Research Projects
Research Projects
Crypto Volatility Across Exchanges
by Alan Chernoff, Le "Tim" Dong and Jasper Pan
Despite extensive debate over the role of cryptocurrencies as a medium of exchange, their primary use remains as speculative digital assets. A central obstacle to broader adoption lies in the high and persistent volatility of these assets. While prior literature has extensively documented the volatility of cryptocurrencies, less attention has been paid to whether such volatility is homogenous across trading venues. In this paper, we examine cross-exchange differences in realized volatility and the incidence of extreme price jumps. Using high-frequency transaction data, we provide robust evidence that volatility dynamics vary significantly across exchanges. Our findings suggest that exchange-specific microstructure features, such as liquidity provision, market depth, and trading frictions, play a critical role in shaping observed volatility. These results contribute to the literature on cryptocurrency market efficiency and highlight the importance of exchange heterogeneity in understanding digital asset risk.
by Alan Chernoff and Julapa Jagtiani (2025) Journal of Credit Risk
Cryptocurrency markets are often characterized by market manipulation or, at the very least, by a sharp distinction between large and sophisticated investors and small retail investors. While traditional assets often see a divergence in the success of institutional traders and retail traders, we find an even more pronounced difference regarding the holders of Ethereum (ETH), the second-largest cryptocurrency by volume. We see a significant difference in how large holders of ETH behave compared with smaller holders of ETH relative to price movements and the volatility of the cryptocurrency. We find that large ETH holders tend to increase their ETH holdings prior to a price increase, while small ETH holders tend to reduce their ETH holdings prior to a price increase. In other words, ETH returns tend to move in the direction that benefits crypto “whales” while reducing returns (or increasing loss) to “minnows.” Additionally, we find that the volatility of ETH returns seems to be driven by small retail investors rather than by the crypto whales.
by Alan Chernoff and Julapa Jagtiani (2024) Journal of Digital Banking, 8 (4), 330-354
Fintech firms are often viewed as competing with banks. Instead, more recently, there has been growth in partnership and collaboration between fintech firms and banks. These partnerships have allowed banks to access more information on consumers through data aggregation, artificial intelligence/machine learning (AI/ML), and other tools. We explore the demographics of consumers targeted by banks that have entered into such partnerships. Specifically, we test whether banks are more likely to extend credit offers (by mail) and/or credit originations to consumers who would have otherwise been deemed high risk either because of low credit scores or lack of credit scores altogether. Our analysis uses data on credit offers based on a survey conducted by Mintel, as well as data on credit originations based on the Federal Reserve’s Y-14M reports. Additionally, we analyze a unique data set of partnerships between fintech firms and banks compiled by CB Insights to identify the relevant partnerships. Our results indicate that banks are more likely to offer credit cards and personal loans to the credit invisible and below-prime consumers — and are also more likely to grant larger credit limits to those consumers — after the partnership period. Similarly, we find that fintech partnerships result in banks being more likely to originate mortgage loans to nonprime homebuyers and that they increase the mortgage loan amounts that banks grant to nonprime buyers as well. Overall, we find that these partnerships could help to move us toward a more inclusive financial system.
Towards Pseudonymous Undercollateralized Loans
Undercollateralized or unsecured loans are often considered impossible in a fully decentralized and permissionless setting due to lack of recourse for lenders in case borrowers default. In this paper, I consider the problem of pseudonymous (semi-anonymous) lenders and borrowers that allows for the possibility of defaulting without any consequences from the borrowers. I study all possible strategies borrowers may use and show the conditions such that always-honest strategy dominates all subgames, i.e., Subgame Perfect Nash Equilibrium. This result may pave the way for experimenting with undercollateralized loans in fully decentralized settings, such as DeFi lending platforms that use public blockchain. Benefits of such a system include increasing liquidity provision and eliminating any source of biases against borrowers.
How Do Shareholder Defaults Influence Corporate Governance?
How do financially distressed shareholders contribute to corporate governance? To explore this question, we analyze data from the decentralized finance (DeFi) market, combining information on individual shareholder loans with their voting participation in company proposals. We find that shareholders significantly increase their voting participation when faced with financial distress.
Block Size, Miners Discretion, and Blockchain Adoption
What is the secret of top cryptocurrencies? Why is Bitcoin number one? Despite the growing literature on blockchain, the dominance of Bitcoin is not well understood. Given that Bitcoin is the slowest blockchain with the most limited programmability, it is puzzling that it can remain at the top position after 15 years. In this paper, I study the trade-offs between choosing a larger block size and keeping the cost of blockchain node low.I show that small-block blockchains, although they offer lower speed and more expensive transactions, can be preferable because the cost of monitoring these blockchains is lower, inducing more node monitoring and thus making the blockchains more secure. This conclusion helps explain why Bitcoin can remain at the top despite all its limitations. Empirical tests support the hypothesis that small-block blockchains gain more trading volume and have higher market capitalization. The result offers several important empirical implications for blockchain developers, regulators, and users.
On the Limiting Distribution of Proof-of-Stake
Proof-of-Stake (PoS) is often promised to decentralize the blockchain security over Proof-of-Work (PoW) by allowing more people to join without specialized mining hardware. However, there is no consensus in the literature on PoS's centralization, with strong arguments from both sides. Furthermore, theoretical models of PoS often assume very strong conditions that cannot be justified in practice. I relax these assumptions and derive a more realistic model that takes into account trading activity and fees. My model shows that the limiting distribution can be centralized regardless of the initial distribution, reconciling conclusions in prior studies.