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Let's Fix it : Fixed-b Asymptotics Versus Small-b Asymptotics in Heteroscedasticity and Autocorrelation Robust Inference

Sun, Yixiao - 2010

In the presence of heteroscedasticity and autocorrelation of unknown forms, the covariance matrix of the parameter …

Persistent link: https://www.econbiz.de/10014188747

Efficient estimation in heteroscedastic varying coefficient models

Wei, Chuanhua; Wan, Lijie - In: Econometrics : open access journal 3 (2015) 3, pp. 525-531

This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct...

Persistent link: https://www.econbiz.de/10011297551

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

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

Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models

Casini, Alessandro - 2022

The literature on heteroskedasticity and autocorrelation robust (HAR) inference is extensive but its usefulness relies on stationarity of the relevant process, say Vt, usually a function of the data and estimated model residuals. Yet, a large body of work shows widespread evidence of various...

Persistent link: https://www.econbiz.de/10013293025

Heteroscedastic Analysis in Nonlinear Modeling

Louangrath, Paul - 2013

nonlinear model. At the heart of nonlinear modeling is the concept of heteroscedasticity. Heteroscedasticity refers to the non … presence of heteroscedasticity may cast doubt on the proposed model if the noise from Xt is big; otherwise, it is no cause for … concern. If the model is a good model, the existence of heteroscedasticity among the independent variable would not vitiate …

Persistent link: https://www.econbiz.de/10013076070

A Model for Long Memory Conditional Heteroscedasticity - (Now Published in Annals of Applied Probability, 10 (2000), Pp.1002-1024.)

Giraitis, Liudas - 2008

Persistent link: https://www.econbiz.de/10012771064

Splines for Financial Volatility

Audrino, Francesco; Buhlmann, Peter - 2007

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

Persistent link: https://www.econbiz.de/10014051065

Another Look at Single-Index Models Based on Series Estimation

Dong, Chaohua - 2016

In this paper, a semiparametric single-index model is investigated. The link function is allowed to be unbounded and has unbounded support that answers a pending issue in the literature. Meanwhile, the link function is treated as a point in an infinitely many dimensional function space which...

Persistent link: https://www.econbiz.de/10012980605

Series Estimation for Single-Index Models Under Constraints

Dong, Chaohua - 2018

Persistent link: https://www.econbiz.de/10012923730