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We propose and test a framework of private information acquisition and decision timing for asset allocators hiring outside investment managers. Using unique data on due diligence interactions between an institutional allocator and 860 hedge fund managers, we find that the production of private information complements public information. The allocator strategically chooses how much proprietary information to collect, reducing due diligence time by 18 months and improving outcomes. Funds selected by the manager outperform those not selected by 9 |$\%$| over 20 months. The outperformance relates to the allocator learning about fund return-to-scale constraints and manager skill before other investors. [ABSTRACT FROM AUTHOR]

We estimate unsmoothed private equity net asset values (NAVs) at weekly frequency for individual funds. Using simulations and large samples of buyout and venture funds, we show that our method yields superior estimates of NAVs relative to simple approaches based on extrapolation of reported NAVs. The market beta of an average buyout (venture) fund is around 1.0 (1.4), and the total risk is 33 |$\%$| (40 |$\%$|⁠) per year. The risk-return profile of the funds varies significantly over time and across funds. Risk-taking and reporting quality appear to persist by manager. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Hedge fund positions are an important component of crowded trades. These vehicles are particularly active, take highly concentrated positions, and utilize leverage and short sales. Using a database of hedge fund holdings, we measure the degree of security-level crowdedness. The difference between the average returns on portfolios sorted by high versus low crowdedness portfolios is sizable, and the variation in the realized portfolio returns is distinct from other traditional risk factors. Further, hedge fund exposures to crowdedness are often significant, and they help to explain downside "tail risk," as funds with higher exposures experience relatively larger drawdowns during periods of industry distress. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jfineco.2006.10.001 Byline: Sohnke M. Bartram (a), Gregory W. Brown (b), John E. Hund (c) Keywords: Systemic risk; Default risk; Credit risk; Banks; Exposure; Emerging markets Abstract: This paper develops three distinct methods to quantify the risk of a systemic failure in the global banking system. We examine a sample of 334 banks (representing 80% of global bank equity) in 28 countries around five global financial crises. Our results suggest statistically significant, but economically small, increases in systemic risk. Although policy responses are endogenous, the low estimated probabilities suggest that the distress of central bankers, regulators and politicians about the events we study could be overstated and that current policy responses to financial crises could be adequate to handle major macroeconomic events. Author Affiliation: (a) Lancaster University, Management School, Lancaster, LA1 4YX, UK (b) Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3490, USA (c) McCombs School of Business, University of Texas, Austin, TX 78712, USA Article History: Received 28 July 2005; Revised 11 July 2006; Accepted 17 October 2006 Article Note: (footnote) [star] We gratefully acknowledge research funding by the Center for Financial Research of the Federal Deposit Insurance Corporation (FDIC), Lancaster University, Lancaster University Management School, the Leverhulme Trust, and The Bank of America Faculty Development Fund, as well as support by Global Reports, Perfect Information, Fitch Ratings, and Thomson Financial in establishing the data set. We also thank Robert Bliss, Jean Dermine, Hans Degryse, Eva Gutierrez, Philipp Hartmann, Shelagh Heffernan, Jean Helwege, Armen Hovakimian, Donald Morgan, Roberto Rigobon, Anthony Saunders, Lynn Shibut, Christian Upper and Giuseppe Vulpes as well as seminar participants at the FDIC Summer Research Workshop, the Financial Intermediation Research Society (FIRS) conference in Capri, the 2005 American Finance Association annual meeting, the 2004 European Finance Association annual meeting, the 2004 Financial Management Association annual meeting, the Emerging Markets Group (EMG)/Economic and Social Research Council (ESRC) workshop 'International Diversification and Contagion' at Cass Business School, 2005 National Bureau of Economic Research (NBER) conference 'Risks of Financial Institutions,' NBER's 2005 Universities Research Conference 'Structural Changes in the Global Economy: Implications for Monetary Policy and Financial Regulation,' the Fourth Joint Central Bank Research Conference 'Risk Measurement and Systemic Risk', the 2005 Australasian Conference on Banking and Finance, Karlsruhe University, The Bank of England, Darden School of Business, Lancaster University, Temple University, University of North Carolina, University of Texas at Austin, Vanderbilt University, and Wake Forest University. Florian Bardong and Nishad Kapadia provided excellent research assistance.

Investigation of multinational company's hedging corporation and of its motivation for engaging in financial risk management reveals the reasons why and how this depends on various factors.

Investors in the public shares of Boston Celtics L.P. react not only to the wins, losses and the results of their team playoffs. The volatility of equity prices are caused by raiders acting on private information.

The two-step extension of the sensitivity-based element-by-element method for finite element models of lightly damped structures with experimentally measured complex modes was proposed. The first iterative step expanded the modes shapes and updated the mass and stiffness matrices. The second step allows the construction of a damping matrix to absorb the remainder of dynamic residuals.