OxfordOMIDr Hao Ding (丁昊)
Postdoctoral Research Fellow
My research encompasses empirical asset pricing, generative and agentic AI, big (alternative) data in finance, and quantitative finance. I develop trading strategies across multiple asset classes using large language models to identify behavioral investment signals, and address systemic risk detection. I received my PhD in Finance and Econometrics from Warwick Business School, University of Warwick.
Research
Working Papers
Retail Investor Attention and Mutual Fund Performance: Evidence from EDGAR Log Files
2024I develop a measure of retail investor attention to mutual funds, Total Views, by distinguishing between retail and sophisticated investors’ access to fund shareholder reports (N-CSR) via EDGAR. Total Views positively predicts retail fund flows and performance, with a 0.28% rise in future flows and a 0.02% improvement in alpha. An equal-weighted high-minus-low portfolio based on abnormal Total Views yields positive returns. Total Views strengthen the flow–performance relationship. Investor attention on reports from outperforming funds help attract additional inflows but do not cause more outflows for underperforming funds. Further analyses show that fund shareholder reports offer valuable, non-time-sensitive information throughout the year.
Presentations: 2024 Financial Management Association (FMA) Annual Meeting, 2025 Swiss Society for Financial Market Research (SGF) Conference, 2025 Sydney Banking and Financial Stability Conference (SBFC), OMI workshop
Mutual Fund Strategy Changes and Performance
2023I introduce a new active portfolio management measure, Strategy Shifting, which represents the divergence of the actual weights from the expected weights that a fund should assign to stocks if it follows previous stock characteristics based trading strategies. The measure assesses changes in trading strategies in response to shifts in fundamental information and is free from the benchmark mismatch problem. I show that mutual funds actively altering strategies contribute to improved fund performance. The finding remains robust after controlling for other active management measures and fund characteristics.
Presentations: 2024 Financial Management Association (FMA) European Conference, 2024 Financial Management Association (FMA) Doctoral Student Consortium, 16th Society for Financial Econometrics (SoFiE) Annual Meeting, 31st Spanish Finance Association (AEFIN) Finance Forum, Behavioural Finance Working Group 17th Annual Conference, 2024 Southwestern Finance Association (SWFA) Annual Meeting, Nippon Finance Association 32nd Annual Conference, 2023 World Finance & Banking Symposium, Warwick Business School Finance Group Brown Bag Seminar
Ongoing Work
The Solo-Authorship Reversal: Generative AI and Academic Team Formation
2026Draft available upon request
Identifies two channels through which AI restructures academic collaboration using difference-in-differences on 1.4 million preprints.
Crash Risk and Market Resilience in Retail-Dominated Markets
2026with Alvaro Cartea
Draft available upon request
Examines the effect of China’s short-selling ban on crash risk using a difference-in-discontinuities design in the Chinese A-share market.
Asset-Based Lending as a Leading Indicator of Systemic Crises
2026with April Goulding
Draft available upon request
Investigates ABL securitisation as an early warning signal for systemic crises using Temporal Fusion Transformers and Graph Attention Networks.
Attention Cycles
Forthcomingwith Alvaro Cartea, Zichuan Guo
SEC Rulemaking and Comments
Forthcomingwith Su Li, Danmo Lin
Beauty in Numbers, Cost in Trades
Forthcomingwith Shubo Kou, Xiyuan Ma
Earlier Work
Readability and Neutralness in Mutual Fund Shareholder Reports
2024Draft available upon request
I use large language models (LLMs) fine-tuned on financial texts to assess the readability and neutrality of mutual fund shareholder reports. A neutral tone typically predicts increased fund inflows, but this effect lessens with higher readability. When reports are highly readable, neutrality leads to outflows for outperforming funds and doesn’t boost inflows for underperforming ones. Retail investors respond minimally to neutrality unless reports are highly readable, and their reactions are less pronounced than those of institutional investors. Limited access to shareholder reports restricts retail investors’ information acquisition. These findings support the adoption of the Tailored Shareholder Report Rule.
Teaching
Teaching Fellow
Queen Mary University of London, School of Business and Management
Weekly · UG/PG · Designed and facilitated weekly workshops
UG/PG · Research support for undergraduate and postgraduate students
UG/PG · One-on-one dissertation training for UG and PG
BUS140 · UG · Teaching Assistant
Senior Graduate Teaching Assistant
Warwick Business School, University of Warwick
IB9KW0 · PG · R lab sessions
IB9JH0 · UG · C++ lab sessions
IB3570 · UG · Seminars + Excel/Python projects
IB2D90 · UG · Quantitative finance seminars
Curriculum Vitae
Postdoctoral Research Fellow
Oxford-Man Institute of Quantitative Finance, University of Oxford
2025 - Present
Researcher (Statistics)
National Education Union
2025 - Present
PhD in Finance and Econometrics
Warwick Business School, University of Warwick
2020 - 2025
MSc Risk Management and Financial Engineering (Distinction)
Imperial College London
2018 - 2019
Contact
More About Me
Snowboarder & Car Guy
I modified and tuned a supercharged, stripped & caged GT86 with 3D-printed and fabricated mods for track days.
Registered Marshal with Motorsport UK since 2022.