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Author Moreira, Alan
Title Career concerns versus entrenchment in money management: quantifying limits to arbitrage using lockup maturities
book jacket
Descript 128 p
Note Source: Dissertation Abstracts International, Volume: 73-04, Section: A, page:
Adviser: Douglas Diamond
Thesis (Ph.D.)--The University of Chicago, 2011
I present a dynamic model of delegated asset management in which investors' learning distorts managers' incentives to time bets in low-probability catastrophe events. Uncertainty about manager skill creates a wedge between the portfolio that maximizes fund expected return and the portfolio that minimizes fund liquidation risk. In equilibrium, managers expose their portfolios to too much tail risk. Rational learning about manager skill and manager equilibrium portfolio choice make this distortion persistent . In Chapter 2, I develop the model and use a calibration exercise to highlight the main properties of the model. In Chapter 3, I estimate the model using the Simulated Method of Moments of Duffee and Singleton [1993]. The estimation results teach us how costly are contracts that entrench bad managers, and the magnitude of limits to arbitrage distortions that good managers face. Under the steady state distribution of manager reputation, a skilled managers forgoes on average 86 basis points a year of a total average skill of 744 basis points in the population. The average entrant in the hedge fund business faces substantially larger limits to arbitrage. The average new manager forgoes 235 basis points a year if she choose the fund lockup maturity optimally and 261 basis points if she is forced to manage a fund with a monthly redemption frequency. The model identifies limits to arbitrage distortions from contract maturity choices and the joint time-series behavior of liquidations, returns, and compensation observed in the hedge fund sector
School code: 0330
Host Item Dissertation Abstracts International 73-04A
Subject Economics, Finance
Alt Author The University of Chicago. Business and Economics
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