Climate and Biodiversity Finance
POSITION FILLED
FACULTY SUPERVISOR:
PROJECT AND POSITION DESCRIPTION:
Stefano Giglio is seeking to recruit one highly skilled and motivated individual to join the Pre-doctoral Fellowship program to work on various research project related to the interaction of climate change and finance, along with Johannes Stroebel at NYU.
The prospective pre-doctoral fellow will work on several projects studying how financial markets affect (and are affected by) climate and biodiversity risks. A first project relates to the measurement and pricing of biodiversity risk in financial markets, and its relation with climate risks. A second project studies the effect of climate transition risk on the production decisions of energy companies, and the equilibrium implications for energy prices. A third project studies the portfolio choices of companies with respect to climate risk management. In our projects, we are planning to make extensive use of machine learning methods.
The pre-doctoral fellow will join a small group of research assistants dedicated to faculty at the Yale SOM, but the candidate will also have access and support to all the resources of the Tobin Center. Previous predoctoral fellows of Professors Giglio and Stroebel have gone to graduate programs at Harvard Economics, Harvard Business Economics, Harvard Kennedy School, MIT Economics, Columbia University and the UC Berkeley.
This position is ideal for someone who is planning to go to graduate school in economics, finance, or a related field. It presents an opportunity for recent graduates to begin training for a career in research and will serve as a stepping stone to doctoral studies.
REQUISITE SKILLS AND QUALIFICIATIONS
Successful candidates should have a well-demonstrated interest in finance and applied econometrics research, and strong communication skills. Most of the projects will involve extensive work with large data sets and especially the use of machine learning methods. Preference will be given to candidates with prior experience of working with statistical software (especially Python, but also Stata and R). Strong analytical skills, including exposure to proof-based math classes required. Applicants must have completed a bachelor’s or master’s degree.