Massachusetts Institute of Technology
What drives hedge fund returns? : models of flows, autocorrelation, optimal size, limits to arbitrage and fund failures
Abstract
dc:description.abstractHedge funds provide an opportunity for investing with few government regulations and high potential returns. Since 1980 this has lead to the dramatic, 25% annual increase in the number of hedge funds, and with nearly $700 billion managed by hedge funds in 2003. However, high risks associated with hedge fund strategies, competition and limited arbitrage opportunities contributed to an annual attrition rate of 7.10%. In this thesis, models were developed and tested that describe characteristics of fund returns, fund flows, optimal size and the life cycles of hedge funds. The TASS hedge fund database provided by the Tremont Company was used for analysis. In Essay One, it was found that hedge fund returns are highly serially correlated compared to the returns of more traditional investment vehicles such as mutual funds. Several sources of such high serial correlation were explored and the research illustrated that the most likely explanation of this derived from asset illiquidity and smoothing of returns. Illiquid securities are not actively traded and market prices are not always available for them. In the case of smoothing, brokers or managers have the flexibility to report partial returns. Consequently, for portfolios of illiquid or smoothed securities, reported returns will tend to be smoother than true economic returns, thereby understating volatility and increasing risk-adjusted performance measures such as the Sharpe ratio. An econometric model of illiquidity exposure was further proposed and estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio were developed.
Degree
thesis:*- Department dc:contributor.department
- Sloan School of Management.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2004
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Getmansky, Mila
- Advisor dc:contributor.advisor
-
- John D. Sterman and Andrew W. Lo.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/29439
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/29439