Research

We document a significant difference in the returns to sustainable investing across investor types. Investors with strict ESG mandates earn 3.1% less than flexible investors. The mechanism is that flexible investors are able to react on expected ESG improvements. They buy stocks that subsequently experience ESG score increases. After ESG improvements have realized, demand from strict mandate investors pushes up stock prices, resulting in positive returns for flexible investors. These returns are higher when accompanied by rising climate sentiment, as seen during the 2010s. Our channel accounts for 51% of the return difference between strict and flexible ESG investment mandates. 

Presented at: OU Energy and Climate Finance Research Conference, AFA PhD Poster Session 2022, T. Row Price, Young Scholars Nordic Finance Workshop 2020, 2nd Conference on Behavioral Research in Finance, Governance, and Accounting, PhD Symposium of the 32nd Northern Finance Association Conference, 19th Conference on Credit Risk Evaluation, Becker Friedman Institute Macro-Finance Research Program Summer Session for Young Scholars, Wharton PhD Brown Bag Series

I empirically investigate wind energy production dynamics and correlations to electricity prices on a turbine-individual level. I find that large turbine production outputs are less negatively correlated to electricity prices than those of small turbines. Apart from the fact that large turbines produce more and are less volatile in their production outputs over time, they sell electricity at a higher average price, outperforming their smaller peers. Additional tests on high-frequency data confirm these results and indicate that the financial impacts are large when considering short-term dynamics. These findings are important for investors to consider when allocating capital to alternative venues as renewable energy. 

I provide a novel theoretical approach to value wind energy investments. It allows to adjust for a number of risk parameters, including wind speeds, electricity price forecasts, discount rates, and uncertainty in subsidies. I use this approach to model wind energy investments under two different subsidy schemes in Denmark through a numerical Monte Carlo simulation. Moreover, I model wind energy investments under the assumption of a subsidy-free asset class. I compare the three systems and expose them to various sources of uncertainty through which I provide more clarity on which risk parameters matter most to wind energy investors and how the three systems compare to each other.