Do human crypto traders know how frequently they trade with automated traders?
Human crypto traders are now much more likely to trade with automated traders than with other humans. This state of affairs has important consequences for prices and trading performance. Crypto traders’ portfolios increasingly include liabilities issued by decentralized autonomous organizations rather than organizations with human boards of directors. This too has important consequences for prices and performance.
These insights derive from new unpublished academic research that was presented at a conference hosted by Santa Clara University.1 The conference program and links to papers can be accessed here.
The conference findings are highly relevant for crypto traders who want to stay current about both big picture issues and technical trading details. Regulation of crypto markets is certainly a big picture issue, especially because of price manipulation. One of the conference presenters pointed out that there are more than a hundred crypto exchanges around the world, with some crypto investors having become “crypto millionaires” and others having lost their entire investments.
Sophisticated crypto traders will want to stay informed about emerging academic research on trading and prices. In this regard, conference presenters discussed patterns associated with automated trading, DAOs, and high fees paid by some traders to have their blockchain trades recorded early in a block.
The conference featured six conference presenters and a panel. The first three presenters focused on CeFi, meaning crypto trades taking place on centralized exchanges. The remaining presenters focused on DeFi, CeFi’s decentralized counterpart. I begin by describing the presenters’ key findings about CeFi, and then move to DeFi.
CeFi: Three Big Picture Issues
Three big picture issues associated with CeFi are:
1. The need for and shape of more effective regulation of crypto trading;
2. Interoperability and integration of blockchain technology with the real economy; and
3. Issues of reputation and dynamic incentives associated with any future transition to Web3.
Will Cong from Cornell University discussed all three issues.2 His presentation offered important insights about the current status of ransomware, real estate transactions recorded on blockchains, and decentralized oracle networks.
CeFi: Human Traders and Automated Traders
Human crypto traders are vulnerable to being manipulated by automated traders who engage in most of CeFi trading.3 Notably, while humans initiate just a tiny fraction of limit orders, they trade more frequently than automated traders. Specifically, human traders account for only 2% of limit orders, but sell cryptocurrency to other humans 27% of the time.
These findings were presented by Greg Zanotti from Stanford University.4 In addition, he pointed out that humans are less patient than automated traders. By less patient I mean that humans are more prone than automated traders to use market orders for immediate execution instead of limit orders. Specifically, the frequency of market orders by humans is 1.7 larger than their corresponding limit order frequency. In contrast, the frequency of market orders by automated traders is a tad below their corresponding limit order frequency. Humans are also more reluctant than automated traders to cancel limit orders, perhaps because of the psychological pitfall known as “status quo bias.”5
CeFi: Comovements of Cryptocurrency Returns
There are significant ways in which different cryptocurrency prices move together. Pairwise return correlations vary widely from -0.26 for some pairs to nearly 0.7 for others. These correlations are persistent, with price impacts spilling over from one exchange to another, and then becoming amplified.
Amin Shams from Ohio State University presented these findings for the largest 100 cryptocurrencies.6 Correlations are an important aspect of the price and return patterns upon which speculative traders focus. This is especially important because speculative trading has dominated blockchain activity on CeFi: Remember that there is still limited interaction between blockchains and the real economy,
Shams reports that among the variables which underlie these return co-movements, the most significant is exposure to similar investor bases. He measures “investor base similarity” with a pairwise “connectivity” variable which is related to cryptocurrencies’ trading locations. Other variables which contribute to higher correlations are similarity in market capitalizations, trading volume, and age. Moreover, cryptocurrencies with similar technical features such as consensus mechanism and tokens also demonstrate higher correlations.
DeFi: Informed Traders Trade Strategically
On DeFi platforms, traders with material information bid high fees in order to have their trades be part of the beginning of new blocks (in a chain). This is important, because these traders’ willingness to pay signals that they are differentially informed. Having their trades recorded at the beginning of blocks reduces informed traders’ execution risk.
Agostino Capponi from Columbia University presented these findings.7 Capponi pointed out that an important difference between CeFi and DeFi. In CeFi, orders are continuously matched following a price-time priority rule; however, in DeFi, orders are matched in discrete time, and significantly, require traders to bid a fee to determine their associated execution priority.
DeFi: Crypto Interest Rates
A defining feature of DeFi lending is that technical constraints limit the ability of blockchain applications to incorporate off-chain, meaning external, information. In particular, DeFi lending relies on an exogenous interest rate function. The associated protocol sets the borrowing and lending rates strictly as a function of the observed ratio of borrowed-to-available loanable funds, referred to as the utilization rate. Although this feature is potentially problematic, Thomas Rivera from McGill University presented a workaround.8
This workaround is important in providing guidance for structuring a protocol to limit the impact of constraints imbedded within the structure of DeFi. In particular, the workaround better enables agents to borrow and lend funds in a peer-to-peer fashion on a blockchain through smart contracts. Keep in mind that a major goal of DeFi is to allow users to access traditional financial services, such as borrowing and lending, without needing to rely on a trusted intermediary.
DeFi: Returns to Governance Quality in DAOs
Investors in DAOs which engage in DeFi, earn superior returns from DAOs that have high quality governance structures. Such structures promote broad participation in decision-making, and/or enhance security. Conversely, investors earn inferior returns when they invest in DAOs which feature barriers to the adoption of improvement proposals.
Ian Appel from the University of Virginia presented these findings.9 Notably, 60% of DAOs in Appel’s research sample primarily engage in DeFi. He pointed out that common functionalities for DeFi-DAOs include staking cryptocurrencies, borrowing and lending, decentralized exchanges, and stablecoins.
Ratings firms take note. Appel described a systematic approach to categorizing DAOs’ governance structures. The approach entails classifying DAOs initially into three broad categories: DeFi, Web3, and infrastructure. Within each category is a further refinement relating to 21 specific functionalities. The classification focuses on 28 dimensions involving voting mechanisms/processes, organizational design, security features, and governance models.
Crypto Trends: AI and Regulation Looming
AI and regulation top the list of issues which the conference panel identified as being on the crypto radar screen.10
The AI issue pertains to innovations which will combine blockchain technology and AI. In this respect, there is great interest in placing models and training data onto blockchains in order to render them immutable. Doing so will help different entities share training data, while preserving elements of privacy.
The regulation issue pertains to the shape of future crypto regulation. In this respect, there is a need to establish property rights and craft a legal framework to protect such rights. The panel was of the opinion that the regulation of crypto markets will take place within existing regulatory structures rather than constructing new structures.
Based on my own work on the behavioral aspects of financial market regulation, I see strong parallels between the evolution of cryptocurrencies in the last few years and the period of the 1920s which featured both great innovation and considerable market manipulation. I note that the events of the 1920s precipitated the strong regulatory measures that were enacted during the 1930s.
To sum up: The speakers at the conference highlighted crypto innovations and crypto manipulation. The panel highlighted the regulatory changes to come. All of these issues are highly relevant to the evolution of crypto markets.
1. The conference was organized by Gustavo Schwenkler, Seoyoung Kim, and Sanjiv Das.
2. The title of Will Cong’s presentation is “The Future of CeFi: Regulation, Forensics, Interoperability, and Reputation.”
3. For a discussion of the impact automated traders can have on equity markets, see the coverage by the Wall Street Journal.
4. Zanotti’s paper, co-authored with Markus Pelger, is titled “Cryptocurrency Market Microstructure: Human vs. Machine.”
5. Humans cancel approximately 85% of their limit orders, compared to automated traders who cancel 99.4%.
6. The title of Amin Shams’ paper is “Cryptocurrency Exchanges and Comovements of Cryptocurrency Returns.”
7. Agostino Capponi’s paper is entitled “Price Discovery on Decentralized Exchanges,” and is written with Ruizhe Jia and Shihao Yu.
8. The title of Thomas Rivera’s paper is “Equilibrium in a DeFi Lending Market” and it is co-authored with Fahad Saleh and Quentin Vandeweyer.
9. The title of Ian Appel’s paper is “Decentralized Governance and Digital Asset Prices,” and it is co-authored with my Santa Clara colleague Jillian Grennan.
10. Four panelists participated in a panel discussion entitled “What’s next for crypto?” The panel was chaired by my Santa Clara colleague Gustavo Schwenkler. The panel members were Jillian Grennan (Santa Clara University), Michael Li (ex Coinbase), Rupam Shrivastava (Frontiers Fund), and Sebastian Spitzer (DuckDAO).
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