Quantile LASSO with changepoints in panel data models applied to option pricing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10419910" target="_blank" >RIV/00216208:11320/20:10419910 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rISFtsbFWG" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rISFtsbFWG</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecosta.2019.12.005" target="_blank" >10.1016/j.ecosta.2019.12.005</a>
Alternative languages
Result language
angličtina
Original language name
Quantile LASSO with changepoints in panel data models applied to option pricing
Original language description
Panel data are modern statistical tools which are commonly used in all kinds of econometric problems under various regularity assumptions. The panel data models with changepoints are introduced together with the atomic pursuit idea and they are applied to estimate the underlying option price function. Robust estimates and complex insight into the data are both achieved by adopting the quantile LASSO approach. The final model is produced in a fully data-driven manner in just one single modeling step. In addition, the arbitrage-free scenarios are obtained by introducing a set of well defined linear constraints. The final estimate is, under some reasonable assumptions, consistent with respect to the model estimation and the changepoint detection performance. The finite sample properties are investigated in a simulation study and proposed methodology is applied for the Apple call option pricing problem.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GJ18-00522Y" target="_blank" >GJ18-00522Y: Advanced Econometric Models for Option Pricing – AdEMOP</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Econometrics and Statistics [online]
ISSN
2452-3062
e-ISSN
—
Volume of the periodical
Neuveden
Issue of the periodical within the volume
01
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
10
Pages from-to
1-10
UT code for WoS article
000689351000011
EID of the result in the Scopus database
2-s2.0-85078186125