Mr Zimmerman shows that the pricing curve for cryptocurrencies can be locally downward-sloping; he identifies a driver of price volatility speciﬁc to blockchain technology; he shows that the volatility eﬀect is ampliﬁed by market illiquidity; and he demonstrates the existence of the digital gold eﬀect.
These results rely on two key conditions. First, there is limited blockchain capacity, so users compete for settlement. Second, the value of cryptocurrency depends on its usage as a means of payment. To my knowledge, there is no other traded asset where both of these conditions are true simultaneously. If such an asset existed, it is possible to expect its price to have similar levels of volatility to cryptocurrencies.
Mr Zimmerman also makes two technical contributions. He builds a model that endogenizes both the ﬁnancial market for cryptocurrency, and the fee-based market for blockchain space. And he contributes to the literature on global games by solving a model in which agents can purchase priority via fees.
The model has testable implications. It predicts that anticipated decreases in the block rate should be associated with higher price volatility. One way to test this is to exploit a feature of Bitcoin through which its block rate changes in a predictable way in the short run. Miners create new blocks by solving complicated cryptographic problems. If miners increase their computing power (called the ‘hash rate’), the rate of new blocks tends to increase. To regulate the long-run supply schedule, the Bitcoin protocol adjusts the diﬃculty of the problems every 2016 blocks, roughly every two weeks. As hash rate tends to increase over time — due to technological progress — there is typically a drop in hash rate after each adjustment. His model predicts that the price volatility should rise on these days.
His results also have implications for the long-term future of cryptocurrencies.
In order to present a closed-form model of cryptocurrency usage and pricing, he has abstracted away from some features that could be worth analyzing further. In particular, he has assumed that the time-frame over which beliefs form about the future value of cryptocurrency is similar to the time-frame over which settlement is delayed. In reality, settlement delays are likely to be of the order of days at most, whereas beliefs about future value will take much longer to form. A multi-period version of the model could provide a more realistic treatment, and allow the long-term value v(y) to be micro-founded.
His model can also be extended to incorporate imperfect information for speculators, as well as households. In the current setting, this may not add much value, because there are no strategic complementarities between an individual speculator’s actions and those of any other agent. However, a diﬀerent setting could give rise to new insights.
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