Blockchain At Berkeley - Crypto Valuation Methodologies Overview→

/

Crypto markets are very new with limited data history pertaining to crypto asset behavior, returns, and correlations. Many of today’s models are simplistic or limited, whether intrinsically (due to difficulty defining and measuring variables such as velocity and its counterparts, for instance) or extrinsically (due to limited applicability to different types of tokens, as seen with NVT and privacy coins, for instance).

In the future when the markets mature and asset relationships and behaviors are more discoverable, valuation models and ratios should be more predictive and informative. However, because of the very diverse nature of crypto assets, which can have different features, structures, payouts, etc., we may never have metrics and models as universal as the P/E ratio and DCF analysis for public equities.

Read More

The Crypto J-Curve→

/

In private equity, the J-curve refers to a portfolio’s cash flows, while in economics it is commonly used to describe the effects of currency devaluation on the national deficit. The basic idea of a crypto J-curve stems from how the market values a cryptoasset over time. The J-curve is a price manifestation of the above shifts in market sentiment and utility value. When expectations are initially high, so too is the price, but often largely composed of “discounted expected utility value (DEUV).” As expectations wane, so too does the price, even if “current utility value” (CUV) grows. Ultimately, as DEUV expands once again, the price of the asset should exceed its prior high as it is supported by more CUV.

Read More

The Circularity Of MV = PQ→

/

Applying MV = PQ to crypto-currencies might yield numbers in the same order of magnitude as on-screen trading prices. But that’s down to a careful selection of the inputs or mere happenstance than any intellectual rigor. It is akin to observing two bananas, ten oranges and five apples on a table, and suggesting that (Apples = Oranges / Bananas). Mathematically correct but not scientifically sound.

Read More

Doubts about the Long-Term Viability of Utility Cryptoassets→

/

I’m increasingly sceptical about the long-term value of utility tokens. When I wrote An (Institutional) Investor’s Take on Cryptoassets last year, I thought utility cryptoassets might end up being collectively worth hundreds of billions of USD, which is a lot of money but not enough potential return over current valuations to compensate for the risk. Now, I’m increasingly thinking that few or no utility cryptoassets will be long-term viable at all.

Read More

Velocity Problem→

/

The velocity of tokens is a key aspect that affects future token value; however, it is also one of the least understood. This post attempts to describe velocity, how it impacts any token price over time and analyses the velocity of the Dala token as an example.

The equation of exchange is defined as: MV=PT

Where: M= money supply, V= velocity of money, P= average price level of goods, T= index of expenditures (such as the total number of economic transactions)

Read More

Thoughtchains - The Velocity Problem→

/

There is an emerging consensus that velocity is a confounding problem in establishing cryptoasset value for single utility tokens.

The widely accepted M = PQ / V model popularized by Chris Burniskeilluminates the effect of velocity on cryptoasset value quite obviously: increasing velocity decreases the value of the asset base in a linear fashion, and, therefore, the price of utility tokens (given a fixed token supply).

While there have been a lot of great discussions about why this model is effective for valuing this type of cryptoasset and quite a few valuations have been done based on it, we continue to ignore the massive white elephant that is the impact of velocity assumptions on these valuations. It is a variable that potentially throws all of these valuations out the door because we may very likely be underestimating velocity by several magnitudes if we just assume that people simply may not hold any of these tokens for any time.

Read More

On the Immaturity of Tokenized Value Capture Mechanisms→

/

Value capture is a topic that always seemed a bit overlooked in business modelling. Traditionally, as Peter Thiel frequently points out, there’s little correlation between value creation and value capture (e.g. one may generate tons of revenue without really profiting from it). Some industries have even established dynamics that clearly separate value creation from capture: think of the film industry, with production companies doing all the creative and operation work on one side, while, on the other hand, distributors and exhibitors take 80–90% of the share of profit, at the end of a movie’s life cycle.

Read More

Logarithmic growth→

/

Logarithmic regression has proven itself to be the best forecasting tool for BTC. Exponential regression overshoots actual growth rates over long time horizons, and logistic analysis requires very strong assumptions regarding the inflection point and estimated max price. Again, any type of analysis should not be used in isolation. Rather, it should only serve as a fraction of evidence to come to a sound conclusion.

Read More

UXTO Analysis→

/

Bitcoin uses a curious accounting structure called a UTXO — an Unspent Transaction Output. All UTXOs are timestamped by the transaction/block in which they were created. Since all bitcoin in existence is contained in some UTXO, this means that all bitcoins have an age: not the age/time when that bitcoin was first mined, but when it was last used in a transaction.

Since Bitcoin stores its full transaction history in the blockchain, it is possible to look backwards and analyze the age distribution of UTXOs over time. Unchained Capital first analyzed Bitcoin’s UTXO history a few years ago and what we learned encouraged us to start our crypto-lending product. We are now sharing our analyses publicly because we think they are fascinating and informative. Let us know if you agree.

Read More

Liveness→

/

Liveliness is new quantitative measure that gives insight to shifts in HODLing behavior.

Whenever someone moves Bitcoins there is a record of that on the blockchain. The blockchain records the move’s time point, the amount and the source of every Bitcoin involved, which again discloses the length of the recent holding period. Such an insight is unique to an asset tracked on a blockchain, and is not attainable in traditional financial markets. Let’s use this information to derive a quantitative measure that gives more insight to investor’s behavior than those available in traditional markets.

Read More

Mayer Multiple→

/

Introduced by Trace Mayer as a way to gauge the current price of Bitcoin against its long range historical price movements (200 day moving average), the Mayer Multiple highlights when Bitcoin is overbought or oversold in the context of longer time frames. It`s worth noting as the market becomes larger and less volatile, the peaks are becoming less exaggerated. This is because a 200 day moving average baseline is a static yardstick against an ever growing, more stable, Bitcoin market.

The Mayer Multiple is calculated by dividing the price of Bitcoin by its 200 day moving average.

Read More

Adamant Capital Bitcoin Report→

/

We suggest two new ways to measure changes in Bitcoin saving behavior:

  • Relative Unrealized Profit/Loss Ratio (≈investor sentiment)

  • HODLer Position Change (≈insider buying/selling)

Also introduced is the Liveliness measure, which reflects the extent to which a cryptocurrency is meaningfully used by savers.

Read More

Socio-economic Signals in the Bitcoin Economy→

/

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena that leave digital footprints, such as online social network usage.

Read More

Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?→

/

Cryptocurrencies have become increasingly popular since the introduction of bitcoin in 2009. In this paper, we identify factors associated with variations in cryptocurrencies’ market values. In the past, researchers argued that the “buzz” surrounding cryptocurrencies in online media explained their price variations. But this observation obfuscates the notion that cryptocurrencies, unlike fiat currencies, are technologies entailing a true innovation potential. 

Read More

Network "Momentum"→

/

There have been some exciting developments in blockchain analysis over the past few months. Highlights include:

  • Willy Woo’s NVT Ratio and Dmitry Kalichkin’s NVT Signal

  • Recent work presented by Nic Carter at this year’s Honey Badger conference

  • The subsequent MVRV (Market Value to Realised Value) paper written by Murad Mahmudov and David Puell

This sort of analysis is valuable and unique to the world of cryptoassets. For the first time, absolutely anybody who is investing in a particular asset can observe its underlying activity and performance — by using blockchain analysis.

Read More

NVT Ratio - Willy Woo→

/

In traditional stock markets, price-earnings ratio (PE Ratio) has been a long standing tool for valuing companies. It’s simply the ratio of a company’s share price to its equivalent earnings per share. A high ratio describes either over valuation or a company in high growth.

What would be the equivalent in Bitcoin-land? We have a price per token, but it’s not a company so there are no earnings to do a ratio. However since Bitcoin at its essence is a payments and store of value network, we can look to the money flowing through its network as a proxy to "company earnings”.

Read More

Introducing Realized Cap→

/

The motivation for the creation of Realized Cap was the realization that “Market Capitalization” is often an empty metric when applied to cryptocurrencies. Market Capitalization, borrowed from the world of equities, is calculated for cryptocurrencies as:

circulating supply * latest market price

However, unlike with equities, large fractions of cryptocurrencies tend to get lost, go unclaimed, or become otherwise inert through bugs.

Read More

Kalichkin NVT→

/

In a traditional PE ratio, the earnings metric in the denominator is used as a proxy for the underlying utility of the company created for the shareholders. While cryptoassets don’t have earnings, one can argue that the total value of transactions flowing through the network is a proxy for how much utility users derive from the chain.

Read More

Puell - Delta Cap→

/

Delta Capitalization

Delta cap is, as seen next, a hybrid of sorts — half “fundamental,” half “technical.” It is calculated through the following formula, measuring the difference between two long-term Bitcoin moving averages:

DeltaCap = RealizedCap - AverageCap

Read More

Black Scholes Adaptation For Crypto→

/

Many have written on cryptocurrency valuations as “bubbles”, implying that token network valuations are inefficient. Instead of the price reflecting future potential value, they believe that people are investing blindly and the price is going up simply because others believe it will continue to increase. The natural conclusion of this phenomenon is a sudden downturn as the bubble pops.

Read More