An accurate and efficient numerical method for solving Black-Scholes equation in option pricing
Bibliographic record
Abstract
An efficient and accurate numerical method for solving the well-known Black-Scholes equation in option pricing is presented in this article. The method can be used for cases in which the coefficients in the Black-Scholes equation are time-dependent and no analytic solutions are available. It is an extension to the method by Liao, W. and Zhu, J. (2008 'A new method for solving convection-diffusion equations', Paper presented in the Proceedings of the 11th IEEE International Conference on Computational Science and Engineering, IEEE Computer Society, Los Alamitos, CA, USA, pp.107-114) for solving 1D convection-diffusion equations with constant diffusion and convection coefficients using the fourth-order Pade approximation on a 3-point stencil. The new method can handle equations with variable diffusion and convection coefficients that depend on x² and x, respectively, where x is the independent variable. Numerical examples are presented in the article to demonstrate the accuracy and efficiency of the method.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".