Novel Approaches To Crypto Asset Evaluation

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Includes: BCH-USD, BTC-USD, ETH-USD, GBTC, LTC-USD, XRP-USD
by: Johann Colloredo-Mansfeld
Summary

The majority of crypto asset evaluation has relied on quite immature and naive indicators and ratios.

While metrics like NVT and NVM have afforded investors some benchmarks, they remain quite primitive in their ability to proxy real supply, demand, and volatility in crypto asset markets.

Herein I present a theoretical overview of the problem confronting crypto asset investors today along with a candidate solution in the form of a novel metric suite.

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Problem: High Pricing Model Uncertainty

The lack of standard metrics, methods of analysis, and performance benchmarks for protocols, networks, tokens, and teams means that valuing any given crypto asset is unusually difficult. This difficulty is more formally known as Pricing Model Uncertainty (PMU).

PMU is a sub-component of the Theory of Rational Beliefs, which empirically suggests that intelligent economic agents may exhibit differences in beliefs even when they have the same information. These differences in beliefs about future price are further exacerbated when the models for processing information with respect to price are weak or have not been formalized, as they have not been with crypto assets.

In context, if ten Bitcoin holders process a singular event, each individual will come to a separate conclusion for what a Bitcoin is worth. By contrast, if ten credit risk free bond holders receive the same piece of information about the future rate of inflation, each individual will come to the same conclusion for what that bond is worth. Not only do individual investors not understand what information is relevant to the price of Bitcoin, but they also lack the models and frameworks that tell them how relevant information may be interpreted with respect to price.

All crypto assets suffer from an extraordinarily high level of PMU, which is evinced in the markets by price volatility. The result of high PMU is that investors in crypto assets are forced to play an event-driven benchmarked trading game where price overshoots are the rational result of investors following the dominating price trend, whether that is up or down. Given the persistence of this condition, traders will continue to speculate on news and drive prices wildly in both positive and negative directions.

Solution: Utility Metrics

Instead of relying on price and order book data, investors require fundamental metrics that describe a network's utility by serving proxy to network supply, demand, and volatility.

Demand-Side Metrics

Wallet Generation Rate: the marginal wallet generation rates can be found through the number of newly transacting wallets in each block

Contract Creation Rate: the contract creation rate can be found through the number of newly issued contracts with every block for smart contract platforms

Velocity: velocity is simply the number of times a unit of account within a crypto network has changed hands per unit time

Supply-Side Metrics

Miner Flow: net asset flow from mining participants can be analyzed to determine the flow of new supply into proof-of-work networks

Pipe Flow: pipe flow describe the amount assets among wallets that act as network intermediaries, which provides a baseline for transactions activity

Sink-Source Flow: source-sink flow describes asset flow from wallets that behave as cold storage for long term holdings

Instantaneous Volatility

Mobility: mobility describes the movement of assets among collections of wallets that function as network hubs and network termini

Block Vitals

Influence Radius: influence radius describes the connectivity of wallets transacting within a given block

Example of Utility Metrics in Action

Figure 1 shows that 30-day velocity of Bitcoin has drawn down considerably since its January price peak.

Figure 1 - Bitcoin 30-Day Velocity and Price over Time (courtesy Boltzmann)

Figure 2 shows a peak in 30-Day Sink-Source Flow around Bitcoin's January ATH followed by a subsequent decline.

Figure 2 - Bitcoin 30-Day Sink-Source Flow and Price over Time (courtesy Boltzmann)

Figure 3 shows a significant increase in 30-Day Influence Radius following Bitcoin's January ATH.

Figure 3 - Bitcoin 30-Day Influence Radius and Price over Time (courtesy Boltzmann)

Utility Metrics and Indicators are critical for investors attempting to navigate and understand price movements in the crypto economy. These metrics can serve as a solid foundation for asset evaluation.

Considering levels of these indicators today, we may begin to form an opinion on the future direction of Bitcoin's price.

Notably, significant changes have occurred with three metrics. Figure 4 shows daily wallet creation rate has begun increasing at an increasing rate for the first time since BTC's ATH in January.

Figure 4 - Bitcoin 24hr Wallet Creation Rate and Price over Time (courtesy Boltzmann)

Second, Figure 5 shows Influence Radius has dropped significantly (almost to pre-crash lows) in the last few weeks. This indicates that wallets transacting within blocks have lower network connectivity. This could suggest two important dynamics: new users are joining the network (corroborated by the increase in wallet creation rate) and that existing users are transacting less frequently, having shifted assets to cold storage.

Figure 5 - Bitcoin 14d Influence Radius and Price over Time (courtesy Boltzmann)

These two dynamics, along with the decrease in Sink-Source flow demonstrated in Figure 6 illustrate favorable structural dynamics for BTC. The decrease in Sink-Source flow offers further support for an increasing tendency of BTC holders to move assets into cold storage.

While myriad factors (hacks, etc.) may dominate short-term price dynamics, the fundamental network data show an uptick in new users and a tendency among existing users to shift assets toward cold storage, which support a bullish long-term price narrative for BTC.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.