Annual Conference

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Accounting

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May 2017

Macroeconomic uncertainty and quantitative vs. qualitative inputs to analyst risk forecasts

Peter JOOS, Khrystyna BOCHKAY
We study how sell-side analysts map both quantitative and qualitative information from earnings conference calls into their forecasts of fundamental firm risk. We find that analysts perceive firm risk to be lower when absolute earnings surprises are small and tone of the earnings conference calls is...
Keywords: Analysts’ risk forecasts, unexpected earnings, tone, macroeconomic uncertainty
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Webinar Series

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Pandemic

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May 2020

Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?

Veronica GUERRIERI, Guido LORENZONI, Ludwig STRAUB, Iván WERNING
We present a theory of Keynesian supply shocks: supply shocks that trigger changes in aggregate demand larger than the shocks themselves. We argue that the economic shocks associated to the COVID-19 epidemic—shutdowns, layoffs, and firm exits—may have this feature. In one-sector economies supply...
Keywords: 2019-nCoVCOVID-19, Disease Outbreak, Supply Shocks, Demand Shortages, Macroeconomic Implications
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Annual Conference

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International Macroeconomics, Money & Banking

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May 2018

Macro-financial Modeling of the Singapore Economy: A GVAR approach

Filippo di MAURO, Alessandro GALESI
No abstract
Keywords: Macro-Financial Modelling, Singapore Economy, GVAR approach
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Annual Conference

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Investment Finance

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May 2022

Macro-Active Bond Mutual Funds

Claire Yurong HONG, Jun PAN, Shiwen TIAN
We document significant outperformance by government bond funds on important macro announcement days such as FOMC and GDP. The macro-day outperformance is persistent, larger during times of high macro disagreement and surprise, and stronger for active funds with larger idiosyncratic volatility. Thei...
Keywords: FOMC, GDP, Bond Mutual Fund, Macroeconomic Announcement, Activeness
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Senior Fellows/Fellows

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Senior Fellows/Fellows

Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles

Prithwiraj (Raj) CHOUDHURY, Dan WANG, Natalie A. CARLSON, Tarun KHANNA
The advent of machine learning (ML) tools presents researchers with the possibility of using large and new datasets related to text and image repositories. In this paper, we document how a novel synthesis of three methods—(1) unsupervised topic modeling of textual data to generate a new measure of...
Keywords: machine learning, topic modeling, facial image recognition, CEO communication, topic entropy
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