The Measure of a MAC: A Machine-Learning Protocol for Analyzing Force Majeure Clauses in M&A Agreements [with comment]
This paper develops a protocol for using a familiar data set on force majeure provisions in corporate acquisitions agreements to tokenize and calibrate a machinelearning algorithm of textual analysis. Our protocol, built on regular expression (RE) and latent semantic analysis (LSA) approaches, serve...
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| Veröffentlicht in: | Journal of institutional and theoretical economics 2012-03, Vol.168 (1), p.181-208 |
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| container_end_page | 208 |
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| container_issue | 1 |
| container_start_page | 181 |
| container_title | Journal of institutional and theoretical economics |
| container_volume | 168 |
| creator | Talley, Eric O'Kane, Drew Kellner, Christian Stremitzer, Alexander |
| description | This paper develops a protocol for using a familiar data set on force majeure provisions in corporate acquisitions agreements to tokenize and calibrate a machinelearning algorithm of textual analysis. Our protocol, built on regular expression (RE) and latent semantic analysis (LSA) approaches, serves to replicate, correct, and extend the hand-coded data. Our preliminary results indicate that both approaches perform well, though a hybridized approach improves predictive power further. Monte Carlo simulations suggest that our results are generally robust to out-of-sample predictions. We conclude that similar approaches could be used more broadly in empirical legal scholarship, especially including in business law. |
| doi_str_mv | 10.1628/093245612799440177 |
| format | Article |
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| language | eng |
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| subjects | Algorithms Clause Contract provisions Contracts Data coding Datasets Latent semantic analysis Latent structure analysis Learning Legal practice Machine learning protocol Market conditions Measurement Modeling Monte Carlo simulation Predictive modeling Semantics Subsidiary companies |
| title | The Measure of a MAC: A Machine-Learning Protocol for Analyzing Force Majeure Clauses in M&A Agreements [with comment] |
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