Modeling the Private-to-Public Transition: IPOs, Direct Listings and De-SPAC Mergers

We have developed a comprehensive mathematical framework that delineates the complete transition of a firm from private to public ownership. This framework explicitly formalizes the endogenous decision to list, pre-listing restructuring, regulatory feasibility constraints, information production, pricing and allocation mechanisms, and post-listing market dynamics. A unified structure is employed to represent traditional IPOs, direct listings, and de-SPAC mergers. The proposed framework integrates the concepts of information asymmetry, free-float constraints, and market impact with equilibrium offer prices, first-day returns, and post-listing volatility. This integration enables the formulation of testable predictions across a range of listing mechanisms.

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Publication Details

Journal
Journal of risk and financial management
Published
2026-01-21
DOI
https://doi.org/10.3390/jrfm19010084
Primary Topic
Corporate Finance and Governance
Type
article
Field-Weighted Citation Impact
0.00
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article

Modeling the Private-to-Public Transition: IPOs, Direct Listings and De-SPAC Mergers

Georgios Angelidis, Vasilios Margaris
Journal of risk and financial management
Corporate Finance and Governance
article

Modeling the Private-to-Public Transition: IPOs, Direct Listings and De-SPAC Mergers

Georgios Angelidis, Vasilios Margaris
article en

Abstract

We have developed a comprehensive mathematical framework that delineates the complete transition of a firm from private to public ownership. This framework explicitly formalizes the endogenous decision to list, pre-listing restructuring, regulatory feasibility constraints, information production, pricing and allocation mechanisms, and post-listing market dynamics. A unified structure is employed to represent traditional IPOs, direct listings, and de-SPAC mergers. The proposed framework integrates the concepts of information asymmetry, free-float constraints, and market impact with equilibrium offer prices, first-day returns, and post-listing volatility. This integration enables the formulation of testable predictions across a range of listing mechanisms.

Journal of risk and financial managementVol. 19(1)
Aristotle University of Thessaloniki (GR)
Openalex Percentile: Top 83%
Corporate Finance and Governance
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