Robustness and sensitivity analyses of rough Volterra stochastic volatility models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43968942" target="_blank" >RIV/49777513:23520/23:43968942 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s10436-023-00433-2" target="_blank" >https://doi.org/10.1007/s10436-023-00433-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10436-023-00433-2" target="_blank" >10.1007/s10436-023-00433-2</a>
Alternative languages
Result language
angličtina
Original language name
Robustness and sensitivity analyses of rough Volterra stochastic volatility models
Original language description
In this paper, we analyze the robustness and sensitivity of various continuous-time rough Volterra stochastic volatility models in relation to the process of market calibration. Model robustness is examined from two perspectives: the sensitivity of option price estimates and the sensitivity of parameter estimates to changes in the option data structure. The following sensitivity analysis consists of statistical tests to determine whether a given studied model is sensitive to changes in the option data structure based on the distribution of parameter estimates. Empirical study is performed on a data set consisting of Apple Inc. equity options traded on four different days in April and May 2015. In particular, the results for RFSV, rBergomi and $alpha$RFSV models are provided and compared to the results for Heston, Bates, and AFSVJD models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA18-16680S" target="_blank" >GA18-16680S: Rough models of fractional stochastic volatility</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Annals of Finance
ISSN
1614-2446
e-ISSN
1614-2454
Volume of the periodical
19
Issue of the periodical within the volume
4
Country of publishing house
DE - GERMANY
Number of pages
21
Pages from-to
523-543
UT code for WoS article
001043052400002
EID of the result in the Scopus database
2-s2.0-85166641024