Lottery preference for factor investing in China’s A-share market
Project Description
This project leverages China’s unique context and financial big data to construct a “factor zoo” and study lottery-like preferences in factor investing, exploring the behavioural drivers and impacts. Specifically, we plan to (1) examine the lottery preferences in factor investing and associated factor MAX anomaly in the Chinese market; (2) effectively measure and quantify the gambling preferences of quantitative funds, thereby elucidating the causes and impacts of their lottery preferences; (3) explain the causes and mechanism of factor MAX anomaly through behavioural finance theory; (4) expand the research to other major markets to enhance the generalisability of the conclusions.
This project has several uniqueness and potential impacts. First, it utilises a comprehensive set of big data in finance and economics and constructs a large sample of factor zoo in the Chinese market. Unlike in developed markets, such as the U.S., big data analysis in China’s financial studies remains limited. Our work addresses this gap by constructing a comprehensive factor zoo and integrating modern behavioural finance theories with the emerging factor investment setting and advanced machine learning methodologies.
Second, this project innovatively aggregates stock-level information to create factor-level proxies that effectively measure institutional investors’ (particularly quantitative funds) gambling preference in factor investing. This approach addresses the lack of effective factor-level proxies and offers a new perspective on quantitative funds in China’s stock market. Findings will support policy guidance for regulatory bodies, strengthen algorithmic trading oversight, manage market risk, and enhance financial stability.
Third and most importantly, this project provides a unique Chinese perspective, examining the high proportion of retail investors and their strong gambling tendencies in China’s stock market. It addresses the controversial role of quantitative funds and their reliance on factor investing strategies. Additionally, China’s rapidly growing digital economy and fintech innovations present both opportunities and challenges for traditional factor investing. Extensive data analysis and high-frequency trading amplify correlations among factors and increase volatility among individual stocks, transforming risk spillover and contagion mechanisms. This project explores the motives and potential risk factors in factor investing and aids in proposing targeted preventive measures to help manage and mitigate financial crises, control market risk, and uphold financial stability. It also provides valuable insights for regulators to formulate more effective financial regulatory policies, regulate investor behaviour, enhance financial system oversight, and support the transformation and growth of the digital economy, ultimately benefiting the development of the real economy.
Project Investigator
Dr WANG Liyao (Department of Accountancy, Economics and Finance)
Funding/Award
- National Natural Science Foundation of China (NSFC) - Young Scientist Fund
