Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models
Author :
Publisher :
Total Pages :
Release :
ISBN-10 : OCLC:953517389
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models by : Shelton Peiris

Download or read book Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models written by Shelton Peiris and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:


Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models Related Books

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models
Language: en
Pages:
Authors: Shelton Peiris
Categories:
Type: BOOK - Published: 2016 - Publisher:

DOWNLOAD EBOOK

Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory
Language: en
Pages: 27
Authors: Manabu Asai
Categories:
Type: BOOK - Published: 2017 - Publisher:

DOWNLOAD EBOOK

In recent years fractionally differenced processes have received a great deal of attention due to their flexibility in financial applications with long memory.
Parameter Estimation in Stochastic Volatility Models
Language: en
Pages: 634
Authors: Jaya P. N. Bishwal
Categories: Mathematics
Type: BOOK - Published: 2022-08-06 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While
Forecasting Realised Volatility Using a Long Memory Stochastic Volatility Model
Language: en
Pages:
Modeling and Forecasting Long Range Dependence in Volatility
Language: en
Pages: 364
Authors: Nan Qu
Categories:
Type: BOOK - Published: 2010 - Publisher:

DOWNLOAD EBOOK

This thesis conducts three exercises on volatility modeling of financial assets. We are essentially interested in the estimation and forecasting of daily volati