Theme 1. Digital Asset Economy
Digital Asset Outlook 2022
1.5
Valuation approaches to digital assets
The question of how to value digital assets is one of the most complex and challenging issues. Digital assets have a relatively brief development history, and new use cases continue to crop up. Applying traditional asset classes' valuation approaches to digital assets poses a few challenges. Digital assets are not cash flow generative, and their limited performance track record makes it difficult to project their future performance. We summarize several common valuation methodologies for cryptoassets. Figure 10. Common valuation methodologies of digital assets Methodology
Thesis
Pros
Cons
Remarks
It estimates and compares the addressable markets with the current market capitalization
Intuitive and straightforward – It provides a solid framework for order-ofmagnitude comparisons between cryptoassets and the markets they address.
Not applicable beyond bitcoin and other storeof-value use cases
Most popular valuation approach
Equation of exchange
The equation is borrowed from traditional models of valuing currencies. It is assumed that a currency’s value is related to the size of the market it supports and its velocity.
Feasibility – Numbers can be forecasted into the future for a mature market and then discounted into present value.
Small changes in this estimate can lead to significant changes in proposed valuations.
MV = PQ M: Total money supply V: Average velocity with which a unit of money is spent P: Price of goods and services Q: Quantity of goods and services
Valuing cryptoassets as a network
This approach is borrowed from technology. It states that the value of a network is proportional to the square of the number of participants.
Intuitive – Given that daily active user is a proxy for adopting a cryptocurrency.
There are limitations: - appropriate only for relative valuations between cryptoassets. - gives equal weight to each user, which is not an accurate assumption
An essential part is that the value of the network is not linearly related to the number of users. Instead, it is related by a square function.
Data supportive – It is supported by empirical backtesting, which shows a relatively strong relationship between bitcoin’s price and the marginal cost of production
Little predictive power;
Cost of production valuation
This approach views bitcoin as a commodity. The cost of producing each marginal bitcoin should align with the price of that bitcoin, according to traditional microeconomic theory.
Uncertain predictive value - The causal relationship between the cost of production and price is not clear.
Total addressable market
It requires estimating the velocity, which is problematic.
It fails to explain the short-term volatility of bitcoin price
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