Abstract: This paper investigates whether and how investors affect firms’ product prices and customer composition. I compile a micro-level dataset that links firms' investors with the products firms sell and the underlying household customers of these products. Exploiting quasi-experimental variation in the composition of investors, I show that after experiencing an increase in benchmark constrained investors, firms (i) set lower product prices, especially for products with lower market share, (ii) expand their customer base towards lower-income households, and (iii) introduce new products and diversify. I provide evidence that benchmark constrained investors influence firms' product market outcomes by reducing their cost of equity. Using a model with product-level habits, I show that in response to the reduction in the cost of capital due to “benchmark subsidy,” firms lower their product prices and forgo current profits in favor of higher market share. Overall, these results suggest that trends such as the growth of ETFs can expand affordable product choices for low-income households, but potentially at the threat of lower market competition.
Conferences and Seminars: Northern Finance Association 2021 (PhD Session); International Risk Management Conference 2021; Nova PhD Final Countdown; Transatlantic Doctoral Conference 2021; London Business School
Semi-finalist, Best Paper, FMA
Abstract: We study the real effects of environmental activist investing. Using plant-level data in a quasi-experimental setting, we find that firms targeted by environmental activist investors reduce their toxic releases, greenhouse-gas emissions, and cancer-causing pollution through preventative efforts. Improvements in air quality within a one-mile of targeted plants suggest potentially important externalities to local economies. We provide evidence supporting the external validity of environmental activism while also ruling out reporting biases, forms of selection, and other alternative hypotheses. Overall, our study suggests that engagements are an effective tool for long-term shareholders to address climate change risks.
Conferences: AFA (American Finance Association) 2022*; SFS Cavalcade 2021; Weinberg Center - Corporate Governance Symposium 2021; Political Economy of Finance Conference 2020 (Chicago Booth); European Finance Association (EFA) 2020; 2021 European Investment Forums*; FMA Annual Meeting 2020; UBC Winter Finance Conference 2020; Texas Finance Festival 2020; World Symposium on Investment Research 2020 (Zurich); ADBI-JBF-SMU Joint Conference on Green and Ethical Finance; Annual Mid-Atlantic Research Conference (MARC); FMA Europe; European Winter Finance Conference; Mid-west Finance Association 2021; ISB Summer Conference 2020; Northern Finance Association 2020; GRASFI 2020 (Columbia University); Wellington Finance Summit 2018; Finance on Cloud 2021; Asia-Pacific Corporate Finance Online Workshop 2021; IRMC 2020;
Co-author: Ishita Sen (Harvard Business School)
Abstract: Exploiting position-level heterogeneity in regulatory incentives to misreport and novel data on regulators, we document that U.S. life insurers inflate the values of corporate bonds using internal models. We estimate an additional $9-$18 billion decline in regulatory capital during the 2008 crisis, i.e., a 30% greater decline than what was reported. Supervision helps dissuade misreporting, but only when close pricing benchmarks exist. Insurers, in response, strategically shift asset selection toward bonds where price verification is harder and corner small bonds. Our findings have consequences for assessing the fragility of financial institutions and for understanding the price discovery of corporate bonds.
Conferences: WFA (Western Finance Association) 2021; EFA (European Finance Association) 2021; FIRS 2021; NBER Insurance Workshop; WFA-CFAR Conference (Washington University in St. Louis); Eastern Finance Association 2021; SGF Conference; AFFECT; TADC; Southern Finance Association 2021*; Northern Finance Association 2021*; FMA*; Harvard-MIT Financial Economics Workshop; EFMA 2021; AFA 2020 (Poster Session);
Abstract: We compile a rich dataset that links institutional investors' position level holdings with corporate bond characteristics and estimate demand elasticities with respect to critical sources of risk. Persistence in institutions' holdings provide us with a powerful instrument to isolate exogenous movement in prices. We find significant heterogeneity in demand elasticities across the main players in the corporate bond market, namely insurers, pension funds, and mutual funds. Long-term investors are sensitive to interest rate movements and supply liquidity, whereas mutual funds, with shorter investment horizon and benchmark constraints, demand liquidity. Price impact increased post-crisis for all institutions and has remained higher than the pre-crisis levels. Our results have wide ranging implications for corporate bond pricing due to heterogeneity in investors and investment mandates, and are hard to reconcile with standard, representative agent based models.
Conferences: AFA (American Finance Association) 2022*; CICF 2021;
Abstract: The effect of economy-wide political uncertainty on stock market returns is well documented in the literature. However, in order to take a stand on the relation between firm-specific political risk and the cross-section of stock returns, we need a measure independent of those returns. Using a machine-learning based firm-specific measure of political risk, we show that political risk is priced in the cross-section of stock returns. On average, a one standard deviation increase in a firm's political risk is associated with a 0.5% to 1.0% increase in their annual returns. Using a related non-price measure that captures the mean of a firm's political-shocks, we disentangle whether the asset pricing implications of political risk stem from news about the discount rate or future cash flows. We further show that political risk is priced only for firms that do not actively manage political risk. Finally, using a natural language processing (NLP) enabled measure of risk associated with political topics, we examine how (and to what extent) sub-components of political risk are priced.