Is shareholder interest in corporate social responsibility driven by pecuniary motives (abnormal rates of return) or non-pecuniary ones (willingness to sacrifice returns to address various firm externalities)? To answer this question, we categorize the literature into seven tests: (1) costs of...

Standard theory implies that the discount rates used by firms in investment decisions (i.e., their required returns to capital) determine investment and transmit financial shocks to the real economy. However, there exists little evidence on how firms' discount rates change over time and affect...

Firms' perceived cost of green capital has decreased since the rise of sustainable investing. Green and brown firms perceived their cost of capital to be the same before 2016, but after the post-2016 surge in sustainable investing, green firms perceived their cost of capital to be on average 1...

We create a firm-level ChatGPT investment score, based on conference calls, that measures managers' anticipated changes in capital expenditures. We validate the score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future...

Climate change is increasing the frequency of natural disasters, which could make municipal bonds a riskier asset class. We study the effects of natural disasters on municipal bond returns, exploiting the repeat sales approach to overcome the challenge that municipal bonds trade extremely...

We propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of...

The abnormal return associated with a stock being added to the S&P 500 has fallen from an average of 3.4% in the 1980s and 7.6% in the 1990s to 0.8% over the past decade. This has occurred despite a significant increase in the percentage of stock market assets linked to the index. A similar...

Using text from 200 million pages of 13,000 US local newspapers and machine learning methods, we construct a 170-year-long measure of economic sentiment at the country and state levels, that expands existing measures in both the time series (by more than a century) and the cross-section. Our...

We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...