Abstract
dc:description.abstractIn this thesis we quantify the risk arbitrage investment process and create trading strategies that generate positive risk-adjusted returns. We use a sample of 895 stock swap mergers, cash mergers, and cash tender offers during 1998-2004Q2. We test the market efficiency hypothesis, and after accounting for transaction costs, we find that our risk arbitrage strategies generate annual risk-adjusted returns in excess of 4.5%. The research also obtains various other merger statistics, and relates them to a variety of economic indicators and merger timing models, as described in past work. We also estimate conditional probabilities of a merger's success, using a deal characteristic-driven prediction model, and combine it with market-implied probabilities. Our analysis suggests that the probability of success of a merger depends on a deal's characteristics. Further, it implies that one can improve on the market-implied estimates thereby creating trading opportunities. The analytical results achieved in this thesis can be used as the foundation for building an effective risk arbitrage trading platform.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2004
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Naheta, Akshay, 1981-
- Advisor dc:contributor.advisor
-
- Leonid Kogan and John Tsitsiklis.
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
- en_US
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/28738
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/28738