Assessing fundamental and speculative value drivers in digital assets
November 24, 2022
The digital assets market often draws comparisons with the dotcom era due to the volatile and speculative nature of investments. However, this comparison is not necessarily accurate, given that cryptocurrencies do not even share enough qualities with technology startups for fund managers to apply traditional valuation models to them. As such, assessing the fundamental versus the speculative value of digital assets represents one of the many challenges facing financial institutions.
Further compounding the issue is the fact that crypto assets do not fall into a single identifiable category, in the same way as publicly traded shares or private equity. Some, such as Bitcoin, are deemed by regulators to be commodities, whereas many tokens are treated as securities. Therefore, asset valuation in the digital sphere has become something of an art rather than a science.
This article does not aim to provide a step-by-step guide to evaluating digital assets. However, it offers various quantitative and qualitative methods and considerations for evaluating digital assets that, taken in combination, can help cut through the noise to reach a realistic view of an asset’s fundamental value, viability, and potential.
Adapting traditional fundamental valuation models to digital assets
Traditional financial valuation models offer a starting point for the quantitative assessment of crypto assets; however, the methodology used can depend heavily on the type of digital asset. For instance, the discounted cash flow model can only be applied to assets that are expected to generate cash flow, which does not necessarily apply to a cryptocurrency like Bitcoin or a pure utility token. Therefore, any attempt to apply traditional financial valuation models to digital assets first requires some kind of categorization.
A paper from EY titled “The valuation of crypto-assets” uses the income test as a means of determining which models to apply to crypto-asset valuation. Acknowledging that market-based approaches can be difficult to apply to any type of digital asset due to high volatility and low liquidity, the paper distinguishes between security tokens, which promise the holder future cash flow, and utility tokens and cryptocurrencies, which typically do not.
It therefore suggests that security tokens can be assessed using an income-based approach based on rigorous testing of forecasts and best estimation of discount rates. However, EY proposes that utility tokens and cryptocurrencies are better suited to a cost approach, evaluating the opportunity cost of utility and the cost of generating new tokens. The paper also notes that it is possible to apply the Quantity Theory of Money to the fundamental analysis of utility tokens – a digital asset class that has long been considered more difficult to evaluate.
Several analysts within the cryptocurrency sector have developed token analysis models or indicators with varying degrees of success at predicting asset prices. One example is the stock to flow methodology, which calculates the value of commodities based on scarcity, and which one self-proclaimed former institutional investor turned analyst has adapted for Bitcoin. However, the model’s accuracy at predicting prices is questionable on anything but the longest-range investment timeline.
The underlying tokenomic model can be a significant driver of fundamental value. However, as the digital asset space has evolved, asset issuers have also become more shrewd in constructing tokenomic models with built-in inflationary measures that can directly affect the price of the token at a given moment.
One of the most prominent examples is in Bitcoin, which is hard-coded to allow a maximum issuance of 21 million bitcoins, with the supply of newly-minted BTC reducing by half every four years or so until the cap is reached. Ethereum adopts a different model, where there is no cap on the issuance of newly minted ETH. However, an upgrade in July 2021 introduced a fee-burning mechanism which means that ether is likely to become a deflationary currency in the longer term, as more ETH will be burned than minted each day.
Founders often put in place lockup and distribution mechanisms that can impact prices. For instance, tokens distributed to founding team members may be subject to staged vesting periods to prevent anyone from a mass sell-off as soon as their allocation becomes available. Staking campaigns have become a popular way of locking up tokens to constrain supply, whereas airdrops may be used to reward engagement and participation.
Any of these measures can impact the token price. The token is typically the core source of financial value for any given project, so assessing the tokenomics should be a core part of any fundamental digital asset evaluation.
Furthermore, they can help an analyst to determine whether there is any future income from the asset and thus, which type of valuation approach could apply.
On-chain analytics have come to play an increasingly prominent role in the fundamental assessment of digital assets. They can provide critical information about the network health of a crypto asset, offering insights into user adoption, viability, and security. On-chain metrics can also show trends relating to buyer and seller behavior and provide a basis for calculating several relative valuation metrics that can be used to try to identify price inefficiencies in the market.
On-chain analytics are of sufficient importance to institutional portfolio managers and analysts that Nuant has covered the topic in-depth in a dedicated blog post.
External factors affecting digital asset value
Not all factors affecting the value of a digital asset are necessarily quantitative or easily quantifiable. Nevertheless, there are several other considerations that could have a potentially dramatic influence on price and should be factored into any investment thesis.
Digital assets do not exist in a bubble and can be subject to macroeconomic forces that could make the difference between success and failure. Currently, regulatory risk represents one of the biggest uncertainties for digital asset operators – however, the extent of the risk depends to a considerable extent on the jurisdiction. For example, the European Union is set to roll out the Markets in Crypto Assets (MiCA) Regulation in the coming year or two, depending on when the text of the new rules are signed off by lawmakers. While the new rules will impose obligations on digital asset operators, it does bring some degree of regulatory certainty that has been absent up until now. However, the US Securities and Exchange Commission has till now adopted an approach of “regulation through enforcement”, leaving operators with little certainty.
There may be other external risks, depending on the asset. For example, Bitcoin’s dependence on electricity means it also faces scrutiny from lawmakers seeking to implement green energy policies, along with the reality of spiraling energy costs across the globe. Ethereum has recently pivoted away from the energy-intensive Proof-of-Work to the greener Proof-of-Stake. Proof-of-Stake makes Ethereum less vulnerable to energy-related externalities, but Proof-of-Stake has never been tested on a platform of Ethereum’s size and scale, or on an asset with the total market value of ETH.
Sentiment and social proof
Activity and sentiment of venture investors can also be a valuable source of input into assessing token fundamentals. A recent report from Galaxy Digital found that even during the current period of bearish volatility, venture funding has continued to flow into the space, with more than $5.5 billion invested in the third quarter of 2022. Examining the underlying deals that represent this value can give some indication as to where venture funds believe the long-term returns lie.
Examining broader sentiment data and social proof risks falling into the realms of purely speculative token value drivers. Many inherently worthless tokens have managed to achieve inexplicable short-term price highs based on little more than social media hype. However, rather than focusing on quantitative data, a qualitative assessment of social proof can actually yield useful insights. For example, a project that has gained 100 followers of high-profile, blue-tick accounts belonging to successful entrepreneurs and seasoned investors is far more worth investigating than a project with thousands of followers that may be mostly bots.
Ultimately, it will take time for the industry to develop categorizations and standards for evaluating digital assets in a way that allows them to be compared and contrasted more easily.
In the meantime, fund managers must leverage the many sources of data at their disposal to reach a holistic assessment of fundamental and speculative value. Nuant aims to make this easy with an integrated and highly customizable portfolio monitoring, analytics, and decision support platform. It is specifically designed for institutional fund managers and analysts, putting on-chain and market data at your fingertips and enabling you to build a more informed investment thesis based on robust fundamental analysis.