I am a third-year finance Ph.D. student at MIT Sloan, interested in cryptocurrencies, entrepreneurship, and labor. Recently, I worked on an anatomy of the largest stablecoin run using depositor-level data from the blockchain. I studied statistics at the University of Chicago, where I briefly researched 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).
- My CV
- Google Scholar: Jiageng Liu
- Twitter: @JiagengLiu
- Email: jiageng @ mit.edu
How to pronounce my name
Research
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, 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
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 by the P/E limit, the trading prices are, on average, 15% to 30% higher than those before the rules. 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.