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Let's get LADE : robust estimation of semiparametric multiplicative volatility models
Koo, Bonsoo; Linton, Oliver - 2013
robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …
Persistent link: https://www.econbiz.de/10009719116
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Quasi-maximum likelihood estimation for long memory stock transaction data - under conditional heteroskedasticity framework
Quoreshi, A. M. M. Shahiduzzaman; Uddin, Reaz; Khan, … - In: Journal of risk and financial management : JRFM 12 (2019) 2/74, pp. 1-13
distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that …
Persistent link: https://www.econbiz.de/10012022130
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Conditional Heteroskedasticity in Long Memory Model 'FIMACH' for Return Volatilities in BRICS Equity Markets
Mollah, Sabur - 2015
This paper introduces a new class of long memory model for volatility of stock returns, and applies the model on squared returns for BRICS (Brazil, Russia, India, China, and South Africa) countries. The conditional first- and second-order moments are provided. The CLS, FGLS and QML estimators...
Persistent link: https://www.econbiz.de/10013017294
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A Latent Factor Model of Multivariate Conditional Heteroscedasticity
Aguilar, Mike - 2010
This paper examines the joint dynamics of a system of asset returns by describing and implementing a factor multivariate stochastic volatility (factor MSV) model. The foundation for the model discussed here is the work of Doz and Renault (2006). Despite its attractive design, that model has not...
Persistent link: https://www.econbiz.de/10013150665
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Conditional Heteroskedasticity in Some Common Count Data Models for Financial Time Series Data
Brannas, Kurt - 2002
Persistent link: https://www.econbiz.de/10014107078
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Decomposing portfolio value-at-risk : a general analysis
Hallerbach, Winfried G. - 1999 - This rev.: May 10, 1999
An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...
Persistent link: https://www.econbiz.de/10011301159
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Penalized sieve estimation and inference of semi-nonparametric dynamic models : a selective review
Chen, Xiaohong - 2011
-based inference for plug-in PSE estimation of smooth or non-smooth functionals; and (4) root-n asymptotic normality of semiparametric …, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results. -- Nonlinear time … ; Semiparametric two-step ; Nonlinear ill-posed inverse ; Mixtures ; Conditional moment restrictions ; Nonparametric endogeneity …
Persistent link: https://www.econbiz.de/10009230387
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Adaptive pointwise estimation in time-inhomogeneous time-series models
Čížek, Pavel (contributor); Härdle, Wolfgang (contributor) - 2008
heteroscedasticity models ; local time-homogeneity …
Persistent link: https://www.econbiz.de/10003635965
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Whittle Estimation of Arch Models
Giraitis, Liudas - 2008
For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to be inconsistent and asymptotically normal. Our conditions require the squares to have short memory autocorrelation, by comparison with the work of Zaffaroni (1999), who established the same...
Persistent link: https://www.econbiz.de/10012771050
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Stationarity and Memory of Arch Models
2008
Sufficient conditions for strict stationarity of ARCH(8) are established, without imposing covariance stationarity and for any specification of the conditional second moment coefficients. GARCH(p,q) as well as the case of hyperbolically decaying coefficients are included, such as the...
Persistent link: https://www.econbiz.de/10012771065