International Money and Stock Market Contingent Claims
Bibliographic record
Abstract
We develop a unified approach with closed-form solutions for pricing bonds, stocks, currencies and their derivatives. The specification assumes a fundamental risk factorrepresented by a stochastic positive definite matrix following a Wishart autoregressive(WAR) process. By assuming a volatility-in-mean specification for the domestic stockreturns and the relative changes of the exchange rates, and a domestic stochastic discountfactor exponential affine with respect to the fundamental risk, it is possible to deriveclosed form solutions for the term structures of interest rates and for the risk neutralprobabilities. In particular:i) The domestic and foreign termstructures are jointly affine and correspond toWishartquadratic term structures, which can ensure the positivity of interest rates;ii) In this framework where the stock price follows a model with stochastic volatilitywe obtain explicit or quasi-explicit formulas for futures and forward contracts, swaps andoptions; this extends results by Heston (1993) and Ball, Roma (1994).
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".