Hello, everyone! I am Yu-Jane Liu from the Intersdisciplinary Innovation Team of Behavioral Science in Action at Guanghua School of Management and let me first introduce our team.
We are a world-leading policy and behavior intervention platform and interdisciplinary research team based on a behavioral science perspective. Our initial goal is to propose a series of research results and policy recommendations that serve national strategies, lead international academic research, and enhance social welfare in government public policy, business strategy, and individual decision-making. To achieve this goal, we will use scientific research methods, combined with artificial intelligence and big data, to design behavioral mechanisms and explore effective ways to promote individual behavior change in a cost-effective way. We serve governments, businesses, NGOs, and individuals by exploring effective pathways for interdisciplinary research.
Our research comprises four main areas. In terms of behavioral finance, we focus on individual and institutional investors' behavioral patterns and cognitive misconceptions in financial and capital markets, and then propose effective ways to improve them; meanwhile, in terms of national strategies, we propose policy implementation paths for investor protection and education. From the aspect of corporate management, we focus on the interaction between individuals, teams and organizations in companies and the design of internal decision-making and incentive mechanisms. In terms of consumer behavior in the digital economy, we use platforms and big data to conduct behavioral intervention experiments and analysis, and focus on consumer preferences, human-computer interaction and human-computer co-integration decisions, algorithmic attitudes and design, and data governance and privacy. In terms of public policy, we analyze individual and organizational behavior patterns and decision-making mechanisms to provide ideas and suggestions for major national policies such as platform economy, anti-monopoly, public health, commonwealth, and "dual carbon" goals.
We use randomized controlled experiments and other research methods to scientifically evaluate the effectiveness of investor education. For example, we track changes in behavioral biases in the same group and in different groups before and after education to accurately assess the effects of interventions.
How interdisciplinary research can improve decision-making behavior
The next question we need to think about is how interdisciplinary research can improve decision-making behavior. First, we can start from the Behavioral Decision Theory (BDT) concepts of reference points, probability weighting, and hyperbolic discounting proposed by scholars including Nobel Prize-winning economists Richard Thaler, Daniel Kahneman and Amos Tversky to think about suboptimal or even irrational human decision-making behavior.
Why start from the study of irrational human behavior? Because humans are not always rational, or the relative complexity of the environment we face leads to the fact that human rationality is limited. Through different research approaches, we can first be informed of what biases (e.g., long- and short-term horizons, preference for gambling, overconfidence, etc.) investors may have, before going on to analyze how to improve investors' decision-making behavior. For example, a very important neuroscience study was published in Science, which suggested that MRI could be used to study whether people are patient or impatient, which helps to further investigate whether the perceptual system or the rational system determines how patient humans are in making decisions.
One of the greatest contributions of Nobel Laureate Richard Thaler's research is his “Nudge Theory”, which suggests the idea of improving decision making behavior by changing the environment in which decisions are made. The subtlety of this is that it ensures that both the "best interests" and the "freedom of choice" are reaped without imposing rules. As Thaler says in his book, "The force that gently pushes you to make the best choice is 'nudging'".
For a long period of time, we have been committed to improving investment behavior by using behavioral science as a guide to advance investor education. Behavioral science investigates how people think and behave, and it helps to uncover the source of psychological biases and reduce the impact of biases at the roots. While traditional financial institutions are working very hard to educate about financial literacy, behavioral finance-based investment education approaches, such as nudging strategies, can play a significant role. It can do so in a way that respects subjective human decision making, reduces the cost of intervention, and improves investment decisions in a subtle way.
Mistakes you could have avoided: Investing Lessons from Behavioral Finance
Next, I will share with you an example of my own research. We all know that governments have always placed great emphasis on investor protection and education. A question that has been of great concern to leaders over the past few years, and one that I am often asked, is "Why are investors still not making money when funds are clearly making money?" If we look at the long-term historical performance of active equity funds, we can see that the long-term returns of the funds are very impressive. But when funds make money in the short term, investors redeem them quickly; conversely, when funds lose money, investors are stuck in them and can't sell them for a long time. This kind of investment behavior can explain why the fund makes money, but the investors do not earn money.
Someone once asked me, "Is it true that smart people do not need investor education?" In fact, I have studied cases that show that "smart people can also make dumb investments." For example, Isaac Newton also lost a lot of money when investing and lamented, "I can calculate the trajectory of the astronomical objects, but not the madness of human beings."
The original intention of publishing the bookMistakes you could have avoided: Investing Lessons from Behavioral Financewas to summarize the various investment biases that investors may make from behavioral finance and behavioral decision theory. In the book, I analyzed many investment cases, hoping to guide people to understand the impact of these biases in actual financial decisions by means of individual cases; I also tried to propose investment countermeasures and mental methods to deal with different biases from the behavioral finance perspective, and guide investors to correct these biases.
How to educate investors?
There are many ways to educate investors. In the past few years, financial institutions have tried to launch many different financial education programs and have done a lot of investment guidance for investors. These guides are certainly good, but to better transform and improve investment behavior, there is a need to better understand the motivations of investors.
For example, to explore whether investors have "ideologies" when investing, we use machine learning to understand the heterogeneity of different investors' investment motivations from multiple dimensions, and thus provide behavioral science support to launch customized investor education programs. Later, we also benchmark the statements made by key opinion leaders online to better analyze and benchmark investors' ideologies - for example, the left wing is very conservative while the right wing is very aggressive. Based on the " ideologies" of investors, we further analyzed what characteristics of investors' behavior. For example, some investors are overly confident, and others are risk-averse. In this study, we divided the experimental and control groups and tested the results of the investment education through a questionnaire. Our study also led to some interesting conclusions, such as that there is no significant difference between the behavioral biases of people with high and low education, which explains why Newton also made bad investments that he regretted. Therefore, we suggest a multi-dimensional investment education system. Specifically, to make the quantitative to qualitative leap in investment education activities, we need to leverage the power of behavioral finance and behavioral science. In the future, our team will also seek the transformation of academic and scientific research results from the five dimensions of investor education: effectiveness, science, personalization, relevance and innovation.
In the practice of investment education, the current education programs in China and worldwide have done very well in popularizing financial knowledge and providing investment guidance based on traditional financial theories, but they are still in the exploration stage in improving investors' decision-making behavior. In my opinion, there are various ways to promote research in this area in the future. For example, sponsoring experience-based learning through investment simulations; offering behavioral finance-related courses to help investors overcome behavioral biases; using social media and online education in the form of videos and interactions; develop tools to help optimize individual decision making quantitatively; evaluating policy effects through focus groups, interviews, and randomized controlled experiments; establishing a quantitative multidimensional investment education evaluation system based on investment effectiveness; improving the decision-making environment to help promote investment behavior; emphasizing behavioral regulation in the mobile Internet environment and other measures to provide effective guidance and assistance in improving investors' decision-making behavior at the practical level.
Here, I would also like to share a study I did with my co-workers on "Whether Mobile Internet Brings Behavioral Bias". Currently, investors often invest through mobile apps, and making decisions in the app interface which may result in fragmented thinking. We found that mobile investors (those who use cell phones to make investment decisions) have a stronger ranking preference, i.e., they prefer the top-ranked investment targets, and the ranking preference reduces their investment performance; the ranking preference of mobile investors is not related to financial literacy, but mainly influenced by two factors: information search and external interference; experienced investors may not be able to avoid the new behavioral bias brought by mobile Internet. This reveals that it is important to fully disclose risks to investors and guide their rational decision-making process.
In addition, many behavioral intervention papers published in leading journals commonly use randomized experiments or quasi-randomized experiments to assess the effectiveness of investment education. For example, many institutions have attempted to use reminders --- smart alerts to prompt investors to stop losses. However, studies have shown that the effectiveness of reminders is not significant, while the use of automated sell-out decisions and improved investor decision environment can effectively reduce the behavioral bias of investors. Therefore, our team also plans to further explore issues such as self-decision improvement methods and how to improve the APP decision-making environment in the future. Recently, there are also international research teams exploring the question of whether financial advisors can provide better investment advice, and we will also conduct research on these issues in the future.
Finally, I sincerely hope that all parties can work together in investor education and protection - with the government playing a leading role, the academia contributing scientific methods, and the financial institutions spreading correct investment concepts, so as to ultimately achieve the wonderful goal of enhancing the well-being of investors and achieving common prosperity.
About the speaker:
Yu-Jane Liu is a tenured Professor of Finance at the Guanghua School of Management, Peking University. At Peking University, she also serves as the director of the PKU Research Center of Finance and Development and the Cross-Strait Communication Fund and once served as the chair of the Department of Finance and the director of the Master of Finance Program at the Guanghua School of Management.
Her expertise includes behavioral finance, market microstructure, wealth management and financial technology in algorithm investment. She has published more than 30 papers in international journals such asJournal of Financial Economics, Review of Financial Studies, Management Science, Journal of Financial and Quantitative Analysis, Review of Asset Pricing Studies, Journal of Corporate Finance, Journal of Financial Markets, and Journal of Banking and Finance. Her paper “Just How Much do Individual Investors Lose by Trading”, published in Review of Financial Studies in 2009, has received more than 800 citations and was highlighted by Nobel laureate Daniel Kahneman in The Economist for its far-reaching influence. Many of her papers have won research awards, including the Yefang Sun Finance Innovation Award, the outstanding papers in the 27th Conference on the Theories and Practices of Securities and Financial Markets, in the Chinese Finance Association’s 25th Annual Conference, and in the 6th Chinese Finance Annual Conference. She has won personal awards including China Finance Research Award in 2016, and ICBC Teaching Award at Peking University.
She has presented papers and participated in discussions at many seminars and national and international conferences. She also served in the committee of conferences including European Financial Management Association, Chinese Finance Annual Conference, China International Conference in Finance, and Chinese Finance Research Conference. She has been the referees for leading international journals such asJournal of Finance, Management Science, Review of Financial Studies, Journal of Financial and Quantitative Analysis and many national journals.
Her research on behavioral finance and market microstructure has profound impact on policy making. She has been providing advice to many financial institutions and financial regulators such as China Securities Regulatory Commission, China Banking Regulatory Commission, Shanghai Stock Exchange, Shenzhen Stock Exchange, China Financial Futures Exchange. She has extensively weighed in on, for example, the policy of call auction trading and the guidance for listed firm dividend policy in the Shanghai Stock Exchange, the regulation of high-frequency trading in China Financial Futures Exchange, and the policy for retail investor education and investment protection in China Securities Regulatory Commission.