Forecasting M&A deals with MIDAS count model

Arbeitspapier

This report focuses on the forecast of the number of monthly cross-border deals in the European Union. We propose a new model to improve the forecasting properties of a count model of Foreign Direct Investment deals in EU, by taking into account past trends in high-frequency (daily) deal data and the decomposition of the conditional overdispersion into short-term and long-term components. Our model relies on the dynamic behaviour of the first two moments of the distribution of FDI deals to explain the evolution of parameters 𝜂 and 𝜋 in the Negative Binomial distribution. We test this model with several subsets of M&A deals from 1998 to 2021 obtaining sizable forecast improvements as compared to benchmark INGARCH models.

Objekt anzeigen

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: JRC Working Papers in Economics and Finance ; No. 2022/15

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Econometric and Statistical Methods and Methodology: General ; Econometric and Statistical Methods: Other ; Multiple or Simultaneous Equation Models: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
• Thema: M&A forecasting ; MIDAS approach ; count process ; overdispersion

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Ferreiro, Javier Ojea ; Gregori, Wildmer Daniel ; Nardo, Michela
• Ereignis: Veröffentlichung
• (wer): European Commission
• (wo): Ispra
• (wann): 2022

Weitere Informationen

• Handle: http://hdl.handle.net/10419/283078