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Keywords Measuring sentiment; Machine learning; Earnings calls; 10-Ks; WSJ Abstract Our paper relies on stock price reactions to colour words, in order to provide new dictionaries of positive and negative words in a finance context. We extend the machine learning algorithm of Taddy (2013), adding a cross-validation layer to avoid over-fitting. In head-to-head comparisons, our dictionaries outperform the standard bag-of-words approach (Loughran and McDonald, 2011) when predicting stock price movements out-of-sample. By comparing their composition, word-by-word, our method refines and expands the sentiment dictionaries in the literature. The breadth of our dictionaries and their ability to disambiguate words using bigrams both help to colour finance discourse better. Author Affiliation: (a) University of Colorado Boulder, United States (b) Southern Methodist University, United States (c) Norwegian School of Economics, Norway * Corresponding author. Article History: Received 9 December 2021; Revised 15 November 2022; Accepted 17 November 2022 (footnote)[white star] Dimitris Papanikolaou was the editor for this paper. We thank Simona Abis (discussant), Will Cong, Tony Cookson, Gerard Hoberg (discussant), Byoung-Hyoun Hwang (discussant), Jim Martin, David Stolin (discussant), Chenhao Tan, and Brian Waters for comments on an early draft, as well as seminar participants at Indiana University, INSEAD, the CU Boulder CS-NLP lab, the CU Boulder Finance division, the FutFinInfo webinar, NHH Finance brown bag, the 2021 FMA conference, the 2021 SFS Cavalcade, The Third Toronto Fintech Conference, the 2020 European Finance Association meetings, and the Michigan State University Fall 2019 conference. This work utilized the RMACC Summit supercomputer, which is supported by the National Science Foundation (Awards ACI-1532235 and ACI-1532236), the University of Colorado Boulder, and Colorado State University. The Summit supercomputer is a joint effort of the University of Colorado Boulder and Colorado State University. Byline: Diego García [http://leeds-faculty.colorado.edu/garcia/] (*,a), Xiaowen Hu [https://www.smu.edu/cox/Our-People-and-Community/Faculty/Xiaowen-Hu] (b), Maximilian Rohrer [https://www.maxrohrer.com] (c)

Keywords Asymmetric information; Welfare; Consumer credit; Fintech; Experiment Abstract Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show how exogenous variation in interest rates can be used to estimate borrower demand and lender cost curves and recover implied welfare losses. While asymmetric information generates large equilibrium price distortions, we find only small overall welfare losses, particularly for high-credit-score borrowers. Author Affiliation: (a) Northwestern University, Kellogg School of Management, 2211 Campus Drive, Evanston, IL 60208, USA (b) London School of Economics, Houghton St, London WC2A 2AE, United Kingdom (c) University of Chicago, Booth School of Business, 5807 S Woodlawn Ave, Chicago, IL 60637, USA (d) National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA 02138, USA * Corresponding author. Article History: Received 17 April 2022; Revised 30 August 2022; Accepted 1 September 2022 (footnote)[white star] Toni Whited was the editor for this article. We thank Isha Agarwal, Scott Baker, Effi Benmelech, Greg Buchak, Doug Diamond, Jason Donaldson, Liran Einav, Arpit Gupta, Zhiguo He, José Ignacio Cuesta, Sasha Indarte, Dirk Jenter, Gregor Matvos, Filippo Mezzanotti, Holger Mueller, Daniel Paravisini, Raghu Rajan, Amir Sufi, Toni Whited, Susan Woodward, Kairong Xiao, Anthony Zhang, Yiwei Zhang and numerous other colleagues for helpful conversations, comments, and suggestions. We are also grateful for comments from seminar and conference participants at the Boulder Summer Conference on Consumer Financial Decision Making, University of Chicago (Booth), Columbia Business School, Copenhagen Business School, Harvard University (HBS), the Hong Kong University of Science and Technology Business School, IDC Herzliya Arison School of Business, the London School of Economics, the Midwest Finance Association, the Moscow Higher School of Economics, the NBER Corporate Finance Spring Meeting, Norges Bank, Northwestern University (Kellogg), the Philadelphia Federal Reserve Bank, the RCFS Winter Conference, the Red Rock Finance Conference, Stanford Business School, the Stanford Institute for Theoretical Economics (SITE) Financial Regulation session, University of Michigan (Ross), University of Pennsylvania (Wharton), and Washington University in St. Louis. Yannelis gratefully acknowledges financial support from the Booth School of Business at the University of Chicago. The experiment we study in this paper has been registered with the AEA RCT Registry (RCT ID: AEARCTR-0008183), available at https://www.socialscienceregistry.org/trials/8183. Byline: Anthony A. DeFusco [anthony.defusco@kellogg.northwestern.edu] (*,a,d), Huan Tang (b), Constantine Yannelis (c,d)

Keywords Empirical methods; Count data; Poisson regression Abstract This paper assesses different econometric approaches to working with count-based outcome variables and other outcomes with similar distributions, which are increasingly common in corporate finance applications. We demonstrate that the common practice of estimating linear regressions of the log of 1 plus the outcome produces estimates with no natural interpretation that can have the wrong sign in expectation. In contrast, a simple fixed-effects Poisson model produces consistent and reasonably efficient estimates under more general conditions than commonly assumed. We also show through replication of existing papers that economic conclusions can be highly sensitive to the regression model employed. Author Affiliation: (a) University of Texas at Austin, McCombs School of Business Austin, TX, United States (b) University of Houston, Bauer College of Business Houston, TX, United States (c) University of Georgia, Terry College of Business, Athens, GA, United States * Corresponding author. Article History: Received 11 April 2022; Revised 10 August 2022; Accepted 12 August 2022 Byline: Jonathan B. Cohn [jonathan.cohn@mccombs.utexas.edu] (a), Zack Liu [zliu@bauer.uh.edu] (b), Malcolm I. Wardlaw [malcolm.wardlaw@uga.edu] (*,c)

Keywords Inequality; Bankruptcy; Climate change; Natural disaster; FEMA; SBA Abstract Outside of flood hazard zones, households must decide whether to insure or rely on disaster assistance to manage flood risk. We use the quasi-random flooding generated by Hurricane Harvey, which hit Houston in August 2017, to understand the implications of flood losses for households with differing access to insurance and credit. Outside the floodplain, credit-constrained homeowners experience a 20% increase in bankruptcies and a 13% increase in the share of debt in severe delinquency in flooded blocks relative to non-flooded areas. Treatment effects are universally insignificant inside the floodplain, implying that flood insurance mitigates the financial impact of flooding across the credit distribution. Disaster assistance, on the other hand, does not appear to counteract the role of initial inequalities on post-disaster credit outcomes. We find SBA disaster loans and, more surprisingly, FEMA grants to both be regressive in allocation. Our results highlight that averages mask important heterogeneity after disasters, which challenges existing narratives of how effectively Federal disaster programs mitigate the financial burden of natural disasters. Author Affiliation: (a) Finance Department, Leeds School of Business, University of Colorado Boulder, 995 Regent Dr, Boulder, CO 80309, USA (b) Federal Reserve Bank of St. Louis, Institute for Economic Equity, USA * Corresponding author at: Finance Department, Leeds School of Business, University of Colorado Boulder, 995 Regent Dr, Boulder, CO 80309, USA. Article History: Received 1 October 2021; Revised 29 November 2021; Accepted 29 November 2021 (footnote)[white star] Toni Whited was the editor for this article. For their valuable feedback, we thank Asaf Bernstein, Ben Collier, Tony Cookson, Justin Gallagher, John Lynch, Sarah Miller, Amiyatosh Purnandam, Tess Scharlemann, Toni Whited, two anonymous referees, as well as representatives at FEMA and SBA. This paper benefited from discussions with participants at the Urban Economics Association meetings, Midwest Finance Association meetings, Federal Reserve Data Research Conference, University of Colorado, University of Michigan, APPAM, AREUEA, MFA, Summer Conference on Consumer Financial-Decision Making. The views expressed in these papers are solely those of the authors and do not reflect the views of the Federal Reserve Bank of St. Louis or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. No statements here should be treated as legal advice. Byline: Stephen B. Billings [stephen.billings@Colorado.edu] (a), Emily A. Gallagher [emily.a.gallagher@colorado.edu] (*,a,b), Lowell Ricketts [lowell.r.ricketts@stls.frb.org] (b)

Keywords Corporate culture; Values; Norms; Leadership; Corporate governance; Incentive compensation; Informal institutions; Intangible assets; Risk-taking; Myopia; Innovation; Firm value; Productivity; M&A valuation; Integrity; Trust; Ethics; Compliance; Earnings management; Intrinsic motivation Abstract Ninety-two percent of the 1348 North American executives we survey believe that improving corporate culture would increase firm value. A striking 84% believe their company needs to improve its culture. But how can that be achieved? Our paper provides some guidance by documenting the following: executives' views on what corporate culture is and how it operates, distinguishing between stated values and everyday norms; the extent to which culture is perceived to influence value creation (productivity, mergers), ethical choices (compliance, short-termism), and innovation (creativity, risk-taking); and a list of obstacles that can prevent culture from being where it should be (inattentive leaders, misaligned incentive compensation). Finally, we provide evidence that the executives' survey responses are consistent with external data. Author Affiliation: (a) Duke University, Durham, NC, 27708 USA (b) National Bureau of Economic Research, Cambridge, MA, 02138 USA (c) Santa Clara University, Santa Clara, CA, 95053 USA (d) Columbia Business School, New York, NY, 10027 USA * Corresponding author at: Finance Department, Fuqua School of Business, Duke University, 100 Fuqua Drive, Durham, NC 27708, USA. Article History: Received 26 June 2019; Revised 27 July 2022; Accepted 27 July 2022 (footnote)[white star] Toni Whited and Bill Schwert were the editors for this article. We thank CFO magazine, Fuqua's Center on Leadership and Ethics (COLE), and Columbia Business School External Relations for their partnership in conducting the survey; the results presented herein do not necessarily reflect their views. We are especially grateful to our research team of 61 RAs who helped transcribe interviews, discover CXO emails, send personal invitations to participants, classify responses, and check tables. We thank the following people for providing helpful feedback on the survey instrument: Sigal Barsade, Charles Calomiris, John Core, Cesare Fracassi, Paul Ingram, Simi Kedia, Hamid Mehran, Thomas Noone, Susan Ochs, Charles O'Reilly, and Suraj Srinivasan. We thank an anonymous referee, Alon Brav, Francois Brochet, Diego Garcia, Simon Gervais, Marina Niessner, Kelly Shue, David Yermack, Luigi Zingales, workshop participants at American Finance Association Meetings, Utah Winter Finance Conference, American Accounting Association Meetings, NBER Summer Institute, Tel Aviv Finance Conference, Conference on Financial Economics and Accounting, Mountain Finance Conference, Journal of Accounting and Economics/Federal Reserve Bank of New York Conference, International Atlantic Economic Society Conference, Duke University, University of Virginia, Rice University, Yale University, Aalto University, Hanken School of Economics, Washington University in St. Louis, University of Illinois, Indian School of Business, Temple University, Rutgers University, Norges Bank, Baruch College, and Fordham University for their helpful comments on earlier drafts of the paper. Replication data can be downloaded at https://dataverse.harvard.edu/dataverse/corporateculturesurveydata Byline: John R. Graham [john.graham@duke.edu] (*,a,b), Jillian Grennan [jgrennan@scu.edu] (c), Campbell R. Harvey [cam.harvey@duke.edu] (a,b), Shivaram Rajgopal [sr3269@gsb.columbia.edu] (d)

Keywords Predictive regression bias; Standard error bias; Out of sample R2 Abstract Analogous to , this paper derives the small sample bias of estimators in J-horizon predictive regressions, providing a closed-form solution in terms of the sample size, horizon and persistence of the predictive variable. For large J, the bias is linear in J/T with a slope that depends on the predictive variable's persistence. The paper offers a number of other useful results, including (i) important extensions to the original setting, (ii) closed-form bias formulas for popular alternative long-horizon estimators, (iii) out-of-sample analysis with and without bias adjustments, along with new interpretations of out-of-sample statistics, and (iv) a detailed investigation of the bias of the overlapping estimator's standard error based on the methods of Hansen and Hodrick (1980) and Newey and West (1987). The small sample bias adjustments substantially reduce the magnitude of long-horizon estimates of predictability. Author Affiliation: (a) Arison School of Business, Reichman University and AQR Capital Management (consultant), United States (b) AQR Capital Management, United States (c) Stern School of Business, NYU, NBER and AQR Capital Management (consultant), 44 West 4th St, New York, NY 10012, United States * Corresponding author. Article History: Received 27 July 2021; Revised 2 September 2021; Accepted 2 September 2021 (footnote) AQR Capital Management is a global investment management firm, which may or may not apply similar investment techniques or methods of analysis as described herein. The views expressed here are those of the authors and not necessarily those of AQR. Bill Schwert and Toni Whited were the editors for this article. We are especially indebted to the referee's comments. We would also like to thank Yakov Amihud, Don Andrews, Jordan Brooks, John Campbell, John Cochrane, Rob Engle, Esben Hedegaard, Erik Hjalmarsson, Bob Hodrick, Cliff Hurvich, Raymond Kan, Bryan Kelly, Ralph Koijen, Andy Lo, Lasse Pedersen, Rob Stambaugh, Jim Stock, and seminar participants at the AQR Research Colloquium and NYU Stern School for helpful comments and suggestions. Byline: Jacob Boudoukh (a), Ronen Israel (b), Matthew Richardson [mrichar0@stern.nyu.edu] (c,*)

Keywords Cross-sectional variation in risk premia; Instability risk factor; Industry and style portfolios; Bayesian analysis Abstract We apply a new methodology for identifying pervasive and discrete changes ('breaks') in cross-sectional risk premia. Size, value, and investment risk premia have fallen off to the point where they are insignificantly different from zero at the end of the sample period. The market risk premium has also declined systematically over time but remains significant and positive as do the momentum and profitability risk premium. We construct a new instability risk factor from cross-sectional differences in individual stocks' exposure to time-varying risk premia and show that this factor earns a premium comparable to that of commonly used risk factors. Author Affiliation: (a) Federal Reserve Board, Constitution Avenue and 20th Street NW, Washington, DC 20551, USA (b) Rady School of Management, University of California, San Diego, Otterson Hall, Room 4S146, 9500 Gilman Drive #0553, La Jolla, CA 92093-0553, USA * Corresponding author. Article History: Received 3 May 2021; Revised 24 June 2021; Accepted 22 July 2021 (footnote)[white star] Bill Schwert was the editor for this article. We thank the editor and an anonymous referee for many constructive comments and suggestions on the paper. We are grateful for suggestions on an early version of this paper from Bryan Kelly, Dacheng Xiu, and seminar participants at the 2018 SoFiE Summer School at the University of Chicago and the March 2019 UK Inquire Group meeting in Windsor. We are also grateful for comments from Gurdip Bakshi, as well as conference and seminar participants at the North American Winter Meeting of the Econometric Society 2021, the SoFiE 2021 meetings, the Stanford Institute for Theoretical Economics 2021, Boston University, and Temple University. Linyan Zhu provided excellent research assistance. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Disclaimer: The views expressed in this paper are those of the authors and do not necessarily reflect the views and policies of the Board of Governors or the Federal Reserve System. Byline: Simon C. Smith [simon.c.smith@frb.gov] (a), Allan Timmermann [atimmermann@ucsd.edu] (*,b)

Keywords Financing constraints; Entrepreneurship; Home equity; Mortgage Abstract We exploit a mortgage reform that differentially unlocked home equity across the Danish population and study how this impacted selection into entrepreneurship. We find that increased entry was concentrated among entrepreneurs whose firms were founded in industries where they had no prior work experience. Nevertheless, we find that marginal entrants benefiting from the reform had higher pre-entry earnings and a significant share of these entrants started longer-lasting firms. Our results are most consistent with a view that housing collateral enabled higher ability individuals with less-well-established track records to overcome credit rationing and start new firms, rather than only leading to 'frivolous entry' by those without prior industry experience. Author Affiliation: (a) Danmarks Nationalbank, Langelinie Allé 47, DK-2100 Copenhagen Ø, Denmark (b) Department of Economics (CEBI), University of Copenhagen, Øster Farimagsgade 5, building 26, DK-1353 Copenhagen K, Denmark (c) Department of Finance, Imperial College Business School, Exhibition Road, London SW7 2AZ, United Kingdom * Corresponding author. Article History: Received 12 August 2020; Revised 25 May 2021; Accepted 9 July 2021 (footnote)[white star] Toni Whited was the editor for this paper. We are extremely grateful to Manuel Adelino, Joan Farre-Mensa, Kristopher Gerardi, Erik Hurst, Raj Iyer, Bill Kerr, Chris Hansman, Renata Kosova, Francine Lafontaine, Josh Lerner, Ross Levine, Gustavo Manso, Matt Notowidigdo, Alex Oettl, Tarun Ramadorai, David Robinson, Matt Rhodes-Kropf, Martin Schmalz, Antoinette Schoar, Elvira Sojli, David Sraer, Peter Thompson and the seminar participants at the NBER summer institute, NBER productivity lunch, Imperial College London, ISNIE conference, Georgia Tech, UC Berkeley, University of Cambridge, University of Copenhagen, University of Southern Denmark, University of Mannheim, Goethe University, OECD, Paris School of Economics, Tilburg University and Rotterdam School of Management for helpful comments. The research presented in this paper is supported by Center for Economic Behavior and Inequality (CEBI), a center of excellence at the University of Copenhagen financed by grant DNRF134 from the Danish National Research Foundation, and by funding from the Danish Council for Independent Research, the Danish Economic Policy Research Network - EPRN, the Kauffman Foundation and the Division of Research and Faculty Development at the Harvard Business School. Leth-Petersen is research fellow at the Danish Finance Institute. Byline: Thais Laerkholm Jensen [tlj@nationalbanken.dk] (a), Søren Leth-Petersen [soren.leth-petersen@econ.ku.dk] (b), Ramana Nanda [ramana.nanda@imperial.ac.uk] (*,c)

Keywords Employment risk; Consumption; Insurance Abstract Using new employer-employee matched data, this paper investigates the impact of uncertainty, as measured by idiosyncratic stock market volatility, on individual outcomes. We find that firms provide at best partial insurance to their workers. Increased firm-level uncertainty reduces total compensation, especially variable pay, and workers reduce their durable goods consumption in response. Such shocks also lead to greater financial fragility among lower-income earners. Constructing a new county-level uncertainty shock, we find that local uncertainty shocks reduce county-level durable consumption. Taken together, these findings show that uncertainty shocks can significantly affect local economic activity through households' consumption and savings decisions. Author Affiliation: (a) Harvard Business School and NBER, United States (b) UC Berkeley Haas Business School and NBER, United States (c) USC Marshall Business School, United States (d) J. Mack Robinson College of Business, Georgia State University, United States (e) Federal Reserve Bank of Philadelphia, United States * Corresponding author. Article History: Received 26 January 2022; Revised 31 March 2022; Accepted 31 March 2022 (footnote)[white star] This paper supersedes an earlier paper titled 'Household Credit and Local Economic Uncertainty.' We want to thank Equifax Inc. for access to anonymized credit bureau data on borrowers including loan and payment amounts, plus anonymized employment and income information for a sample of borrowers. The views in this paper are those of the authors and do not necessarily reflect those of Equifax Inc., the Federal Reserve Bank of Philadelphia, or the Federal Reserve System. We thank Luigi Pistaferri, Jonathan Berk, Darrell Duffie, Scott Baker, Indraneel Chakraborty, Steve Davis, Harry DeAngelo, Matt Kahn, Jose Fillat, Justin Murfin, Pascal Noel, Anna Orlik, and Luke Stein as well as numerous seminar participants.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Byline: Marco Di Maggio [mdimaggio@hbs.edu] (a), Amir Kermani [kermani@berkeley.edu] (*,b), Rodney Ramcharan [rramchar@marshall.usc.edu] (c), Vincent Yao [wyao2@gsu.edu] (d), Edison Yu [edison.yu@phil.frb.org] (e)

Keywords Cross-listing; Takeover deterrent; Poison pills Abstract This paper tests a theory conjecturing that cross-listing can insulate firms from potential hostile takeovers owing to the increased cost concern of bidders. We find a significant and positive relation between the corporate control threat and the likelihood that firms cross-list in a foreign country. Firms facing takeover threats are more likely to choose hosting countries with greater accounting differences from the US GAAP. Subsample evidence suggests that cross-listing is more likely to be used as an antitakeover device if firms have foreign market exposure or when all-cash offers are less likely. Tests based on quasi-natural experiments provide further support. Author Affiliation: School of Accounting and Finance, The Hong Kong Polytechnic University, Kowloon, Hong Kong * Corresponding author. Article History: Received 18 May 2021; Revised 10 June 2021; Accepted 11 June 2021 (footnote) We thank Bill Schwert (the editor) and an anonymous referee for constructive and insightful comments and suggestions that have significantly improved the paper. We thank Yuan Tao (discussant), Agnes Cheng, Ji-Chai Lin, Jeffery Ng, Qiang Wu, and other seminar participants at The Hong Kong Polytechnic University and Southwestern University of Finance and Economics for their many helpful comments and suggestions. We thank James Nordlund for providing the bootstrapping code. We are grateful for financial support from the Faculty of Business at The Hong Kong Polytechnic University. Byline: Albert Tsang [hl-albert.tsang@polyu.edu.hk] (*), Nan Yang [nyang@polyu.edu.hk], Lingyi Zheng [lingyi.zheng@polyu.edu.hk]

Keywords Stock market participation puzzle; Stock return ignorance; Overoptimism; Financial literacy; Intelligence; Trust Abstract Optimal stock investment decisions rely on assessments of the distribution of expected returns. Using a representative sample, we find over half the US population cannot answer simple questions on expected stock returns. Respondents who are unable to make any return prediction, who cannot answer questions on the distribution of expected returns, or who reveal unlikely distributional beliefs participate less in the stock market and have smaller stock investments. However, overoptimistic investors are more likely to participate in the stock market and have larger stock investments. These results persist after controlling for financial literacy, intelligence, education, and demographics. People who are ignorant about stock return distribution are more likely to invest in equities if they have higher levels of trust. Therefore, trust can substitute for cognition as a factor positively associated with individuals' propensity to invest. Author Affiliation: (a) Monash Business School, Monash University, 900 Dandenong Road, Caulfield East 3145, VIC, Australia (b) Monash Business School, Monash University, Australia * Corresponding author. Article History: Received 15 December 2020; Revised 20 April 2021; Accepted 19 May 2021 (footnote) We thank Ilan Cooper, Neal Galpin, Li Ge, Guy Kaplanski, Evgeny Lyandres, Ron Masulis, Lyndon Moore, Amale Scally, and seminar participants at Curtin University, Monash University, and Swinburne University for their useful comments. Abe de Jong, Amale Scally, and John Watson provided helpful comments on the survey instrument. Special thanks to go to an anonymous referee and to David Hirshleifer (the editor) for their helpful comments. The project described in this paper relies on data from surveys administered by the Understanding America Study (UAS), which is maintained by the Center for Economic and Social Research at the University of Southern California (USC). The content of the paper is solely the responsibility of the authors and does not necessarily represent the official views of USC or UAS. We thank Jill Darling for her help with the panel. The authors acknowledge financial support from the Department of Banking and Finance of Monash Business School. Byline: Yulia Merkoulova [yulia.merkoulova@monash.edu] (a,*), Chris Veld [chris.veld@monash.edu] (b)

Keywords Structural change; Reallocation; Financial frictions Abstract The decline of the U.S. manufacturing share since 1960 has occurred disproportionately during recessions. Using evidence from two natural experiments--the collapse of Lehman Brothers in 2008 and U.S. interstate banking deregulation in the 1980s--I find a role for credit reallocation in explaining this phenomenon by showing that losing access to credit disproportionately hurt manufacturing firms, and that the creation of new credit disproportionately benefited nonmanufacturing firms. These results arise endogenously from a model with technology-driven structural change and fixed costs of establishing new financial relationships. The model suggests an important role for long-run industry trajectories in properly accounting for the costs and benefits of policy interventions in credit markets. Author Affiliation: Federal Reserve Bank of Kansas City, 1 Memorial Drive, Kansas City MO 64108, USA Article History: Received 3 November 2020; Revised 6 May 2021; Accepted 28 May 2021 (footnote)[white star] This is an updated version of the first chapter of my PhD dissertation at the University of Texas at Austin. I would like to thank Toni Whited (the editor) and an anonymous referee for insightful comments that substantially improved the paper. I also thank Olivier Coibion, Saroj Bhattarai, and Aysegül Sahin for their invaluable guidance and support, and I am grateful to Hassan Afrouzi, Wouter den Haan, Kinda Hachem, Alina Kovalenko, Kevin Kuruc, Andi Mueller, Mauricio Ulate, Neil White, and numerous seminar participants for helpful discussions. The views expressed in this paper are those of the author and do not represent those of the Federal Reserve Bank of Kansas City or the Federal Reserve System. Byline: Cooper Howes [cooper.howes@kc.frb.org]

Keywords Flood insurance; Social learning; Peer effects; Social networks Abstract Flooding is the most costly natural disaster faced by US households, yet policymakers are puzzled by the low take-up rates for flood insurance. Leveraging novel transaction-level data, this paper studies the influence of social interactions on households' insurance decisions. I show that households increase flood insurance purchases by 1--5 percent when their geographically distant friends are exposed to flooding events or to campaigns for flood insurance. These exogenous shocks to far-away friends should not affect local households' own insurance decisions except through peer effects. I provide evidence suggesting that social interactions facilitate learning through information dissemination and attention triggering. Author Affiliation: Chinese University of Hong Kong, Shenzhen, China Article History: Received 2 August 2021; Revised 19 February 2022; Accepted 19 February 2022 (footnote)[white star] David Hirshleifer was the editor for this article. I am thankful for the comments of the editor, two anonymous referees, Ashwini Agrawal, Asaf Bernstein (discussant), Tom Chang (discussant), Fabrizio Core, Andreas Fagereng, Francisco Gomes, Juanita González-Uribe, Daniel Gottlieb, Benjamin Guin (discussant), Isaac Hacamo, Bob Hartwig, Dirk Jenter, Ankit Kalda, Peter Koudijs, Dong Lou, Diogo Mendes, Greg Niehaus, Daniel Paravisini, Cameron Peng, Paolo Sodini, Jan Starmans, Per Stromberg, and Su Wang. I am also grateful to seminar and conference participants at the London School of Economics, University of South Carolina, Chinese University of Hong Kong, Chinese University of Hong Kong (Shenzhen), University of Toronto, Stockholm School of Economics, BI Norwegian Business School, SGF Conference 2021, SEHO 2021 Annual Meeting, SFS Cavalcade North America 2021, and WFA 2021, for helpful feedback. This paper was previously circulated under the title 'Salience and Households' Flood Insurance Decisions.' This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Byline: Zhongchen Hu [huzhongchen@cuhk.edu.cn]

Keywords Household finance; Credit expansion; Human Capital; Loan default Abstract This paper studies the link between credit availability and student loan repayment using administrative federal student loan data. We demonstrate that policy-driven changes in credit available to high-default institutions explain almost all of the historical time-series variation in defaults. Between 1981 and 1988, eligibility for federal loans was expanded, leading to the entry of institutions with borrowers more likely to default. From 1988 to 1992, credit access was tightened, leading to the exit of many institutions with high default rates. After 1992, the cycle was repeated, with credit access gradually loosened by unwinding many of the pre-1992 reforms. Author Affiliation: (a) Department of Finance, University of Utah, 1655 East Campus Center Drive, Salt Lake City, UT 84112, United States (b) The Brookings Institution, 1775 Massachusetts Ave NW, Washington, DC 20036, United States (c) University of Chicago Booth School of Business and NBER, 5807 S Woodlawn Ave, Chicago, IL 60637, United States * Corresponding author. Article History: Received 19 October 2020; Revised 12 February 2021; Accepted 18 March 2021 (footnote) The authors wish to thank Nick Bloom, Sylvain Catherine, Raji Chakrabarti, Michael Dinerstein, Darrell Duffie, Jean Helwege, Dan Herbst, Sabrina Howell, Caroline Hoxby, Adam Isen, Donghoon Lee, Neale Mahoney, John Mondragon, Holger Mueller, Taylor Nadauld, Miguel Palacios, Daniel Paravisini, Rob Richmond, Maxime Roy, Amir Sufi, Wilbert van der Klaauw, Emil Verner, David Wessel and Toni Whited for helpful comments and discussions, as well as seminar participants at the NBER Economics of Education, NBER Household Finance Summer Institute Workshop, the University of Michigan Ross School of Business, the Columbia Workshop in New Empirical Finance, the SFS Cavalcade, the Western Finance Association, the University of Chicago Booth School of Business, the New York University Stern School of Business, the University of Illinois Gies College of Business, the Penn State Smeal College of Business, the Federal Reserve Bank of New York, the Federal Reserve Board of Governors, the BYU Marriott School of Business, the Midwest Finance Association, the JPMorgan Chase Institute Conference on Economic Research, the University of Calgary Haskanye School of Business, and the University of Miami Business School. We are grateful to Katerina Nikalexi, Greg Tracey, George Voulgaris, Jun Xu and Emily Zhang for excellent research assistance. Adam Looney gratefully acknowledges support for this project from the John and Laura Arnold Foundation. Any views or interpretations expressed in this paper are those of the authors and do not necessarily reflect the views of the Treasury or any other organization. Byline: Adam Looney [adam.looney@eccles.utah.edu] (a,b), Constantine Yannelis [constantine.yannelis@chicagobooth.edu] (c,*)

Keywords Managers; Beliefs; Overprecision; Overextrapolation; Adjustment costs; Reallocation Abstract This paper studies how biases in managerial beliefs affect managerial decisions, firm performance, and the macroeconomy. Using a new survey of US managers I establish three facts. (1) Managers are not overoptimistic: sales growth forecasts on average do not exceed realizations. (2) Managers are overprecise: they underestimate future sales growth volatility. (3) Managers overextrapolate: their forecasts are too optimistic after positive shocks and too pessimistic after negative shocks. To quantify the implications, I estimate a dynamic general equilibrium model in which managers of heterogeneous firms use a subjective beliefs process to make forward-looking hiring decisions. Overprecision and overextrapolation lead managers to overreact to firm-level shocks and overspend on adjustment costs, destroying 2.1% to 6.8% of the typical firm's value. Pervasive overreaction leads to excess volatility and reallocation, lowering consumer welfare by 0.5% to 2.3% relative to the rational-expectations equilibrium. These findings suggest overreaction could amplify asset-price and business-cycle fluctuations. Author Affiliation: Instituto Tecnológico Autónomo de México, Mexico Article History: Received 9 April 2020; Revised 18 March 2021; Accepted 14 April 2021 (footnote)[white star] This paper is based on the second chapter of my dissertation at Stanford University. I thank my advisers Nick Bloom, Monika Piazzesi, Amit Seru, Pete Klenow, and Juliane Begenau for their invaluable guidance. I also received helpful comments from Adrien Auclert, Katy Bergstrom, Steve Davis, William Dodds, Paul Dolfen, Ricardo de la O, Alex Fakos, Bob Hall, Charles Hodgson, Eran Hoffmann, Pablo Kurlat, Sean Myers, Christopher Palmer, Bobby Pakzad-Hurson, Alessandra Peter, Nicola Pierri, Martin Schneider, Stephen Terry, Toni Whited (the editor), and an anonymous referee. I thank David Altig, Brent Meyer, and Nicholas Parker at the Atlanta Fed for access to data from the Survey of Business Uncertainty. I gratefully acknowledge financial support from: Asociación Mexicana de Cultura A.C.; the Ewing Marion Kauffman Foundation; the B.F. Haley and E.S. Shaw Fellowship for Economics via SIEPR; and the Stanford Institute for Research in the Social Sciences. All errors are my own, and the contents of this paper are solely my responsibility. Byline: Jose Maria Barrero [http://www.jmbarrero.com]

Keywords Stock market; Value added; Listing; Market capitalization; Employment Abstract Publicly traded firms contribute less to total nonfarm employment and GDP now than in the 1970s. Major reasons for this development are the decline of manufacturing, the shift towards more production abroad in manufacturing, and the growth of the service economy as firms providing services are less likely to be listed on exchanges. A firm's stock market capitalization is much less instructive about its employment now than earlier. Market capitalizations have not become systematically less informative about firms' contribution to GDP. Listed stock market superstars account for less employment than they did in the 1970s. Author Affiliation: (a) Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260, USA (b) Fisher College of Business, The Ohio State University, 2100 Neil Avenue, Columbus, OH, USA (c) National Bureau of Economic Research, Cambridge, MA 02138, USA (d) European Corporate Governance Institute, 1000 Brussels, Belgium * Corresponding author. Article History: Received 26 January 2021; Revised 30 March 2021; Accepted 6 April 2021 (footnote) This paper is a revision of the paper titled: 'Has the stock market become less representative of the economy?' We thank Leandro Sanz for excellent research assistance. We are grateful for comments from an anonymous referee and from Harry DeAngelo, Craig Doidge, Sinan Gokkaya, Andrei Gonçalves, Andrei Shleifer, and seminar participants at Ohio State, Tulane, and Wharton. Byline: Frederik P. Schlingemann [schlinge@katz.pitt.edu] (a,d), René M. Stulz [stulz.1@osu.edu] (b,c,d,*)

Keywords Trade credit; Supply chains; Production networks; Profitability Abstract We construct a sample of over 200,000 supply chains between 2003 and 2018 to conduct a chain-based analysis of trade credit. Our study uncovers novel stylized facts about trade credit both within and across supply chains. More upstream firms borrow more from suppliers, lend more to customers, and hold more net trade credit. This upstreamness effect in trade credit is weaker for more profitable firms and for longer chains. Firms in more central or more profitable chains provide more net trade credit. Our results are generally consistent with the recursive moral hazard theory of trade credit. Evidence for the financing advantage theory is mixed. Author Affiliation: (a) Simon Business School, University of Rochester, Rochester, NY 14627, United States (b) Lundquist College of Business, University of Oregon, Eugene, OR 97403, United States * Corresponding author. Article History: Revised 4 March 2021; Accepted 10 March 2021 (footnote)[white star] We are grateful to an anonymous referee for comments and suggestions. This paper was previously circulated under the title 'Profitability, Trade Credit and Institutional Structure of Production.' The paper has benefited from discussions with Timothy Conley, Douglas Diamond, Briana Chang, Milton Harris, Alon Kalay, Anil Kashyap, Roni Kisin, Mathias Kronlund, Asaf Manela, Gregor Matvos, Alan Moreira, Daniel Quint, Raghuram Rajan, Shastri Sandy, Alexi Savov, Amit Seru, Hyun Shin, Luigi Zingales, and from comments at presentations at the University of Chicago, UW-Madison, and the AEA 2012 Meetings. All remaining errors are our own. Byline: Michael Gofman [michael.gofman@simon.rochester.edu] (*,a), Youchang Wu [ywu2@uoregon.edu] (b)

Keywords GSIB surcharges; Basel III regulation; Bank capital requirements; Bank lending Abstract Capital surcharges on global systemically important banks (GSIBs) decrease lending to firms but do not have any real effects. Banks subject to higher surcharges reduce loan commitments relative to other banks and also lower their estimates of firm risk. Firms' total borrowing, however, does not fall, as firms switch to other banks. We establish these results using supervisory data on corporate loans and variation in surcharges in the United States. These results contribute to the debate on the costs and benefits of surcharges and regulatory tailoring and their effects on the reallocation of credit supply across financial institutions. Author Affiliation: (a) Division of Monetary Affairs, Board of Governors of the Federal Reserve System, Washington DC, 20551, USA (b) Division of Research and Statistics, Board of Governors of the Federal Reserve System, Washington DC, 20551, USA * Corresponding author. Article History: Received 7 October 2019; Revised 20 October 2020; Accepted 23 December 2020 (footnote) We thank an anonymous referee for detailed and constructive feedback on the paper. We also thank our conference discussants Viral Acharya, Adam Ashcraft, Klaus Schaeck, and Gregor Weiss as well as Nate Cooper, Sergio Correia, Scott Frame, Holly Kirkpatrick, Eric Rosengren, Kasper Roszbach, Skander van den Heuvel, and seminar participants at the 2019 Bank of Mexico 3rd Conference on Financial Stability, 2019 Norges Bank Conference The Costs and Benefits of Financial Regulation, the Columbia University/Bank Policy Institute 2020 Bank Regulation Research Conference, the 2020 Impact of Post-Crisis Regulation on Financial Markets Conference at the Federal Reserve Bank of Philadelphia, the 2021 Bristol Workshop on Banking and Financial Intermediation, and the Federal Reserve Board for comments. The views expressed in this paper are those of the authors and do not necessarily represent those of the Federal Reserve Board or the Federal Reserve System. Byline: Giovanni Favara [giovanni.favara@frb.gov] (a,*), Ivan Ivanov [ivan.t.ivanov@frb.gov] (b), Marcelo Rezende [marcelo.rezende@frb.gov] (b)

Keywords Continuous time contracting; Multiple tasks; Delegated investment; Managerial compensation; Investment dynamics Abstract We study non-contractible intangible investment in a dynamic agency model with multitasking. The manager's short-term task determines current performance, which deteriorates with investment in the firm's future profitability, his long-term task. The optimal contract dynamically balances incentives for short- and long-term performance. Investment is distorted upwards (downwards) relative to first-best in firms with high (low) returns to investment. These distortions decrease as good performance relaxes endogenous financial constraints, implying negative (positive) investment-cash flow sensitivities. Our results shed light on how corporate investment policies, liquidity management, and executive compensation structure differ across industries with different returns to intangible investment. Author Affiliation: (a) KU Leuven, Faculty of Economics and Business, Leuven 3000, Belgium (b) Erasmus University Rotterdam, Rotterdam 3062 PA, the Netherlands * Corresponding author. Article History: Received 20 March 2017; Revised 27 September 2020; Accepted 31 October 2020 (footnote)[white star] This paper benefited significantly from comments by the co-editor Ron Kaniel, and an anonymous referee. We also thank Patrick Bolton, Wei Cui (CICF discussant), Guido Friebel, Sebastian Gryglewicz, Roman Inderst, Peter Kondor, Christian Leuz, Stephan Luck, Thomas Mariotti, Konstantin Milbradt (AFA discussant), Jean-Charles Rochet, Paul Schempp, Vladimir Vladimirov, Neng Wang, John Zhu, and conference and seminar participants at AFA Boston, CICF Shanghai, Columbia Business School, Erasmus School of Economics, Frankfurt School of Finance and Management, Stockholm School of Economics, Tilburg University, University of Amsterdam, University of Bonn, and University of Zürich for helpful comments. An earlier version of this paper has been circulated under the title 'A Dynamic Agency Theory of Delegated Investment.' Hoffmann gratefully acknowledges financial support from Internal Funds KU Leuven (STG/20/033). Pfeil gratefully acknowledges financial support by the University Research Priority Program 'FinReg' of the University of Zürich. Byline: Florian Hoffmann [florian.hoffmann@kuleuven.be] (a), Sebastian Pfeil [pfeil@ese.eur.nl] (b,*)

Keywords Climate change; Carbon emissions; ESG; Big three; Shareholder activism; Institutional ownership Abstract This paper examines the role of the 'Big Three' (i.e., BlackRock, Vanguard, and State Street Global Advisors) on the reduction of corporate carbon emissions around the world. Using novel data on engagements of the Big Three with individual firms, we find evidence that the Big Three focus their engagement effort on large firms with high CO.sub.2 emissions in which these investors hold a significant stake. Consistent with this engagement influence being effective, we observe a strong and robust negative association between Big Three ownership and subsequent carbon emissions among MSCI index constituents, a pattern that becomes stronger in the later years of the sample period as the three institutions publicly commit to tackle Environmental, Social, and Governance (ESG) issues. Author Affiliation: (a) IESE Business School, School of Economics and Business, University of Navarra & CEPR, Avenida Pearson 21, Barcelona 08034, Spain (b) IESE Business School, Avenida Pearson 21, Barcelona 08034, Spain (c) IESE Business School, CEPR & ECGI, Avenida Pearson 21, Barcelona 08034, Spain * Corresponding author. Article History: Received 14 July 2020; Revised 26 October 2020; Accepted 17 November 2020 (footnote) We thank Eloy Lanau, Christopher Nance, Vicent Peris, Sergio Ribera, and Claudia Serra for their excellent research assistance. We also thank participants at the 7th International Symposium on Environment and Energy Finance Issues, the Refinitiv seminar on recent advances in CSR research, the 1st UZH Young Researcher Workshop on Climate Finance (University of Zurich), the 18th Paris December Finance Meeting, the ESSEC Amundi Chair Webinar, and the EAA Virtual Annual Congress for helpful comments and suggestions. This paper has also benefited from comments by an anonymous referee, Marco Ceccarelli (discussant), Madison Condon, Alon Kalay, Steven Ongena, Shiva Rajgopal, Alex Wagner, Olivier David Zerbib (discussant), and seminar participants at Bocconi University, Columbia Business School, ESSEC Business School, Luiss Guido Carli University, and Universidad Autonoma de Barcelona. Gaizka Ormazabal thanks the 'Cátedra de Dirección de Instituciones Financieras y Gobierno Corporativo del Grupo Santander,' the BBVA Foundation (2016 grant 'Ayudas a Investigadores, Innovadores, y Creadores Culturales'), the Marie Curie and Ramon y Cajal Fellowships, and the Spanish Ministry of Science and Innovation, grant ECO2015--63,711-P. Miguel Duro acknowledges financial assistance from research projects ECO2016--77,579-C3--1-P and PID2019--111143GB-C31, funded by the Spanish Ministry of Economics, Industry, and Competitiveness, and the Ministry of Science and Innovation, respectively. Igor Kadach acknowledges financial assistance from research grant ECO2017--84,016-P, funded by the Spanish Ministry of Science, Innovation, and Universities. Byline: José Azar [jazar@iese.edu] (a), Miguel Duro [mduro@iese.edu] (b), Igor Kadach [ikadach@iese.edu] (b), Gaizka Ormazabal [gormazabal@iese.edu] (c,*)

Keywords Midpoint; Micro-price; Liquidity demand elasticity; Illiquidity; Rule 605 Abstract The effective bid-ask spread measured relative to the spread midpoint overstates the true effective bid-ask spread in markets with discrete prices and elastic liquidity demand. The average bias is 13%--18% for S&P 500 stocks in general, depending on the estimator used as benchmark, and up to 97% for low-priced stocks. Cross-sectional bias variation across stocks, trading venues, and investor groups can influence research inference. The use of the midpoint also undermines liquidity timing and trading performance evaluations, and can lead non-sophisticated investors to overpay for liquidity. To overcome these problems, the paper proposes new estimators of the effective bid-ask spread. Author Affiliation: Stockholm Business School, Stockholm University, Stockholm SE-10691, Sweden Article History: Received 6 December 2019; Revised 29 August 2020; Accepted 27 September 2020 (footnote)1 Björn Hagströmer is at Stockholm Business School, Stockholm University, and a visiting researcher at the Swedish House of Finance. I thank the editor (Bill Schwert), an anonymous referee, Jonathan Brogaard, Petter Dahlström, Thierry Foucault, Jungsuk Han, Peter Hoffmann, Anqi Liu, Albert Menkveld, Lars Nordén, Olga Obizhaeva, Andreas Park, Angelo Ranaldo, Kalle Rinne, Ioanid Rosu, Patrik Sandås, Paul Schultz, Ingrid Werner, and Bart Yueshen, as well as seminar and conference participants at the Bank of America Global Quant Conference, Central Bank Workshop on Market Microstructure, CEPR-Imperial-Plato Market Innovator Conference, ECB, HEC Paris, Lund University, NBIM, the SEC Annual Conference on Financial Regulation, Stockholm Business School, the Swedish House of Finance, University of Luxembourg, and Warwick Frontiers of Finance Conference for helpful comments. I thank Nasdaq and Frank Hatheway for providing the HFT data. Nasdaq makes the data freely available to academics providing a project description and signing a nondisclosure agreement. I am grateful to the Jan Wallander Foundation and the Tom Hedelius Foundation for research funding. A previous version of the paper was circulated under the title Overestimated Effective Spreads: Implications for Investors. Byline: Björn Hagströmer [bjh@sbs.su.se] (1)

Keywords Arbitrage; Liquidity; ADR; Efficiency; Market integration Abstract I study how arbitrage affects liquidity by analyzing several billion trades in the American Depositary Receipt (ADR) market from 2001 to 2016. Price deviations persist, on average, for 12 min, and mainly arise because of price pressure. Impulse response functions estimated at 1 min intervals indicate that a positive shock to arbitrage--simultaneous trades of the ADR and the home-market share in the opposite direction--decreases deviations and bid-ask spreads. I confirm these findings by exploiting institutional details that create exogenous variation in the impediments to arbitrage across days. Overall, these results suggest that arbitrage decreases price pressure and provides liquidity. Author Affiliation: State University of New York at Buffalo, 244 Jacobs Management Center, Buffalo, NY 14260-4000 USA Article History: Received 4 October 2018; Revised 15 September 2020; Accepted 28 September 2020 (footnote)[white star] I thank the editor (Bill Schwert) and an anonymous referee for many valuable suggestions which greatly improved the paper. I also thank Lamont Black, Ekkehart Boehmer, Dion Bongaerts, Jonathan Brogaard, Howard Chan, Tarun Chordia, Ruben Cox, Thierry Foucault, Louis Gagnon, Nicolae Gârleanu, Michael Goldstein, Amit Goyal, Allaudeen Hameed, Terry Hendershott, Shing-yang Hu, Jonathan Kalodimos, Andrew Karolyi, Albert Kyle, Su Li, Albert Menkveld, Pamela Moulton, Maureen O'Hara, Louis Piccotti, Gideon Saar, Piet Sercu, René Stulz, Avanidhar Subrahmanyam, Raman Uppal, Dimitrios Vagias, Mathijs van Dijk, Manuel Vasconcelos, Kumar Venkataraman, Axel Vischer, Avi Wohl, and participants at the 2016 Research in Behavioral Finance Conference (Amsterdam), 2014 FMA (Nashville), the 2014 NFA (Ottawa), the 2014 Asian FA (Bali), 2014 Eastern FA (Pittsburgh), the 2013 Erasmus Liquidity Conference (Rotterdam), the 2013 Conference on the Theories and Practices of Securities and Financial Markets (Kaohsiung), the 2013 World Finance and Banking Symposium (Beijing), and at seminars at Babson College, Cass Business School, City University of Hong Kong, Cornell University, Erasmus University, Frankfurt School Of Management, and the University at Buffalo for valuable comments. I am grateful for the hospitality of the Department of Finance at the Johnson Graduate School of Management (Cornell University), where some of the work on this paper was carried out, especially from my hosts, Andrew Karolyi and Pamela Moulton. This work was carried out on the National e-infrastructure with the support of SURF Foundation. This work is supported in part by NSF ACI-1541215. I thank OneMarket Data for the use of their OneTick software. Byline: Dominik Rösch [drosch@buffalo.edu]

Keywords Options returns; Implied volatility; Straddles; Foreign exchange Abstract We study the cross-section of returns on FX options sorting currencies based on implied volatilities (IVs). Long straddle positions in currencies with low (high) IVs perform well (poorly). A long low IV-short high IV strategy produces large average returns after transaction costs. Total volatility matters rather than any component or transformation of volatility. The returns are distinct from those in the literature on foreign exchange returns or equity option returns and cannot be explained convincingly by standard risk factors. We argue cross-sectional differences in hedging demand combined with limits to arbitrage contribute to mispricing in FX options. Author Affiliation: (a) Bank of England, Threadneedle Street, London EC2R 8AH, UK (b) Commerzbank, 30 Gresham Street, London EC2V 7PG, UK (c) Bayes Business School (formerly Cass), City, University of London, 106 Bunhill Row, London EC1Y 8TZ, UK * Corresponding author. Article History: Received 15 May 2019; Revised 27 July 2020; Accepted 24 August 2020 (footnote)[white star] We are grateful to the editor, Bill Schwert, and the anonymous referee whose comments greatly improved the paper. We thank audiences at Cass Business School, Manchester Business School, Essex Business School, University of Paris Dauphine, Heriot Watt University, and Swansea University, together with Kevin Aretz, Eser Arisoy, Laura Ballotta, Peter Billington, Constantin Bolz, Michael Brennan, Giulia Fantini, Thomas Flury, Divya Goel, Guenter Grimm, Aneel Keswani, Mamdouh Medhat, Nick Motson, Anthony Neuberger, Richard Payne, Ser-Huang Poon, Marco Realdon, Lucio Sarno, Maik Schmeling, and Daniel Trum for helpful comments and discussions. All errors are our own. The views expressed in this document are those of the authors and not those of Commerzbank or the Bank of England. The information contained in is paper may be based on trading ideas where Commerzbank may trade in such financial instruments with customers or other counterparties. Any prices provided herein are historical only, and do not represent firm quotes as to either size or price. The past performance of financial instruments is not indicative of future results. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Byline: Jonathan Fullwood [jonathan.fullwood@bankofengland.co.uk] (a), Jessica James [jessica.james@commerzbank.com] (b,c), Ian W. Marsh [i.marsh@city.ac.uk] (*,c)

Keywords Repo; Clearing house; EMIR; Basel III; Leverage ratio Abstract We analyze the effects of prudential regulation on short-term interest rates. The European Market Infrastructure Regulation (EMIR) induces clearing houses (CCPs) to supply large amounts of cash in reverse repurchase agreements (repos). Basel III, in contrast, disincentivizes the borrowing demand by tightening banks' balance sheet constraints. Using unique regulatory data of CCP investment activity and repo transactions, we find compelling evidence for both the supply and demand channels. The overall effects are decreasing short-term rates and increasing market imbalances in various forms, all of which entail unintended consequences due to the new regulatory framework. Author Affiliation: (a) University of St.Gallen, SBF, Unterer Graben 21, St. Gallen CH-9000, Switzerland (b) Bank of England, Threadneedle Street, London EC2R 8AH, United Kingdom (c) Norges Bank Investment Management, Queensberry House, 3 Old Burlington Street, London W1S 3AE, United Kingdom * Corresponding author. Article History: Received 5 February 2020; Revised 12 August 2020; Accepted 19 August 2020 (footnote)[white star] We are grateful for excellent research assistance from Gerardo Ferrara and valuable comments from Jonathan Acosta-Smith, Christoph Aymanns, Morten Linnemann Bech, Alexander Bechtel, Evangelos Benos, Giovanni Calice, Pavel Chichkanov, Antoine Martin, Sean McGrath, David Murphy, Mariam Harfush-Pardo, Pedro Gurrola-Perez, Russell Jackson, Linda Kirschner, Philipp Lentner, Katia Pascarella, Loriana Pelizzon, Dagfinn Rime, Gary Robinson, Pablo Rovira Kaltwasser, Glenn Schepens, Guillaume Vuillemey and participants of the 2020 AEA Meetings, BCBS/CEPR Workshop on the Impact of Regulation, CARF, Central Bank Workshop on Microstructure of Financial Markets, ECB Money Market Workshop, ESSEC/Banque de France Workshop on OTC Markets, SAFE Market Microstructure Conference, SFI Research Days, and seminars at the Bank of England, Bank of Italy, BI (Oslo), ESCP, LUISS, and the Swiss National Bank. We acknowledge the support of the Bank of England and of the Swiss Institute of Banking and Finance. Angelo Ranaldo also acknowledges financial support from the Swiss National Science Foundation (SNSF grant 182303). An earlier version of this paper was published as Bank of England Staff Working Paper No. 801. The views expressed in this paper are those of the authors, and not those of the Bank of England or Norges Bank Investment Management. Michalis Vasios worked on this paper while he was at the Bank of England. Byline: Angelo Ranaldo [angelo.ranaldo@unisg.ch] (*,a), Patrick Schaffner [patrick.schaffner@protonmail.ch] (a,b), Michalis Vasios [michalis.v@gmail.com] (c)

Keywords Market funding; Leverage; Bank crises Abstract Banks' funding sources have changed significantly during the last two decades. The share of non-core funding (NCF) was high before the 2008 crisis but declined substantially after the crisis. We propose a general equilibrium model where NCF provides insurance against idiosyncratic risks faced by banks. Insurance makes leverage and investment more attractive, but it also increases the vulnerability of the banking sector to crises. We show that learning about the likelihood of a crisis could have been important for generating the observed dynamics of NCF and leverage, which in turn affected the dynamics of the macro-economy. Author Affiliation: (a) ESG UQAM, 315 St. Catherine st. East, Montreal, Quebec, Canada (b) European Central Bank, Monetary Policy Strategy Division, Sonnemannstrasse 20, Frankfurt am Main, Germany (c) Marshall School of Business, University of Southern California, 701 Exposition Boulevard, HOH 715 Los Angeles, CA 90089, United States (d) Peking University, and CEPR, USA (e) Central Bank of Ireland * Corresponding author at: Marshall School of Business, University of Southern California, 701 Exposition Boulevard, HOH 715 Los Angeles, CA 90089, United States. Article History: Received 16 January 2019; Revised 28 May 2020; Accepted 25 June 2020 (footnote)[white star] We would like to thank Juliana Begenau, Tobias Broer, Ester Faia, and Matej Marinc for discussing the paper in various conferences. We would also like to thank Matija Lozej and participants at several conferences and seminars for useful comments and suggestions. Alessandro Barattieri acknowledges financial support from the Einaudi Institute for Economics and Finance (EIEF) Research Grants 2016, and Vincenzo Quadrini from NSF Grant 1460013. The views expressed in this paper do not reflect the views of the ECB, the Central Bank of Ireland, or the European System of Central Banks. All errors are ours. Corresponding author: Vincenzo Quadrini, Byline: Alessandro Barattieri (a), Laura Moretti (b,e), Vincenzo Quadrini [quadrini@usc.edu] (*,c,d)

Keywords Disclosure; Sticky deposits; Financial regulation; Inattention; Switching costs Abstract While popular with policymakers, most evidence on consumer financial disclosure's effectiveness studies borrowing decisions (where optimality is unclear) or lab experiments (where attention is not scarce). We provide field evidence from randomized controlled trials with 124,000 savings account holders at five UK depositories. Treated consumers were disclosed varying degrees of salient information about alternative products, including one with their current provider strictly dominating their current product. Despite switching taking roughly 15 minutes and the moderate average potential gains ($190/year), switching is rare across disclosure designs and depositors. We find pessimistic beliefs drive disclosure inattention and limit disclosure's effectiveness, helping explain deposit stickiness. Author Affiliation: (a) Authority for the Financial Markets, Everard Meijsterlaan 52, Utrecht 3533CN, the Netherlands (b) Competition and Markets Authority, 25 Cabot Square, London E14 4QZ, UK (c) Massachusetts Institute of Technology, NBER, and J-PAL, 100 Main Street, E62-639, Cambridge, MA 02142, USA (d) UBS, 100 Rope Street #5, London SE16 7TQ, UK * Corresponding author. Article History: Received 18 February 2020; Accepted 18 May 2020 (footnote)[white star] For helpful comments, we thank our discussants Xiao Liu, Daniel Martin, and Adair Morse; seminar and conference participants at Advances with Field Experiments 2018 Conference, Boulder Summer Conference on Consumer Financial Decision Making, Central Bank of Ireland, CFPB Research Conference, Chicago Booth, MIT, NBER Summer Institute (Law & Economics; Risks of Financial Institutions), RAND Behavioral Finance Forum, and SITE; and Paul Asquith, Joseph Briggs, Karen Croxson, Peter Ganong, Michael Grubb, Arvind Krishnamurthy, Sheisha Kulkarni, David Laibson, Christian Leuz, Peter Lukacs, Brigitte Madrian, Jeroen Nieboer, Philipp Schnabl, Rodrigo Verdi, and Jonathan Zinman. Matthew Ward and Tim Burrell provided invaluable help with execution. We thank Margarita Alvarez-Echandi, Sam Hughes, Tammy Lee, and Lei Ma for their research assistance. This research was conducted in conjunction with the Financial Conduct Authority, where Adams, Hunt, and Zaliauskas were employed during the trials. The views expressed in this paper are those of the authors and not the Financial Conduct Authority, which has reviewed the paper for human subjects compliance and the release of confidential information. All errors and omissions are the authors' own. This randomized controlled trial (RCT) was registered in the American Economic Association Registry for RCTs under trial number AEARCTR-0004053. Byline: Paul Adams (a), Stefan Hunt (b), Christopher Palmer [cjpalmer@mit.edu] (*,c), Redis Zaliauskas (d)

Keywords Disagreement; Return predictability; PLS; LASSO; Machine learning Abstract Disagreement measures are known to predict cross-sectional stock returns but fail to predict market returns. This paper proposes a partial least squares disagreement index by aggregating information across individual disagreement measures and shows that this index significantly predicts market returns both in- and out-of-sample. Consistent with the theory in Atmaz and Basak (2018), the disagreement index asymmetrically predicts market returns with greater power in high-sentiment periods, is positively associated with investor expectations of market returns, predicts market returns through a cash flow channel, and can explain the positive volume-volatility relationship. Author Affiliation: (a) Lee Kong Chian School of Business, Singapore Management University, 50 Stamford Road, 178899, Singapore (b) School of Finance, Shanghai University of Finance and Economics, 777 Guoding Rd., Shanghai 200433, China (c) School of Business, Hong Kong Baptist University, 34 Renfrew Road, Kowloon Tong, Kowloon, Hong Kong * Corresponding author. Article History: Received 29 August 2019; Revised 26 April 2020; Accepted 27 April 2020 (footnote)[white star] We are grateful to G. William Schwert (the editor) and Seth Pruitt (the referee) for very insightful and helpful comments that improved the paper significantly. We thank Adem Atmaz, Suleyman Basak, Bong-Geun Choi, Liyuan Cui, Zhi Da, Stefano Giglio, Shiyang Huang, Tao Li, Weikai Li, Ye Li, Francis Longstaff, Sungjune Pyun, and Guofu Zhou as well as seminar and conference participants at St. Louis University, Washington University in St. Louis, 2018 Asian Bureau of Finance and Economic Research (ABFER) Annual Conference, 2018 AsianFA Annual Meeting, 2018 City University of Hong Kong International Finance Conference on Corporate Finance and Financial Markets, 2018 Research in Behavioral Finance Conference, and 2018 SMU Finance Summer Camp for insightful comments. Dashan Huang acknowledges that this study was partially funded at the Singapore Management University through a research grant (MSS18B004) from the Ministry of Education Academic Research Fund Tier 1. Byline: Dashan Huang [dashanhuang@smu.edu.sg] (*,a), Jiangyuan Li [lijiangyuan@mail.shufe.edu.cn] (b), Liyao Wang [lywang@hkbu.edu.hk] (c)

Keywords Central bank liquidity; Wholesale funding dry-ups; Short-term funding; Central bank collateral Abstract We analyze the role of loan maturity and collateral eligibility in the transmission of central bank liquidity provisions to banks following a wholesale funding dry-up. We analyze the transmission of the three-year LTRO, which substantially extended the ECB liquidity maturity, in Italy, where banks benefited from a government guarantee program that effectively relaxed the ECB collateral requirements. Combining the national credit register with banks securities holdings, we find that (i) the maturity extension supported banks' credit supply and (ii) banks used most liquidity to buy domestic government bonds and substitute missing wholesale funding, two possibly unstated goals of the intervention. Author Affiliation: (a) Bank of Italy, Via Nazionale 91, Rome 00184, Italy (b) The Federal Reserve Bank of New York, 33 Liberty Street, New York, NY 10025, USA * Corresponding author. Article History: Received 20 August 2018; Revised 1 June 2020; Accepted 30 June 2020 (footnote) We thank Bill Schwert (editor), an anonymous referee, and our discussants Marco Di Maggio, Florian Heider, Matthew Plosser, Umit Gurun, Sven Klinger, David Miles, Camelia Minoiu, Michele Boldrin, and Alessandro Barattieri. We are grateful to Viral Acharya, Philipp Schnabl, Alexi Savov, and Andres Liberman for many helpful comments and also thank Marcello Bofondi, Eduardo Dávila, Tim Eisert, Antonella Foglia, Xavier Gabaix, Gary Gorton, Valentina Michelangeli, Holger Mueller, Stefan Nagel, Stefano Neri, Matteo Piazza, Amiyatosh Purnanandam, Joao Santos, Johannes Stroebel, Toni Whited, Luigi Zingales, and seminar and conference participants at Bank of Italy, NYU Stern, McGill Desautels, ECB, Boston Fed, UCLA Anderson, Michigan Ross, NY Fed, Fordham, Fed Board, AFA, Fifth MoFiR Workshop on Banking, Fourth Workshop in Macro Banking and Finance, Third ECB Forum on Central Banking, 'Credit Solutions for the Real Economy' conference, 'The Impact of Extraordinary Monetary Policy on the Financial Sector' conference, MFM Group Winter 2017 Meeting, Workshop on Empirical Monetary Economics (Sciences Po), 'Banks, Systemic Risk, Measurement and Mitigation' conference, BdP conference on Financial Intermediation, Yale 'Fighting a Financial Crisis' conference, and Oxford-NY Fed Monetary Economics conference for valuable comments. We also thank Alberto Coco, Stefania De Mitri, Roberto Felici, and Nicola Pellegrini for helping us interpret the data and understand the institutional setting. Matteo Crosignani is grateful for the support of the Macro Financial Modeling Group. The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Federal Reserve Bank of New York, the Federal Reserve System, the European Central Bank, the Bank of Italy, or anyone associated with these institutions. All results have been reviewed to ensure that no confidential information is disclosed. All errors are our own. A previous version of this paper circulated as 'The Effect of Central Bank Liquidity Injections on Bank Credit Supply.' First draft: December 2015. Byline: Luisa Carpinelli (a), Matteo Crosignani [matteo.crosignani@ny.frb.org] (*,b)

Keywords Securities; Credit supply; Bank capital; Monetary policy; Reach for yield Abstract Monetary policy transmission may be impaired if banks rebalance their portfolios toward securities. We identify the bank lending and risk-taking channels of monetary policy by exploiting--Italy's unique--credit and security registers. In crisis times, with higher central bank liquidity, less capitalized banks react by increasing securities over credit supply, inducing worse firm-level real effects. However, they buy securities with lower yields and haircuts. Unlike in crisis times, in precrisis times, securities do not crowd out credit supply. The substitution from lending to securities in crisis times helps less capitalized banks repair their balance sheets and restart credit supply with a one-year lag. Author Affiliation: (a) Imperial College London, ICREA-UPF, Barcelona GSE, CREi, CEPR, South Kensington Campus, Exhibition Rd, London SW7 2AZ, UK (b) Luiss University, Universitat Pompeu Fabra, Barcelona GSE, EIEF, CEPR, ECGI, Viale Romania 32, 00197 Rome, Italy (c) Bank of Italy, Via Nazionale 91, 00184 Rome, Italy * Corresponding author. Article History: Received 23 October 2018; Revised 27 April 2020; Accepted 24 May 2020 (footnote) We thank Bo Becker, Patrick Bolton, Markus Brunnermeier, Douglas Diamond, Mark Flannery, Jordi Galí, Emilia Garcia Appendini, Nicola Gennaioli, Peter DeMarzo, Filippo De Marco, Victoria Ivashina, Marco Pagano, Huw Pill, Soledad Martinez Peria, Ricardo Reis, Stefano Rossi, Tano Santos, Amit Seru, Sylvana Tenreyro, Annette Vissing-Jorgensen, David Web, and seminar and conference participants at Berkeley, Stanford, Copenhagen Business School, University of Copenhagen, CREI, Zurich, LSE, Bocconi, Cattolica Milan, IESE, ECB, CFM-LSE Money Macro Workshop, the Barcelona GSE Summer Forum FIR Workshop 2016, St. Gallen, the 'Empirical Monetary Economics Workshop' organized by Sciences Po-Banque de France-Bank of England, the conferences on 'Non-Standard Monetary Policy Measures', and on 'Monetary Policy Pass-Through and Credit Markets' at the ECB, the 42° Simposio de la Asociación Española de Economía, and the DNB-CEPR Conference on 'Bank Equity over the Cycle' for helpful comments and suggestions. The views of this paper are those of the authors and do not represent the views of Banca d'Italia or of the Eurosystem. This paper has been developed through CEPR's Restarting European Long-Term Investment Finance (RELTIF) Program, which is funded by Emittenti Titoli. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 648398). Peydró also acknowledges financial support from the Spanish Ministry of Economy and Competitiveness through grants ECO2012-32434 and ECO2015-68182-P (MINECO/FEDER, UE) and through the Severo Ochoa Program for Centres of Excellence in R&D (SEV-2015-0563). Byline: José-Luis Peydró [jose.peydro@gmail.com] (a,*), Andrea Polo [andreapolo@gmail.com] (b), Enrico Sette [enrico.sette@bancaditalia.it] (c)

Keywords Peer disclosure; Spillover; Product market rivalry; Technology proximity; Social media Abstract This paper provides first evidence of negative peer disclosure (NPD), an emerging corporate strategy to publicize adverse news of industry peers on social media. Consistent with NPDs being implicit positive self-disclosures, disclosing firms experience a two-day abnormal return of 1.6--1.7% over the market and industry. Further exploring the benefits and costs of such disclosures, we find that NPD propensity increases with the degree of product market rivalry and technology proximity and disclosing firms outperform nondisclosing peers in the product markets in the year following NPDs. These results rationalize peer disclosure and extend the scope of the literature beyond self-disclosure. Author Affiliation: (a) J. Mack Robinson College of Business, Georgia State University, 35 Broad St NW, Atlanta, GA 30303, USA (b) Carlson School of Management, University of Minnesota, 321 19th Ave S, Minneapolis, MN 55455, USA (c) Bryan School of Business and Economics, University of North Carolina at Greensboro, 516 Stirling St, Greensboro, NC 27412, USA * Corresponding author. Article History: Received 24 October 2019; Revised 28 May 2020; Accepted 29 May 2020 (footnote) We are grateful for helpful comments from one anonymous referee, Bill Schwert (the editor), Cyrus Aghamolla, Alan Benson, Phil Berger, Beth Blankespoor, Ed deHaan, Shane Dikolli, Alex Edmans, Fabrizio Ferri, Ilan Guttman, Iftekhar Hasan, Mirko Heinle, Allen Huang, Gerry Hoberg, Xu Jiang, Jinhwan Kim, S.P. Kothari, Charles Lee, Tim Loughran, Hai Lu, Russ Lundholm, Josh Madsen, Mark Maffett, Iván Marinovic, Ken Merkley, Jim Naughton, Doug Skinner, Rodrigo Verdi, Wenyu Wang, Michael Weisbach, T.J. Wong, Gaoqing Zhang, Dexin Zhou, and Christina Zhu. This paper also benefited from comments by seminar participants at Tsinghua University, the University of Houston, the US Securities and Exchange Commission, and the Applied Econ Workshop Series at the University of Minnesota, and conference participants at the 2020 MFA meeting, the 2020 FARS Meeting, the 2020 CAFR Fintech Research Workshop at the ASSA Meeting, the 3rd Conference on Intelligent Information Retrieval in Accounting and Finance, the 2019 UVA Darden Accounting Mini-Conference, and the 2019 Stanford Accounting Summer Camp. We are grateful to Kenneth French for sharing US research returns data, Gordon Philips and Gerry Hoberg for sharing the TNIC industry classification data, Xuan Tian for sharing US patent data through 2014, and Xinyuan Shao and Yifan Yan for excellent research assistance. Byline: Sean Shun Cao [scao@gsu.edu] (a), Vivian W. Fang [fangw@umn.edu] (b,*), Lijun (Gillian) Lei [l_lei2@uncg.edu] (c)

Keywords Asset pricing; Efficient markets; Portfolio theory; Capital structure; Dividend policy; Investment policy; Corporate finance; Corporate control; Corporate governance; Market microstructure; Financial intermediation; Behavioral finance; Citations Abstract The field of academic finance has grown and evolved in the 47 years since the Journal of Financial Economics (JFE) began publishing papers. This paper examines detailed data on the 3,003 papers written by 3,358 different authors published in the JFE over the period 1974--2020. Advances in computing power and electronic communication have driven trends toward more empirical work, more coauthorship, and more complex papers. The set of authors, referees, and editors has also evolved as the field spans a much larger geographic footprint and as women have come to play a larger role in all aspects of academic finance. Growth in the demand for finance faculty has driven up faculty compensation and the demand for scarce journal space. Author Affiliation: (a) Simon School of Business, University of Rochester, Rochester, NY 14627, USA (b) National Bureau of Economic Research, Cambridge, MA, USA * Correspondence to: Simon School of Business, University of Rochester, Rochester, NY 14627, USA. Article History: Received 4 December 2020; Accepted 13 March 2021 (footnote)1 This is a personal assessment of the evolution of academic finance during my career. It does not reflect the opinions of the Journal of Financial Economics, the University of Rochester, or the National Bureau of Economic Research. Many people have provided helpful comments and suggestions, especially Jonathan Brogaard, Harry DeAngelo, Ken French, Campbell Harvey, David Hirshleifer, Laura Liu, Lubos Pastor, Jim Poterba, René Stulz, Avanidhar Subrahmanyam, and Ivo Welch. Michelle Lowry, Laura Liu, and Kathleen Madsen provided special help with several aspects of the data collection for this paper. Janice Willett edited the manuscript. Byline: G. William Schwert [schwert@simon.rochester.edu] (a,b,1,*)

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jfineco.2017.06.017 Byline: Alex Edmans (a)(b)(c), Sudarshan Jayaraman (d), Jan Schneemeier (e) Abstract: This paper shows that real decisions depend not only on the total amount of information in prices, but the source of this information -- a manager learns from prices when they contain information not possessed by him. We use the staggered enforcement of insider trading laws across 27 countries as a shock to the source of information that leaves total information unchanged: enforcement reduces (increases) managers' (outsiders') contribution to the stock price. Consistent with the predictions of our theoretical model, enforcement increases investment-q sensitivity, even when controlling for total price informativeness. The effect is larger in industries where learning is likely to be stronger, and in emerging countries where outsider information acquisition rises most post-enforcement. Enforcement does not increase the sensitivity of investment to cash flow, a non-price measure of investment opportunities. These findings suggest that extant measures of price efficiency should be rethought when evaluating real efficiency. More broadly, our paper provides causal evidence that managers learn from prices, by using a shock to price informativeness. Author Affiliation: (a) London Business School, Regent's Park, London NW1 4SA, UK (b) Centre for Economic Policy Research, London EC1V 0DX, UK (c) European Corporate Governance Institute, Rue Ducale 1, 1000 Bruxelles, Belgium (d) Simon Business School, University of Rochester, Rochester, NY 14627, USA (e) Kelley School of Business, Indiana University, Bloomington, IN 47405, USA Article History: Received 12 April 2016; Revised 19 September 2016; Accepted 19 October 2016 Article Note: (footnote) [star] We thank the Referee (Thomas Philippon), the Editor (Toni Whited), Jennie Bai, Karthik Balakrishnan, Taylor Begley, Bastian von Beschwitz, Stijn Claessens, Valentin Dimitrov, Laurent FrAaAaAeA@sar Itay Goldstein, Todd Gormley, Kose John, Marcin Kacperczyk, Ralph Koijen, Randall Morck, Joseph Piotroski, Alexi Savov, Henri Servaes, Rui Silva, Luke Taylor, and conference/seminar participants at the AFA, Arizona State University, Conference on Financial Economics and Accounting, ECB, Frankfurt School of Finance and Management, Imperial CEPR Conference, Lancaster, London Business School, Mannheim, National Taiwan University Conference, NHH Corporate Finance Conference, Rising Star Conference, Temple, UT Austin, and Wharton for valued input. We thank Nuno Fernandes and Miguel Ferreira for generously providing us with data that was used in an earlier version of the paper. Alex Edmans gratefully acknowledges financial support from European Research Council Starting Grant 638666.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jfineco.2017.06.001 Byline: Zhen Shi Abstract: Consistent with the argument that portfolio disclosure reveals trade secrets, a difference-in-differences estimation suggests a drop in fund performance after a hedge fund begins filing Form 13F as well as an increase in return correlations with other funds in the same investment style. The drop in performance is concentrated among funds with larger expected proprietary costs of disclosure, for instance, funds that disclose a greater fraction of their assets or hold more illiquid stocks. The drop in performance cannot be fully explained by alternative explanations such as decreasing returns to scale or mean reversion in fund returns. Author Affiliation: Georgia State University, J. Mack Robinson College of Business, 35 Broad Street, Atlanta, GA 30303, USA Article History: Received 29 June 2015; Revised 19 May 2016; Accepted 20 May 2016 Article Note: (footnote) [star] This paper is based on my dissertation at Arizona State University. I am grateful for the guidance and support from my dissertation advisors George Aragon (co-chair), Michael Hertzel (co-chair), and Jeffrey Coles. I am thankful to an anonymous referee for the constructive comments. Thanks to Bill Schwert, Vikas Agarwal, Ilona Babenko, Thomas Bates, Sreedhar Bharath, David Hirshleifer, Bing Liang, Oliver Boguth, Nicolas Bollen (discussant), Mark Chen, Claudia Custodio, Gerald Gay, Itay Goldstein, Xin Hong (discussant), Lixin Huang, Wei Jiang, Jayant Kale, Omesh Kini, Laura Lindsey, Tingjun Liu, Vikram Nanda, Istvan Nagy (discussant), Josh Pierce, Dale Rosenthal, Harley Ryan, Scott Murray, Laura Starks, Yuehua Tang, Yuri Tserlukevich, Sunil Wahal, Na Wang, PengCheng Wan, Baozhong Yang, and conference and seminar participants at the Western Finance Association 2012 annual meeting, the Fourth Annual Hedge Fund Research Conference (2012), the Networks Financial Institute 2011 Financial Services Regulatory Reform Conference, the Financial Management Association 2010 Doctoral Student Consortium, the Eastern Finance Association annual meeting 2012, and the Financial Management Association annual meeting 2012, Arizona State University, Georgia State University, and Hong Kong University. I acknowledge financial support from the Networks Financial Institute at Indiana State University and its honorable mention award for best paper in financial services regulatory reform for 2010-2011.