Publication
Title
Determining and benchmarking risk neutral distributions implied from option prices
Author
Abstract
Risk neutral probability density functions (RNDs) play a central role in assessing models for stock market behavior. However, it remains challenging to distill a realistic estimate for the RND from empirical data. In this work we introduce a novel method to infer a RND estimate from observed option prices. Our method efficiently yields a realistic rational function approximation to the RND, it is flexible w.r.t. the shape of the underlying distribution and robust in the presence of noise. To show this, we first investigate how well a method can actually retrieve a known distribution from noisy option prices. Then we consider real market data and show how our method can be used to derive a single continuously differentiable RND estimate from empirical call and put option price data.
Language
English
Source (journal)
Applied mathematics and computation. - New York, N.Y.
Publication
New York, N.Y. : 2015
ISSN
0096-3003
Volume/pages
258(2015), p. 372-387
ISI
000351668500036
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 01.04.2015
Last edited 22.07.2017
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