Recently, the growth of cryptocurrencies has led to widespread questions in many aspects of distributed finance among the public and academic communities. Professor Cong gave a comprehensive talk at our recent Luohan Webinar where he discussed two topics elucidated by two of his papers. He primarily covered his recent paper and explored how staking rewards in his recent paper co-authored with Zhiheng He and Ke Tang. Second, he discussed evidence on the extent DeFi is aiding financial inclusion in another paper.
Staking is the action of pledging for a set period tokens one owns to be used as validators of blockchain activity in Proof-of-Stake (PoS) protocols. For this contribution, the individual who 'stakes' their coins is rewarded with yields, generally in the form of the same token. Prof. Cong provided an economic way to understand staking, by introducing a dynamic model of the token-based economy, where agents endogenously allocate their wealth on and off a digital platform. One of the key themes from his recent work is that the staking ratio is important in the system. His findings have implications for decentralized finance, token financing, and financial inclusion.
Prof. Cong began by giving a general background from his perspective on Tokenization and Tokenomics, which has been enabled by the multi-decade rise of the digital economy, peer-to-peer interactions, and on-demand digital platforms such as Uber and Airbnb. The focus of research into this field has been on what type of innovations are available in the decentralized structure and a more decentralized system, in contrast to those traditional centralized structures of intermediary platforms.
Prof. Cong importantly laid out a categorization of tokens that goes beyond whether a token is only a security or utility token. He posits four categories: 1) general payment tokens, such as Bitcoin 2) platform tokens, where tokens are used as means of payment on a well-specified platform, 3) product/ownership tokens, including NFTs and 4) security tokens. There is strong segmentation across different categories. Moving to platform token valuation, he suggests understanding it as a hybrid between money and investable asset in terms of the token’s roles, its sources of value, and sources of volatility. Coming to staking there are two main forms we can use to analyze staking. At a more base layer, it is the PoS protocols. At a higher layer, in the sense of business innovation, is Decentralized Finance (DeFi).
In the paper, the main model describes the staking economy with a continuous and infinite time horizon. Platform productivity and token utility are defined and the staking and price process is detailed. The key metric, the staking ratio, is defined as the ratio of the aggregate number of staked tokens to the total number of tokens under the currently given system states. It is crucial in this work because it links individual choices to the aggregated states, and it is public information on a platform’s official website. The model predicts three main results (in equilibrium). First, a higher staking reward ratio affects agents’ staking choices and leads to a higher system staking ratio. Second, he found the higher the staking ratio, the higher the future price appreciation, relative to the other cryptocurrencies. Third, uncovered interest rate parity (UIP) is violated in the cryptocurrency market.
Figure 1: This figure plots the positive correlation between staking ratio and staking reward ratio. For each token, they plot its mean staking ratio (y-axis) and reward (x-axis) over the entire time interval (up to Feb. 2022). The grey dashed line is the linear regression of all scattered points, while the steeper blue dashed line depicts the regression after removing the influential points with large rewards.
Source: William's slide @ Luohan Webinar, Aug 2022
To empirically examine the model predictions, they looked at 60 stackable tokens, spanning 2018-2022, on both pan-PoS protocols and on-chain (DeFi) projects. Cross-sectionally, they observed the patterns that higher average staking reward ratios lead to more people staking (Figure 1). Higher rewards attract more staking with time lags, which implies that individual actors take time for people to react. The regression result also shows that the previous staking ratio predicts the next period’s token price return. Comparing against traditional currency dynamics, the authors examined whether UIP is violated with staked tokens. The research does find UIP violations in cryptocurrency strategies, which is of high relevance for practitioners. Prof. Cong posits one explanation as the convenience yield factor alongside financial yields.
During the discussion session, one comment from the audience suggested that it could be empirically important to estimate the curvature of the staking ratio curve on price appreciation. This could be informative for investors and regulators to understand, for example, if the curve is concave and has a diminishing return.
Lastly, Prof. Cong discussed another crucial question - do Web3 and DeFi give benefits for financial inclusion and democratization? presented his finding in another paper Inclusion and Democratization Through Web3 and DeFi. He discussed some empirical patterns in the Ethereum ecosystem (Figure 2), such as the distributions of miners, token owners, and transactions. Specifically, he highlights that miners and token owners are a highly concentrated group, and that significantly more usage of the network is by large players. Financial democratization and inclusion are hindered by the current mechanisms that lead to, among others, high token volatility. To mitigate the issues and facilitate financial inclusions, they emphasized the redistributive effect of the EIP-1559 fee mechanism, which benefits small players. He also highlights the airdrop programs of DeFi, designed to distribute a token more widely, as an area that has not been studied enough yet.
Figure 2: This figure shows the competition and partnership among various categories of DApps on the Ethereum Network. The DApps with the same color close to each other are competitive, and the DApps with different colors close to each other are cooperative.
Source: William's slide @ Luohan Webinar, Aug 2022
Paper: https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=4059460
If you would like to give a presentation in a future webinar, please contact our Senior Economist Dr. Wen Chen (wen.chen@luohanacademy.com).
For other inquires, contactevents@luohanacademy.com.
