Salvato in:
Dettagli Bibliografici
Autori principali: Ballestra, Luca Vincenzo, D'Innocenzo, Enzo, Tezza, Christian
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:https://arxiv.org/abs/2410.14585
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866912076253888512
author Ballestra, Luca Vincenzo
D'Innocenzo, Enzo
Tezza, Christian
author_facet Ballestra, Luca Vincenzo
D'Innocenzo, Enzo
Tezza, Christian
contents We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S\&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices.
format Preprint
id arxiv_https___arxiv_org_abs_2410_14585
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A GARCH model with two volatility components and two driving factors
Ballestra, Luca Vincenzo
D'Innocenzo, Enzo
Tezza, Christian
Econometrics
We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S\&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices.
title A GARCH model with two volatility components and two driving factors
topic Econometrics
url https://arxiv.org/abs/2410.14585