Bibliographic record
Abstract
<p>This paper gives a theorem for the continuous time super-replication cost of European options where the stock price follows an exponential L\'{e}vy process.<br />Under a mild assumption on the legend transform of the trading cost function, the limit of the sequence of the discrete super-replication cost is proved to be greater than or equal to an optimal control problem.<br />The main tool is an approximation multinomial scheme based on a discrete grid on a finite time interval [0,1] for a pure jump L\'{e}vy model.<br />This multinomial model is constructed similar to that proposed by (Szimayer {\&amp;} Maller, Stoch. Proce. {\&amp;} Their Appl., 117, 1422-1447, 2007).<br />Furthermore, it is proved that the existence of a liquidity premium for the continuous-time model under a L\'{e}vy process.<br />This paper concentrates on the L\'{e}vy processes with infinitely many jumps in any finite time interval.<br />The approach overcomes some difficulties that can be encountered when the L\'{e}vy process has infinite activity.</p>
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".