Yes / This paper compares several widely-used and recently-developed methods to extract
risk-neutral densities (RND) from option prices in terms of estimation accuracy. It
shows that positive convolution approximation method consistently yields the most
accurate RND estimates, and is insensitive to the discreteness of option prices. RND
methods are less likely to produce accurate RND estimates when the underlying process
incorporates jumps and when estimations are performed on sparse data, especially for
short time-to-maturities, though sensitivity to the discreteness of the data differs across
different methods.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/17201 |
| Date | 31 July 2019 |
| Creators | Lu, Shan |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2019 Wiley This is the peer reviewed version of the following article: Lu, S (2019) Monte Carlo analysis of methods for extracting risk-neutral densities with affine jump diffusions. Journal of Futures Markets. 39(12): 1587-1612, which has been published in final form at https://doi.org/10.1002/fut.22049. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
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