Decentralized Exchanges (DEX) with Automated Market Maker (AMM) Protocols

UCL Information Security Research Seminar on 09.12.21

Abstract: As an integral part of the decentralized finance (DeFi) ecosystem, decentralized exchanges (DEX) with automated market maker (AMM) protocols have gained massive traction with the recently revived interest in blockchain and distributed ledger technology (DLT) in general. Instead of matching the buy and sell sides, AMMs employ a peer-to-pool method and determine asset price algorithmically through a so-called conservation function. To facilitate the improvement and development of AMM-based DEX, we create the first systematization of knowledge in this area. We first establish a general AMM framework describing the economics and formalizing the system's state-space representation. We then employ our framework to systematically compare the top AMM protocols' mechanics, illustrating their conservation functions, as well as slippage and divergence loss functions. We further discuss security and privacy concerns, how they are enabled by AMM-based DEX's inherent properties, and explore mitigating solutions. Finally, we conduct a comprehensive literature review on related work covering both DeFi and conventional market microstructure.

Speaker: Jiahua Xu, Centre for Blockchain Technologies, Financial Computing and Analytics Group, UCL Computer Science (https://jiahua-xu.com/)

Bio: Dr. Jiahua Xu is Lecturer in Financial Computing at UCL, where she teaches Blockchain Technologies and Machine Learning in Finance. She is a researcher at the university’s Centre for Blockchain Technologies, and serves as Programme Director of the MSc Emerging Digital Technologies under the Computer Science Department. Jiahua’s research interests lie primarily in blockchain economics, behavioural finance, and risk management. Jiahua earned her PhD from the University of St. Gallen in Switzerland, MSc from the University of Mannheim in Germany, and BA from Fudan University in China. She visited and has ongoing research collaboration with Harvard Business School, Imperial College London, and Vienna University of Economics and Business