主题：加密货币市场的分化动量：残差反应不足与信息离散度过度反应

时间：2026年5月18日（周一）下午14:00-15:30

线下地点：上海市闵行区紫竹国际教育园区A1楼101报告厅

主持人：刘都，华东师范大学亚欧商学院、上海国际首席技术官学院 助理教授

主讲人：翟佳，西交利物浦大学西浦国际商学院 副教授

Theme: Decoupling Momentum in Cryptocurrency Markets: Underreaction to Residuals and Overreaction to Information Discreteness

Time:May 18 (Monday), 14:00-15:30 pm

Venue: Room 101, Building A1, Zizhu International Education Park

Host:Du Liu, Assistant Professor, Asia Europe Business School & Shanghai International School of Chief Technology Officer, East China Normal University

Lecturer: Jia Zhai, Associate Professor, Department of Finance, International Business School Suzhou , Xi’an Jiaotong-Liverpool University

主讲人简介：

翟佳博士现任西交利物浦大学国际商学院金融学副教授、创新与新兴科技卓越研究中心主任。加入西交利物浦大学前，曾在英国多所高校担任助理教授职务。其主要研究方向涵盖大数据、资产定价、衍生品、金融风险管理，以及机器学习与人工智能在金融领域的应用。迄今已发表学术论文 40 余篇，成果刊发于多本中科院一区、二区期刊，包括 European Journal of Operational Research、Quantitative Finance、European Journal of Finance、International Journal of Finance and Economics、Decision Support Systems、Expert Systems with Applications 等国际权威期刊，以及《管理科学学报》《系统工程理论与实践》等国内重要核心期刊。翟佳博士担任多本中科院一区、二区期刊副主编及客座编辑，其中包括 Financial Research Letters、Journal of Chinese Economics and Business Studies；同时受聘为 International Journal of Finance and Economics、British Accounting Review、Technological Forecasting and Social Change、Sustainable Futures 等期刊客座编辑，并长期担任 Scientific Reports、European Journal of Finance 等多个国际期刊审稿人。作为项目负责人与核心成员，翟佳博士主持及参与包括国家自然科学基金青年项目在内的多项国家级与省部级科研课题。2022 年起加入英国中国经济学家协会，担任正式会员。自2021年起，担任中国衍生品青年论坛委员会成员。作为硕士研究生与博士研究生导师，她已培养博士生10余人，毕业生均赴国内一流高校任职或从事博士后研究工作，其中包括清华五道口金融研究院等学术机构。

Bio of lecturer:

Dr. Jia Zhai is currently an Associate Professor of Finance and Director of the Center for Excellence in Innovation and Emerging Technologies at the International Business School of Xi’an Jiaotong-Liverpool University. Prior to joining Xi’an Jiaotong-Liverpool University, she held assistant professor positions at several universities in the UK. Her main research areas cover big data, asset pricing, derivatives, financial risk management, and the application of machine learning and artificial intelligence in the financial field. To date, she has published over 40 academic papers in numerous journals ranked in the first and second tiers by the Chinese Academy of Sciences, including authoritative international journals such as the European Journal of Operational Research, Quantitative Finance, European Journal of Finance, International Journal of Finance and Economics, Decision Support Systems, and Expert Systems with Applications, as well as important domestic core journals such as the Journal of Management Science and Systems Engineering—Theory & Practice. Dr. Zhai Jia serves as associate editor and guest editor for several journals in the first and second tiers of the Chinese Academy of Sciences (CAS) accreditation, including Financial Research Letters and Journal of Chinese Economics and Business Studies. She is also a guest editor for journals such as International Journal of Finance and Economics, British Accounting Review, Technological Forecasting and Social Change, and Sustainable Futures, and has long served as a reviewer for several international journals, including Scientific Reports and European Journal of Finance. As a project leader and core member, Dr. Zhai has led and participated in numerous national and provincial-level research projects, including a National Natural Science Foundation of China (NSFC) Youth Project. She joined the British Association of Chinese Economists in 2022 as a full member. Since 2021, she has served as a member of the Committee of the China Derivatives Youth Forum. As a supervisor of master’s and doctoral students, she has mentored more than 10 doctoral students, all of whom have gone on to hold positions at top universities in China or engage in postdoctoral research, including academic institutions such as the Tsinghua University PBC School of Finance.

Abstract:

We investigate the cross-sectional return predictability and behavioral origins of momentum in the cryptocurrency market by disentangling it into residual (RMOM) and information discreteness momentum (IDMOM). Using a comprehensive sample of over 2,000 cryptocurrencies from 2014 to 2023, we find that both strategies generate economically significant premiums with annualized Sharpe ratios exceeding unity. We find that a two-factor model incorporating these components successfully captures the return variations of 12 out of 14 prominent characteristics. We uncover a marked behavioral difference: RMOM exhibits prolonged persistence, consistent with investor underreaction to idiosyncratic information; conversely, IDMOM generates transient profits that reverse within two weeks, signaling a speculative overreaction to the structure of information arrival. This “flash-in-the-pan” overreaction in IDMOM represents a significant divergence from the “frog-in-the-pan” underreaction documented in equity markets. Our findings suggest that cryptocurrency momentum is a complex synthesis of trend-following and idiosyncratic bias, highlighting unique information-processing dynamics in decentralized markets.