Investmentstrategien im Rahmen von Übernahmen börsennotierter Gesellschaften – Merger Arbitrage und Maschinelles Lernen (Merger Arbitrage and Machine Learning)

ifes Schriftenreihe Band 19

87 Pages Posted: 21 Oct 2019

See all articles by Frank Lehrbass

Frank Lehrbass

L*PARC (Lehrbass Predicitive Analytics and Risk Consulting); FOM University of Applied Sciences for Economics and Management; University of the Bundesbank

Alexander Raasch

affiliation not provided to SSRN

Date Written: June 1, 2019

Abstract

German Abstract: Wir stellen verschiedene Investmentstrategien rund um M&A vor. Cash Merger Arbitrage und Stock Merger Arbitrage werden behandelt als auch die Wette auf Compensation Schemes. Zudem untersuchen wir empirisch, ob der Erfolg von M&A mit ökonometrischen Methoden und maschinellem Lernen vorhergesagt werden kann.

English Abstract: We introduce various investment strategies related to M&A situations, explain their risks and returns. Cash Merger Arbitrage and Stock Merger Arbitrage are explored as well as betting on Compensation Schemes. Also, we investigate empirically whether the binary variable success/failure of an attempted M&A deal can be forecasted using classical econometrics and machine learning.

Note: Downloadable document is in German.

Keywords: trading strategies, investment strategies, logit regression, decision trees

JEL Classification: G34, C450

Suggested Citation

Lehrbass, Frank and Raasch, Alexander, Investmentstrategien im Rahmen von Übernahmen börsennotierter Gesellschaften – Merger Arbitrage und Maschinelles Lernen (Merger Arbitrage and Machine Learning) (June 1, 2019). ifes Schriftenreihe Band 19. Available at SSRN: https://ssrn.com/abstract=3454408 or http://dx.doi.org/10.2139/ssrn.3454408

Frank Lehrbass (Contact Author)

L*PARC (Lehrbass Predicitive Analytics and Risk Consulting) ( email )

Dusseldorf
Germany

HOME PAGE: http://lehrbass.de

FOM University of Applied Sciences for Economics and Management ( email )

Toulouser Allee 53
Dusseldorf, 40476
Germany

University of the Bundesbank ( email )

Schloss
Hachenburg, 57627
Germany

Alexander Raasch

affiliation not provided to SSRN

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