Quantile LASSO with changepoints in panel data models applied to option pricing

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Quantile LASSO with changepoints in panel data models applied to option pricing

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Quantile LASSO with changepoints in panel data models applied to option pricing

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GJ18-00522Y" target="_blank" >GJ18-00522Y: Pokročilé Ekonometrické Modely pro Oceňování Opcí – AdEMOP</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Econometrics and Statistics [online]

ISSN

2452-3062

e-ISSN

—

Svazek periodika

Neuveden

Číslo periodika v rámci svazku

01

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

1-10

Kód UT WoS článku

000689351000011

EID výsledku v databázi Scopus

2-s2.0-85078186125