Circumstances defining the purchase price in acquisitions of unlisted companies : Is the pricetag set by the broker, the buyer or the seller?
Bibliographic record
Abstract
Background: The first quarter of 2006, acquisitions at a value of 2 600 billion SEK were announced. If this trend holds for the entire year, 2006 will go to history as the most active year of acquisitions ever. The fundamentals of an acqui-sition is to generate added value through different forms of synerigies that are potentially created from the combined companies or to pay a lower price than the company is actually worth. Company valuation has because of this increased in importance to determine what the correct price of a company is. The valuation of a company performed by a business broker is not always consistent with the price a company pays for another due to different strategic circumstances that affect the purchase price. Purpose: The purpose of this thesis is to analyse the valuation process in connection with acquisitions of unlisted companies. The study also aims to clearify the circumstances causing the purchase price to differ from the cashflow or book valuation. Method: To meet the purpose of this thesis, a qualitative approach based on three acquisition processes in the Jönköping region has been chosen. The collection of empirical data has been made through personal interviews with Svensk Företagsförmedling (SFF) in Jönköping with complementing telephone interviews. Conclusion: Based on the cashflow or book valuation, which is the foundation upon which the selected companies are priced, we can draw the conclusion that in every unique case the broker must be presented with several strategical variations the different acquistions presents. These strategic presumptions considered, a company should be valuated to its highest defendable value. The study also demonstrates that a company’s fundamental value alone only constitutes a guideline in coming negotiaions. The strategic categories goodwill, potential synergies and form of payment makes up the the negotiable part of the purchase price.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".