Shuyue Li is a doctoral candidate in Banking and Finance at the University of Southampton, with an anticipated completion in 2024. His research focuses on information efficiency and memory dynamics within virtual currency markets, with particular emphasis on strategy optimization using machine learning and deep reinforcement learning techniques. Through his interdisciplinary work, Shuyue explores the application of quantitative methods to financial market analysis, aiming to enhance our understanding of long-memory system modeling.
Shuyue holds a Master of Science in Finance from the University of Southampton, where he graduated with distinction. During his master's studies, he conducted advanced research in time series forecasting using long-memory models, contributing to the development of innovative approaches to financial analysis.
In addition to his academic work, Shuyue has gained significant industry experience through roles in both financial services and data analysis. Notably, as an intern at SAS, he played a key role in the implementation of IFRS 17, optimizing financial reporting processes and contributing to the development of automated workflows that enhanced the efficiency and accuracy of financial statement generation. His experience also includes an internship at Dongguan Securities, where he supported investment strategies through comprehensive data collection and analysis of macroeconomic indicators, policy, and financial markets.
Shuyue’s technical expertise extends across various programming languages and analytical tools, including Python, MATLAB, VBA, SQL, and SAS Enterprise Miner. He has demonstrated his capacity for high-level quantitative analysis and real-world application through achievements such as securing 1st place in the Bloomberg Global Trading Challenge by developing and optimizing algorithmic trading strategies.
Shuyue's research interests lie at the intersection of financial technology, quantitative finance, and market dynamics. His work aims to contribute to the development of more efficient financial systems through the application of advanced analytical techniques.
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