Abstract
A primary motivation of higher-order asymptotic statistical analysis is to improve the first-order limiting result in accordance with the celebrated Central Limit Theorem in the sense that a better approximation with higher order accuracy can be attained. In this article, several important tools in asymptotic analysis for obtaining higher-order approximations, including Edgeworth expansions, saddle-point approximations and Laplace integral method, will be revisited together with an introduction of some of their applications in finance. A new result on bounds for the difference between American and European calls on small dividend paying stock is also provided. © 2012 Wiley Periodicals, Inc.
| Original language | English |
|---|---|
| Pages (from-to) | 571-587 |
| Journal | Wiley Interdisciplinary Reviews: Computational Statistics |
| Volume | 4 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Nov 2012 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Bayesian asymptotics
- Cornish-Fisher expansion
- Edgeworth approximation
- Laplace integral method
- Option pricing and its bounds
- Saddle-point approximation
- Value-at-risk
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