Peak Trump
Trump, Twitter, and Treasuries
Peter Tillmann
Contemporary Economic Policy, forthcoming
Abstract:
After appointing Federal Reserve Chairman Powell, President Trump put pressure on the Fed to cut interest rates. We show that, on average, a statement from Trump on the Fed led to lower long‐term interest rates, consistent with expectations of lower expected future short rates. However, the impact of Trump's statements declined over time.
When the market drives you crazy: Stock market returns and fatal car accidents
Corrado Giulietti, Mirco Tonin & Michael Vlassopoulos
Journal of Health Economics, forthcoming
Abstract:
This paper provides evidence that daily fluctuations in the stock market have important - and hitherto neglected - spillover effects on fatal car accidents. Using the universe of fatal car accidents in the United States from 1990 to 2015, we find that a one standard deviation reduction in daily stock market returns is associated with a 0.6% increase in fatal car accidents that happen after the stock market opening. A battery of falsification tests support a causal interpretation of this finding. Our results are consistent with immediate emotions stirred by a negative stock market performance influencing the number of fatal accidents, in particular among inexperienced investors.
Do Role Models Affect Risk-Taking Behavior? The Case of Minorities
Yosef Bonaparte, Sarah Khalaf & George Korniotis
University of Colorado Working Paper, February 2019
Abstract:
We show that social changes, like the success of role models, affects household financial decisions. Specifically, minorities underinvest in equity, which contributes to the widening racial wealth gap. But the election of President Obama in 2008, who is a role model from minorities, is a positive social change that should encourage investing. Indeed, post-2008 and compared to White Americans, minorities, trade more often, have a higher propensity to increase risk tolerance as well as allocations to risky assets and savings, and a lower propensity to exit the market. Overall, we show that societal factors affect the racial stock ownership gap.
Man versus Machine: A Comparison of Robo-Analyst and Traditional Research Analyst Investment Recommendations
Braiden Coleman, Kenneth Merkley & Joseph Pacelli
Indiana University Working Paper, January 2020
Abstract:
Advances in financial technology (FinTech) have revolutionized various product offerings in the financial services industry. One area of particular interest for this technology is the production of investment recommendations. Our study provides the first comprehensive analysis of the properties of investment recommendations generated by “Robo-Analysts,” which are human-analyst-assisted computer programs conducting automated research analysis. Our results indicate that Robo-Analysts differ from traditional “human” research analysts across several dimensions. First, Robo-Analysts collectively produce a more balanced distribution of buy, hold, and sell recommendations than do human analysts, which suggests that they are less subject to behavioral biases and conflicts of interest. Second, consistent with automation facilitating a greater scale of research production, Robo-Analysts revise their reports more frequently than human analysts and also adopt different production processes. Their revisions rely less on earnings announcements, and more on the large, volumes of data released in firms’ annual reports. Third, Robo-Analysts’ reports exhibit weaker short-window return reactions, suggesting that investors do not trade on their signals. Importantly, portfolios formed based on the buy recommendations of Robo-Analysts appear to outperform those of human analysts, suggesting that their buy calls are more profitable. Overall, our results suggest that Robo-Analysts are a valuable, alternative information intermediary to traditional sell-side analysts.
The Social Media Risk Premium
Amin Hosseini et al.
George Washington University Working Paper, January 2020
Abstract:
Using novel corporate Twitter data on all U.S. public firms, we show that firms with a Twitter account earn 50 basis points per month higher returns than similar firms without a Twitter account. This 'Twitter premium' is higher among smaller firms and firms with higher fundamentals uncertainty, and is not explained by existing risk-factor models. Having a Twitter account presents opportunities for value creation but also raises social media risks. We show that a social media risk factor is priced in the cross-section of U.S. stock returns and carries a premium of 30 to 75 basis points per month controlling for other risk factors.
I am a blockchain too: How does the market respond to companies’ interest in blockchain?
Daniel Cahill et al.
Journal of Banking & Finance, forthcoming
Abstract:
We investigate the price reaction of listed companies in response to blockchain-related announcements. The average abnormal return based on a global sample of 713 firm announcements is approximately 5% on the announcement day, with significantly higher returns for U.S. firms, smaller firms and announcements in late 2017 and early 2018. We show that abnormal returns are linked to the performance of bitcoin. Additionally, speculative announcements exhibit higher returns than non-speculative announcements, and blockchain-related Form 8-K disclosures have negligible difference in performance compared to their U.S. peers. Whilst we acknowledge the possibility of a latent variable that affects both the abnormal returns and the performance of bitcoin, we hypothesise that investors have confused bitcoin and blockchain, and used the performance of bitcoin as an indicator of the expected success of the blockchain technology.
Did Mutual Fund Return Persistence Persist?
James Choi & Kevin Zhao
NBER Working Paper, January 2020
Abstract:
A seminal study of persistence in mutual fund performance is Carhart (1997), who found that U.S. equity mutual funds’ past-year returns positively predict their raw excess return and one-factor alpha over the next year. Based on these results, an investor may believe that she can earn higher returns by buying mutual funds with high past-year returns. We are able to replicate Carhart’s results in his 1963-1993 sample period, but we find that significant performance persistence does not exist in the 1994-2018 period. Even during the 1963-1993 period, performance persistence weakened in later years. The disappearance of significant performance persistence is due to lower returns to favorable styles, as well as less favorable style tilts and increased style-adjusted underperformance by past winning funds.
The Real Effects of Financial Statement Recognition: Evidence from Corporate Credit Ratings
Riddha Basu & James Naughton
Management Science, forthcoming
Abstract:
We examine whether the recognition versus disclosure of identical accounting information affects the credit rating process and ultimately corporate credit ratings. The primary input into corporate credit ratings is adjusted financial statements, which the rating agencies create by modifying reported financial statements to reflect credit-relevant items not recognized under U.S. Generally Accepted Accounting Principles. The rating agencies have claimed that this process means that accounting changes that move previously disclosed information onto firms’ financial statements have virtually no effect on firms’ adjusted financial statements or their credit ratings. We show that this claim is incorrect using the implementation of Financial Accounting Standards Board Statement No. 158 (SFAS158). This standard did not prescribe any new financial information. Rather, it simply required the balance sheet recognition of a previously disclosed item. We find that firms recognizing an additional pension liability due to SFAS158 had lower leverage on the rating agency adjusted financial statements and received higher corporate credit ratings. This counterintuitive result occurs because the rating agency adjustments made before SFAS158 were punitive relative to the combination of the SFAS158 changes and the rating agency adjustments made after SFAS158. The difference in rating agency adjustments before and after SFAS158 was primarily due to rating agency adjustments in the pre-SFAS158 period that did not account for minimum liability adjustments, an aspect of pension accounting eliminated by SFAS158. Overall, our results indicate that SFAS158 generated real changes in rating agency adjustments and that these changes had real consequences for firms’ credit ratings.
The Persistent Effect of Initial Success: Evidence from Venture Capital
Ramana Nanda, Sampsa Samila & Olav Sorenson
Journal of Financial Economics, forthcoming
Abstract:
We use investment-level data to study performance persistence in venture capital (VC). Consistent with prior studies, we find that each additional initial public offering (IPO) among a VC firm’s first ten investments predicts as much as an 8% higher IPO rate on its subsequent investments, though this effect erodes with time. In exploring its sources, we document several additional facts: successful outcomes stem in large part from investing in the right places at the right times; VC firms do not persist in their ability to choose the right places and times to invest; but early success does lead to investing in later rounds and in larger syndicates. This pattern of results seems most consistent with the idea that initial success improves access to deal flow. That preferential access raises the quality of subsequent investments, perpetuating performance differences in initial investments.
Impact Investing
Brad Barber, Adair Morse & Ayako Yasuda
NBER Working Paper, December 2019
Abstract:
We document that investors derive nonpecuniary utility from investing in dual-objective VC funds, thus sacrificing returns. Impact funds earn 4.7 percentage points (ppts) lower IRRs ex post than traditional VC funds. In random utility/willingness-to-pay (WTP) models investors accept 2.5-3.7 ppts lower IRRs ex ante for impact funds. The positive WTP result is robust to fund access rationing and investor heterogeneity in fund expected returns. Development organizations, foundations, financial institutions, public pensions, Europeans, and UNPRI signatories have high WTP. Investors with mission objectives and/or facing political pressure exhibit high WTP; those subject to legal restrictions (e.g., ERISA) exhibit low WTP.
Venture Capital Communities
Amit Bubna, Sanjiv Das & Nagpurnanand Prabhala
Journal of Financial and Quantitative Analysis, March 2020, Pages 621-651
Abstract:
Although venture capitalists (VCs) can choose from thousands of potential syndicate partners, many co-syndicate with small groups of preferred partners. We term these groups “VC communities.” We apply computational methods from the physical sciences to 3 decades of syndication data to identify these communities. We find that communities comprise VCs that are similar in age, connectedness, and functional style but undifferentiated in spatial location. Machine-learning tools classify communities into 3 groups roughly ordered by their age and reach. Community VC financing is associated with faster maturation and greater innovation, especially for early-stage firms without an innovation history.