is partly due to the increasing mining equipment efficiency and effectiveness .

There have been only a handful of months in the last ten years where the block’s difficulty ended at a lower value than when it started. The relentless growth is even more evident in graphs illustrating the Bitcoin network’s average hash rate per month and year. There hasn’t been a month, year on year, where the Bitcoin network hash rate dropped.

Take into account seasonal variations

So, now that we have established that bitcoin hash rate, over long enough time frames, is aggressive NgU (Number Go Up), is there validity for the theory that seasonal fluctuations cause significant changes in network hash rate?

The graph above shows that in the years 2020, 2019 and 2018, the average hash rates on the network by the end of the year were all lower than in the late summer and early fall. And what about other years?

Fall 2013

For 2013, the network does not appear to have had a downward difficulty. This aggressive upward movement may be due to the revolution in ASIC effectiveness that took place during this time.

Fall 2014

For 2014, there were some downward adjustments of the difficulty level at the end of November. However, the difficulty seems to go up for most of the season.

Fall 2015

2015 is a similar story to 2013: the network does not appear to have had a downward difficulty. More and better ASICs were rapidly being developed at this point.

Fall 2016

So 2016 will see a small adjustment in difficulty down around the October time frame. It also seems that the growth of the hash rate and the difficulty of the network is slowing during the same time frame, NgU however.

Fall 2017

2017 tells a similar story to 2016: the network hash rate growth is stagnating, and the difficulty level actually adjusts down a few times. This is especially notable as the price rose aggressively in the same timelines. However, these fluctuations may not be due to migrating miners. In the same seasonal timeframes in 2017, some major miners split the network and manipulated the hash rate to walk other avenues.

Fall 2018

Fall 2018 shows perhaps the most obvious seasonal trend of difficulty and hash rate decreasing rapidly across the network. It is important to note that during these time frames, the price also fell from its all-time highs. A significant percentage of the network, nearly half, went offline seasonally. But because of the elegance of the difficulty adjustment algorithm, the peer-to-peer network kept running.

Fall 2019

Fall 2019 doesn’t show as significant a drop as the 2018 season, but it does show some significant downward difficulty adjustments and hash rate reductions. It also shows a similar barrier to network hash power growth in the same time frames.

Also see

With some of the fastest hash rates ever, the Bitcoin mining industry has endured a harsh 2020 and has increasingly moved out of China.

Fall 2020

So this brings us to today. Centralization of mining is a common criticism of Bitcoin, and the story that many Chinese ASICs are shutting down seasonally appears to be valid for the fall of 2020. Where else would people have about 48 Eh / s (30 percent of the network, as stated above ) unemployed by waiting for abundant and affordable energy? This equates to approximately 3 million Antminer S9 ASIC mining units.

So, where does this drop-off under previous difficulty levels stand in the October and November time frames?

In fact, with chain data, we can see that 2011 had the biggest downward difficulty adjustment and an even larger month-to-month drop, which occurred after a few different difficulty adjustments. This November 2020 difficulty is the largest we’ve seen in recent years, caused by apparent seasonal fluctuations from entrepreneurial Chinese hydropower plants. Between 2012 and 2015, there were no decreases in difficulty between these months.

How do these seasonal difficulty and hash rate fluctuations stack up to full block history on the Bitcoin network? The histograms for both the difficulty adjustments and the hash rate changes provide some insight:

Is this a Bitcoin Mining Death Spiral?

When bitcoin’s network hash rate or price falls, there is always a lot of speculation about the possibility of what is colloquially referred to as the ‘Mining Death Spiral’. The claim is that if the price falls low enough, miners will decide to close and the network will lose a significant percentage of its hash rate. This would force some miners to liquidate their earnings, push market prices down and further this vicious feedback loop until a death spiral ensues. For a network like Bitcoin, this would result in miners being shut down, blocks no longer being mined and the time chain no longer spreading – Bitcoin would fail.

For example, Dogecoin ($ DOGE) is still hitting blocks, so this doom and gloom theory may not hold true for these types of distributed systems. There are many enthusiasts, fanatics and “miners of last resort” who will maintain some of these systems, simply to maintain them, and the belief of the faith.

So let’s imagine that 50 percent of miners stopped mining at the difficulty adjustment block and quit; what would happen?

It would take the remaining half of the network about twice as long to find the 2016 blocks. This would mean four weeks, or about a month, to get to the next difficulty adjustment point. What would the consequences be for the network?

The mempoolwould start to build up, transactions would slow down and fees would increase as people offer new, even scarcer block space. This is actually exactly what we saw a few days after the hash rate dropped recently.

However, the Bitcoin network eventually adjusted the difficulty, as it surfaced every time the 2016 block in the past. This difficulty adjustment algorithm is a very elegant solution to a few different challenges facing the Bitcoin network, and it is because of these types of solutions that the self-regulatory system continues to propagate.



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