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   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Leonid Kogan and John Tsitsiklis.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Naheta, Akshay, 1981-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2005-09-27T18:04:15Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2004</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (leaves 59-60).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">In 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.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Akshay Naheta.</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Risk arbitrage : analysis and trading systems</dim:field>
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   	&lt;Title>Risk arbitrage : analysis and trading systems&lt;/Title>
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   	&lt;Abstract>In 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&amp;apos;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&amp;apos;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.&lt;/Abstract>
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