We study asset pricing when agents face risk and uncertainty and empirically demonstrate that uncertainty has a substantial effect on asset prices. We measure risk with past volatility and uncertainty with the degree of disagreement of professional forecasters, attributing different weights to each forecaster. We run regressions representing the typical risk-return trade-off and augment these regressions with a measure of uncertainty. We find stronger empirical evidence for a uncertainty-return trade-off than for the traditional risk-return trade-off. We investigate the performance of a two-factor model with risk and uncertainty in the cross-section. * Evan Anderson: Northern Illinois University, Department of Economics, Zulauf 515, DeKalb, IL 60115, phone: (630) 450-0533, email: ewanderson@niu.edu. Eric Ghysels: Department of Finance, Kenan-Flagler Business School, and Department of Economics, University of North Carolina -Chapel Hill, Chapel Hill, NC 27599-3305, phone: (919) 966-5325, email: eghysels@unc.edu. Jennifer L. Juergens: Arizona State University, W.P. Carey School of Business, Department of Finance, Tempe, AZ 85287, phone: (480) 965-3131, email: Jennifer.Juergens@asu.edu. We would like to thank Lars Hansen, Peter Hansen, Chris Jones, Leonid Kogan, Jianjun Miao, Athanasios Orphanides, Simon Potter, Eric Renault, Robert Rich, Tom Sargent and Raman Uppal for very helpful comments. This paper was presented at Northern Illinois University, SAMSI Opening Workshop, 2006 EFA meetings, 2006 Winter Meetings of the Econometric Society, the SAMSI Conference on Model Uncertainty, 2006 NBER Summer Institute Asset Pricing Workshop, 2007 AFA meetings, UC Santa Cruz, University of Illinois at Urbana-Champaign, and University of Wisconsin-Madison. Early versions of the ideas in this paper were also presented at the Board of Governors, the FDIC, the Federal Reserve Bank of New York, Simon Fraser University and Stanford University. We thank seminar participants for helpful comments.Electronic copy of this paper is available at: http://ssrn.com/abstract=890621One of the most studied theoretical relationships in empirical finance is that the expected excess return of the market over a risk-free bond should vary positively and proportionally to the volatility of the market return. This risk-return trade-off is so fundamental that it could well be described as the "first fundamental law of finance." Merton (1973) derived this theoretical relationship in a continuous time model in which all agents have power preferences and hedging concerns are negligible, and it is sometimes referred to as Merton's ICAPM or simply the ICAPM.The empirical evidence for a risk-return trade-off is mixed. Many studies have run versions of the following regression:where r et+1 is the excess return of the market over a risk-free bond, γ is a risk aversion coefficient, and V t is (market) risk. 1 The goal has been to find a significantly positive γ coefficient that captures the trade-off between risk and return. Baillie and DeGennaro (199...
* We thank Stan Levine (previously of First Call) and First Call/Thomson for providing the earnings data used in this study. We express our appreciation to Campbell Harvey and anonymous referees for providing invaluable comments and suggestions. This paper is a substantially revised version of an earlier paper by the last two authors, Ghysels and Juergens (2001). We also like to thank Günter Franke, Raman Uppal and Fernando Zapatero for their comments as well as participants at the 2002
This paper investigates the effects of analyst recommendations issued after a merger announcement on deal completion. We find the probability of completion increases (decreases) with the favorability of acquirer (target) recommendations. Results from instrumental variables tests support causality running from recommendations to merger outcomes. Additional tests suggest that these relations are driven by target shareholders reassessing the merger offer in response to movements in acquirer and target valuations. We also find that favorablyrecommended firms in a proposed merger underperform following deal resolution, suggesting that investors overreact to post-merger announcement recommendations.
This paper examines trading volume for Nasdaq market makers around analyst recommendation changes issued by an analyst at the same firm. Using Nasdaq PostData, we find a disproportionate increase in market making volume associated with the firm's recommendation changes and evidence of elevated sell volume at the recommending analyst's firm in the 2 days preceding a downgrade. The implications are that the information source matters in determining the placement of trades and that the issuing analyst's firm appears to be rewarded for prereleasing information through increased volume. These findings constitute new evidence of compensation for research production through the market making channel. Copyright (c) 2009 the American Finance Association.
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