Alphas and Betas
Presidential economic approval rating and the cross-section of stock returns
Zilin Chen et al.
Journal of Financial Economics, January 2023, Pages 106-131
Abstract:
We construct a monthly presidential economic approval rating (PEAR) index from 1981 to 2019, by averaging ratings on the president’s handling of the economy across various national polls. In the cross-section, stocks with high betas to changes in the PEAR index significantly under-perform those with low betas by 1.00% per month in the future, on a risk-adjusted basis. The low PEAR beta premium persists up to one year, and is present in various sub-samples and even in other G7 countries. PEAR beta dynamically reveals a firm’s perceived alignment to the incumbent president’s economic policies and investors seem to misprice such an alignment.
Sustainability Preferences Under Stress: Evidence from COVID-19
Robin Döttling & Sehoon Kim
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
We document fragile demand for socially responsible investments (SRI) by retail mutual fund investors. Using COVID-19 as an economic shock, we show funds with higher sustainability ratings experienced sharper declines in retail flows during the pandemic, controlling for fund characteristics. The decline in retail SRI fund flows is sharper than that of institutional flows, more pronounced when economies are hit harder by COVID-19, and unlikely to be driven by fund performance, past flows and size, or shifting investor attention. Corroborated by out-of-sample survey evidence, our findings highlight high sensitivity of SRI demand by retail investors with respect to income shocks.
Acute illness symptoms among investment professionals and stock market dynamics: Evidence from New York City
Gabriele Lepori
Journal of Empirical Finance, January 2023, Pages 165-181
Abstract:
In the U.S., stock market professionals (e.g., traders, portfolio managers, and analysts) are clustered in New York City (NYC). In view of this, I exploit daily changes in the incidence of acute illness symptoms among 18-64 year old New Yorkers to identify exogenous variation in the rate of acute illness among market professionals and estimate its causal impact on key stock market outcomes. A detailed analysis of taxi trips from a sample of financial institutions to local hospitals provides support for my identification assumption. Other things equal, increased rates of acute physical illness (i.e., reduced productivity) among market professionals hamper price discovery and lower trading activity, volatility, and returns. A one-standard-deviation increase in my illness incidence proxy reduces by 18% (6.7%) the immediate response of stock prices to earnings surprises (changes in analysts’ consensus recommendations) and increases by 29% (42%) their delayed response.
How Fast Do Investors Learn? Asset Management Investors and Bayesian Learning
Christopher Schwarz & Zheng Sun
Review of Financial Studies, forthcoming
Abstract:
We study the speed with which investors learn about managers’ skills by examining how quickly investor and managers’ beliefs converge. After showing our measure proxies for the change in the dispersion of beliefs, we find that hedge fund investors learn as fast as suggested by Bayes’ rule. However, we find mutual fund investors learn more slowly than suggested by Bayes’ rule. Mutual fund investors’ slow learning is not due to the use of different performance measures, institutional frictions, or lack of sophistication, but could be due to a low payoff from learning. Our results indicate learning speed depends on financial participants’ incentives.
The Disappearing Index Effect
Robin Greenwood & Marco Sammon
NBER Working Paper, December 2022
Abstract:
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 pattern has occurred for index deletions, with large negative abnormal returns on average during the 1980s and 1990s, but only -0.6% between 2010 and 2020. We investigate potential drivers of this surprising phenomenon and discuss the implications for market efficiency.
Identifying The Effects of Macroeconomic Attention Through Foreign Investor Distraction
Paul Marmora
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
While the causal impact of limited attention to macroeconomic news is difficult to detect, this paper proposes one solution: exploiting when foreign investors are “distracted” by risk factors in their home markets. I demonstrate that financial activity in the average foreign investor’s home market decreases foreign attention paid to 21 emerging economies, measured using Google search volume for economy-specific financial terms that emanate from outside each economy’s border. Exploiting this effect using an instrumental variables approach, I find that an exogenous increase in foreign attention preceding a scheduled monetary policy rate announcement raises preannouncement stock returns and announcement day turnover.
The One-Man Show: The Effect of Joint Decision-Making on Investor Overconfidence
Dominik Piehlmaier
Journal of Consumer Research, forthcoming
Abstract:
This study examines the impact of shared decision-making on investor overconfidence. Data from 2,000 investors, 6,394 consumers, and 657 experimental participants shed light on whether consumers who engage in joint financial decision-making are less affected by investor overconfidence than those who decide on their own. The findings show that investors who jointly decide are substantially less overconfident. However, family- or friend-inclined interactions are more effective in reducing overconfidence than relying on a financial advisor. The current research theoretically argues and empirically shows that shared metaknowledge drives this diminishing effect by highlighting unknown aspects of a financial decision. Compared to providing investors with solutions, problem reformulation, validation, or legitimation, only metaknowledge consistently decreases overconfidence in joint financial decision-making. It is argued that the process of highlighting unknowns can explain why interactions with family and friends have a more pronounced impact on investor overconfidence than consulting a professional advisor. The study provides a feasible debiasing tool to consumers, financial institutions, and other financial service providers to decrease overconfidence by emphasizing unknown aspects of an investment toward improving the quality of a consumer’s financial decisions under uncertainty.
Artificially Intelligent Analyst Sentiment and Aggregate Market Behavior
Vidhi Chhaochharia et al.
University of Miami Working Paper, December 2022
Abstract:
This study develops a new machine learning-based measure of aggregate analyst sentiment. We first train analyst-specific neural network models that capture each analyst's predictable forecast bias across firms and then aggregate the information at the industry and market levels. We decompose the aggregated forecast errors of analysts into predictable and non-predictable components, and interpret the non-predictable component as a measure of analyst sentiment. Variation in analyst sentiment along the business cycle suggests that they systematically underreact to macroeconomic information. A Long-Short trading strategy based on industry-level analyst sentiment earns an annualized alpha of over 7%.
Ambiguity Aversion and Beating Benchmarks: Does it Create a Pattern?
Adam Kolasinski et al.
Management Science, forthcoming
Abstract:
The prior literature on analyst forecasts has focused almost exclusively on firms that just meet or beat the mean or median consensus analyst forecast, without much regard to alternative benchmarks within the forecast distribution. Anecdotal evidence suggests that there is institutional significance to the lowest (minimum) and highest (maximum) analyst earnings forecast. We rigorously explore whether these two new benchmarks actually have incremental significance and, if so, whether there are differences in how managers and investors perceive the importance of these three benchmarks (i.e., minimum, mean, and maximum). Consistent with the theory of investor ambiguity aversion, which predicts an asymmetric market response to good and bad news, our results support the notion that of the three benchmarks we explore, firms act most aggressively to exceed the minimum forecast, followed by the mean, and then finally the maximum. This order is consistently supported by the following evidence: the existence of higher incentives to beat the benchmark; the likelihood of earnings management to beat the benchmark; accrual reversal after firms just barely achieve each benchmark; accrual mispricing around each benchmark; and, finally, a faster incorporation into the stock price of the bad news that a firm misses the minimum than of the good news that a firm meets or beats the maximum. These findings fill a void in academic research on these two new benchmarks and offer a consistent explanation as to why the popular press and managers frequently highlight and discuss beating these benchmarks as a separate and notable achievement.
Brokerage House Initial Public Offerings and Analyst Forecast Quality
Mark Bradshaw at al.
Management Science, forthcoming
Abstract:
We examine how brokerage firm initial public offerings (IPOs) influence the research quality of sell-side analysts employed by the brokerage. Our main results focus on earnings forecast bias and absolute forecast errors as proxies for research quality. Using a staggered difference-in-differences analysis, we document significant decreases in forecast bias and absolute forecast error during the two-year period centered on the analysts’ brokerage house IPO. In additional analyses, we explore several potential explanations for the short-term benefits of brokerage house IPOs. We find some evidence that IPOs delay the departure of more talented analysts and that the effects are more concentrated among analysts and brokers that face more scrutiny.