macro

CRYPTO: How to Value Bitcoin and other Crypto Assets

Source :   EconomyMonitor  (Clustering, sample from the Bitcoin B2X social network)

Source: EconomyMonitor (Clustering, sample from the Bitcoin B2X social network)

As the space matures, so does the thinking about what it's worth. We seem to be at least somewhat out of the "Why is Bitcoin worth anything" valley, with macro arguments about the evolution of money no longer needed to pacify critics. For those, see Nick Szabo's treatise on history of valuable tokensOle Bjerg's discussion of the commodity, credit and fiat theories of money applied to BTC, or the thesis that BTC intrinsic value comes from the economic cost of mining. These are important ideas as to why humans value things at all, but we are now in a place (i.e., BTC marketcap at $125 billion) where supply and demand have taken over.

The value of crypto tokens is also starting to be modeled more formally, and thankfully is moving away from being traded merely on technical analysis. Crypto investors are discarding the theory of the firm, and all of its associated discounted cash flow analysis, for a theory of token projects as circumscibed money/utility supplies within a machine economy. A major articulation of this approach was done by Chris Burniske, who starts with MV = PQ (money supply times velocity of exchange equals price of token times quantity of token), and expands the arithmetic to include timeline and structure of token issuance, percentage of long term holders, likely size of target market, discount rates, and generated token utility. Another iteration from Brett Winton implies massive devaluation in the VC and traditional financial markets as a result of crypto networks.

Vitalik Buterin is not entirely convinced that the money supply approach does the right thing longer term, and encourages token sinks and token buy-backs. Perhaps investors can then discount the impact of the buy-back to get to a more tangible valuation (fewer tokens worth more at a fixed rate) -- though it's likely that other factors influence token price more. For more articulated thoughts on Crypto dividends, see also CryptoFundamental.

Another useful tool is the Network Value to Transactions Ratio (NVT) from Woobull or CoinMetrics, that functions as a P/E ratio for crypto assets by comparing their activity to valuation. In reality, that is simple arithmetic in the face of complexity economics, a field of study that leverages the mathematics of physics, fluid dynamics, machine learning and network analysis to model economic activity and structure. A fascinating, albeit quiet difficult, article by EconomyMonitor traces the role of the attention economy in separate crypto ecosystems. One of our takeaways is that specialization -- i.e., ecosystems that have more actors with non-overlapping functions and high information density -- is a leading indicator of economic activity, and potentially, market value. So did we clear all this up? 

Source:  Woobull  (NVT)

Source: Woobull (NVT)