REVERSE LEVERAGED BUYOUT RETURN BEHAVIOR: SOME EUROPEAN EVIDENCE
Bibliographic record
Abstract
This study investigates the stock performance of reverse leveraged buyouts (RLBOs) before, during, and after the global financial crisis.An RLBO consists of the return to public investors (i.e. the offering of stocks to the public) of a company that had gone private after a leveraged buyout (LBO) led by a private equity fund.The value created by an RLBO resides in the changes brought by the LBO fund while it owns the company.After a "repackaging" of the bought company, the private equity fund sells the company's shares to the public.Most of the research on this topic, based on RLBOs that occurred between 1980 and 2005 in the US, has shown that RLBOs outperform their peers (i.e.other IPOs) and outperform the market after going public again.Focusing on RLBO companies in Europe in the financial crisis era, this study investigates whether they also outperform other IPOs and the market.The study is based on a sample of 421 IPOs occurring between 2001 and 2011 in France, Germany and the UK, of which 52 are RLBOs.We examine RLBO performance one day, one month, one year and three years after the offering.We also use event study methods to investigate the impact of the global financial crisis on RLBO performance.We find that European RLBOs outperform both their peers (i.e."classic" IPOs) and the market during the period studied.This outperformance does not diminish in the long-term.The global financial crisis appears to have affected RLBO performance, which weakened between 2007 and 2009, though RLBOs still outperformed the market.In addition, multivariable regressions were used to examine various extant explanations for RLBO outperformance.This analysis did not support any of the prevailing theories.In particular, the value created by RLBOs does not appear to be linked to LBO duration, sponsor reputation, or to the level of leverage employed.There is no evidence of time or industry effects.Moreover, RLBO performance shows no correlation with market capitalization.The explanation of why RLBOs outperform both other IPOs and the market continues to be a puzzle.Further theoretical elaboration is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".