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Summary

Dissecting Mechanisms of Financial Crises: Intermediation and Sentiment
Author(s):
Arvind Krishnamurthy, Stanford University and NBER
Wenhao Li, University of Southern California, Marshall School of Business
Discussant(s):
Wei Xiong, Princeton University and NBER
Abstract:

Krishnamurthy and Li develop a model of financial crises with both a financial amplification mechanism, via frictional intermediation, and a role for sentiment, via time-varying beliefs about an illiquidity state. They confront the model with data on credit spreads, equity prices, credit, and output across the financial crisis cycle. In particular, the researchers ask the model to match data on the frothy pre-crisis behavior of asset markets and credit, the sharp transition to a crisis where asset values fall, disintermediation occurs and output falls, and the post-crisis period characterized by a slow recovery in output. A pure amplification mechanism quantitatively matches the crisis and aftermath period but fails to match the pre-crisis evidence. Mixing sentiment and amplification allows the model to additionally match the pre-crisis evidence. Krishnamurthy and Li consider two versions of sentiment, a Bayesian belief updating process and one that overweighs recent observations. Both models match the crisis patterns qualitatively, while the non-Bayesian model better matches the pre-crisis froth quantitatively. Finally, they show that a lean-against-the-wind policy has a quantitatively similar impact in both versions of the belief model, indicating that policy need not condition on true beliefs.

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This paper was distributed as Working Paper 27088, where an updated version may be available.

Famous Firms, Earnings Clusters, and the Stock Market
Author(s):
Yixin Chen, University of Rochester
Randolph B. Cohen, Harvard University
Zixuan Wang, Harvard University
Discussant(s):
Kelly Shue, Yale University and NBER
Abstract:

Chen, Cohen, and Wang show that much of the market premium for the year occurs on a handful of days, identifiable well in advance, on which several of the market’s most famous, high-media-attention firms simultaneously announce earnings after the market close. Puzzlingly, the market surges occur during the 24 hours prior to the earnings announcements, from close to close. Since there is no overlap between the price increase period and the information revelation, the high returns do not appear to represent a risk premium, and their tests seem to rule out information-leakage explanations. Deepening the puzzle, the market delivers high returns only prior to post-close earnings-announcement clusters, not in advance of clusters that occur in the pre-open period. In addition to being economically large and easily tradeable, the effect is statistically significant, and the results hold in all subperiods in researcher's sample. Chen, Cohen, and Wang argue that the best explanation for their findings is that of Miller (1977) as extended by Hong and Stein (2007): when over a short “attention” period difference of opinion combines with short-sale constraints, prices will rise as optimists buy while pessimists cannot sell.

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Duration-Driven Returns
Author(s):
Niels Joachim Gormsen, University of Chicago
Eben Lazarus, Massachusetts Institute of Technology
Discussant(s):
Stefano Giglio, Yale University and NBER
Abstract:

Gormsen and Lazarus propose a duration-based explanation for the major equity risk factors, including value, profitability, investment, low-risk, and payout factors. Both in the US and globally, these factors invest in firms that earn most of their cash flows in the near future. The factors could therefore be driven by a premium on near-future cash flows. The researchers test this hypothesis using a new dataset of single-stock dividend futures, which are claims on annual dividends for individual firms. Consistent with their hypothesis, risk-adjusted returns are higher on near- than on distant-future cash flows. In addition, the returns on individual cash flows do not vary across firms once controlling for maturity.

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Don't Take Their Word For It: The Misclassification of Bond Mutual Funds
Author(s):
Huaizhi Chen, University of Notre Dame
Lauren Cohen, Harvard University and NBER
Umit Gurun, University of Texas at Dallas
Discussant(s):
Yiming Ma, Columbia University
Abstract:

Chen, Cohen, and Gurun provide evidence that bond fund managers misclassify their holdings, and that these misclassifications have a real and significant impact on investor capital flows. In particular, many funds report more investment grade assets than are actually held in their portfolios to important information intermediaries, making these funds appear significantly less risky. This results in pervasive misclassification across the universe of US fixed income mutual funds. The problem is widespread - resulting in up to 31.4%of funds being misclassified with safer profiles, when compared against their true, publicly reported holdings. "Misclassified funds" - i.e., those that hold risky bonds, but claim to hold safer bonds -appear to on-average outperform the low-risk funds in their peer groups. Within category groups, "Misclassified funds" moreover receive higher Morningstar Ratings (significantly more Morningstar Stars) and higher investor flows due to this perceived on-average outperformance. However, when Chen, Cohen, and Gurun correctly classify them based on their actual risk, these funds are mediocre performers. These Misclassified funds also significantly underperform precisely when junk-bonds crash in returns. Misreporting is stronger following several quarters of large negative returns.

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Why Does the Fed Move Markets so Much? A Model of Monetary Policy and Time-Varying Risk Aversion
Author(s):
Carolin Pflueger, University of Chicago and NBER
Gianluca Rinaldi, Harvard University
Discussant(s):
Howard Kung, London Business School
Abstract:

Pflueger and Rinaldi build a new model integrating a work-horse New Keynesian model with investor risk aversion that moves with the business cycle. They show that the same habit preferences that explain the equity volatility puzzle in quarterly data also naturally explain the large high frequency stock response to Federal Funds rate surprises. In the model, a surprise increase in the short-term interest rate lowers output and consumption relative to habit, thereby raising risk aversion and amplifying the fall in stocks. The model explains the positive correlation between changes in breakeven inflation and stock returns around monetary policy announcements with long-term inflation news.

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This paper was distributed as Working Paper 27856, where an updated version may be available.

Retail Financial Innovation and Stock Market Dynamics: The Case of Target Date Funds
Author(s):
Jonathan A. Parker, Massachusetts Institute of Technology and NBER
Antoinette Schoar, Massachusetts Institute of Technology and NBER
Yang Sun, Brandeis University
Discussant(s):
John Y. Campbell, Harvard University and NBER
Abstract:

The rise of Target Date Funds (TDFs) has moved a significant share of retail investors into contrarian trading strategies that rebalance between stocks and bonds so as to maintain age-appropriate portfolio shares. Parker, Schoar, and Sun show that i ) TDFs actively rebalance within a few months following differential asset-class returns to maintain stable portfolio shares, ii ), this rebalancing drives contrarian rebalancing flows across funds held by TDFs, iii ) investors do not move funds into or out of TDFs to offset these flows, and iv) these flows impact the prices of stocks. Across otherwise similar stocks, those with higher (indirect) TDF ownership experience lower returns after higher market-wide performance, a results that holds when looking only at variation in TDF ownership driven by S&P index inclusion. Consistent with this price impact, the stock market exhibits more reversion at the monthly frequency during the recent TDF era. Together, Parker, Schoar, and Sun's results suggest that continued growth in TDFs may affect return dynamics and the relation between stock and bond returns.

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This paper was distributed as Working Paper 28028, where an updated version may be available.

Participants

Simona Abis, Columbia University
Rob Arnott, Research Affiliates
Gurdip Bakshi, University of Maryland
Simcha Barkai, Boston College
Yixin Chen, University of Rochester
Zhongtian Chen, University of Pennsylvania
Thummim Cho, London School of Economics
Randolph B. Cohen, Harvard University
Thomas J. Gilbert, University of Washington
Christopher M. Hrdlicka, University of Washington
Sophia Hua, University of Pennsylvania
Eben Lazarus, Massachusetts Institute of Technology
Yiming Ma, Columbia University
Indrajit Mitra, Federal Reserve Bank of Atlanta
Federico Nucera, Bank of Italy
Claudia Robles Garcia, Stanford University
Riccardo Sabbatucci, Stockholm School of Economics
Gill Segal, University of North Carolina at Chapel Hill
Jinfei Sheng, University of California Irvine
Andrea Tamoni, Rutgers Business School
Quentin Vandeweyer, University of Chicago
Michela Verardo, London School of Economics
Theresa Whitmarsh, Washington State Investment Board

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