LIN  WILLIAM  CONG

Blockchains have various applications in Finance. In particular, smart contracts enlarge the contracting space but the decentralization and transparency may also enable tacit collusion. Welfare consequences are mixed.

We provide one of the earliest dynamic asset pricing framework for cryptocurrencies and tokens, recognizing their hybrid nature as digital money and investible assets. Tokens can accelerate platform adoption and stabilizes the userbase, but endogenous user adoption amplifies token return volatility.

Contrary to the industry heuristics, mining pools as risk-sharing contracts do not lead to over-concentration. It has to be vertical integration that leads to centralization. That said, mining pools contributed as much as, if not more than, cryptocurrency prices, to the increase in the electricity devoted to cryptocurrency mining, augmenting environmental harms.

In a dynamic tokenomics framework with endogenous adoption, token pricing, and supply policy, entrepreneurs' optimal "monetary" supply follows a double-threshold policy, issuing more token dividend and compensations to reward themselves and stimulate economic activities when token supply - platform productivity ratio is low and burning tokens when it is high.

This is the CS implementation of the theoretical framework introduced in Cao, Cong, and Yang (2018). We build the architecture for auditing automation and financial disclosure using permissioned blockchains and secure multi-party computation.

When crypto taxation tightens, traders wash trade to take advantage of the lack of coordination between tax authorities and cryptocurrency trading regulatory bodies for tax-loss harvesting.

We provide the earliest rigorous and systematic detection and quantification of wash trading on centralized crypto exchanges. Unregulated exchanges on average fake over 70% of transaction volume, but regulation effectives prevents such manipulation.  

Editorial for the first special issue on the topic at a top journal summarizing recent advances in the literature, highlighting important developments and issues in research and in practice,  and proposing promising directions for future research.

We provide initial empirical evidence on the economic implications of layer-2 solution for scaling smart contracts. In a parallel-system experiment in a dominant oracle network, we observe significantly reduced operating costs and greater decentralization and improved data accuracy when the system moved from on-chain to P2P networks. 

Editorial article for the special issue on the topic summarizing recent advances in the literature, highlighting important developments and issues in research and in practice,  and proposing promising directions for future research.

We analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a setting with endogenous adoption of permissioned/federated blockchains and secure MPC. Multiple equilibria can ensue. Private incentives for firms and first-mover advantages for auditors can create inefficient under-/ partial adoption that favors larger auditors. 

Assembling a diverse set of public on-chain and off-chain, proprietary and hand-collected data, we present an initial anatomy of crypto-enabled cybercrimes, highlighting relevant economic issues and proposing areas for future research. We identify ransomware as a most dominant crypto-enabled cybercrime, entails criminal gangs and business-like operations.

Oracle integration enables interoperability and information exchanges between blockchain networks with off-chain economies. Drawing parallels with international integration, and as one of the first empirical studies on oracle networks, our paper reveals symbiotic gains and risk-sharing improvements. 

We analyze how fiat, cryptocurrencies, private payment systems, and CBDCs in an international and dynamic setting. We find that countries with dominant currencies are less incentivized to introduce CBDC relative to the ones with slightly weaker currencies, whereas small, open economies are better off adopting cryptocurrencies.

Assembling the most comprehensive cryptocurrency data to date, we construct a 5-factor model for pricing the returns of crypto assets. We systematically categorize crypto-tokens based on their economic functions and then leverage on international finance models to show significant segmentation across the categories, with "local" factor pricing models performing the best.

We offer the first systematic documentation of income, wealth, and transaction distributions in the Ethereum Ecosystem. The fixed component in fees disadvantages small players but recent changes such as the EIP-1559 and airdrop programs as redistributive monetary policies turn out to make the system more equal and democratic.

We incorporate tokens' platform consumption, investment speculation, and staking functions in a dynamic setting with potentially heterogeneous agents and stochastic aggregate shocks, for which we apply mean-field game and the master equation to solve. We identify staking ratio as the key state variable for predicting asset returns. Empirical data corroborate our model predictions.

We provide empirical evidence of households adopting cryptocurrencies for inflation hedging using proprietary data from a dominant crypto exchange in India and the country’s Household Inflation Expectations Inflation expectations prompt more new investors, particularly male investors, to begin purchasing cryptocurrencies. The effects are concentrated in Bitcoin and Tether.