The Mystery in Valuing Cryptos

Apr 27, 2018

Properly determining the value of cryptocurrencies has proven to be a monumental task, even for experienced economists and traders. What makes cryptocurrencies appealing to some investors (a lack of regulation, high volatility, entirely digital) has caused others to avoid the crypto market altogether. 

The disagreement among traders, as well as a lack of traditional valuation metrics for cryptocurrencies, creates hurdles in the process of price discovery for cryptos. Author Lionel Laurent, despite the title of his piece, details the challenges of evaluating cryptos in his work “What Bitcoin is Really Worth May No Longer Be Such a Mystery”. The lack of structured methodologies for valuing cryptocurrencies provides investors with freedom to define their own valuation processes and input variables. This process is the source of the significant disagreement between different investors about how to properly determine the value cryptocurrencies. 

The measurement methodologies analyzed in Laurent’s piece entailed using Irving Fisher’s Quantity Theory of Money. This theory asserts that the value of a currency can be related to the total supply of the currency, the number of transactions the currency is used in, and the total spending value that these transactions represent. 
This is how it works in cryptos: start by taking the number of coins in circulation for a cryptocurrency (e.g. 15), and the number of times a year each coin is traded (e.g. 10). This results in 150 total transactions for the year (15 * 10). Next take the total transaction value that these trades represented for the year (e.g. $10,000) and divide it by the number of transactions that took place ($10,000/150). Using this method, assume each coin is worth $66.67. It seems simple enough, but the assumption of these variables is where a problem arises. The lack of accessibility to accurate information regarding the number of coins being traded, how many times each coin is traded, and the transaction value these trades represent has led to analysts “filling in the blanks” with estimates they believe to be correct. These assumptions can be significantly different which can lead to wildly dispersed price targets. 

There are other external factors that can be used to determine the potential of a cryptocurrency, which can be difficult to properly quantify. Due to anonymity of cryptocurrencies, they have become an appealing medium for criminals and the illicit drugs market. It has been estimated by the United Nations that the illegal drug black market for cryptocurrencies has a value of $120 billion, but this figure is nearly impossible to measure with certainty. Another factor to consider is that cryptocurrency investors in developing countries may find cryptos to be an appealing alternative to the unstable currency systems they currently use. These growing markets offer significant potential for crypto expansion, which is difficult to tangibly calculate. The basic premise of the Occam’s Razor principal is that the simplest answer is usually the correct one. Using this principal, it becomes clear why the inclusion of such undefined variables as those mentioned above has led to valuations that are so diverse.

While the relative infancy of cryptocurrency trading leads to difficulties in deriving a crypto’s value, the application of massively powerful AI algorithms to the crypto market may be eliminating uncertainty by using definable and tangible measures, in place of assumptions and guesswork. Machine learning has enabled traders to aggregate information from a wide range of sources, allowing them to overcome the information deficiency that applies to most crypto investors. A shift away from human trading toward algorithmic stock investing has accelerated significantly in the past decade. Algorithmic crypto trading may be the next evolution. 

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The full Bloomberg Businessweek article discussed: