Do human crypto traders know how often they trade with automated traders?
Human crypto traders are now much more likely to trade with automated traders than with other humans. This situation has a significant impact on price and trading performance. Cryptocurrency traders’ portfolios increasingly include debt issued by decentralized autonomous organizations rather than organizations with human boards of directors. This also has important implications for price and performance.
These insights are based on new, unpublished academic research presented at a conference hosted by Santa Clara University.1 The conference program and links to papers can be accessed here.
The conference results will be highly relevant to crypto traders who want to stay up to date on both big-picture issues and technical trading details. Regulation of the cryptocurrency market is certainly a big issue, especially because of price manipulation. One of the speakers at the conference said that there are over 100 crypto exchanges around the world, and that some crypto investors have become “crypto millionaires” while others have lost their entire investment. He pointed out that he had lost it.
Sophisticated crypto traders want to stay informed about new academic research on trading and pricing. In this context, conference presenters discussed patterns related to automated trading, DAOs, and high fees paid by some traders to record blockchain transactions early in the block. .
The conference featured six conference presenters and one panel. The first of his three presenters focused on his CeFi, which stands for crypto trading conducted on centralized exchanges. The remaining presenters focused on DeFi, CeFi's decentralized counterpart. We begin by explaining the presenter's main findings regarding CeFi, and then move on to DeFi.
CeFi: Three big picture questions
The three big issues related to CeFi are:
1. The need for and form of more effective regulation of virtual currency transactions.
2. Interoperability and integration of blockchain technology with the real economy.and
3. Reputation and dynamic incentive issues with future migration to Web3.
Will Cong of Cornell University discussed all three issues.2 His presentation provided important insights into the current state of ransomware, blockchain-recorded real estate transactions, and decentralized oracle networks.
CeFi: Human traders and automated traders
Human crypto traders can be manipulated by automated traders who do most of the CeFi trading.3 It's worth noting that humans initiate only a small percentage of limit orders, but they trade more frequently than automated traders. Specifically, human traders only account for 2% of limit orders, but sell cryptocurrencies to other humans 27% of the time.
These findings were presented by Greg Zanotti from Stanford University.Four Additionally, he pointed out that humans have less patience than automated traders. Being less patient means that humans are more likely than automated traders to use market orders for immediate execution rather than limit orders. Specifically, the frequency of market orders by humans is 1.7 times greater than the frequency of corresponding limit orders. In contrast, the frequency of market orders by automated traders is slightly lower than the frequency of corresponding limit orders. Humans are also more reluctant than automated traders to cancel limit orders, perhaps due to a psychological pitfall known as “status quo bias.”Five
CeFi: Cryptocurrency return movement
There are important ways in which the prices of different cryptocurrencies move in tandem. Pairwise return correlations vary widely, from -0.26 for some pairs to almost 0.7 for others. These correlations are persistent, and the price impact cascades from one exchange to another and is further amplified.
Amin Shams of Ohio State University published these findings on up to 100 cryptocurrencies.6 Correlation is an important aspect of price and return patterns that speculative traders focus on. This is especially important as speculative trading dominates blockchain activity in CeFi. Remember that the interaction between blockchain and the real economy remains limited.
Shams reports that among the variables underlying this synergy of returns, the most important is exposure to a similar investor base. He measures “investor base similarity” using a pairwise “connectivity” variable related to where cryptocurrencies are traded. Other variables that contribute to higher correlations are market capitalization, trading volume, and age similarity. Furthermore, cryptocurrencies with similar technical characteristics such as consensus mechanisms and tokens also show higher correlations.
DeFi: Informed traders trade strategically
On DeFi platforms, traders with sensitive information bid high fees to have their trades part of the beginning of a new block (in the chain). This is important because the fact that these traders are willing to pay indicates that they are receiving discriminatory information. Recording trades at the beginning of the block reduces execution risk for informed traders.
Agostino Capponi of Columbia University presented these findings.7 Capponi pointed out an important difference between CeFi and DeFi. In CeFi, orders are continuously matched according to price and time priority rules. However, in DeFi, orders are matched in discrete time, so traders must bid fees to determine the associated execution priority.
DeFi: Cryptocurrency interest rates
DeFi lending is characterized by technical constraints that limit the ability of blockchain applications to incorporate off-chain, i.e. external, information. In particular, DeFi lending relies on an exogenous interest rate function. The associated protocols set the borrowing and lending rates strictly as a function of the ratio of observed borrowed funds to available loanable funds, called the utilization rate. There may be a problem with this feature, but Thomas Rivera from McGill University has provided a workaround.8
This workaround is important in providing guidance for building protocols that limit the impact of constraints built into the structure of DeFi. In particular, this workaround allows agents to lend and borrow funds in a peer-to-peer manner on the blockchain through smart contracts. Keep in mind that the main goal of DeFi is to allow users to access traditional financial services, such as lending and borrowing, without relying on trusted intermediaries.
DeFi: A return to quality governance in DAOs
Investors in DAOs working in DeFi can earn superior returns from DAOs with high-quality governance structures. Such structures encourage broad participation in decision-making and enhance security. Conversely, investors who invest in his DAOs that have barriers that prevent the adoption of improvement proposals will have inferior returns.
Ian Appel from the University of Virginia presented these findings.9 Notably, 60% of DAOs in Appel's research sample are primarily engaged in DeFi. He pointed out that common features of DeFi-DAOs include cryptocurrency staking, lending and borrowing, decentralized exchanges, and stablecoins.
Rating companies are paying attention. Mr. Appel described a systematic approach to classifying DAO governance structures. In this approach, we must first classify DAOs into three broad categories: DeFi, Web3, and Infrastructure. Within each category, further improvements are made related to 21 specific features. This classification focuses on 28 aspects including voting mechanisms/processes, organizational design, security features, and governance models.
Cryptocurrency trends: AI and regulation looming
AI and regulation are at the top of the list of issues that the conference committee has identified as being on the crypto radar screen.Ten
The issue of AI concerns innovation that combines blockchain technology and AI. In this regard, there is a great deal of interest in placing models and training data on the blockchain to make it immutable. Doing so allows different entities to share training data while maintaining an element of privacy.
Regulatory issues concern the shape of future cryptocurrency regulation. In this regard, there is a need to establish property rights and create a legal framework to protect such rights. The panel was of the opinion that regulation of the virtual currency market will take place within the existing regulatory structure rather than building a new one.
Based on my own research on the behavioral aspects of financial market regulation, I see strong similarities between the evolution of cryptocurrencies in recent years and the era of the 1920s, which was characterized by both great innovation and significant market manipulation. It turns out that there is. He notes that the events of the 1920s prompted the strong regulatory measures he enacted in the 1930s.
In summary, conference speakers highlighted cryptocurrency innovation and crypto operations. The panel highlighted upcoming regulatory changes. All these issues are very relevant to the evolution of the cryptocurrency market.
1. This conference was hosted by Gustavo Schwenkler, Seoyoung Kim, and Sanjiv Das.
2. Will Cong's presentation is titled “The Future of CeFi: Regulation, Forensics, Interoperability, and Reputation.”
3. See the Wall Street Journal coverage of how automated traders are impacting the stock market.
4. Zanotti's paper, co-authored with Markus Pelger, is titled “The Microstructure of Cryptocurrency Markets: Man vs. Machine.”
5. Humans cancel about 85% of limit orders, while automated traders cancel 99.4%.
6. Amin Shams’ paper is titled “Cryptocurrency Exchanges and Cryptocurrency Return Communities”.
7. Agostino Capponi's paper is titled “Price Discovery in Decentralized Exchanges” and is co-authored with Ruizhe Jia and Shihao Yu.
8. Thomas Rivera's paper is titled “Equilibrium in a DeFi Lending Market” and was co-authored with Fahad Saleh and Quentin Vandeweyer.
9. Ian Appel's paper is titled “Decentralized Governance and Digital Asset Prices” and was co-authored with Santa Clara colleague Jillian Grennan.
10. Four panelists participated in a panel discussion titled “What’s Next for Cryptocurrency?” The panel discussion was chaired by my Santa Clara colleague Gustavo Schwenkler. Panelists included Jillian Grennan (Santa Clara University), Michael Li (ex-Coinbase), Rupam Shrivastava (Frontiers Fund), and Sebastian Spitzer (DuckDAO).