I am a fourth-year Ph.D. student at MIT Sloan Finance. I'm interested in cryptocurrency, banking, and entrepreneurship. I am working on understanding banks in Brazil in the 1990s. Previously, I worked on fund competitions and stablecoin runs in cryptocurrency. I studied statistics at the University of Chicago, where I briefly reflected on the IPO market in China. I received B.S. in mathematics summa cum laude from UCLA, where I worked on large-scale optimization algorithms. A native of Zhengzhou, China, I constantly miss hulatang, a spicy soup.
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- Google Scholar: Jiageng Liu
- Twitter: @JiagengLiu
- Email: jiageng @ mit.edu
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Research
Research
4. Banking, Inflation, and Development, 2025
4. Banking, Inflation, and Development, 2025
with Tomás da Nóbrega. Work in progress.
3. Competition in Crypto Staking, 2024
3. Competition in Crypto Staking, 2024
with Igor Makarov and Antoinette Schoar. Working paper to come.
We study the economics of the Cardano staking market, which shares many similarities with traditional financial industries such as index and money market funds. Using detailed blockchain data, we present two main findings. First, we construct a measure of delegator mobility and document significant heterogeneity in mobility across delegators. Second, we show that validators strategically set their fees by considering delegator mobility and variations in scale economies. These findings provide direct evidence of the important role of capital mobility in shaping pricing strategies in equilibrium and offer important implications for the design of staking markets in decentralized finance.
Presented at CBER, LSE, MIT Sloan Finance Brownbag, SDA Bocconi, Warwick Business School, Innovations in Financial Intermediation Symposium, and Bank of Canada.
Distribution of capital mobility rates. The upper panel plots the cross-sectional capital mobility distribution of delegators (investors) at the beginning, middle, and end of the sample period. The bottom panel plots the distribution of the value-weighted average rates on the validator (fund) level.
with Igor Makarov and Antoinette Schoar. Working paper.
Terra, the third largest cryptocurrency ecosystem after Bitcoin and Ethereum, collapsed in four days in May 2022 and wiped out $50 billion in valuation. At the center of the collapse was a run on a blockchain-based borrowing and lending protocol (Anchor) that promised high yields to its stablecoin (UST) depositors. Using detailed data from the Terra blockchain and trading data from exchanges, we show that the run on Terra was a complex phenomenon that happened across multiple chains and assets. It was unlikely due to concentrated market manipulation by a third party but instead was precipitated by growing concerns about the sustainability of the system. Once a few large holders of UST adjusted their positions on May 7th, 2022, other large traders followed. Blockchain technology allowed investors to monitor each other's actions and amplified the speed of the run. Wealthier and more sophisticated investors were the first to run and experienced much smaller losses. Poorer and less sophisticated investors ran later and had larger losses. The complexity of the system made it difficult even for insiders to understand the buildup of risk. Finally, we draw broader lessons about financial fragility in an environment where a regulatory safety net does not exist, pseudonymous transactions are publicly observable, and market participants are incentivized to monitor the financial health of the system.
Presented at LSE, Northwestern Kellogg, MIT Sloan, 2nd Annual DeFi conference, ICI–SNPI Conference, NYU Stern, McGill, MIT Digital Currency Initiative, LUISS, Bocconi, Chicago Fed, Chicago Booth, NBER Summer Institute 2023, 7th Annual Macroprudential Policy Conference, OSU, CFRI Conference, Federal Reserve Board, Tulane, Frankfurt, Banque de France, Vanderbilt, King's, LBS, Jackson Hole.
Withdrawals from Anchor from May 6 to May 14, 2022, broken down by the size of the deposit balance of addresses as of May 6, before the run.
1. Delayed and Distorted Price Discovery: Post-IPO Stocks in China, 2020
1. Delayed and Distorted Price Discovery: Post-IPO Stocks in China, 2020
Master's thesis. Resting.
Abstract: I document that regulatory changes in the Chinese IPO market in 2013-14 distorted the price of new stocks and delayed price discovery. The rules impose a low price-to-earnings cap on the IPO price and restrict the daily price changes after listing. Under the new regulations, prices stay at the (increasing) upper limit with minimal trading for about two weeks after the listing date. Although the listing prices are suppressed, the trading prices are, on average, 15% to 30% higher. This translates to a 240 billion CNY higher valuation among post-IPO stocks, though the overvaluation reverses to the market median level over the first year after listing. A shift in IPO industry composition from high-P/E to low-P/E after the rule change is consistent with market distortion.
Presented at MIT Golub Center for Finance and Policy (GCFP).
Price-to-Earnings (P/E) of IPOs in China, 2010-2020. Black points are the P/E of new stocks being listed on the Shanghai or Shenzhen Stock Exchanges. The blue line is the median P/E of all stocks being traded on the market. The 2014 rule caps new listings at 23.
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