Results 71 to 80 of about 989 (203)

Forecasting daily conditional volatility and h-step-ahead short and long Value-at-Risk accuracy: Evidence from financial data

Journal of Finance and Data Science, 2016
In this article we evaluate the daily conditional volatility and h-step-ahead Value at Risk (VaR) forecasting power of three long memory GARCH-type models (FIGARCH, HYGARCH & FIAPARCH).
Samir Mabrouk
doaj   +1 more source

Functional central limit theorems for augmented GARCH(p, q) and FIGARCH processes

, 2017
Augmented GARCH; FIGARCH; Fractional FCLT; Functional central limit ...
이외숙
core   +1 more source

Commonality in the LME aluminium and copper volatility processes through a Figarch lens [PDF]

We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME).
Christopher L. Gilbert, Isabel Figuerola-Ferretti   +1 more
core  

İKİLİ UZUN HAFIZADA ASİMETRİ ETKİSİ: BİST BANKA ÖRNEĞİ

Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2019
Çalışmanın amacı, Türk bankacılık sektör endeksiningetiri ve volatilitesinde ikili uzun hafıza özelliğini ARFIMA-FIGARCH veARFIMA-FIEGARCH modeli ile inceleyerek etkin piyasalar hipotezini testetmektir. Bu amaçla modelde veri seti olarak 2008-2017 dönemi
Harun Kaya, İsmail Çelik
doaj   +1 more source

Testing for long memory in ISE using Arfima-Figarch model and structural break test [PDF]

, 2009
This study examines long memory in Istanbul Stock Exchange (ISE) by using the structural break test in variance and ARFIMA-FIGARCH model. Our findings indicate that long memory does not exist in the equity return; however, it exits in volatility ...
Cevik, Emrah Ismail, Korkmaz, Turhan, Özataç, Nesrin   +2 more
core   +3 more sources

Long term hedging of the Australian All Ordinaries Index using a bivariate error correction FIGARCH model [PDF]

This article compares the performance of bivariate error correction GARCH and FIGARCH models when estimating long term dynamic minimum variance hedge ratios (MVHRs) on the Australian All Ordinaries Index.
Jonathan Dark
core  

PERAMALAN DATA RUNTUN WAKTU DENGAN PEMODELAN ARFIMA-FIGARCH [PDF]

, 2009
Pemodelan Autoregressive Fractional Integrated Moving Average – Fractional Integrated Generalized Autoregressive Conditional Heteroskedastic (ARFIMA-FIGARCH) adalah salah satu model peramalan dimana data time series mempunyai memori jangka panjang dengan
Selvi Affriani, -
core  

基于GARCH类模型的中国股市收益率分析

四川大学学报. 自然科学版, 2012
自二十世纪八十年代以来,金融时间序列的波动群聚性,尖峰厚尾性和长记忆性特征的研究已经成为众多研究的论题,是当今金融风险管理的核心.GARCH类模型是波动群聚性建模中常用的模型.作者在简要介绍金融时间序列波动性的GARCH模型的基础上,运用MATLAB软件包编程,利用FIGARCH模型、NAGARCH模型和EGARCH模型对中国股市波动特征进行建模,并比较了正态分布、Student-t分布、GED分布和偏t分布等四种不同分布特征的FIGARCH、NAGARCH和EGARCH模型对中国股市波动特征的拟合 ...
张琳, 罗杨飞, 唐亚勇
doaj  

Enhancing Forecasting Accuracy in Commodity and Financial Markets: Insights from GARCH and SVR Models

International Journal of Financial Studies
The aim of this study is to enhance the understanding of volatility dynamics in commodity returns, such as gold and cocoa, as well as the financial market index S&P500. It provides a comprehensive overview of each model’s efficacy in capturing volatility
Apostolos Ampountolas
doaj   +1 more source

Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures [PDF]

In this paper we extend the univariate FIGARCH and FIAPARCH models to a bivariate framework. We estimate bivariate error correction FIGARCH and FIAPARCH models between the All Ordinaries Index and its SPI futures using constant correlation and diagonal ...
Jonathan Dark
core