NM–QELE for ARMA–GARCH models with non-Gaussian innovations

2011 ◽  
Vol 81 (6) ◽  
pp. 694-703 ◽  
Author(s):  
Jeongcheol Ha ◽  
Taewook Lee
Keyword(s):  
Garch Models ◽  
Non Gaussian

Learning for infinitely divisible GARCH models in option pricing

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Fumin Zhu ◽  
Michele Leonardo Bianchi ◽  
Young Shin Kim ◽  
Frank J. Fabozzi ◽  
Hengyu Wu
Keyword(s):  
Option Pricing ◽  
Stock Returns ◽  
Bayesian Learning ◽  
Space Structure ◽  
Estimation Methods ◽  
Garch Models ◽  
Learning Approaches ◽  
Infinitely Divisible ◽  
Asymmetric Garch ◽  
Non Gaussian

AbstractThis paper studies the option valuation problem of non-Gaussian and asymmetric GARCH models from a state-space structure perspective. Assuming innovations following an infinitely divisible distribution, we apply different estimation methods including filtering and learning approaches. We then investigate the performance in pricing S&P 500 index short-term options after obtaining a proper change of measure. We find that the sequential Bayesian learning approach (SBLA) significantly and robustly decreases the option pricing errors. Our theoretical and empirical findings also suggest that, when stock returns are non-Gaussian distributed, their innovations under the risk-neutral measure may present more non-normality, exhibit higher volatility, and have a stronger leverage effect than under the physical measure.

scholarly journals Quadratic hedging schemes for non-Gaussian GARCH models

2014 ◽  
Vol 42 ◽  
pp. 13-32 ◽  
Author(s):  
Alexandru Badescu ◽  
Robert J. Elliott ◽  
Juan-Pablo Ortega
Keyword(s):  
Garch Models ◽  
Quadratic Hedging ◽  
Non Gaussian

Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

2011 ◽  
Vol 165 (2) ◽  
pp. 246-257 ◽  
Author(s):  
Christian Francq ◽  
Guillaume Lepage ◽  
Jean-Michel Zakoïan
Keyword(s):  
Garch Models ◽  
Two Stage ◽  
Non Gaussian

scholarly journals Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling

2020 ◽  
Vol 527 ◽  
pp. 1-26 ◽  
Author(s):  
Roy Cerqueti ◽  
Massimiliano Giacalone ◽  
Raffaele Mattera
Keyword(s):  
Garch Models ◽  
Non Gaussian
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