top of page
halftone_grunge_gray_small_mediumspace_less_transparent.png
IMG_6845 3.jpeg

I am a doctoral candidate at the London Business School. I am an empirical researcher who works on climate risk and sustainability. I apply econometric and deep learning methods on big and alternative data to address questions around this theme. I have also served as a senior consultant for data science and investment management organisations.

00:00 / 01:04

solo authored

I compile seven million residential real estate transactions in the United Kingdom and recover discount rates used by homeowners to value dwelling sustainability. To do this, I calibrate the present value of energy savings from subsequent improvements in dwelling sustainability to the observed price premium. I show that homeowners accept lower returns for greener dwellings, evidenced by the declining structure of discount rates with increasing dwelling sustainability. Moreover, I exploit the spatial, temporal, tenurial, and vintage variation in premium to demonstrate that homeowners price sustainability following economic principles. My estimates provide direct measures for rates used to discount climate investments.

Presentations: Society of Finance Studies (SFS) Cavalcade, Northern Finance Association (NFA, upcoming), ESG Conference at Cornell SC Johnson College of Business, Business Schools for Climate Leadership Conference at IESE Business School, Ageing and Sustainable Finance Conference by Leibniz-Centre for European Economic Research, 31st Finance Forum by Spanish Finance Association, INFORMS Annual Meeting, and  Trans-Atlantic Doctoral Conference at London Business School
Grants: SFS PhD Travel Grant, NFA PhD Travel Grant

To study the impact of green-transition regulation on firm value, we analyze stock returns around legislator tweets about climate change. Green stocks significantly outperform brown stocks in the one-to-ten-minute window around pro-transition tweets. The cumulative daily-average green-minus-brown portfolio return around pro-transition tweets is 6.9% higher than around anti-transition ones. For tweets that mention environmental regulations, the spread increases in the weeks before a congressional vote and is stronger before close votes and when Congress is split. Our findings suggest that the green transition impacts the relative performance of green and brown stocks, at least partly, via a regulatory channel.

PresentationsAsset Pricing and Machine Learning conference at Gothenburg University, INFORMS Annual Meeting, Workshop on Unstructured Data and Language Models at Michigan Ross*, ESG Workshop at Toulouse Business School*, Spring Workshop at ESADE*, Dauphine University*, Frankfurt School of Finance and Management*, WHU Otto Beisheim School of Management*, and Conference in Sustainable Finance at the  University of Luxembourg (upcoming)
(* co-authors)
Grants: INQUIRE Europe Research Grant
halftone_grunge_gray_small_mediumspace_less_transparent.png

Copyright @ Milind Goel (2025)

bottom of page