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Contribution Details
| Type | Bachelor's Thesis |
| Scope | Discipline-based scholarship |
| Title | Quantitative Analysis of Investment Strategies for the S&P 500 Based on Announced M&A Transactions |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 72 |
| Date | 2023 |
| Abstract Text | This thesis uses the fundamental concept of merger arbitrage investing to derive rule-based investment strategies. The strategies are based on research findings regarding five deal-specific factors influencing deal success probabilities and aim to identify profitable merger arbitrage opportunities. A backtesting approach applied to a dataset of 160 M&A deals with targets that were, at the time of the transaction announcement, constituents of the S&P 500 index between 2010 and 2022 is used to test the proposed strategies. The results cannot confirm significant differences in returns between a long-only baseline strategy and the proposed strategies, disproving the effectiveness of the factors. |
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