Pricing weather derivatives and managing weather risks under regime switching
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Accepted by: Aris Syntetos A large number of empirical studies have shown that regime switching is an important characteristic of temperature processes. Thus, this work develops an efficient finite difference scheme with one-sided difference to price weather derivatives with the partial differential equations (PDEs) of regime-switching temperature models. For management purposes, an initial management model framework is then proposed to manage portfolios incorporating weather derivatives. This work also performs statistical analysis on the temperature dataset from Toronto, Canada and recalibrates the regime-switching temperature models, as one parameter value is found incorrect in the literature. Numerical experiments indicate that the finite difference scheme is much more competitive than the Monte Carlo simulations and the lattice approaches. The PDEs pricing approach has great potential to be used in practical portfolio management problems involving weather risks.
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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 | 0.000 | 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 | 0.000 |
| 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