On calibration of stochastic and fractional stochastic volatility models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929047" target="_blank" >RIV/49777513:23520/16:43929047 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S0377221716302521" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0377221716302521</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ejor.2016.04.033" target="_blank" >10.1016/j.ejor.2016.04.033</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On calibration of stochastic and fractional stochastic volatility models

Popis výsledku v původním jazyce

In this paper we study optimization techniques for calibration of stochastic volatility models to real market data. Several optimization techniques are compared and used in order to solve the nonlinear least squares problem arising in the minimization of the difference between the observed market prices and the model prices. To compare several approaches we use a popular stochastic volatility model firstly introduced by Heston (1993) and a more complex model with jumps in the underlying and approximative fractional volatility. Calibration procedures are performed on two main data sets that involve traded DAX index options. We show how well both models can be fitted to a given option price surface. The routines alongside models are also compared in terms of out-of-sample errors. For the calibration tasks without having a good knowledge of the market (e.g. a suitable initial model parameters) we suggest an approach of combining local and global optimizers. This way we are able to retrieve superior error measures for all considered tasks and models.

Název v anglickém jazyce

On calibration of stochastic and fractional stochastic volatility models

Popis výsledku anglicky

In this paper we study optimization techniques for calibration of stochastic volatility models to real market data. Several optimization techniques are compared and used in order to solve the nonlinear least squares problem arising in the minimization of the difference between the observed market prices and the model prices. To compare several approaches we use a popular stochastic volatility model firstly introduced by Heston (1993) and a more complex model with jumps in the underlying and approximative fractional volatility. Calibration procedures are performed on two main data sets that involve traded DAX index options. We show how well both models can be fitted to a given option price surface. The routines alongside models are also compared in terms of out-of-sample errors. For the calibration tasks without having a good knowledge of the market (e.g. a suitable initial model parameters) we suggest an approach of combining local and global optimizers. This way we are able to retrieve superior error measures for all considered tasks and models.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

—

Projekt

<a href="/cs/project/GA14-11559S" target="_blank" >GA14-11559S: Analýza frakcionálních modelů stochastické volatility a jejich implementace v gridu</a><br>

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

ISSN

0377-2217

e-ISSN

—

Svazek periodika

254

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

1036-1046

Kód UT WoS článku

000378663000029

EID výsledku v databázi Scopus

2-s2.0-84973557324