This is Part Four of a multipart series that aims to answer the following question: What is the “fundamental value” of Bitcoin? Part One is about valoarea penuriei, Partea a doua - piata se misca in bule, Part Three — the rate of adoption, and Part Four — the hash rate and the estimated price of Bitcoin.
Hash rate and the estimated price of Bitcoin
In data mining, the term “hash rate” is a security metric. The greater the hashing power, the greater its safety and resistance to external attacks. It’s one thing for a hacker to attack your home computer, but it’s another when a hacker tries to attack tens of thousands of computers around the world at the same time.
The hash rate growth is due to the ever-increasing computing power of mining servers, which also means increasing costs to mine Bitcoin (BTC). A simple rule tells us that a given activity must have economic convenience in order for it to be sustainable over time. Those who extract oil from the ground must sell it at a cost greater than the cost of extraction, those who produce electricity must sell it at a cost greater than the cost of production, and so on.
The same rule applies to Bitcoin mining, whereby the cost of electricity, the amortization of increasingly powerful servers, etc., must be lower than the revenues generated by receiving Bitcoin for the activity carried out.
Related: Este Bitcoin o risipă de energie? Avantaje și dezavantaje ale mineritului Bitcoin
Therefore, the growing difficulty of mining Bitcoin must be matched by economic convenience.
In the first months of 2010, Bitcoin paid miners about $10,000 per month. Today, thanks to the growth in the price of Bitcoin, the network of miners in the world are distributed a wealth of over $500 million per month — and this value is destined to grow.
The figure is enormous, even if partially commensurate with the consumption of electricity, but it allows us to understand the generation of wealth that this “social experiment” is able to create. As we can see from the graph, the growth of the hash rate is higher than the growth of monthly remuneration. Therefore, in order to estimate the correct price of Bitcoin based on hash rate, it is first necessary to understand the trend of remuneration for each unit of hash over time.
As we can see, the dollar remuneration of the hash rate is in sharp decline. This means that security increases almost exponentially over time, but the cost of security drops considerably over that time.
For a better understanding, while the remuneration for each block grows — despite or thanks to the halving that increases scarcity — the difficulty of undermining a new block increases much more quickly, at least for now. Therefore, the price/hash rate ratio goes down because the denominator goes up more substantially than the numerator.
So, to estimate the (non-linear) trend of decline in remuneration for hash rate, the function that best represents this trend is, as always, the power law function, as shown in the following figure.
Once we obtain this function by multiplying the two functions of hash rate growth and payment by a single hash rate, it is possible to obtain the function that approximates the monthly remuneration in U.S. dollars over time.
This result does not approximate the value of the price of a single Bitcoin but of the monthly remuneration that is growing over time, as can be seen on the previous graph.
To estimate the Bitcoin price, corrected according to this hash rate metric, it is necessary to divide this value by the average number of Bitcoin that is mined in a given month. By doing so, we obtain the typical stepped trend of the stock-to-flow model described earlier.
Concluzie
We can conclude that even in the face of strong volatility and apparently incomprehensible price movements, the principal three factors that move the price of Bitcoin — the scarcity, the demand and the cost of production — can be really useful to understand the dynamics of Bitcoin price movements.
We can argue that there are long-term fundamental value trends that can help to consider Bitcoin a “strategic asset class” of investment.
Acest articol a fost co-autor de Ruggero Bertelli și Daniele Bernardi.
Acest articol nu conține sfaturi sau recomandări privind investițiile. Fiecare mișcare de investiții și tranzacționare implică riscuri, iar cititorii ar trebui să își desfășoare propriile cercetări atunci când iau o decizie. Părerile, gândurile și opiniile exprimate aici sunt singure ale autorilor și nu reflectă sau reprezintă neapărat opiniile și opiniile lui Cointelegraph.
Ruggero Bertelli is a professor of financial intermediaries economics at the University of Siena. He teaches banking management, credit risk management and financial risk management. Bertelli is a board member of Euregio Minibond, an Italian fund specializing in regional SME bonds, and a board member and vice president of the Italian bank Prader Bank. He is also an asset management, risk management and asset allocation adviser for institutional investors. As a behavioral finance scholar, Bertelli is involved in national financial education programs. In December 2020, he published La Collina dei Ciliegi, o carte despre finanțarea comportamentală și criza piețelor financiare.
Daniele Bernardi este un antreprenor în serie în căutarea constantă a inovației. El este fondatorul Diaman, un grup dedicat dezvoltării de strategii de investiții profitabile care a emis recent cu succes Tokenul PHI, o monedă digitală cu scopul de a fuziona finanțele tradiționale cu activele cripto. Munca lui Bernardi este orientată către dezvoltarea modelelor matematice, care simplifică procesele decizionale ale investitorilor și family office-urilor pentru reducerea riscului. Bernardi este, de asemenea, președintele revistei de investitori Italia SRL și Diaman Tech SRL și este CEO al firmei de administrare a activelor Diaman Partners. În plus, el este managerul unui fond de cripto speculative. El este autorul Geneza activelor criptografice, o carte despre activele criptografice. El a fost recunoscut ca „inventator” de Oficiul European de Brevete pentru brevetele sale europene și rusești legate de domeniul plăților mobile.
Acest articol a fost trimis cu succes la Conferința Mondială a Finanțelor.
Sursa: https://cointelegraph.com/news/forecasting-bitcoin-price-using-quantitative-models-part-4
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