What The Market Bears
Partisan bias in securities enforcement
Reilly Steel
Journal of Law, Economics, and Organization, forthcoming
Abstract:
In this article, I present a partisan theory of agency enforcement and empirically investigate the possibility of partisan bias in the enforcement of the federal securities laws. Leveraging plausibly exogenous shocks to partisan control of the U.S. Securities and Exchange Commission (SEC), I find evidence that a firm’s partisan alignment with the SEC substantially reduces the likelihood of enforcement. For a firm that is ex ante equally likely to be targeted for enforcement or not, my estimates indicate that a typical increase in partisan alignment following a change in party control of the SEC reduces the likelihood of enforcement by over 19%. Partisan alignment also appears to reduce aggregate monetary sanctions, though these estimates are less certain. By contrast, I find little evidence of partisan bias in the initial opening of investigations. These findings suggest there may be meaningful partisan bias in SEC enforcement and have important implications for democratic governance.
Watching the Watchdogs: Tracking SEC Inquiries using Geolocation Data
William Gerken et al.
University of Kentucky Working Paper, August 2024
Abstract:
The Securities and Exchange Commission's investigative process remains opaque and challenging to study due to limited observability. Leveraging de-identified smartphone geolocation data, we provide new insights into the SEC's monitoring practices by tracking SEC-associated devices that visit firm headquarters. Our findings reveal that the majority of SEC visits occur outside of formal investigations, with larger firms and those with a history of SEC enforcement actions being more frequently visited. These visits often cluster within industries. Notably, the SEC associated devices venture to firms both within and outside their own regions. On average, these visits are material, evidenced by significant stock price reactions, even in the absence of subsequent formal investigations or enforcement actions. Last, we observe a chilling effect on insider behavior around these SEC interactions; insiders are less likely to sell around visits. However, when sales do occur, insiders avoid substantial losses.
Expected EPS × Trailing P/E
Itzhak Ben-David & Alex Chinco
NBER Working Paper, September 2024
Abstract:
All of asset-pricing theory currently stems from one key assumption: price equals expected discounted payoff. And much of what we think we know about discount rates comes from studying a particular kind of expected payoff: the earnings forecasts in analyst reports. Researchers typically access these numbers through an easy-to-use database and never read the underlying documents. This is unfortunate because the text of each report contains an explicit description of how the analyst priced their own earnings forecast. We study a sample of 513 reports and find that most analysts use a trailing P/E (price-to-earnings) ratio not a discount rate. Instead of computing the present value of a company’s future earnings, they ask: “How would a firm with similar earnings have been priced last year?” Even if other investors do things differently, it does not make sense to put discount rates at the center of every asset-pricing model if market participants do not always use one. There are other options. Trailing twelve-month P/E ratios account for 91% of the variation in analysts’ price targets. We construct a new kind of asset-pricing model around this fact and show that it explains the market response to earnings surprises.
Too good to be true: A theory
John Conlon & Feng Liu
Economics Letters, forthcoming
Abstract:
We use a Gaussian mixture prior with two clusters to explain market fears. We show that a surprisingly positive signal can shake investors’ confidence in their understanding of the market, and in the process, potentially lower their expectation of an asset’s value.
Business News and Business Cycles
Leland Bybee et al.
Journal of Finance, October 2024, Pages 3105-3147
Abstract:
We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text-augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.
Earnings News and Local Household Spending
Brandon Gipper et al.
Stanford Working Paper, February 2024
Abstract:
Using debit and credit card data, we find a one standard-deviation increase in firms’ earnings surprise is linked to a 3% or $5.6 billion increase in aggregate quarterly consumption of local households near the disclosing firms’ headquarters. The effect is more pronounced when earnings news is informative about local households’ wealth, is widely disseminated through media, and is more intensely searched by locals. The change in consumption is concentrated in less expensive goods, such as dining out, and among various local stakeholders, including employees and business owners. Consistent with households not being able to unravel fraud, their consumption reacts even to fraudulent earnings, which reverses only after the fraud is revealed. To corroborate our mechanism, we conduct a nationwide survey of 500 randomly selected households. Nearly 50% of the respondents say their spending decisions are influenced by the financial news of local firms via its effect on local job or investment opportunities. Our findings yield important policy implications of financial reporting on household welfare.
Temporal Dynamics of Venture Capital Funds: Investment Timing and Fund Performance
Jonathan Zandberg et al.
University of Pennsylvania Working Paper, July 2024
Abstract:
This study investigates the impact of investment timing within the lifecycle of venture capital (VC) funds on investment outcomes. We find empirical evidence of diminishing returns in VC investments, demonstrating that firms funded in the early stages of a fund's lifecycle have a higher probability of successful exits. Building on this observation, we develop a theoretical model that highlights the importance of temporal factors in investment decisions. Our model decomposes fund performance into three components: selection, monitoring, and financing, and illustrates how these factors affect the matching process between startups and VC funds. Empirical results support our theoretical predictions, showing stable matching between high-quality entrepreneurs and younger funds. Our findings suggest that entrepreneurs' preference for younger funds, a previously overlooked aspect, plays an important role in the matching process and overall investment success.
The Portfolio-Driven Disposition Effect
Li An et al.
Journal of Finance, October 2024, Pages 3459-3495
Abstract:
The disposition effect for a stock significantly weakens if the portfolio is at a gain, but is large when it is at a loss. We find this portfolio-driven disposition effect (PDDE) in four independent settings: U.S. and Chinese archival data, as well as U.S. and Chinese experiments. The PDDE is robust to a variety of controls in regression specifications and is not explained by extreme returns, portfolio rebalancing, tax considerations, or investor heterogeneity. Our evidence suggests that investors form mental frames at both the stock and the portfolio levels and that these frames combine to generate the PDDE.
The Effect of New Information Technologies on Asset Pricing Anomalies
David Hirshleifer & Liang Ma
NBER Working Paper, August 2024
Abstract:
We test and compare the effects of introduction of two new financial information technologies, EDGAR and XBRL, on well-known asset pricing anomalies often attributed to mispricing. EDGAR facilitates easier access to public accounting information about public firms; XBRL reduces the cost of processing such information. Using stacked difference-in-differences regressions, we find that both EDGAR and XBRL reduce mispricing for accounting-based anomalies but not for non-accounting-based anomalies. The economic magnitudes of the effects on accounting-based anomalies are similar for EDGAR and XBRL. These results suggest that both easier access to and less costly processing of public information enhance market efficiency.
The Less-Efficient Market Hypothesis
Clifford Asness
Journal of Portfolio Management, forthcoming
Abstract:
Market efficiency is a central issue in asset pricing and investment management, but while the level of efficiency is often debated, changes in that level are relatively absent from the discussion. I argue that over the past 30+ years markets have become less informationally efficient in the relative pricing of common stocks, particularly over medium horizons. I offer three hypotheses for why this has occurred, arguing that technologies such as social media are likely the biggest culprit. Looking ahead, investors willing to take the other side of these inefficiencies should rationally be rewarded with higher expected returns, but also greater risks. I conclude with some ideas to make rational, diversifying strategies easier to stick with amid a less-efficient market.