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Monte Carlo analysis of methods for extracting risk-neutral densities with affine jump diffusions

Lu, S. (2019) Monte Carlo analysis of methods for extracting risk-neutral densities with affine jump diffusions. Journal of Futures Markets, 39 (12). pp. 1587-1612. (doi:10.1002/fut.22049) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:89962)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1002/fut.22049

Abstract

This article compares several widely used and recently developed methods to extract risk-neutral densities (RNDs) from option prices in terms of estimation accuracy. It shows that the 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. © 2019 Wiley Periodicals, Inc.

Item Type: Article
DOI/Identification number: 10.1002/fut.22049
Uncontrolled keywords: Risk-neutral density, Monte Carlo simulation, Affine jump diffusions
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Shan Lu
Date Deposited: 31 Aug 2021 10:50 UTC
Last Modified: 03 Sep 2021 12:41 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/89962 (The current URI for this page, for reference purposes)
Lu, S.: https://orcid.org/0000-0002-7588-8599
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