UROP Proceedings 2020-21

School of Science Department of Mathematics 44 Department of Mathematics Statistical Analysis in Portfolio Construction Supervisor: CHEN Kani / MATH Student: SONG Wenxin / DSCT Course: UROP1100, Spring Stable coins are a new kind of cryptocurrency. They are backed by some tangible assets and are designed to obtain price stability; usually, 1:1 pegged to some widely used real-world currencies like US Dollar, Bound or Korean. It now plays a significant role in decentralized finance. This project focus on some popular stable coins and data analysis about them. This project first investigates some widely used coins like Dai, MKR, and their mechanism. Then we obtain some relevant data of some coins to do explanatory analysis to see their properties and characteristics. Further, we explore the possibility of arbitrage through stable coins. Statistical Analysis in Portfolio Construction Supervisor: CHEN Kani / MATH Student: NAN Xi / DSCT Course: UROP1100, Summer Noncustodial automated market makers such as Uniswap serve as an on-chain system of smart contracts on the Ethrereum blockchain, implementing an automated liquidity protocol. The development of Uniswap Version 3 provides increased capital efficiency and fine-tuned control to liquidity provides, improves the accuracy and convenience of the price oracle, and has a more flexible fee structure. At the macroscopic level, this improves capital efficiency while significantly raises the bar for liquddidity providers from microscopic. In this project, we try to find out some Uniswap V3 LP strategies. Statistical Analysis in Portfolio Construction Supervisor: CHEN Kani / MATH Student: ZHANG Kaizheng / QFIN Course: UROP1100, Summer The background of this UROP project is a recent V3 update of the largest DEX, (decentralized exchange), Uniswap. Specifically, Uniswap used to manage liquidity providers’ stored tokens uniformly. In V3, however, it divides liquidity on different price ranges, and liquidity providers are required to specify the range on which they will provide every piece of liquidity. This fundamentally changes the strategies of liquidity providers – previously LPs could simply profit by putting a static pair in the pool (passive strategy). However, V3 would require LPs to predict the volatility of the relative price, making passive strategies unprofitable. Making a prediction of such near-future volatility and optimize other aspects of the strategy is the key for us when designing a practically profitable “proactive” liquidity management strategy. During the project, several PLM strategies were designed, optimized and backtested.