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A Long Memory Conditional Variance Model for International Grain Markets

Jin, Hyun Joung - 2008

models, nested in an ARMA(p,q)- FIGARCH(P,D,Q), to capture dependence of grain cash price volatility and compares the …-t density intended to account for fat-tailed properties of the data. We find suitability of the FIGARCH type models under the … student-t distribution and competitiveness of the parsimonious FIGARCH(1,d,0) for modeling long memory volatility. …

Persistent link: https://www.econbiz.de/10009445769

A Long Memory Conditional Variance Model for International Grain Markets

Jin, Hyun Joung - In: Journal of Rural Development/Nongchon-Gyeongje 31 (2008) 2

Persistent link: https://www.econbiz.de/10005536155

Estimating persistence in the volatility of asset returns with signal plus noise models

Caporale, Guglielmo Maria; Gil-Alana, Luis A. - 2010

This paper examines the degree of persistence in the volatility of financial time series using a Long Memory Stochastic Volatility (LMSV) model. Specifically, it employs a Gaussian semiparametric (or local Whittle) estimator of the memory parameter, based on the frequency domain, proposed by...

Persistent link: https://www.econbiz.de/10010271356

Estimating Persistence in the Volatility of Asset Returns with Signal Plus Noise Models

Caporale, Guglielmo Maria; Gil-Alana, Luis A. - DIW Berlin (Deutsches Institut für Wirtschaftsforschung) - 2010

Persistent link: https://www.econbiz.de/10008584359

Estimating persistence in the volatility of asset returns with signal plus noise models

Caporale, Guglielmo Maria; Gil-Alaña, Luis A. - In: International journal of finance & economics : IJFE 17 (2012) 1, pp. 23-30

Persistent link: https://www.econbiz.de/10009507857

Econometric analysis of financial derivatives : an overview

Chang, Chia-Lin; McAleer, Michael - 2014

One of the fastest growing areas in empirical finance, and also one of the least rigorously analyzed, especially from a financial econometrics perspective, is the econometric analysis of financial derivatives, which are typically complicated and difficult to analyze. The purpose of this special...

Persistent link: https://www.econbiz.de/10010465152

Assessing volatility persistence in fractional Heston models with self-exciting jumps

Truchis, Gilles de; Desgraupes, Bernard; Dumitrescu, … - In: Econometric reviews 44 (2025) 3, pp. 275-311

Persistent link: https://www.econbiz.de/10015196602

Do ESG Ratings Reduce the Asymmetry Behavior in Volatility?

Zarafat, Hashem; Liebhardt, Sascha; Eratalay, Mustafa Hakan - In: Journal of Risk and Financial Management 15 (2022) 8, pp. 1-32

apply autoregressive moving average models for the conditional means and GARCH and stochastic volatility models for the …

Persistent link: https://www.econbiz.de/10014332521

Testing for linear autoregressive dynamics under heteroskedasticity

Hafner, Christian M.; Herwartz, Helmut - 1998

the volatility process we assume GARCH, TGARCH and stochastic volatility. The results indicate that standard QML inference …

Persistent link: https://www.econbiz.de/10010310056

Inflation uncertainty revisited: A proposal for robust measurement

Grimme, Christian; Henzel, Steffen; Wieland, Elisabeth - 2011

Any measure of unobserved inflation uncertainty relies on specific assumptions which are most likely not fulfilled completely. This calls into question whether an individual measure delivers a reliable signal. To reduce idiosyncratic measurement error, we propose using common information...

Persistent link: https://www.econbiz.de/10010312179