By David Grider
Ænigma’s Cryptocurrency Store of Value Framework is presented below. A copy of our full report can be downloaded on our website via the following link:Full Report
Investing in the emerging cryptocurrency market is daunting for even the most experienced of investors. Not only is crypto a new alternative asset class, it requires a unique skillset drawn from fields that rarely cross paths in traditional finance. At Ænigma Capital, we see market behavior as a complex interaction among technology, behavioral game theory, finance, economics, and political science. But most investors are experienced in only some of the key knowledge areas. Often they look at the market through the lens of their own background — whether or not the assumptions of their discipline hold true for crypto.
Without a comprehensive understanding of market dynamics, investors have struggled to value assets and navigate a volatile crypto space. Many come to the conclusion that the problem is crypto itself. They view the markets as a black box of fundamentally irrational price movements where the risks are too high in comparison to the returns.
But the problem is not cryptocurrency. The problem is information asymmetry, a feature typical of both emerging economies and evolving asset classes. Some investors have benefited from the information gap, extracting astronomical returns from the market, while others have incurred significant losses.
What separates the successful crypto investor from the unsuccessful one? A thorough understanding of the mechanics of crypto market behavior.
Aenigma Capital has published Store of Value, an in-depth report that expands upon our monetary store of value component of digital asset valuations and its role in the larger crypto market cycles. This post provides a summary of the full report which can be accessed via the following link: Store of Value.
While many analysts claim that cryptocurrencies have no store of value property, we believe that the proof-of-work (PoW) consensus protocol encourages the capture and storage of value in the form of mining costs expended. Given the predominance of PoW mineable coins in the digital asset markets, this model of value creation is highly relevant to fundamental valuation now and as markets mature in the future.
How does mining create monetary store of value? Blockchain technology requires some method to validate the transactions being added to the chain (i.e., its “blocks”). One method is PoW mining, in which miners verify transactions by completing encrypted algorithms solvable only through brute force computation. As a result, PoW mining incurs high costs of power, hardware, mining facility overhead, labor, and other inputs.
These costs are semi-permanent commitments of value that influence behavioral incentives for market incentives. Having invested value in the form of mining costs, participants are more likely to hold their assets during downturns and to support the price floor, restricting the supply and contributing to price stabilization.
The Ænigma store of value model measures the cumulative sunk costs deployed into the system though the mining process. We leveraged this estimate to produce the Price-to-Store of Value (P/SoV) ratio, that we introduced publicly in June of 2018. The P/SoV ratio is a fundamental metric for examining potential digital asset valuations. The P/SoV ratio functions similarly to traditional Price/Book, EV/EBITDA, and P/E ratios. We calculate P/SoV on an overall network value basis as the ratio of: 1) aggregate market capitalization, and 2) total store of value, approximated using cumulative mining rewards (CMR).
Ænigma graph of Bitcoin logarithmic price and the P/SoV ratio. Coinmetrics.io and Ænigma estimates.
In the most basic terms, the P/SoV ratio helps investors measure whether:
● A crypto asset is more likely to be relatively cheap or expensive. ● The market is potentially nearing a price bottom or top.
Ænigma graph of Bitcoin market cap vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
The difference between P and SoV represents the estimated amount of unrealized profit in the system; i.e., the net value that all holders would receive if they sold their coins at current market prices. In other words, the P/SoV ratio helps us quantify the probability that investors will buy or sell.
Ænigma graph of Bitcoin logarithmic price vs. the P/SoV ratio; Bitcoin market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
The P/SoV ratio is a price-agnostic relative valuation metric that applies across differing network sizes, time periods, and price cycles.
2011- 2018 Bitcoin P/SoV estimated standard deviation and daily multiple frequency. Source: Coinmetrics.io and Ænigma estimates.
Movements in price and the P/SoV ratio are highly correlated, and the ratio is a mean-reverting valuation metric, such that price is more likely to rise if the ratio drops and fall if the ratio increases.
2011–2018 SoV standard deviation and daily multiple frequency. Source: Coinmetrics.io and Ænigma estimates
The P/SoV ratio is a mean-reverting valuation metric. Because P/SoV describes the probability of coin holders selling in order to realize profit, at Ænigma we consider selling when the ratio spikes and buying when the ratio dips.
Ænigma Estimates: Bitcoin age distribution vs. Price; Bitcoin age distribution vs. the P/SoV ratio. Source: Coinmetrics.io.
The chart above shows the Bitcoin age distribution percentages of all outstanding coins over time. The coins are grouped into age buckets by the time since they were last moved in a transaction. The P/SoV ratio does more than indicate whether a coin is relatively cheap or expensive compared to alternative assets. It also functions as a leading indicator for coin supply-side economics, indicating whether a price movement is sufficient to induce other investors to buy or sell soon.
Ænigma Estimates: Bitcoin Price vs. Bitcoin Days Destroyed; Bitcoin Days Destroyed vs. the CMR ratio. Source: Coinmetrics.io.
The P/SoV ratio in combination with Bitcoin Days Destroyed (BDD) is a leading indicator of price movement. What does the combination of BDD and P/SoV reveal? It offers potential insight into the profitability of moving coins and possibly the intent of the investors.
The P/SoV ratio is highly relevant to macro market valuations, given that the majority of top digital assets are PoW mineable currencies such as Bitcoin, Ethereum, Bitcoin Cash, Litecoin, Monero, and DASH. Of these, Bitcoin remains the leading macro driver of the market because of its relative size, with its market capitalization representing approximately 55% of the total crypto space. In aggregate, PoW mineable coins account for approximately 70% of the cryptocurrency global market capitalization. We present a summery of the P/SoV data for other coins below and include key considerations in the full report for examining the unique characteristics and market dynamics of each coin in executing our analysis of store of value.
ETH price vs. the P/SoV ratio; ETH market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
Bitcoin Cash (BCH)
BCH price vs. the P/SoV ratio; BCH market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
LTC price vs. the P/SoV ratio; LTC market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
XMR price vs. the P/SoV ratio; XMR market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
DASH price vs. the P/SoV ratio; DASH market capitalization vs. the P/SoV ratio. Source: Coinmetrics.io and Ænigma estimates.
Improvements to Prior Work
The P/SoV model provides improvements to previous attempts at crypto asset valuation. We also discuss the implications of this finding in detail by examining the distinction between this model and other approaches that have been employed.
The Equation of Exchange Model popularized by Chris Burniske applies a framework that treats cryptocurrencies like their fiat alternatives and values them as a product of supply, demand and velocity. However, this approach does not produce a basis for accurately understanding velocity. The model does not distinguish between the different types of digital assets and the varying economic characteristics they represent. This model requires a re-examination of community assumptions about the role of store of value and its implication on velocity and price.
A Cost of Production Model for Bitcoin developed by Adam Hayes employs an approach which theorizes that the current mining break-even costs of production will produce a value around which market prices tend to gravitate. The model accurately treats minable cryptocurrencies as digital commodities and properly asserts that production costs play a critical role in the assets fundamental value. However, the model focuses only on current production costs which influence the incentive behavior of miners producing new coins. This approach does not accurately account of the incentives of other holders in the system which have the ability to influence price and consequently miner behavior for expending additional production costs.
The P/SoV model assets that the cumulative production costs instead play the most critical role in influencing the long-term value of a cryptocurrency and its store of value property. The cumulative sunk costs spent on production influence the tendency of the majority of participants in the system to sell or hold their coins which in turn influences the current miner production cost incentives.
Ænigma Fundamental Valuation Framework
Since 2017, Ænigma Capital has published several components of our comprehensive fundamental framework for digital asset valuation. Our framework starts from the premise that crypto assets are incredibly diverse, and their economic characteristics are best evaluated at component level as any combination of the following:
Discounted Cash Flow (DCF): In Fundamental Valuation Approaches: DCF, we provided an overview of the forms, both traditional and alternative, that cash flows may take when delivered to token holders. In A “Killer App” for Crypto: Distributed Autonomous Corporations (DACs), we delved deeper into the DCF component of valuation, examining the cryptoeconomic characteristics of DAC networks and their equivalence to equity in a traditional corporation.
Utility Usage: In Leveraging the Cryptoeconomic Machine, we examined the fundamental characteristics of digital assets that derive value from their utility to users. We also walked through the mechanical effects of market scenarios related to supply, demand, velocity, and price. These ideas bring us to the final component of fundamental valuation, monetary store of value.
Store of Value: In the full Store of Value report, we expand upon the overview discussed in this post. The data underlying our analysis can be accessed though the following link: Store of Value Model Data.
The crypto economic valuation study that we published in January of 2018 provides an example framework for how the three components of DCF, utility usage and store of value may theoretically culminate together within a single valuation model.
We hope that this latest expansion on the Ænigma collection of frameworks will give the community a toolkit for thinking about store of value with new clarity and predictive power.
Special thanks to the following people for the help and feedback with this report: Wesley Pryor, Mazin Hamad, and David Nage.
Disclaimer: This information is for educational purposes only. It should not be considered investment advise or any recommendation to transact in any security or other financial asset. Please consult with your qualified financial adviser for recommendations specific to your own investment situation.