Market News

Kevin Lewis

December 14, 2021

Sectoral Media Focus and Aggregate Fluctuations
Ryan Chahrour, Kristoffer Nimark & Stefan Pitschner
American Economic Review, December 2021, Pages 3872-3922

We formalize the editorial role of news media in a multisector economy and show that media can be an independent source of business cycle fluctuations, even when they report accurate information. Public reporting about a subset of sectoral developments that are newsworthy but unrepresentative causes firms across all sectors to hire too much or too little labor. We construct historical measures of US sectoral news coverage and use them to calibrate our model. Time-varying media focus generates demand-like fluctuations that are orthogonal to productivity, even in the absence of non-TFP shocks. Presented with historical sectoral productivity, the model reproduces the 2009 Great Recession. 

Using Social Media to Identify the Effects of Congressional Viewpoints on Asset Prices
Francesco Bianchi, Howard Kung & Roberto Gomez Cram
NBER Working Paper, October 2021

This paper examines the extent to which individual politicians affect asset prices using a high-frequency identification approach. We exploit the regular flow of viewpoints contained in a large volume of tweets from members of US Congress. Congressional tweets targeting individual firms are collected and classified based on their tone. Supportive (critical) tweets increase (decrease) stock prices of the targeted firm in minutes around the tweet. The price response persists for several days, during which analysts revise their forecasts about the firm cash flows. Selected politician tweets linked to legislation affect the stock prices of firms in the same industry as the targeted firm. The timeline of politician viewpoints within a particular bill exhibits surges in relevant news that predict roll call votes months before the signing of the bill. We highlight how the social media accounts of politicians are a valuable source of political news. 

The True Colors of Money: Racial Diversity and Asset Management
Lina Han et al.
Washington University in St. Louis Working Paper, November 2021

This paper studies the role of race and ethnicity in the investment decisions of mutual fund managers and mutual fund investors. Mutual funds managed by a white-dominant team account for more than 90% of all funds. Such funds invest a smaller proportion of their portfolios in firms led by minority CEOs compared to funds managed by a minority-dominant team. Fund managers do not deliver superior performance on equity holdings for which the CEO's race coincides with their own, suggesting no race-related informational advantage. Considering flow-performance sensitivity, we find that funds managed by a minority-dominant team are equally penalized when they perform poorly but are not rewarded as much for superior performance as white-dominant funds. Our results uncover the differential treatment of minority-led funds and firms by investors. 

COVID-19 Uncertainty: A Tale of Two Tails
Philip Bunn et al.
University of Chicago Working Paper, November 2021 

Uncertainty about own-firm sales growth rates over the year ahead roughly doubled in reaction to the COVID shock, according to our surveys of U.S. and U.K. business executives. Firm-level uncertainty receded after spring 2020 but remains much higher than pre-COVID levels. Moreover, the nature of firm-level uncertainty has shifted greatly since the pandemic struck: Initially, business executives perceived an enormous increase in downside uncertainty, which has now dissipated. As of October 2021, almost all of the extra firm-level uncertainty is to the upside. In short, economic uncertainty associated with the pandemic has morphed from a tale of the lower tail into a tale about the upper tail. 

Is Hard and Soft Information Substitutable? Evidence from Lockdown
Jennie Bai & Massimo Massa
NBER Working Paper, November 2021 

We study information substitutability in the financial market through a quasi-natural experiment: the pandemic-triggered lockdown that has hampered people's physical interactions hence the ability to collect, process, and transmit soft information. Exploiting the cross- sectional and time-series variations of lockdown, we investigate how the difficulty to use soft information has prompted a switch to hard information and its implication on fund investment, performance, and risk management. We show that lockdown reduces fund investment in proximate stocks and generates a portfolio rebalancing toward distant stocks. The re- balancing negatively impacts fund performance by reducing fund raw (excess) return of an additional 0.76% (0.29%) per month during lockdown, suggesting that soft and hard information is not easily substitutable. Lastly, we show that soft information originates mainly from physical human interactions, primarily in cafés, restaurants, bars, and fitness centers; and the virtual world based on Zoom/Skype/Team fails to substitute physical interactions fully, thus cannot provide sufficient soft information. 

Do Hedge Fund Managers Understand Politics? Political Sensitivity and Investment Skill
Honghui Chen et al.
Journal of Banking & Finance, forthcoming

We show that hedge fund managers who more actively and astutely adjust the political sensitivity of their portfolios, in line with the dynamic U.S. political landscape, improve their investment performance. Funds that tilt their portfolios toward market segments expected to perform better during the new political regime, specifically around U.S. Presidential elections, generate significantly higher alphas. Further, hedge fund families with greater responsiveness to political changes exhibit persistently superior performance and are more likely to survive. Hedge fund investors reward more responsive fund managers with greater inflows. 

New Accounting Standards and the Performance of Quantitative Investors
Travis Dyer, Nicholas Guest & Elisha Yu
Cornell Working Paper, November 2021

Quantitative investing relies on historical data and limited day-to-day human involvement, which could create short-term inflexibility in the face of changing economic conditions. In this study, we examine quantitative investors’ ability to navigate a common and occasionally material change to the financial data generating process: new accounting standards. We find that returns of quantitative mutual funds temporarily decrease following the implementation of standards that change the definition of key accounting variables. The lower performance we document is relative to more traditional “discretionary” funds that rely heavily on human discretion to make investment decisions. Our result is stronger for value funds, which rely heavily on accounting data, and absent among funds slanted towards price-based strategies, including momentum and size. When we further investigate funds’ operations, we observe excess portfolio turnover following the implementation of accounting standards. Relatedly, quantitative underperformance is concentrated among funds holding more stocks. Overall, our results highlight a significant adjustment cost associated with accounting regulation that could become even more significant as more investors turn to quantitative strategies. 

Forecasting Skills in Experimental Markets: Illusion or Reality?
Brice Corgnet et al.
Management Science, forthcoming

There is an ongoing debate regarding the degree to which a forecaster’s ability to draw correct inferences from market signals is real or illusory. This paper attempts to shed light on the debate by examining how personal characteristics do or do not affect forecaster success. Specifically, we investigate the role of fluid intelligence, manipulativeness, and theory of mind on forecast accuracy in experimental asset markets. We find that intelligence improves forecaster performance when market mispricing is low, manipulativeness improves forecaster performance when mispricing is high, and the degree to which theory of mind skills matter depends on both the level of mispricing and how information is displayed. All three of these results are consistent with hypotheses derived from the previous literature. Additionally, we observe that male forecasters outperform female forecasters after controlling for intelligence, manipulativeness, and theory of mind skills as well as risk aversion. Interestingly, we do not find any evidence that forecaster performance improves with experience across markets or within markets. 

Forecasting building permits with Google Trends
David Coble & Pablo Pincheira
Empirical Economics, December 2021, Pages 3315–3345

We propose a useful way to predict building permits in the USA, exploiting rich data from web search queries. The relevance of our work relies on the fact that the time series on building permits is used as a leading indicator of economic activity in the construction sector. Nevertheless, new data on building permits are released with a lag of a few weeks. Therefore, an accurate nowcast of this leading indicator is desirable. In this paper, we show that models including Google search queries nowcast and forecast better than many of our good, not naïve benchmarks. We show this with both in-sample and out-of-sample exercises. In addition, we show that the results of these predictions are robust to different specifications, the use of rolling or expanding windows and, in some cases, to the forecasting horizon. Since Google queries information is free, our approach is a simple and inexpensive way to predict building permits in the USA.


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