Title
Determining and benchmarking risk neutral distributions implied from option prices Determining and benchmarking risk neutral distributions implied from option prices
Author
Faculty/Department
Faculty of Sciences. Physics
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
New York, N.Y. ,
Subject
Mathematics
Physics
Computer. Automation
Source (journal)
Applied mathematics and computation. - New York, N.Y.
Volume/pages
258(2015) , p. 372-387
ISSN
0096-3003
ISI
000351668500036
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
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.
E-info
https://repository.uantwerpen.be/docman/iruaauth/190004/37c22b5e956.pdf
Full text (open access)
https://repository.uantwerpen.be/docman/irua/55672e/9785.pdf
E-info
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Handle