From constant to rough: A survey of continuous volatility modeling

Fuente: arXiv
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Autori principali: Di Nunno, Giulia, Kubilius, Kęstutis, Mishura, Yuliya, Yurchenko-Tytarenko, Anton
Natura: Preprint
Pubblicazione: 2023
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author Di Nunno, Giulia
Kubilius, Kęstutis
Mishura, Yuliya
Yurchenko-Tytarenko, Anton
author_facet Di Nunno, Giulia
Kubilius, Kęstutis
Mishura, Yuliya
Yurchenko-Tytarenko, Anton
contents In this paper, we present a comprehensive survey of continuous stochastic volatility models, discussing their historical development and the key stylized facts that have driven the field. Special attention is dedicated to fractional and rough methods: we outline the motivation behind them and characterize some landmark models. In addition, we briefly touch the problem of VIX modeling and recent advances in the SPX-VIX joint calibration puzzle.
format Preprint
id arxiv_https___arxiv_org_abs_2309_01033
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle From constant to rough: A survey of continuous volatility modeling
Di Nunno, Giulia
Kubilius, Kęstutis
Mishura, Yuliya
Yurchenko-Tytarenko, Anton
Mathematical Finance
Probability
91-02, 91-03, 62P05, 60H10, 60G22, 91G15, 91G30, 91G80
In this paper, we present a comprehensive survey of continuous stochastic volatility models, discussing their historical development and the key stylized facts that have driven the field. Special attention is dedicated to fractional and rough methods: we outline the motivation behind them and characterize some landmark models. In addition, we briefly touch the problem of VIX modeling and recent advances in the SPX-VIX joint calibration puzzle.
title From constant to rough: A survey of continuous volatility modeling
topic Mathematical Finance
Probability
91-02, 91-03, 62P05, 60H10, 60G22, 91G15, 91G30, 91G80
url https://arxiv.org/abs/2309.01033