There is no causal relationship between cryptocurrency computing power and price, but the expectation of future mining revenue and the expectation of hash rate growth are mutually reinforcing.
Written by: Leo Zhang and Karthik Venkatesh, founders and data analysts of Anicca Research, a research organization for computing power and derivatives, respectively
When an event has subjective participants, the subject is no longer limited to facts, but also includes the participants’ opinions. The chain of causality is not directly caused by individual facts, but is triggered by facts and fed back from perception to facts.
——Financial predator George Soros, “Financial Alchemy”
The previous text, ” read a hash of” Alchemy “: characteristics and challenges Bitcoin considered force assets “, we discussed the force will be considered as an asset class framework. Everything is related in crypto mining. To fully understand the rules of market dynamics force calculation, we need to study the impact of the relationship between the force variable count careful look.
In this article, we will first mining market cycle is defined as four basic phases, each with a different price trends, hardware capacity and market sentiment. We studied the main driving factors in the market in each context and demonstrated the role of hardware reflex arcs and the reflexivity of computing power in shaping these macrocycles.
Through a series of case studies and theoretical arguments, we intend to introduce a guiding framework to understand the different mining investment environment. At the end, we discussed the broader significance of transaction fees for the growing revenue of mining. New opportunities based on market transaction costs, as well as a major variable rates, how will profoundly change the structure of the market force count.
Four seasons of the computing power market
The dynamics of the computing power market is driven by the complex linkage relationship between external and internal factors such as price trends, reflexivity, hardware reaction time and handling fees. Although their logical connection appears to be very clear, but the randomness of each variable is very difficult to establish the generalized model.
For this reason, sometimes the macroscopic phenomenon shown by the market will appear illogical, as if price and hash rate are in a completely different time frame of reference. Nevertheless, the actual profitability of miners can be traced and determined. Based on how historical mining income has evolved in different market environments, we can identify the basic patterns of prosperity and depression in the mining cycle:
Source: Bitcoin data in CoinMetrics
Specifications ant to the mining machine S19 Pro for example, by a vector network hash price and rate of movement to divide the cycle phases at different rates in different directions, so mining revenue will vary in different environments:
The Rising Bull
Token price growth exceeds hash rate growth
When the growth rate of mining difficulty lags significantly behind the price increase, mining is the most profitable. The ” rising bull market ” phase usually occurs after a long period of relatively weak volatility. Prices have just begun to form momentum, and most of the market is still uncertain about the next direction. Operators force growth rate much lower than the price growth. The increase in computing power is mainly attributable to miners who expect price increases or miners who can get very low electricity bills. For example, during the period from January 2019 to April 2019, the BCH-BSV ” computing power war ” overlapped with the dry season, and the price of Bitcoin was suppressed. Resourceful miners on the secondary market to buy cheap second-hand mining machine. Some also use synthetic mining contracts or cloud mining to establish positions at low prices.
Although Bitcoin prices are on the rise at this stage, sometimes environmental factors may even cause the hash rate to drop. Usually related to the physical condition, such as extreme weather, floods, forcing large-scale mines off the assembly line. 2020 Sichuan floods during the rainy season, especially with destructive. But these are temporary setbacks, which usually recover over time.
Another possible cause exceptional circumstances considered force decline was initiated by the developer of hard fork. After a bit continent for the first time it announced its ASIC chip ore mining machine may Monroe currency (Monero), Monero developers decided to switch once every six months algorithm. Each time the network changes its algorithm, part of the network hash rate will drop. A phenomenon that is not only hard on the mining machine have forked hostility project developers start in. Sia mining ASIC developers very accepted, but they will be a bit of Continental and Jianan Yun Chi ASIC mine clearance machines on the network via a special fork out hard.
Source: Monero data in CoinMetrics
This special situation may temporarily prevent the increase in hash rate, but as the overall upward trend continues, the positive sentiment of participants further strengthens, and the demand for computing power also increases.
Mining Gold Rush
The price of tokens is rising rapidly, and the growth rate of hash rate is rising
Once the bull market pattern is confirmed, people will be more eager to buy mining machines. The new mining machine was sold out almost immediately. Large miners placed generous orders to mining machine manufacturers to strive for priority in supplying them. In alchemy article, we describe the pricing mining machine with a static-based break-even break even number (chain smell Note: China is generally referred back to the days, static days-to-breakeven) day relevance. The shorter the return days, the higher the price set by the seller for the mining machine. Token prices quickly rebounded, followed by a demand for new mining machine, but the whole network operators force growth rate has not accelerated. This period is the mining machine manufacturer for astronomical profits of the window. The secondary market for mining machines and the cloud mining market are also trading at a premium.
This is true for ASIC chips and GPU graphics mining. From 2016 to the end of 2017, major graphics card manufacturers AMD and Nvidia benefited greatly from the rapid development of Ethereum. Miners are willing to pay the highest bid for each GPU available on the market. GPU was very serious short supply, Nvidia even consider asking the retailer for the purchase of each buyer within two. In the current market, the DeFi boom has once again triggered people’s strong interest in Ethereum.
It is easy to create a bubble of speculation, “not to worry about the car on FOMO panic” among the miners. The positive price bias continues to strengthen itself, and expectations rise faster. Alternative currency projects that have experienced this stage for the first time with a relatively short birth time may attract the attention of ASIC mining machine manufacturers, such as the recently popular Handshake and Filecoin .
At the beginning of 2019, rumors about Grin’s investment of hundreds of millions of dollars spread like wildfire. The venture capital VC is scrambling to provide funds for companies specializing in Grin mining to purchase and operate GPU mining machines. The project soon, mining difficulty after a sharp rise in the main online start mining machine manufacturers such as core action and Obelisk competing to build the first dedicated ASIC Grin mining mining machine. History shows that the project failed to match the hype from the expectations, corresponding ASIC mining machine also from not getting enough orders to put into production.
Inventory-flush
Token prices are falling, and the hash rate growth rate remains strong
As founder Howard Marks, Oaktree Capital (Howard Marks) said: “Any abnormal profitability things will attract incremental capital until the capital overcrowding.”
After the token bull market and mining machine manufacturers overproduced machines, it is not uncommon for mining machine inventory to be dumped . 2017, mainland China and other bits of the mining machine manufacturers misjudged the market development, the production of excessive mining machine during 2018. They had to cut prices to gradually by dumping mining machine inventory. In order to clear the stock of excessive chips, Bitmain even launched products with extremely flat market demand, such as home Wifi routers that can be mined. As a result, despite the drop in Bitcoin prices, computing power continued to climb for several months until profit margins were fully squeezed out.
During the same period, due to the exponential increase in hash rate competition, many GPU mining farms became unprofitable. Altcoin ASIC mining machines (Monero, Zcash, Sia, etc.) were released into the market, while altcoins The price has fallen all the way. Bear market quickly blow to the hardware supply chain, so they had little time to react. Nvidia released a disappointing earnings report, its founder Jen-Hsun Huang Jen-Hsun Huang argument from the time of 2017, Bitcoin record high “encryption currency will become an important driving force of our business” to “I do not want anyone to buy Cryptocurrency, okay? Stop. Enough. Don’t buy Bitcoin, don’t buy Ethereum.”
Since the stock overproduction caused dumping in many encounters highly reactive delayed market appeared. For example, about 10 years ago, due to the large sums of overseas buyers, there was an epic bull market in luxury apartments in New York City. Developers are eager to start new projects. In recent years, due to various reasons (such as capital control), the purchasing power has gradually dried up, but the newly built luxury apartments have just been put on the market. The results hit the empty real estate in the hands of developers.
The Shakeout
The price of tokens has dropped and the hash rate has dropped sharply
Sometimes, mining revenue will drop below a threshold, and it has been unprofitable for miners who persist. Chinese miners call it the ” shutdown price .” In the traditional market, when there is a price correction, the negative bias will start to snowball, bringing the price into a downturn. However, since the computing power rate is self-referenced, the more computing power that is eliminated from the market, the “richer” the remaining computing power.
In Bitcoin, this excessive price correction tends to be short-lived. Miners’ expectations of future mining revenues buffer the decline in computing power. They believe that the chance of recovery is very high, and therefore are willing to adhere to mining at a loss, even still buy new mining machine when the market experienced shuffling out. On the other hand, if the network is flooded with speculative miners, such surrendering out will happen frequently.
Things that underperform for a long time will eventually appear cheap. Because of what the American economist John Kenneth Galbraith called ” financial memory is extremely short, ” cycle changes will repeat itself again and again.
Plato’s prediction of market fundamentals
Why does the computing power market exhibit these cycles? Intuition get on with the force of growth and price trends are positively correlated. But why does the change in token price not bring about a commensurate adjustment of computing power? In other words, why is the computing power market inefficient ?
Conceptually, market information is a summary of equipment, the views of the participants can be refined into pricing information. The faster the price absorbs new information, the more efficient the market. Upon reaching equilibrium theory, network convergence should be mining more difficult to operate the majority of miners near the break-even level.
Nakamoto wrote in BitcoinTalk years ago in a post: price “of any goods tend to cost about the ups and downs of production if the price is below cost, then the production will slow down if the price is higher than the cost, then. It can be profitable by producing and selling more products. At the same time, the increase in output will increase the difficulty and push up the production cost and move closer to the price.”
In the current market, the price of Bitcoin is far from a passive reflection of production costs. In reality, we rarely see this kind of balance envisioned by Satoshi Nakamoto.
For most physical commodities, supply is mainly determined by the manufacturer and consumer demand, but speculation leading to encrypt currency investors to make decisions based on expectations of future price rather than the current supply and demand curves. Therefore, a simple calculation of mining costs can hardly provide insight into the market.
Market participants in dealing with the new information is always with his own prejudices. This is similar to guessing the shape of a high-dimensional object through its projection in a low-dimensionality. This is the market fundamentals of Plato’s allegory.
Cognitive error-prone brought reflexivity. Reflexivity is an iterative process: the market as a melting pot of prejudice, in reality the reaction is always flawed. When investors bet on the market, price changes begin to affect market fundamentals (for example, the company’s capitalization amount goes up or down), which in turn affects prices, thus forming a reflexive feedback loop.
Rather than focusing on the results of hypothesis, it is better study the change process. After years of development, the theory of reflexivity has gained mainstream favor. Researchers have conducted extensive reflexive observations in the stock, currency, cryptocurrency, and even mining markets.
Reflexivity of computing power
How does reflexivity behave in the computing power market?
As we all know the demand for hash rate is driven by the value of tokens generated. Trading decisions are based on the participant’s own prejudice against future mining income expectations. Equity investors set expectations for future prices through macro, industry and company analysis. Hash rate investors set expectations for future mining revenue by evaluating the trend of token prices, handling fees, and network hash rate growth.
Everyone has their own (often flawed) to determine price trends. It is much more difficult to build a forecasting model for computing power growth. One reason is that it is dynamic recursive: the more hash rate into the market, diluting unit miners have hash rate is higher. Changes will lead to adjustments in expectations, and therefore will recursively affect current mining revenue. Every participant in the computing power market is constantly changing the rest of the market.
This means that the growth rate forecast hash of the most scientific method is to collect sales data from the mining machine mining machine manufacturers, large-scale miners, service providers and distributors there. However, information asymmetry is a major feature of the mining machine manufacturing industry. It takes a lot of effort to obtain accurate and updated data. Since it is difficult to reliably set expectations for hashrate growth, and transaction fees are not particularly important in the proportion of mining revenue, expectations for the future price of tokens have naturally become the main variables in the development of the mining industry. After all, if people are not optimistic about the future price, why they would spend so much capital and energy involved in mining?
Collect data mining is an onerous task, but is it possible for a token price trends between the operator and the establishment of quantified force growth model?
As demonstrated by the four phases of the market cycle, we often see the divergence of computing power and token price trends. Information in the capital market spreads rapidly. Hardware manufacturing and mining machine shipments are very slow. Hash rate idealized market and the efficient market hypothesis showed the opposite trend. This makes pure correlation analysis useless. We need to review the data on different time scales.
Recently, the digital asset financial services company BitOoda published a comprehensive research report ( Chain Wen Chinese version ). They found that the change in the price of the token and the change in the hash rate in the past year have found that the change in the hash rate is relative to the increase in the price of the token. The lag time of the trend is about 4-6 months .
Note that this lag time is not fixed. Depending on the production capacity and supply availability of the secondary market for mining machines, the lag time varies with each market. The corresponding time of different blockchain networks is also different.
To litecoin example, the hash mining rate of price changes in January 2018 to May response lag a long time. The Litecoin price and hash rate changes became very “synchronized” after July 2018.
Source: Litecoin data in CoinMetrics
Extending this analysis to the corresponding lagging studies of Bitcoin, ETH, and Litecoin over a longer period of 2017-2020 , we found that the average response time was 60-120 days, 30-60 days, and 15 days, respectively.
Analysis process:
1. 15-day data summary
- The columns in the data set are date (15-day end date), 15-day average price, and 15-day average hash rate
2. Calculated for each 15-day period:
- The percentage change in the price of 15 days, 30 days, 45 days 180 days ……
- Percentage of 15 days, 30 days, 45 days 180 days hash change rate ……
3. Calculate the correlation between price changes and hash rate changes in different time periods
4. The matrix is read as: the correlation between the price change in “y” days and the hash rate change in “y” days (after the price change in x days)
Response time is essentially not good or bad. It is a function of the market over a given period of time mining machine availability. Generally speaking, the response time of smaller blockchain networks based on general mining hardware is much shorter. Due to the low loyalty of the miners on these networks, so their operators can respond more quickly force prices up and down. Compared with ASIC miners, they can easily switch to other network mining when it is profitable. Some mining operator force pool provides automatic switching service, constantly jumping between multiple different networks, in order to maximize profits (called “profit Switch” or “machine guns pool”).
Please note, led by the mining machine mining ASIC blocks chain network and not necessarily value-driven (eg 2019 after litecoin); GPU-led network of mining is not entirely speculative (such as Ethernet Square).
Changes in the price of tokens in most cases considered earlier than force change. Sometimes we can observe the opposite in the altcoin market, usually altcoins that are about to undergo a halving. The halving is one of the recurring and self-fulfilling prophecies in cryptocurrencies. The anticipation of the token rise after the halving has prompted miners to deploy new mining machines in advance. Sometimes, the joint collaboration of currency speculation organization will deploy a force to be considered accumulate enough tokens, and then push the operation to obtain the final token price gains.
This mode is also common in GPU miners speculating on new projects. After issuing new tokens, tokens are in the majority on the OTC market exclusive OTC trading, liquidity is poor. Miners do not have a good exit channel for positions. They continue to operate at a loss until project development gains momentum. With the development of the community, the tokens of the project are listed and traded on larger exchanges, giving miners a chance to earn some income.
The increase in the hash rate does not guarantee a future increase in the token price. This is a risky bet, examples of failure abound. Many factors are needed to coordinate to ensure that this process goes smoothly. In each step of the following process, problems may occur:
Various GPU mining projects were very popular between 2017 and early 2019. Some analysts said that the simple agreement of SAFT issuance of future tokens from VC projects to venture capital is fairer than ICO. How to issue coins more fairly is a very broad issue. Even in the DeFi field, which has nothing to do with PoW , it is still a controversial topic. The coin issuing mechanism and the obtained computing power cannot guarantee future price increases. In essence, this is a form of ICO with a high barrier to entry, which is the same as a casino game that throws darts in the dark.
Mining hardware response time nature of the source (regardless of length) are within. This means that when modeling the impact of price on hash rate growth (and vice versa), the impact may be underestimated or overestimated. Therefore, using model-based inference decisions as one of the input values of investment decisions may bring catastrophic consequences.
Thrust of this article is considered a token force, and the price of such a link does not mean that there is a causal relationship between the two. One will not automatically induce the other. The expectation of future mining revenue and the expectation of hash rate increase mutually strengthen each other.
The influence of transactions continues to increase
To further refine the macro model at the beginning of this article, the change trend of handling fees should also be the main variable. As mentioned above, current expectations for mining revenue are mainly driven by token price trends. In August this year, Ethereum miners made a total of 113 million U.S. dollars. The previous record (64 million USD) was in January 2018. The continuous increase in the on-chain traffic of the DeFi project can explain the soaring income of miners from the commission.
The transaction fees as a key variable for the new model opens up the possibility of profit. For example, the arbitrage opportunity in the decentralized exchange in Ethereum encourages competitive automatic market makers to continuously increase their bids in the gas priority auction bidding. Miners who control the sorting of transaction orders can profit from these auctions by optimizing the gas fee sorting. This is a miner can extract part of the value of MEV, namely miners MEV value can be obtained directly from the intelligence contracts. There will be more services and infrastructure projects (such as the Taichi network of the Spark Mine Pool that can improve transaction broadcasts) that can solve all aspects of the new rate market.
With trading revenue in the proportion of mining revenues continue to increase, mining income is calculated adds a new dimension. Both price expectations and fee expectations will affect the expected future mining revenue:
The theory of reflexivity is an effective way to understand the ebb and flow calculation force. However, this model cannot replace the understanding of the basic loopholes in the computing power market. As the mining industry become more industrialized, capital expenditures will inevitably increase. At the same time, the percentage of handling fees in mining revenue will increase, and the four basic stages of the mining cycle will expand to even more complex scenarios. This comprehensive impact will bring more challenges and uncertainties to the cash flow management of miners.
After 10 years of development, the computing power capital market is still plagued by the lack of standard contract terms and pricing ideas. The industry needs proper risk management practices and mature market mechanism to ensure sustained long-term investment in the count forces.
In the next article, we will discuss in depth the risk management framework, innovative financing and hedging strategies, and the long-term impact of financialization on the mining industry.
