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Risk arbitrage in emerging markets

Author(s)
Goh, Mengkiat
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Roy E. Welsch.
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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. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Risk arbitrage is one of the investment strategies commonly employed by hedge funds and financial investment firms. In essence, it constitutes a bet on whether a merger deal is consummated. Several academic studies have found that risk arbitrage trading strategies are able to generate sustainable positive returns. However, these studies have been largely confined to risk arbitrage investments in developed markets. In this thesis, we quantify the risk arbitrage investment process and create trading strategies that generate positive risk-adjusted returns in emerging markets. We use a sample of 810 stock and cash mergers and acquisitions in emerging markets from 2001 to 2007. We find that returns in excess of 7.9% can be obtained using the prediction model formulated in this thesis. 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 in emerging markets.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
 
Includes bibliographical references (p. 63-64).
 
Date issued
2008
URI
http://hdl.handle.net/1721.1/46107
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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