Holding Shares
Why is Stock Market Concentration Bad for the Economy?
Kee-Hong Bae, Warren Bailey & Jisok Kang
Journal of Financial Economics, forthcoming
Abstract:
The stock market should fund promising new firms, thereby breeding competition, innovation, and economic growth. However, using three decades of data from 47 countries, we show that concentrated stock markets dominated by a small number of very successful firms are associated with less efficient capital allocation, sluggish IPO and innovation activity, and slower economic growth. These findings are robust to alternative sample periods, econometric specifications, and competing explanatory variables. Our evidence is consistent with the paradox that the capital market of a competitive economy can impede the continuing competitiveness of that economy.
Monetary Policy and Asset Price Overshooting: A Rationale for the Wall/Main Street Disconnect
Ricardo Caballero & Alp Simsek
NBER Working Paper, August 2020
Abstract:
We analyze optimal monetary policy when asset prices influence aggregate demand with a lag (as is well documented). In this context, as long as the central bank's main objective is to minimize the output gap, the central bank optimally induces asset price overshooting in response to the emergence of a negative output gap. In fact, even if there is no output gap in the present but the central bank anticipates a weak recovery dragged down by insufficient demand, the optimal policy is to preemptively support asset prices today. This support is stronger if the acute phase of the recession is expected to be short lived. These dynamic aspects of optimal policy give rise to potentially large temporary gaps between the performance of financial markets and the real economy. One vivid example of this situation is the wide disconnect between the main stock market indices and the state of the real economy in the U.S. following the Fed's powerful response to the Covid-19 shock.
Information Dispersion across Employees and Stock Returns
Ashwini Agrawal, Isaac Hacamo & Zhongchen Hu
Review of Financial Studies, forthcoming
Abstract:
Rank-and-file employees are becoming increasingly critical for many firms, yet we know little about how their employment dynamics matter for stock prices. We analyze new data from the individual CV’s of public company employees and find that rank-and-file labor flows can be used to predict abnormal stock returns. Accounting data and survey evidence indicate that workers’ labor market decisions reflect information about future corporate earnings. Investors, however, do not appear to fully incorporate this information into their earnings expectations. The findings support the hypothesis that rank-and-file employees’ entry and exit decisions reveal valuable insights into their employers’ future stock performance.
FASB was Right: Earnings Beat Cash Flows when Predicting Future Cash Flows
Ray Ball & Valeri Nikolaev
University of Chicago Working Paper, September 2020
Abstract:
Do accruals-based accounting earnings provide better information to investors about future operating cash flows than operating cash flows themselves, as predicted by FASB's conceptual framework? The most recent evidence (Nallareddy et al., 2020) is that operating cash flows, when measured correctly using cash flow statement data, consistently outperform earnings. However this evidence is based on "bottom line" earnings, which handicaps earnings by including non-operating components with no corresponding operating cash flow. Operating earnings consistently dominate operating cash flow's predictive ability in a battery of tests, especially after addressing cross-sectional differences among firms.
The Influence of Short Selling on the Production and Market Consequences of Negative Press Coverage
Robert Bushman & Jedson Pinto
University of North Carolina Working Paper, July 2020
Abstract:
The production, dissemination and market consequences of firm-specific information are shaped by the incentives of market players operating within the constraints imposed by securities regulation. In this paper we focus on constraints to short selling activity and address two questions: Do short sale constraints influence (1) the extent to which the business press reports negative news stories?; and (2) the speed and intensity with which market participants respond to the publication of negative news reports? Following exogenous relief of short sale constraints, we find that treated firms’ press coverage tilts significantly more negative relative to untreated firms still facing higher constraints. This result is stronger for media-initiated articles than for firm-initiated press releases. With respect to market consequences we find that for treated firms, stock returns and open short interest become significantly more sensitive to negative news reports, and news sentiment-based trading strategies earn lower abnormal returns.
A Text-Based Analysis of Corporate Innovation
Gustaf Bellstam, Sanjai Bhagat & Anthony Cookson
Management Science, forthcoming
Abstract:
We develop a new measure of innovation using the text of analyst reports of S&P 500 firms. Our text-based measure gives a useful description of innovation by firms with and without patenting and R&D (research and development). For nonpatenting firms, the measure identifies innovative firms that adopt novel technologies and innovative business practices (e.g., Walmart’s cross-geography logistics). For patenting firms, the text-based measure strongly correlates with valuable patents, which likely capture true innovation. The text-based measure robustly forecasts greater firm performance and growth opportunities for up to four years, and these value implications hold just as strongly for innovative nonpatenting firms.
False (and Missed) Discoveries in Financial Economics
Campbell Harvey & Yan Liu
Journal of Finance, October 2020, Pages 2503-2553
Abstract:
Multiple testing plagues many important questions in finance such as fund and factor selection. We propose a new way to calibrate both Type I and Type II errors. Next, using a double‐bootstrap method, we establish a t‐statistic hurdle that is associated with a specific false discovery rate (e.g., 5%). We also establish a hurdle that is associated with a certain acceptable ratio of misses to false discoveries (Type II error scaled by Type I error), which effectively allows for differential costs of the two types of mistakes. Evaluating current methods, we find that they lack power to detect outperforming managers.
Why do investment banks buy put options from companies?
Stanley Gyoshev et al.
Journal of Corporate Finance, forthcoming
Abstract:
Companies have collected billions in premiums from privately sold put options written on their own stock. It is puzzling that counterparties, investment banks, would agree to make such transactions with better-informed companies which have extraordinary ability to time the market as documented by Jenter et al. (2011). To resolve this puzzle, we develop a model that shows that investment banks, by offering to buy put options from better-informed parties, receive private information about issuing companies. Our model also incorporates the practice of firms (such as Microsoft) of sometimes repurchasing their own put options and thus providing additional private information to investment banks. Empirically, we find support for our theory from an abnormal 9% increase in the stock prices and a 40% increase in the trading volumes around the put sales. Examination of 13D filings reveals that trading by upper management insiders cannot completely account for the change in volume.
Do High-Frequency Traders Anticipate Buying and Selling Pressure?
Nicholas Hirschey
Management Science, forthcoming
Abstract:
This study provides evidence that high-frequency traders (HFTs) identify patterns in past trades and orders that allow them to anticipate and trade ahead of other investors’ order flow. Specifically, HFTs’ aggressive purchases and sales lead those of other investors, and this effect is stronger at times when it is more difficult for non-HFTs to disguise their order flow. Consistent with some HFTs being more skilled or more focused on anticipatory strategies, I show that trades from a subset of HFTs consistently predict non-HFT order flow the best. The results are not explained by HFTs reacting faster to news or past returns, by contrarian or trend-chasing behavior by non-HFTs, or by trader misclassification. These findings support the existence of an anticipatory trading channel through which HFTs increase non-HFT trading costs.
Slow-moving capital and execution costs: Evidence from a major trading glitch
Vincent Bogousslavsky, Pierre Collin-Dufresne & Mehmet Sağlam
Journal of Financial Economics, forthcoming
Abstract:
We investigate the impact of an exogenous trading glitch at a high-frequency market-making firm on standard measures of stock liquidity (spreads, price impact, turnover, and depth) and institutional trading costs (implementation shortfall and volume-weighted average price slippage). Stocks in which the firm accumulates large long (short) positions increase (decrease) by about 4% during the glitch and become substantially more illiquid. It takes one day for prices and spread-based liquidity measures to revert. Institutional trading costs, however, remain significantly higher for more than one week. Both liquidity measures are also weakly correlated outside the glitch period, suggesting they capture different aspects of liquidity.