Today’s post is on a famous economic principle that can be used to impute the value of a specific cryptographic token – Metcalfe’s law.
Metcalfe’s law states that the value of a telecommunications network is proportional to the square of the number of connected users of the system (n2 ).
Only later with the globalisation of the Internet did this law carry over to users and networks as its original intent was to describe Ethernet purchases and connections. The law is also very much related to economics and business management, especially with competitive companies looking to merge with one another.
Metcalfe’s law characterises many of the network effects of communication technologies and networks such as the Internet, social networking and the World Wide Web. Former Chairman of the U.S. Federal Communications Commission Reed Hundt said that this law gives the most understanding to the workings of the Internet.
The law has often been illustrated using the example of fax machines: a single fax machine is useless, but the value of every fax machine increases with the total number of fax machines in the network, because the total number of people with whom each user may send and receive documents increases.
Likewise, in social networks, the greater number of users with the service, the more valuable the service becomes to the community.
Applying the same rules to Blockchain tokens, it seems to be displaying the same set of behaviour with market capitalization of tokens following the mathematical formulae of market capitalization = k.n2 where k is a specific constant and n is the number of wallets in a blockchain token community.
Katalyst community is now presently confirming the hypothesis by selecting 50 tokens by analysing also their transactional volume and frequency. We also believe and now hypothesizing that market capitalization of tokens to have a reciprocal relationship with the transactional friction in the market.
The transactional friction in a given blockchain community could be contributed via the following manner:
- Lack of an exchange listing the tokens;
- Lack of a use case, that participants do not trade;
We are still thinking of how to qualify and quantify the transactional friction correctly. While we may know qualitatively what factors affect the transactional friction in a given blockchain token, we may not necessarily know how to quantify it.
Quantifying it is important because while we are more or less sure than market capitalisation has a reciprocal relationship with its transactional friction we would not be able to quantify the exact / approximate market capitalisation without a proper quantification of the transactional friction.
In short, we hypothesise the following mathematical equation:
Where k is a constant, n is the number of wallets in a given blockchain token community and f is the eventual quantification of f.
If the hypothesis is verified, it allows us to
- be able to predict the potential market cap, prices by inferring from the value exchange and increment from trading parties; and
- select tokens from the start or infancy stages to see whether it would survive and grow in value.
From the tokenomics, the growth of the number of n and also various other parameters like trading frequency and volume, we would be able to prognosticate the increase (or even decrease) of price and market cap of the tokens.
Most importantly, we would be able to find or design tokenomics that would give us 1000 times the returns. These utility tokens, if they were part of a balance sheet of a community or a business project, would further strengthen the balance sheet.
Imagine having a balance sheet item categorized under “intangible asset” and having its price and thus market cap validated via the market and increasing in value of 1,000x, the company’s valuation would grow tremendously, leading to advantages in the capital markets, either in the form of ease of fundraising. Or at least fundraising at favourable valuations.
The above post is modified from our whitepaper.
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