Startups’ key characteristics for a successful exit: a statistical model to predict likelihood to succeed in the European startup M&A ecosystem

Quercia, Alessandro Niccolò (A.A. 2020/2021) Startups’ key characteristics for a successful exit: a statistical model to predict likelihood to succeed in the European startup M&A ecosystem. Tesi di Laurea in M&A and investment banking, Luiss Guido Carli, relatore Luigi De Vecchi, pp. 97. [Master's Degree Thesis]

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Abstract/Index

Fundamentals. Startup ecosystem. Data science. Startup environment in Europe. Startup nation standard. Capital raising context in Europe. Startup M&A experience in Europe. Introduction to the analysis. Fundamentals of the analysis. The sample. Variables. The regression. Statistical methodology in the regression. Sample of the regression.

References

Bibliografia: pp. 91-97.

Thesis Type: Master's Degree Thesis
Institution: Luiss Guido Carli
Degree Program: Master's Degree Programs > Master's Degree program in Corporate Finance, English language (LM-77)
Chair: M&A and investment banking
Thesis Supervisor: De Vecchi, Luigi
Thesis Co-Supervisor: Pattofatto, Leone
Academic Year: 2020/2021
Session: Autumn
Deposited by: Alessandro Perfetti
Date Deposited: 26 May 2022 15:17
Last Modified: 26 May 2022 15:17
URI: https://tesi.luiss.it/id/eprint/32529

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