Academics offer important insights into the evolution of crypto markets

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mobile with Crypto.com seen onscreen in the background. On February 19, 2023 in Brussels, Belgium. (Photo illustration by Jonathan Raa/NurPhoto via Getty Images)NurPhoto via Getty Images

Academic studies reveal a lot about how the crypto markets are evolving, both in terms of the big picture and the underlying technical issues. In this article, I discuss key insights from a set of research studies whose results were presented at a recent conference held at Santa Clara University.1 The conference program and links to the articles can be accessed here.

Some of the big issues discussed at the conference include automated crypto trading, decentralized autonomous organizations, and regulations aimed at combating crypto price manipulation. Regarding regulation, one of the presenters at the conference pointed out that there are over a hundred crypto exchanges in the world, with some crypto investors having become crypto millionaires and others having lost all of their investments. Among the technical issues discussed are the high fees paid by traders to have their blockchain transactions recorded at the start of a block, and the efficient setting of interest rates in peer-to-peer crypto lending markets.

The conference brought together six speakers and a panel. The first three presenters focused on CeFi, meaning that crypto transactions take place on centralized exchanges. The remaining presenters focused on DeFi, the decentralized counterpart of CeFis. I begin by outlining the key takeaways from the presenters on CeFi, then move on to DeFi.

Will Cong from Cornell University gave a presentation titled The Future of CeFi: Regulation, Forensics, Interoperability, and Reputation. It begins with a statement that many investors believe: cryptocurrencies and digital assets will ultimately provide cheap, fast, and secure ways to transfer value. This belief is plausible and the transformation, if it occurs, will greatly disrupt traditional financial systems. As an example of the real economy, Cong mentions the use of blockchain technology for real estate transactions.

Notably, Cong points out that in the absence of effective market regulation, crypto markets have provided new channels for cybercrime and market manipulation. Going forward, he suggests CeFi can benefit from effective regulation, interoperability with other platforms, and with non-blockchain components of the economy.

Regarding market manipulation, Greg Zanotti from Stanford University presented a paper suggesting that human crypto traders seem to respond to manipulation attempts more easily than automated traders. His article, co-authored with Markus Pelger, is titled Cryptocurrency Market Microstructure: Human vs. Machine.

Zanotti and Pelger investigate a series of important questions about the relative activity of human traders and automated traders on centralized exchanges. Notably, while humans only initiate a tiny fraction of limit orders, they trade more frequently than automated traders. Specifically, although human traders only account for 2% of limit orders, humans sell cryptocurrency to other humans 27% of the time. Humans are also less patient than automated traders. By this I mean that humans are more inclined than automated traders to use market orders for immediate execution instead of limit orders. In this regard, the frequency of market orders by humans is 1.7 greater than their corresponding limit order frequency. In contrast, the frequency of market orders by automated traders is somewhat lower than their corresponding limit order frequency.

Given the current limited interaction between blockchains and the real economy, speculative trading has dominated blockchain activity on CeFi. In this regard, price and yield patterns are important things that speculators focus on. Amin Shams from Ohio State University presented a paper titled Cryptocurrency Exchanges and Comovements of Cryptocurrency Returns. It asks to what extent the top 100 cryptocurrencies move together, as well as the variables underlying these co-movements.

Shams reports that back pair correlations vary widely from -0.26 for some pairs to nearly 0.7 for others. Moreover, he notes, this correlation structure is persistent, with price impacts propagating from exchange to exchange and then amplifying.

Shams reports that among the variables underlying these co-movements, the most important is exposure to similar investor bases. It measures basic investor similarity with a pairwise connectivity variable that is related to cryptocurrency trading venues. Other variables that contribute to higher correlations are market capitalization similarity, trading volume, and age. Moreover, cryptocurrencies with similar technical characteristics such as consensus mechanism and token industry also show higher correlations.

The next three presentations focus on DeFi.

Agostino Capponi from Columbia University presented a paper titled Price Discovery on Decentralized Exchanges, written with Ruizhe Jia and Shihao Yu. Capponi highlights an important difference between CeFi and DeFi. In CeFi, orders are continuously matched according to 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. Capponi and his co-authors report that traders with important information offer high fees so that their transactions become part of the start of new blocks (in the chain). This reduces the execution risk for these savvy traders.

DeFi allows users to access traditional financial services, such as borrowing and lending, without the need to rely on a trusted intermediary. Thomas Rivera from McGill University presented a paper titled Equilibrium in a DeFi Lending Market which analyzes the properties of DeFi protocols that allow agents to borrow and lend peer-to-peer funds on a blockchain via smart contracts. The article is co-authored with Fahad Saleh and Quentin Vandeweyer. A defining feature of DeFi lending is that technical constraints 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 that sets borrowing and lending rates strictly based on the observed ratio of borrowed funds to available loanable funds, called the utilization rate. This feature is potentially problematic; however, Rivera and his co-authors discuss how to structure protocols to limit the impact of these constraints.

One of the most intriguing aspects of cryptocurrency markets is the concept of a decentralized autonomous organization. DAOs are crypto-native organizations that operate without centralized management. Ian Appel from the University of Virginia presented an insightful article on the topic of DAOs, titled Decentralized Governance and Digital Asset Pricing. The article is co-authored with my colleague from Santa Clara, Jillian Grennan. In a DAO, management and financial decisions are made by token holders using a decentralized voting process. Appel and Grennan examine the relationship between governance and performance. They find higher returns associated with DAOs that feature governance structures that promote broad participation in decision-making or improve security. Conversely, lower returns are associated with DAOs that present barriers to the adoption of improvement proposals.

Four panelists participated in a panel discussion titled Whats next for crypto? The panel was chaired by my colleague from Santa Clara, Gustavo Schwenkler, and focused on two main issues. The first challenge concerns new innovations that will combine blockchain technology and AI. There is great interest in placing models and training data on blockchains to make them immutable. This will help different entities to share training data, while preserving privacy elements. The second issue concerns the form of future crypto regulation. It is necessary to establish property rights and develop a legal framework to protect these rights.

Based on my own work on the behavioral aspects of financial market regulation, I see strong parallels between the evolution of cryptocurrencies in recent years and the period of the 1920s which featured both a large innovation and considerable market manipulation. I note that the events of the 1920s precipitated the strong regulatory measures that were adopted during the 1930s.

Conference speakers highlighted cryptographic innovations and cryptographic manipulation. The panel highlighted upcoming regulatory developments.

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1. The conference was organized by Gustavo Schwenkler, Seoyoung Kim and Sanjiv Das.

I have been a behavioral economist for over 45 years, and I have had the good fortune to study the impact of psychology on the functioning of the financial world. Currently the Mario L. Belotti Chair in Finance at Santa Clara University, I earned my BSc from the University of Manitoba, earned my MSc in Mathematics from the University of Waterloo, and I have a doctorate. from the London School of Economics. Books I’ve written include Beyond Greed and Fear, A Behavioral Approach to Asset Pricing, Behavioral Corporate Finance, Ending the Management Illusion, Behavioralizing Finance, and Behavioral Risk Management. I have been recognized as an academic finance star by CFO magazine and a leading economic theorist for influencing the empirical work of the American Economic Review.

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