Bayesian estimation of generalized long-memory stochastic volatility

Bayesian estimation of generalized long-memory stochastic volatility

We propose a Bayesian approach to estimating the parameters of a Generalized Long-Memory Stochastic Volatility (GLMSV) model, a versatile framework designed to address both persistent (long-memory) and seasonal (cyclic) behaviors across various frequencies. This provides an alternative method incorp...

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Bibliographic Details
Main Author: Gonzaga Alex C.
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Subjects:
bayesian estimation
stochastic volatility
generalized long-memory
intraday volatility
microsoft stock prices
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/38/e3sconf_greenenergy2024_04014.pdf

Internet

https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/38/e3sconf_greenenergy2024_04014.pdf

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