2021 HEC FOUNDATION - DOCTORAL DISSERTATION AWARD
I cannot be more grateful to my advisor, Jean-Edouard Colliard. I have benefited a lot from his insightful comments, his patient guidance, and his generous help and support. I wish I could become as a good advisor as he is in the future. I’m also very grateful to other faculty members at HEC as well, for what I’ve learned from them and their help over the past 5 years. Their help made the winter of 2020, which was the toughest period to me in the past 5 years, less bearable. I also appreciate the time and efforts that have been devoted by the juries. Their advice and comments helped me improve my dissertation a lot. Finally, I would also like to thank HEC Foundation for awarding me this price and its support in the past 5 years. Without its financial support, I cannot dive into research fully and achieve what I have done. Junli Zhao.
Junli Zhao, HEC PhD in Finance and today lecturer in Finance at Bayes Business School - City University of London, is interested in how asymmetric information and information technologies affect the behaviors of intermediaries such as asset managers, brokers, and financial advisors. He questions whether and how sell-side analyst research aggravates the agency conflict between asset managers and their clients, and whether a regulation like MiFID II helps to alleviate this problem. He's also interested in whether the abundance of data makes financial analysts less valuable for their employers. In his dissertation, he used both theoretical and empirical methods to answer these questions.
Junli’s highly interesting research deals with the way different sources of information interact on financial markets.His three papers are very promising because all of them deal with recent evolutions in financial markets such as automation, trends in equity research or brokers and financial advisers influence. Junli deserves his prize ! » The Jury.
Subject: « Machine-readable data and financial experts in Asset Management.Essays on intermediation in financial markets.»
Supervisor: Professor Jean-Edouard Colliard
Abstract: Should financial experts (e.g., buy-side asset managers and analysts) fear the rise of algorithms? As machine-readable (clean and structured) data are essential for the development and functioning of algorithms, I study this question by investigating whether financial experts benefit from more machine-readable data in information production in asset management. I first develop a model in which an institutional investor’s performance and asset holdings depend on two inputs: the amount of machine-readable data and the number of financial experts, and derive how changes induced by an increase in the amount of machine-readable data depend on the relation between the two inputs. Exploiting an exogenous regulatory shock that makes corporate filings more machine-readable, I find that institutions with more financial experts experience larger performance improvement than institutions with fewer financial experts, consistent with financial experts benefiting from more machine-readable data. This result helps evaluate the disruption brought by modern algorithms.
Learn more about why Junli chose HEC Paris to be part of his PhD journey