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 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".