Corporate Sponsorship of the 2008, 2012, and 2016 Summer Olympics: A Test of Market Efficiency
Bibliographic record
Abstract
Corporate sponsorship is a form of advertising that companies pay to be associated with certain events. Firms with corporate sponsorships of an event such as the Olympic Games can maximize stockholder wealth by evaluating the returns on these investments. In order to evaluate the returns on these investment decisions, this study employs an event study methodology in the finance literature. Using the risk-adjusted event study methodology, this study tests the hypothesis that the risk-adjusted rates of return on the sponsor companies’ stock prices are significantly positively affected by this type of information. The event study tested the effect of the 2008 Beijing, 2012 London and 2016 Rio Summer Olympic games on the sponsor company’s stock prices. The opening ceremonies took place on August 8th, 2008, July 27th, 2012 and August 5th, 2016. Results for all 3 summer Olympic games and the combined global sample show positive gains to their risk-adjusted rates of return of stock prices leading to the opening ceremony, with small gains following the opening ceremony. The evidence also supports the semi-strong form of market efficiency. No investor was able to make an above normal return by acting on the event.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".