Predicting Status of Pre and Post M&A Deals Using Machine Learning and Deep Learning Techniques

@article{Karatas2021PredictingSO,
  title={Predicting Status of Pre and Post M\&A Deals Using Machine Learning and Deep Learning Techniques},
  author={Tugce Karatas and Ali Hirsa},
  journal={Econometric Modeling: Corporate Finance \& Governance eJournal},
  year={2021}
}
  • Tugce Karatas, Ali Hirsa
  • Published 5 August 2021
  • Economics, Computer Science
  • Econometric Modeling: Corporate Finance & Governance eJournal
Risk arbitrage or merger arbitrage is a well-known investment strategy that speculates on the success of M&A deals. Prediction of the deal status in advance is of great importance for risk arbitrageurs. If a deal is mistakenly classified as a completed deal, then enormous cost can be incurred as a result of investing in target company shares. On the contrary, risk arbitrageurs may lose the opportunity of making profit. In this paper, we present an ML and DL based methodology for takeover… 

References

SHOWING 1-10 OF 42 REFERENCES
Predicting Takeover Success Using Machine Learning Techniques
TLDR
A thorough study using machine learning techniques to predict takeover success prediction as a binary classification problem, and it is found that the support vector machine with linear kernel and the Adaboost with stump weak classifiers perform the best for the task.
A note on takeover success prediction
A takeover success prediction model attempts to use information that is publicly available at the time of the announcement in order to predict the probability that a takeover attempt will succeed.
Predicting Successful Takeovers and Risk Arbitrage
In this paper, we explore the probability of merger completion/success for the 1991 to 2001 period We construct a prediction model for merger completion and, among other issues, test how payment
Unbalanced data, type II error, and nonlinearity in predicting M&A failure
TLDR
A forecasting model is developed that combines two complementary approaches: a generalized logit model framework and a context-specific cost-sensitive function that provides excellent forecasts when compared with traditional forecasting methods.
An Option‐Based Approach to Risk Arbitrage in Emerging Markets: Evidence from Taiwan Takeover Attempts
Predicting the accuracy rate of takeover completion is the major key to risk arbitrage returns. In emerging markets, data on takeover attempts are either unavailable or of poor quality. Therefore,
Limited Arbitrage in Mergers and Acquisitions
A diversified portfolio of risk arbitrage positions produces an abnormal return of 0.6% to 0.9% per month over the period from 1981 to 1996. We trace these profits to practical limits on risk
SMOTE: Synthetic Minority Over-sampling Technique
TLDR
A combination of the method of oversampling the minority (abnormal) class and under-sampling the majority class can achieve better classifier performance (in ROC space) and a combination of these methods and the area under the Receiver Operating Characteristic curve (AUC) and the ROC convex hull strategy is evaluated.
Predicting mergers and acquisitions in the food industry
Two logit models are estimated to explain merger and acquisition (M&A) activities in US food manufacturing using firm level data for public firms: a “target model” predicting the likelihood of a firm
Takeover Success Prediction - European acquisitions between 1999 and 2008
The purpose of the study is to identify the determinants of takeover bid success on the European market, to create a model that can be used for takeover success prediction and to test the effect of
The Shrinking Merger Arbitrage Spread: Reasons and Implications
The merger arbitrage spread has declined by more than 400 bps since 2002. This decline, which is both economically and statistically significant, corresponds to the decline in aggregate returns of
...
1
2
3
4
5
...