Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Stablecoins and Lending Markets
Fixed-Rate Lending Protocols and Derivatives
Staking Derivatives
Staking Fees as Stable Interest
Stabilization Mechanisms
Some Caveats
Diversification, Interest Rates Swaps, and Tranching
Towards Universal Basic Income
Closing Remarks
Acknowledgements and References Stablecoins and Lending Markets Stablecoins and Lending Markets Fixed-Rate Lending Protocols and Derivatives Fixed-Rate Lending Protocols and Derivatives Staking Derivatives Staking Derivatives Staking Fees as Stable Interest Staking Fees as Stable Interest Stabilization Mechanisms Stabilization Mechanisms Some Caveats Some Caveats Diversification, Interest Rates Swaps, and Tranching Diversification, Interest Rates Swaps, and Tranching Towards Universal Basic Income Towards Universal Basic Income Closing Remarks Closing Remarks Acknowledgements and References Acknowledgements and References 8 Diversification, Interest Rates Swaps, and Tranching As reviewed so far, the key idea behind the generation of highly competitive interest rates in decentralized finance is to make use of the staking fees as a source of income for savings. In section 4 we mentioned some advantages of not directly staking the savings, and only receiving staking yield via the lending market. However, there may also be advantages in directly engaging with generating income with the deposited savings, rather than lending the money out to borrowers. One such advantage is the economy of scale. For example, the Yearn protocol [47] systematically searches for maximal gain with a combination of lending interest rates, staking fees, leveraged reinvestments of the borrowed money, etc , and can achieve much higher return than simple staking strategies. It takes considerable effort to keep track of the changing fee rates, availability of new yieldearning products, etc. But for a decentralized organization at the scale of a bank, the overhead cost incurred is more likely to be worthwhile. One lucrative way of generating passive income is liquidity pool yield farming [48]. In decentralized finance, in order to create a market to exchange, rather than relying on a traditional central market maker, one needs to create a pool of funds to allow trades to happen instantly and smoothly. By contributing to such a liquidity pool, one earns fees in return, when transactions take place. In other words, for an automated market to be able to allow trades between two currencies X and Y, that mechanism needs to have enough flowing infantry of both currencies. But merely putting down these currencies into the mechanism, one is thereby facilitating trades. So, in a way not unlike staking, one earns the deserved reward through the process; accordingly this kind of ‘investment ‘ is sometimes called liquidity pool ‘staking’, even though it is distinct from the type staking in PoS networks mentioned earlier. The fees one can earn in joining liquidity pools are typically on the order of under 10% annual rate. However, when a new pool is formed, often there are extra incentives to attract initial endowment, and those can be extremely lucrative, sometimes reaching over 100% annual rate. The process of earning these high annual rates is sometimes called yield farming, as one is essentially investing into a new pool hoping that it would grow as expected, to allow yields to be ‘harvested’. As expected, at such high annual rates there are also risks involved. The incentives in yield farming are typically given in the native currency of the protocol, which may not turn out to be so valuable in the long run if the protocol does not turn out to be successful. Besides that, similar to staking, the value of the assets deposited into the liquidity pool may fluctuate in time. Besides simple depreciation, when the balance of the two deposited assets changes (e.g. one increases in value while the other does not), this can create another kind of deficit known as impermanent loss [49, 50]. Despite these risks, there are arguments to be made that as a bank-like organization, these are investment opportunities worth pursuing. One reason is that at a large enough scale, one can methodically and effectively make use of insurance and hedging instruments. For example, earlier in section 3 we mentioned the use of interest rate swaps to turn a variable-rate future income into fixed-rate income. In decentralized finance, protocols like Horizon [51] are also creating opportunities for doing so. Even in the absence of a fluid interest rates market, Horizon makes use of game theoretic and auction-like mechanisms to facilitate the swaps. This way, one can opt to take a smaller but fixed yield from farming liquidity pools. To manage risks, protocols like Barnbridge [52] and Saffron [53] also allow one to break down an investment or loan into ‘tranches’, each representing different risk levels. For example, a ‘senior’ tranche may lead to a lower yield overall, but the rate will be more guaranteed. A bank-like organization can select the appropriate risk level given the reserve level at the moment, with the guiding principle that higher risks are only affordable when there is sufficient excess in reserve. These strategies are not mutually exclusive with extracting staking fees via borrowers’ collateral, which is admittedly virtually risk-free. That is because when there is enough borrowing demand, essentially the borrowers absorb most of the risk involved. However, these riskier and higher yield strategies can be employed in parallel, especially when borrowing demand is low. As with competitive banks in the real world, financial institutions typically participate in various activities including both investment and lending. If the goal is to give savers the highest stable interest rates at minimal risks, an algorithm that explicitly optimizes for the ideal combination of different strategies to achieve this goal should be in principle more advantageous than fixating onto a single strategy a priori. Authors:
(1) Hakwan Lau, Center for Brain Science, Riken Institute, Japan (hakwan@gmail.com);
(2) Stephen Tse, Harmony.ONE (s@harmony.one). Authors: Authors (1) Hakwan Lau, Center for Brain Science, Riken Institute, Japan (hakwan@gmail.com); (2) Stephen Tse, Harmony.ONE (s@harmony.one). This paper is available on arxiv under CC BY-SA 4.0 DEED license. This paper is available on arxiv under CC BY-SA 4.0 DEED license. available on arxiv

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