In any market, whether it is fruit and vegetables or financial assets, prices are determined by the intersection of supply and demand.
If tomatoes were scarce due to flooding, given the same demand, prices in supermarkets would inevitably be higher – just as they would be higher if, given the same supply, people wanted to buy twice as many tomatoes.
In financial markets, if supply is unlimited, prices are not changed by demand, as in the case of mutual funds for example.
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If more customers want to buy the fund, more shares are issued at something called the net asset value (NAV) — that is, the true value of the fund’s assets.
For example, a fund has a capitalization of $100 million, consisting of 10 million units with a value of $10. If an investor wants to invest $10 million, 1 million units are issued with a value of $10, and the fund’s capitalization becomes $110 million.
It’s a different story if the available shares are limited to only 10 million, then anyone who wants to buy those shares must find someone who wants to sell them. In this case, the price may no longer be $10, but will depend on how much the buyer is willing to pay and how much the seller is willing to earn. This will create a situation where prices fluctuate according to supply and demand imbalances. If an asset is in high demand, of course, its price could be significantly higher than its actual price.
But how can you estimate the correct price?
In 2021, I published data trying to estimate the fair value price of Bitcoin, which is illustrated in the graph below. That suggests that in June of that year, we had hit a relative maximum for Bitcoin (BTC). (I hoped at the time that this would not prove true, but it did.) How do I estimate this value?
The previous examples of funds help us understand the logic behind these estimates.
If the capitalization of a fund is determined by the number of units in circulation multiplied by its NAV, or price, it is also true that it can also be estimated as the number of investors in the fund per the average number held by each investor.
So, in the case of Bitcoin, if I can estimate the average amount stored in each wallet
the number of wallets in circulation, I can also estimate the Bitcoin capitalization and, consequently, by dividing it by the number of Bitcoins in circulation, get the price.
Luckily for us, the transparency offered by the blockchain allows us to collect this vast amount of information with a high degree of reliability. For example, the number of Bitcoin addresses with a balance different from zero can be easily tracked by simply running a network node.
As can be seen from the graph, the average amount (United States dollars) in a wallet fluctuates due to supply and demand (many wallets store Bitcoins without ever transferring them), so if we take the 90th and 10th percentiles, we can find range that can lead us to further estimate the price of Bitcoin.
Now that the growth curve (on a logarithmic scale) of circulating wallets has been estimated, it is possible to estimate the range in which the Bitcoin price should move.
This model is simple, but simplicity is its strength: we don’t know if users have different addresses or if one address is “owned” by multiple users — as in the case of exchange cold wallets — but we can rely on this relationship especially when compared in bulk and on time horizon of a complete price cycle.
Related: Bitcoin ETFs: Worse for crypto than centralized exchanges
For example, in the last days of crypto winter — as in recent months — typically, we can detect increased withdrawals from crypto exchanges and reduced balances held on these centralized platforms. Since holding crypto assets in third-party custodians is usually considered more dangerous, this signal is considered bullish as it indicates a preference for investors to hold long positions of Bitcoin over the long term rather than holding them in trading accounts to profit short term. – long term speculative opportunities.
This phenomenon is therefore accompanied by an increase in addresses (withdrawals from multiple cold wallets cumulative to replenish a single address lot controlled by an individual) and lays the foundation for cyclical price appreciation also based on the model described in this article.
The data from this chart and this model suggest Bitcoin price could reach its next high in the fall of 2025 at $130,000 — and possibly higher.
As always, it’s important to note that these forecasts are not financial advice. It can only be taken as an expected value based on some assumptions with a certain level of confidence. But similar price growth forecasts also emerge from other predictive models. The recent surge in interest in this asset class among institutional players such as BlackRock — the world’s largest asset manager, which is seeking approval for an exchange-traded Bitcoin spot fund — may indicate that they are putting some faith in this model.
Daniele Bernardi is the founder of Diaman, a group dedicated to developing profitable investment strategies. He is also chairman of Investor Magazine Italia SRL and Diaman Tech SRL, and is the CEO of asset management firm Diaman Partners. Additionally, he is a crypto hedge fund manager. He is the author of The Genesis of Crypto Assets, a book about crypto assets. He is recognized as an “inventor” by the European Patent Office for European and Russian patents related to the field of mobile payments.
This article is for general informational purposes and is not intended to and should not be construed as legal or investment advice. The views, thoughts and opinions expressed here are those of the authors themselves and do not necessarily reflect or represent the views and opinions of Cointelegraph.