As much as cryptocurrency and decentralised finance (DeFi) markets had giveth, this year they taketh away. Market participants were rudely awakened to the fact that the decentralised utopia envisioned in Satoshi Nakamoto’s 2008 writing on bitcoin was simply an unrealistic dream. Investors walked in, lured by incentives and computer code; they walked out, with displaced trust.
Terra Luna
The first notable blow came from the Terra Luna crash in May 2022. Terra’s algorithmic decentralised stablecoin was touted to be trustless and, through dynamic trading, to be able to generate higher yield than other alwaysfully-backed stablecoins. In the parlance of cryptocurrencies, “trustless” refers to the decentralised quality of blockchains, where there is no need for users to rely on trust in a third party. Terra came up with a creative market-based mechanism that aimed to maintain stability. However, the white paper implied that users needed to believe in continuous demand for Terra’s token Luna. When demand collapsed, the project promptly failed. Research shows that algorithmic stablecoins can never be jointly stable, efficient and decentralised.
DAOs
Apart from token prices, we also learned this year that decentralised autonomous organisations (DAOs) are not fully trustless. For example, in June, a majority voted to seize a whale’s account on the DeFi lending platform Solend. Although they later backtracked, this experience highlights two forms of trust. First, you must trust the rest of the ecosystem to honour basic property rights and not gang up on you. Second, you must trust that fundamentally human decisions will get implemented in code. It turns out that Kenneth Arrow’s impossibility theorem, written in 1951 and for which he won a Nobel prize in 1972, still rings true. The theorem states that when there are three or more alternatives, no system can always generate a society-level decision that can evaluate all societal choices, ensure non-dictatorship, agree to an outcome even if all participants prefer it, and be insensitive to adding irrelevant options. The year 2022 tells us that DAOs are not infallible.
3AC and Celsius
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Things become complicated when economic activities involve off-chain transactions. Three Arrows Capital (3AC) was a hedge fund that participated in a wide range of centralised and decentralised assets. When it blew up in June 2022, it imposed losses of over US$3.5 billion ($4.75 billion), much of it from decentralised assets. The fund owed US dollars and bitcoin, among others, and its creditors included “decentralised” protocols that had entrusted their treasury to the fund in the first place.
It turns out that if your decentralised protocol trusts someone, it is no longer decentralised. Once you step even a tiny bit off-chain, all bets are off. Something similar happened with the cryptocurrency lending company Celsius around the same time. Celsius was a trusted centralised service. But as it unwound on-chain positions, it drained a lot of liquidity from protocols like Aave. Celsius was a large player across DeFi and was the largest user of some protocols. Aave shrank a lot when this centralised off-chain player went under. The core product, in much the same style as Terra’s UST in May, relied on everyone responding to incentives in a specific way. It turns out that when a large player acts differently, protocols can explode.
FTX
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“Decentralised” protocols and networks have hidden some trust assumptions. The more recent FTX blow-up bears witness. FTX was a large, centralised exchange whose affiliated proprietary trading arm used customer funds to trade and incurred huge losses. Importantly, when FTX blew up, we learned just how much of DeFi was dependent on their services to work. The DeFi exchange Serum is all but gone, and it is not obvious if the blockchain platform Solana will survive. The Sollet protocol turned out to rely entirely on FTX, and its wrapped tokens broke the peg. It turns out that much of DeFi relies heavily on trusted parties. If your plan is to “centralise first, decentralise later”, a risk is that you do not survive until “later”.
History does not repeat, but it rhymes
Mark Twain said: “History does not repeat, but it rhymes.” These phenomena in DeFi markets are not entirely new.
American economic historian Charles Kindleberger pointed out that as novelties emerge, early adopters start making outsized returns, enticing more uninformed investors, driving a bubble followed by a subsequent crash. However, following the crash comes a deeper understanding of the risks, more regulation, and a deeper appreciation of the novelty beyond surface platitudes of “ground-breaking” and “paradigm-shifting” technology.
Hence, despite the crashes and panic this year, we may end up in a better place in 2023. Participants in the cryptocurrency markets may now better understand why certain regulations in traditional finance exist. With deeper technology insights, we may also better appreciate how financial technologies can improve compliance and safety of financial institutions.
For example, the US Securities and Exchange Commission Rule 17a-5 requires broker-dealer companies to attest to “moment-to-moment compliance” with Financial Responsibility Rules that require the segregation of client assets from a broker-dealer’s own assets (something we now wish FTX did). In fact, the rule was passed in response to large-scale Ponzi schemes like those by Bernie Madoff in 2008 and large bankruptcies like MF Global in 2011. Broker-dealers appeared to scramble to invest in regulatory technology to comply with this new rule, spending billions of dollars. Perhaps, with on-chain data, regulators can easily verify moment-to-moment compliance by reading off balances of ledgers of the appropriate wallets.
Ben Charoenwong is an assistant professor of finance at the National University of Singapore (NUS) Business School, where he teaches international finance and conducts research on financial regulation. The opinions expressed are those of the writer and do not represent the views and opinions of NUS. Jonathan Reiter is co-founder of Data Finnovation