Joint tails impact in stochastic volatility portfolio selection models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10246252" target="_blank" >RIV/61989100:27510/20:10246252 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s10479-020-03531-w" target="_blank" >https://link.springer.com/article/10.1007/s10479-020-03531-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10479-020-03531-w" target="_blank" >10.1007/s10479-020-03531-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Joint tails impact in stochastic volatility portfolio selection models

Popis výsledku v původním jazyce

This paper examines the impact of the joints tails of the portfolio return and its empirical volatility on the optimal portfolio choices. We assume that the portfolio return and its volatility dynamic is approximated by a bivariate Markov chain constructed on its historical distribution. This allows the introduction of a non parametric stochastic volatility portfolio model without the explicit use of a GARCH type or other parametric stochastic volatility models. We describe the bi-dimensional tree structure of the Markov chain and discuss alternative portfolio strategies based on the maximization of the Sharpe ratio and of a modified Sharpe ratio that takes into account the behaviour of a market benchmark. Finally, we empirically evaluate the impact of the portfolio and its stochastic volatility joint tails on optimal portfolio choices. In particular, we examine and compare the out of sample wealth obtained optimizing the portfolio performances conditioned on the joint tails of the proposed stochastic volatility model.

Název v anglickém jazyce

Joint tails impact in stochastic volatility portfolio selection models

Popis výsledku anglicky

This paper examines the impact of the joints tails of the portfolio return and its empirical volatility on the optimal portfolio choices. We assume that the portfolio return and its volatility dynamic is approximated by a bivariate Markov chain constructed on its historical distribution. This allows the introduction of a non parametric stochastic volatility portfolio model without the explicit use of a GARCH type or other parametric stochastic volatility models. We describe the bi-dimensional tree structure of the Markov chain and discuss alternative portfolio strategies based on the maximization of the Sharpe ratio and of a modified Sharpe ratio that takes into account the behaviour of a market benchmark. Finally, we empirically evaluate the impact of the portfolio and its stochastic volatility joint tails on optimal portfolio choices. In particular, we examine and compare the out of sample wealth obtained optimizing the portfolio performances conditioned on the joint tails of the proposed stochastic volatility model.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA19-11965S" target="_blank" >GA19-11965S: Teorie sítí při problému optimalizace a trackování portfolia</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

Annals of Operations Research

ISSN

0254-5330

e-ISSN

—

Svazek periodika

292

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

16

Strana od-do

833-848

Kód UT WoS článku

000520047700001

EID výsledku v databázi Scopus

2-s2.0-85079726831