Abstract
We model cryptocurrencies as utility tokens used by a decentralized digital platform to facilitate transactions between users of certain goods or services. The network effect governing user participation, in conjunction with the nonneutrality of the token price, can cause the token market to break down. We show that token retradability mitigates this risk of breakdown on younger platforms by harnessing user optimism but worsens this fragility when sentiment trading by speculators crowds out users. Elastic token issuance mitigates this fragility, but strategic attacks by miners exacerbate it because users' anticipation of future losses depresses the token's resale value.
Keywords: cryptocurrency, token price nonneutrality, optimism, platform fragility
Key Data Points
Key Insights Summary
Token Price Nonneutrality
A user's benefit from using the token is increasing in the quantity, rather than value in fiat currency, of tokens that she holds. This nonneutrality of token prices directly affects user participation and amplifies price shocks through network effects.
Platform Fragility
The network effect among users can lead to market breakdown when there is nonneutrality of the token price on users' participation decisions. This fragility is mitigated by user optimism but exacerbated by speculator sentiment.
Strategic Attacks
Strategic attacks by miners occur when the platform fundamental is sufficiently weak. Users' anticipation of future losses from these attacks exacerbates the fragility of the token market.
Life-Cycle Effects
As the platform matures and token supply increases, the token's expected retrade value falls, and user participation becomes driven more by convenience yields from transactions rather than capital gains.
Empirical Predictions
The model predicts momentum patterns in token price appreciation, a size effect in cryptocurrency returns, and a role for both news and investor sentiment in explaining cryptocurrency price changes.
Policy Implications
State-contingent token issuance policies and transaction fee adjustments can potentially mitigate market breakdown, though practical implementation challenges exist.
Content Overview
Document Contents
1. Introduction
The rapid growth of the cryptocurrency market in the last few years promises a new funding model for innovative digital platforms. Rampant speculation and volatility in the trading of many cryptocurrencies, however, have also raised substantial concerns that associate cryptocurrencies with potential bubbles. The failure of the DAO only a few months after its initial coin offering (ICO) raised $150 million in 2016, together with a number of other similar episodes, particularly highlights the risks and fragility of cryptocurrencies.
Understanding the risks and potential benefits of cryptocurrencies requires a systematic framework that incorporates several integral characteristics of cryptocurrencies—their role in funding digital platforms and in serving as investment assets for speculators and their integration of blockchain technology with decentralized consensus protocols to record transactions on the platforms. We develop such a model in this paper.
Our model analyzes the properties of cryptocurrencies on platforms that rely on network effects. Cryptocurrencies cover a wide range of tokens and coins facilitated by crypto technologies. For simplicity, we anchor our analysis on utility tokens, but our model can also be applied to coins and altcoins.
2. The Model
We model a cryptocurrency as membership in a platform, which has been created by its developer to facilitate decentralized bilateral transactions of certain goods or services among a pool of users by using a blockchain technology. Users face difficulty in making such transactions outside the platform as a result of severe search frictions.
The platform fills the users' transaction needs by pooling a large number of users who need to transact with each other. A user's transaction need is determined by its endowment in a consumption good and its preference of consuming its own good together with the goods of other users. As a result of this preference, users need to trade goods with each other, and the platform serves to facilitate such trading.
Specifically, when two users are randomly matched, they can trade their goods with each other only if they both belong to the platform. Consequently, there is a key network effect—each user's desire to join the platform grows with the number of other users on the platform and the size of their goods endowments.
3. Equilibrium
Our analysis highlights the fragility of cryptocurrency platforms induced by the network effect of user participation and decentralized token trading. Because of the network effect, users' demand curve for tokens is hump shaped (rather than downward sloping), whereas the net token supply faced by users is upward sloping.
As a result, even though a trivial equilibrium with zero user demand and zero token price always exists, the token price may fail to simultaneously clear the supply and demand for tokens with positive user participation. In this case, the token market breaks down, which occurs when the platform's demand fundamental is sufficiently weak.
Users' optimism about token price appreciation can alleviate this instability by inducing users to join the platform even when their transaction needs are low. In contrast, speculators' sentiment exacerbates this fragility by raising the cost for users to participate and crowding them out.
4. Mining and Strategic Attacks
The risk of strategic attacks by validators is a central concern for cryptocurrency platforms. Attacks on Bitcoin Gold, ZenCash, Vertcoin, Monacoin, Ethereum Classic, and Verge (twice) have already led to losses of approximately $18.6 million, $550,000, $50,000, $90,000, $1.1 million, and $2.7 million, respectively.
Such attacks include, for instance, 51% attacks under the proof of work protocol that lead to "double-spending" fraud and transaction failures through denials of service. In this section, we demonstrate that strategic attacks occur when the platform fundamental is sufficiently weak.
More importantly, the risk of such attacks in the future exacerbates the region of market breakdown by reducing the token's retrade value, which feeds back into the likelihood of a strategic attack. This adverse feedback loop is novel to decentralized cryptocurrency platforms.
5. Empirical Implications
Our framework provides a rich set of empirical predictions for token price appreciation. As only part of users' token return, the expected token price appreciation is determined by the marginal user's equilibrium condition—it equals the total cost of capital and participation minus the convenience yield from transaction surplus.
Consistent with Liu and Tsyvinski (2021), our model predicts a role for both news and investor sentiment in explaining the time series of cryptocurrency price appreciation, not through risk premia but rather, by predicting the marginal user's convenience yield.
In addition, our model can rationalize the momentum patterns that they observe in token price appreciation through the persistence of user participation costs and convenience yields, as well as the size effect that Liu et al. (2022) show in the cross-section of cryptocurrency price appreciation.
6. Conclusion
This paper develops a model to analyze the price dynamics and stability of cryptocurrencies. In our model, a cryptocurrency comprises both an asset and a membership in a platform developed to facilitate transactions of certain goods or services.
As a result of the strong network effect among users to participate on the platform and the rigidity induced by market clearing with token speculators, the market can break down so that there is only an equilibrium with zero user participation. In such a setting, token retradeability plays an important role in harnessing the optimism of users to mitigate this instability.
In contrast, it can exacerbate such fragility if it attracts speculators whose enthusiasm crowds out users. As a result of token inflation, this novel benefit of token retradeability fades as the platform matures and the token price becomes driven more by the current platform fundamental.
References
The complete paper includes extensive references to the academic literature on cryptocurrency economics, blockchain technology, and financial modeling. Key references include works by Cong et al., Biais et al., Liu and Tsyvinski, and others in the emerging field of cryptocurrency economics.
Note: The above is only a summary of the paper content. The complete document contains extensive mathematical models, proofs, data analysis, and detailed discussion. We recommend downloading the full PDF for in-depth reading.