Bitcoin Halving Reward and Price History Analysis: Part II
Bitcoin Halving Reward and Price History Analysis: Bitcoin Price Target $404,626.62 by Jan 2022
Interpretation:
1) The orange vertical lines are 1 year before the bitcoin halving. The next 1 year out from halving is May 2019. The bitcoin market usually starts a bull market 1 year out from the halving.
2) The green vertical lines are the bitcoin halving dates. The next halving date is May 2020. The previous halving dates were Nov 2012 and July 2016.
3) The blue vertical lines are a time projection of when we should return to all time new highs based on the last bitcoin halving cycle.
4) The red vertical line is a time projection of the next new high based on the 2020 halving cycle. The high of 2020 cycle should come on Jan 2022.
5) The red horizontal line is a price prediction of the next new high of the 2020 halving cycle. The bitcoin price high prediction on Jan 2022 is $404,626
6) The yellow trend lines trace the projected price movement produced by the halving cycle.
7) The purple box lines trace the bitcoin bear market cycle from the high to the low and back to the old high.
Important Points:
1) The bitcoin halving cycle doubles the cost of production: the same energy and computational power produces only half the number of bitcoins . Read "A Cost of Production Model for Bitcoin" by Adam Hayes for a primer on the importance of the halving cycle for understanding the value of bitcoin.(Ref 1)
2) The bitcoin price drop in the first bitcoin cycle was 86%. If we have a similar decline this halving cycle, then bitcoin can drop to $2606.62 before May 2019 and the next 2020 halving cycle.
3) I believe that the bull run starts one year before the halving because miners stop deploying new computational capital/power in anticipation of the doubling of future production costs.
4) Bitcoin price accelerates up into the halving, and one year after, as market participants engage in price discovery under a new cost of production regime. The market over shoots and we crash in the 3rd year of the cycle. Specifically, we run in 2011,2012, 2013 and crash in 2014. Similarly, we run in 2015, 2016, 2017, and crash in 2018. Therefore, I propose that we run in 2019, 2020, 2021, and crash in 2022. This analysis may also partially explain the crash of 2010.
5) Finally, these halving dates reflect perfect symbolic singularities. Symbolic singularities are discursive/argumentation phenomena where market participants have foreknowledge of market moving events e.g., presidential elections, Olympic events, earnings reports, etc.. Certain classes of symbolic singularities have a bullish bias, such as when limited cognitive/market attention is distributed over under attended assets e.g.,
a) the HGP or Human Genome Project’s (Ref 2) claim that it would map the human genome before 2000 led to the genomic/biotech bubble of the late 1990s.
b) the Chinese Olympics of 2008 as a showcase of China's arrival on the global economic stage and the ensuing 2006/2007 Chinese bubble.
Further Bitcoin Mining Analysis:
1) The difficulty (Ref 3) of mining a bitcoin block is adjusted by the bitcoin code every 2016 blocks. This averages out to adjustment every two weeks. The mining difficulty normally follows the hash rate very closely.(Ref 4) When the hash rate declines the difficulty declines. When the hash rate rises the difficulty increases. When the average cost of mining falls below the cost of production,(Ref 5) marginal or high cost miners begin to take mining rigs offline. This causes the hash rate to fall and thus a fall in the difficulty of mining a block. Those mining rigs that remain and continue to mine usually have a competitive advantage and experience an increase in profitability as competing mining rigs leave the mining process. This process also works in reverse as price rises. Interestingly, where mining at a loss causes price suppression in most commodity markets, rational miners will continue to mine bitcoin at a loss to accelerate the time to the next difficulty adjustment and thus drop the cost of mining. This creates a theoretic game of “chicken” where every miner hopes that every other miner will take their mining rigs offline first.
2) Bitcoin price fluctuates far more than bitcoin mining costs (e.g., rent, wages, computer equipment, energy, etc.,). This creates a reflexive or self-reinforcing positive price dynamic where increases in price leads to further increases in price during booms and declines in price lead to further declines in price during crashes. The largest and most constant factor shaping bitcoin price is the sale of bitcoin by miners to meet the cost of production. In the current Bitcoin Halving Cycle, 12.5 bitcoins are produced every ten minutes, 1800 per day, 54,000 per month.(Ref 6) Within a boom or rising price environment, miners need to sell less bitcoin every month to meet their costs. Every month the supply of bitcoin available for sale decreases and this leads to future price increases. In contrast, within a crash or falling price environment, miners need to sell more bitcoin every month to meet their costs. Every month the supply of bitcoin available for sale increases and this leads to future price decreases. Once this price dynamic begins from the bottom of a crash or the top of a boom, it accelerates until the reflexive price dynamic switches back to the previous reflexive price dynamic.
3) What causes the switch in this reflexive price dynamic at the bottom or top of the Bitcoin Price Halving Cycle? I am researching this important question right now. My preliminary thoughts suggest at least two critical factors that require further analysis.
a) The first factor is fundamental - the critical mass of marginal miners entering or leaving the bitcoin mining process long enough to allow for the difficulty rate to encourage or discourage new entrants into the mining space. Once the rise in bitcoin price is greater than the price miners need to sell bitcoin to meet their costs, demand will begin to outstrip supply and higher prices will lead to higher prices. Conversely, once the decline in bitcoin price is less than price miners need to sell bitcoin to meet their costs, demand will begin to fall behind supply and lower prices will lead to lower prices. Knowing the average production costs of marginal miners as well as the bitcoin reserves of weak and strong participants in the mining community should shed light on the probability of critical mass miner capitulation and/or entry.
b) The second factor is rhetorical/psychological - miners’ foreknowledge of the bitcoin halving cycle itself. Specifically, miners know from the bitcoin code an approximate date where the costs of producing a bitcoin is going to double. This knowledge is a symbolic singularity or rhetorical/psychological trigger for miners that shapes miners estimates of their ability to play and win the “game of chicken” with other miners. Miners at the margin surmise that they are not going to survive the current bitcoin halving cycle and those more established and efficient players surmise they will survive the cycle. This knowledge/belief shapes miners’ decision to remain in the game or capitulate. Historically, the time frame of one year before the halving has resulted in the bottoming of the market and the beginning of a new rising price dynamic. In addition, anticipation of this rising price dynamic may also encourage miners with bitcoin reserves to decrease their selling of bitcoin thus increasing the rise in bitcoin price.
References
1 economicpolicyresearch.org/econ/2015/NSSR_WP_052015.pdf
2 en.wikipedia.org/wiki/Human_Genome_Project
3 en.bitcoin.it/wiki/Difficulty
4 theblockcrypto.com/tiny/bitcoins-mining-difficulty-saw-the-largest-drop-in-the-asic-era/
5 coinshares.co.uk/wp-content/uploads/2018/11/Mining-Whitepaper-Final.pdf
6 quora.com/How-many-new-bitcoins-are-created-on-average-per-day
Interpretation:
1) The orange vertical lines are 1 year before the bitcoin halving. The next 1 year out from halving is May 2019. The bitcoin market usually starts a bull market 1 year out from the halving.
2) The green vertical lines are the bitcoin halving dates. The next halving date is May 2020. The previous halving dates were Nov 2012 and July 2016.
3) The blue vertical lines are a time projection of when we should return to all time new highs based on the last bitcoin halving cycle.
4) The red vertical line is a time projection of the next new high based on the 2020 halving cycle. The high of 2020 cycle should come on Jan 2022.
5) The red horizontal line is a price prediction of the next new high of the 2020 halving cycle. The bitcoin price high prediction on Jan 2022 is $404,626
6) The yellow trend lines trace the projected price movement produced by the halving cycle.
7) The purple box lines trace the bitcoin bear market cycle from the high to the low and back to the old high.
Important Points:
1) The bitcoin halving cycle doubles the cost of production: the same energy and computational power produces only half the number of bitcoins . Read "A Cost of Production Model for Bitcoin" by Adam Hayes for a primer on the importance of the halving cycle for understanding the value of bitcoin.(Ref 1)
2) The bitcoin price drop in the first bitcoin cycle was 86%. If we have a similar decline this halving cycle, then bitcoin can drop to $2606.62 before May 2019 and the next 2020 halving cycle.
3) I believe that the bull run starts one year before the halving because miners stop deploying new computational capital/power in anticipation of the doubling of future production costs.
4) Bitcoin price accelerates up into the halving, and one year after, as market participants engage in price discovery under a new cost of production regime. The market over shoots and we crash in the 3rd year of the cycle. Specifically, we run in 2011,2012, 2013 and crash in 2014. Similarly, we run in 2015, 2016, 2017, and crash in 2018. Therefore, I propose that we run in 2019, 2020, 2021, and crash in 2022. This analysis may also partially explain the crash of 2010.
5) Finally, these halving dates reflect perfect symbolic singularities. Symbolic singularities are discursive/argumentation phenomena where market participants have foreknowledge of market moving events e.g., presidential elections, Olympic events, earnings reports, etc.. Certain classes of symbolic singularities have a bullish bias, such as when limited cognitive/market attention is distributed over under attended assets e.g.,
a) the HGP or Human Genome Project’s (Ref 2) claim that it would map the human genome before 2000 led to the genomic/biotech bubble of the late 1990s.
b) the Chinese Olympics of 2008 as a showcase of China's arrival on the global economic stage and the ensuing 2006/2007 Chinese bubble.
Further Bitcoin Mining Analysis:
1) The difficulty (Ref 3) of mining a bitcoin block is adjusted by the bitcoin code every 2016 blocks. This averages out to adjustment every two weeks. The mining difficulty normally follows the hash rate very closely.(Ref 4) When the hash rate declines the difficulty declines. When the hash rate rises the difficulty increases. When the average cost of mining falls below the cost of production,(Ref 5) marginal or high cost miners begin to take mining rigs offline. This causes the hash rate to fall and thus a fall in the difficulty of mining a block. Those mining rigs that remain and continue to mine usually have a competitive advantage and experience an increase in profitability as competing mining rigs leave the mining process. This process also works in reverse as price rises. Interestingly, where mining at a loss causes price suppression in most commodity markets, rational miners will continue to mine bitcoin at a loss to accelerate the time to the next difficulty adjustment and thus drop the cost of mining. This creates a theoretic game of “chicken” where every miner hopes that every other miner will take their mining rigs offline first.
2) Bitcoin price fluctuates far more than bitcoin mining costs (e.g., rent, wages, computer equipment, energy, etc.,). This creates a reflexive or self-reinforcing positive price dynamic where increases in price leads to further increases in price during booms and declines in price lead to further declines in price during crashes. The largest and most constant factor shaping bitcoin price is the sale of bitcoin by miners to meet the cost of production. In the current Bitcoin Halving Cycle, 12.5 bitcoins are produced every ten minutes, 1800 per day, 54,000 per month.(Ref 6) Within a boom or rising price environment, miners need to sell less bitcoin every month to meet their costs. Every month the supply of bitcoin available for sale decreases and this leads to future price increases. In contrast, within a crash or falling price environment, miners need to sell more bitcoin every month to meet their costs. Every month the supply of bitcoin available for sale increases and this leads to future price decreases. Once this price dynamic begins from the bottom of a crash or the top of a boom, it accelerates until the reflexive price dynamic switches back to the previous reflexive price dynamic.
3) What causes the switch in this reflexive price dynamic at the bottom or top of the Bitcoin Price Halving Cycle? I am researching this important question right now. My preliminary thoughts suggest at least two critical factors that require further analysis.
a) The first factor is fundamental - the critical mass of marginal miners entering or leaving the bitcoin mining process long enough to allow for the difficulty rate to encourage or discourage new entrants into the mining space. Once the rise in bitcoin price is greater than the price miners need to sell bitcoin to meet their costs, demand will begin to outstrip supply and higher prices will lead to higher prices. Conversely, once the decline in bitcoin price is less than price miners need to sell bitcoin to meet their costs, demand will begin to fall behind supply and lower prices will lead to lower prices. Knowing the average production costs of marginal miners as well as the bitcoin reserves of weak and strong participants in the mining community should shed light on the probability of critical mass miner capitulation and/or entry.
b) The second factor is rhetorical/psychological - miners’ foreknowledge of the bitcoin halving cycle itself. Specifically, miners know from the bitcoin code an approximate date where the costs of producing a bitcoin is going to double. This knowledge is a symbolic singularity or rhetorical/psychological trigger for miners that shapes miners estimates of their ability to play and win the “game of chicken” with other miners. Miners at the margin surmise that they are not going to survive the current bitcoin halving cycle and those more established and efficient players surmise they will survive the cycle. This knowledge/belief shapes miners’ decision to remain in the game or capitulate. Historically, the time frame of one year before the halving has resulted in the bottoming of the market and the beginning of a new rising price dynamic. In addition, anticipation of this rising price dynamic may also encourage miners with bitcoin reserves to decrease their selling of bitcoin thus increasing the rise in bitcoin price.
References
1 economicpolicyresearch.org/econ/2015/NSSR_WP_052015.pdf
2 en.wikipedia.org/wiki/Human_Genome_Project
3 en.bitcoin.it/wiki/Difficulty
4 theblockcrypto.com/tiny/bitcoins-mining-difficulty-saw-the-largest-drop-in-the-asic-era/
5 coinshares.co.uk/wp-content/uploads/2018/11/Mining-Whitepaper-Final.pdf
6 quora.com/How-many-new-bitcoins-are-created-on-average-per-day
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