Airfare price insurance: a real option model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the uncertainty of acquiring the lowest possible airfare when contemplating the purchase of a ticket. A real option model is applied to value insurance contracts that could be offered to passengers to cope with price risk. Furthermore, the premiums charged for such airfare price insurance contracts can augment airline carrier revenues. Design/methodology/approach Prices on 14 airfares were collected for 79 consecutive days on an assortment of US domestic and international flights from four airline carriers. Volatility in airfares was shown using the price range and SD. The Black‐Scholes‐Merton model was employed to value the call and put options representing different airfare price insurance contracts. Findings Airfare price insurance contracts affordability was demonstrated ranging from 1.55 to 11.28 percent of the average dollar ticket price. Research limitations/implications The valuations in the paper were based on ex post data that would not be available to the customer purchaser. Nonetheless, the airline carriers that sell the insurance would have better estimates of the price volatility and therefore could price the contracts to make a profit. Practical implications Airline passengers would have an opportunity to reduce the ticket price risk they face when buying their tickets. Airline carrier could increase revenues by offering such products. Social implications The opportunity to manage price risk contributes to the completeness of markets. Originality/value The paper shows that airfare price insurance contracts are a viable tool in the management of price risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it