Education

2014.09-2018.01，Ph.D. in Financial Mathematics, University of Manchester, Degree: Doctor of Philosophy

2011.09-2012.09，M.A. in Economics, University of Manchester, Degree: Master of Arts

2008.09-2011.07，B.A. (Hons) in Economics , University of Manchester, Degree: Bachelor of Arts (Honors)

 

Work Experience

2021.01-Present，Assistant Professor, School of Statistics, Renmin University of China

2018.09-2020.01，Assistant Professor, Department of Statistics, Universidad Carlos III de Madrid

2017.10-2018.06，Postdoctoral Research Associate, Department of Mathematics, University of Manchester

 

Research Interests

Financial Risk and Financial Network Analysis, Blockchain Regulation (Digital Asset Pricing and Volatility, Financial Risk, Anomaly and Fraud Detection, etc.), Statistical Distribution Theory

 

Honors and Awards

1. Selected for the Elsevier 2024 Highly Cited Chinese Researchers List

 

Funding

1. “Anomaly detection methods for blockchain-based networks”, National Natural Science Foundation China Research Fund for International Young Scientists (RFIS-I), W2433186, P.I., 2025-2027

2. “Graph-Theoretic Analysis for Consumer Credit Risk Assessment in Personal Lending”, ETH Zurich Leading House Asia 2023 Applied Research Partnership Grant, ARP_112023_08, Asia Partner, 2024-2025

3. “Research on Detecting Illicit Activity in Digital Cryptocurrency Networks”, Beijing Natural Science Foundation International Scientists Project, IS23126, P.I., 2023-2025

4. “Research on Blockchain-Based Risk Assessment and Management”, Ministry of Science and Technology of the People’s Republic of China National Foreign Young Talent Program Project, QN2023103001L, Foreign Expert, 2023-2024

 

Educational Reform Project

1. Statistics and Data Science Talent Cultivation “Regression Analysis (English)” Course Development Project，Renmin University of China School of Statistics, P.I., 2023

2. “Probability Theory” Major Core Curriculum Development Project (123 Gold Course), Renmin University of China, Project Team Member, 2021-2026

 

Publications

(* indicates corresponding author)

1. Stephen Chan, Durga Chandrashekhar, Ward Almazloum, Yuanyuan Zhang, Nicholas Lord, Joerg Osterrieder, Jeffrey Chu* (2024). “Stylized Facts of Metaverse Non-Fungible Tokens. Physica A: Statistical Mechanics and its Applications”, 653, 130103.

2. Xin Liao*, Qin Li, Stephen Chan, Jeffrey Chu, Yuanyuan Zhang (2024). “Interconnections and contagion among cryptocurrencies, DeFi, NFT and traditional financial assets: Some new evidence from tail risk driven network”, Physica A: Statistical Mechanics and its Applications”, 647, 129892.

3. Yuanyuan Zhang, Stephen Chan, Jeffrey Chu, Xin Liao, Min Helu (2024). “Stylized Facts of Decentralized Finance (DeFi)”, In La Torre, D. (ed.) Artificial Intelligence and Beyond for Finance, pp. 289-314, World Scientific Publishing Europe.

4. Jeffrey Chu*, Stephen Chan, Yuanyuan Zhang (2023). “An analysis of the return-volume relationship in decentralised finance (DeFi)”, International Review of Economics & Finance, 85, pp. 236-254.

5. Yuanyuan Zhang, Stephen Chan*, Jeffrey Chu, Shou-hsing Shih (2023). “The adaptive market hypothesis of Decentralized finance (DeFi)”, Applied Economics, 55(42), pp. 4975-4989.

6. Stephen Chan, Jeffrey Chu, Yuanyuan Zhang*, Saralees Nadarajah (2022). “An extreme value analysis of the tail relationships between returns and volumes for high frequency cryptocurrencies”, Research in International Business and Finance, 59, 101541.

7. Jeffrey Chu*, Stephen Chan, Yuanyuan Zhang (2021). “Bitcoin versus high-performance technology stocks in diversifying against global stock market indices”, Physica A: Statistical Mechanics and its Applications, 580, 126161.

8. Jeffrey Chu* (2021). “A statistical analysis of the novel coronavirus (COVID-19) in Italy and Spain”. PLoS ONE, 16, e0249037.

9. Stephen Chan, Jeffrey Chu, Yuanyuan Zhang, Saralees Nadarajah* (2021). “Count regression models for COVID-19”, Physica A: Statistical Mechanics and its Applications, 563, 125460.

10. Jeffrey Chu*, Yuanyuan Zhang, Stephen Chan, Saralees Nadarajah (2020). “Bias reduction in the population size estimation of large data sets”, Computational Statistics & Data Analysis, 145, 106914.

11. Jeffrey Chu, Stephen Chan*, Yuanyuan Zhang (2020). “High Frequency Momentum Trading with Cryptocurrencies”, Research in International Business and Finance, 52, 101176.

12. Jeffrey Chu, Oliver Dickin, Saralees Nadarajah* (2019). “A review of goodness of fit tests for Pareto distributions”, Journal of Computational and Applied Mathematics, 361, pp. 13-41.

13. Jeffrey Chu*, Yuanyuan Zhang, Stephen Chan (2019). “The adaptive market hypothesis in the high frequency cryptocurrency market”, International Review of Financial Analysis, 64, pp. 221-231.

14. Jeffrey Chu, Saralees Nadarajah* (2018). “Estimating order statistics of network degrees”, Physica A: Statistical Mechanics and its Applications, 490, pp. 869-885.

15. Jeffrey Chu, Saralees Nadarajah* (2017). “A statistical analysis of UK financial networks”, Physica A: Statistical Mechanics and its Applications, 471, pp. 445-459.wu

 

Teaching

1. Undergraduate: Data Mining (English) (Fall Semester, 2021-Present), Investments B (English) (Spring Semester, 2022-Present), Econometrics (English) (Fall Semester, 2022-Present), Special Topics in Data Science (Fall Semester, 2022-2023)

2. Graduate: English for Statistics (Spring Semester, 2023-Present), Statistical Learning (Spring Semester, 2022)

 

Invited Talks

1. “Digital Assets in War: A Double-Edged Sword”, The 4th International Conference on Mathematics and Statistics (AUS-ICMS’25), 20th – 22nd February 2025, American University of Sharjah, Dubai, United Arab Emirates.

2. “Digital Assets in War: A Double-Edged Sword”, Workshop on Blockchain and Decentralized Finance，2nd-3rd November 2024，HKUST (GZ), Guangzhou, China.

3. “Network Transitions in the Cryptocurrency Market: The Impact of Regional Conflicts”, The 7th International Conference on Econometrics and Statistics (EcoSta 2024), 17th – 19th July 2024, Beijing Normal University, Beijing, China.

4. “The financial impact of war on cryptocurrencies”, (Online) The 6th International Conference on Econometrics and Statistics (EcoSta 2023), 1st – 3rd August 2023, Waseda University, Tokyo, Japan.

5. “Network transitions in the cryptocurrency market: Evidence from military conflict”, Joint Conference on Statistics and Data Science in China (JCSDS 2023), 11th – 13th July 2023, Beijing, China.

6. “An analysis of the return-volume relationship in decentralised finance (DeFi)”, ICSA China Conference, 30th June – 3rd July 2023, Chengdu, China.

7. “An analysis of the return-volume relationship in decentralised finance (DeFi)”, (Online) Cryptocurrency Research Conference 2022, 22nd – 23rd September 2022, Durham University, Durham, UK.

8. “Bitcoin versus high-performance technology stocks in diversifying against global stock market indices”, The 4th International Conference on Econometrics and Statistics (EcoSta 2021), 24th – 26th June 2021, (Online) Hong Kong University of Science and Technology, Hong Kong, China.