Job Market Paper

Investors' Over-Optimism and ESG Stcok Volatility 

Abstract:  This paper discovers a novel variable that negatively explains the cross-sectional volatility of ESG stocks, namely the correlation coefficient between their ESG rating and earnings. This result is driven by the over-optimism of a subgroup of ESG investors about the financial payoff of ESG stocks. Existing surveys and experiments confirm the presence of investors who overestimate the financial payoff of ESG investment opportunities. I construct a general equilibrium model with one rational and one optimistically biased investor, with the latter's overestimation of a stock's financial performance following its ESG rating. My model finds that the over-optimism induced by the greenness of a stock could hedge against the uncertainty in its earnings. When the ESG rating and earnings are more positively correlated, the risk from the two processes offset each other more, lowering the volatility of stock return. I find empirical support for this prediction. 

Presentations: 14th Financial Markets and Corporate Governance Conference 2024, 2024 FMA European Doctoral Student Consortium, The 31st Annual Global Finance Conference, International Risk Management Conference 2024, 2024 17th Annual Meeting of ABF&E, Doctoral Finance Symposium ICMA, ESSEC Student Research Seminar 2024, ESSEC Brown Bag 2023

Working Paper

ESG Rating Uncertainty: Who Wins? (with Elise Gourier)

Abstract:  We show that investors whose green taste is indexed on the ESG rating as opposed to the true greenness, benefit from the uncertainty.

Draft available upon request

Other Projects

Combined Customised Hedging with the Finite Element Method (with Andrea Roncoroni)

Short research project on  finding the optimal portfolio for hedging claimable and non-claimable risk. Specifically, by using finite element method, I approximate the optimal investment strategy by a projection onto a functional basis consisted of Hermite polynomial.

Nondiversification Trap (with Marie Kratz)

A review of Ibragimov's nondiversification trap, which describes the situation where diversification is bad for insruance companies when the risk insured is very heavy tailed (the distribution of the claim amount has no finite expectation or variance). I find  an analytical expression for the expected utility of insurance companies using contour integration.

Brownian Excursion Measure (Master thesis, supervised by Laurence Field)

First class honours awarded by the Mathematical Science Institute of Australian National University.