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Estimation and testing in a perturbed multivariate long memory framework

Less, Vivien; Sibbertsen, Philipp - 2022

We propose a semiparametric multivariate estimator and a multivariate score-type testing procedure under a perturbed multivariate fractional process. The estimator is based on the periodogram and uses a local Whittle criterion function which is generalised by an additional constant to capture...

Persistent link: https://www.econbiz.de/10014247836

Long Memory in Stock Returns : An Analysis Using a Wavelet Based Semi-Parametric Estimator

Bhandari, Avishek - 2018

The estimation and the analysis of long memory parameters have mainly focused on the analysis of long-range dependence in stock return volatility using traditional time and spectral domain estimators of long memory. The definitive ubiquity and existence of long memory in the volatility of stock...

Persistent link: https://www.econbiz.de/10012920334

A Coupled Component GARCH Model for Intraday and Overnight Volatility

Linton, Oliver - 2018

We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility that allows the two intraday periods to have different properties. To capture the very heavy tails of overnight returns, a dynamic conditional score model with t innovations is adopted. We propose a...

Persistent link: https://www.econbiz.de/10012928908

A Coupled Component GARCH Model for Intraday and Overnight Volatility

Linton, Oliver - 2016

We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility that allows the two periods to have different properties. To capture the very heavy tails of overnight returns, we adopt a dynamic conditional score model with t innovations. We propose a several...

Persistent link: https://www.econbiz.de/10012978717

Semiparametric Estimation of Markov Decision Processes with Continuous State Space

Srisuma, Sorawoot; Linton, Oliver - 2010

We propose a general two-step estimation method for the structural parameters of popular semiparametric Markovian discrete choice models that include a class of Markovian Games and allow for continuous observable state space. The estimation procedure is simple as it directly generalizes the...

Persistent link: https://www.econbiz.de/10014192735

Nonparametric regression on latent covariates with an application to semiparametric GARCH-in-Mean models

Conrad, Christian; Mammen, Enno - 2008

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

Persistent link: https://www.econbiz.de/10003747376

Robust tests for ARCH in the presence of a misspecified conditional mean : a comparison of nonparametric approaches

Maki, Daiki; Ota, Yasushi - In: Cogent economics & finance 9 (2021) 1, pp. 1-18

This study compares the size and power of autoregressive conditional heteroskedasticity (ARCH) tests that are robust to … the conditional mean: an ARCH test with a Nadaraya-Watson kernel regression and an ARCH test using a polynomial … nonlinear models, which are unknown a priori. The results reveal that the ARCH tests are robust to the misspecfied conditional …

Persistent link: https://www.econbiz.de/10013183738

Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models

Theodossiou, Panayiotis - 2011

This paper discusses three families of flexible parametric probability density functions: the skewed generalized t, the exponential generalized beta of the second kind, and the inverse hyperbolic sin distributions. These families allow quite flexible modeling the first four moments of a...

Persistent link: https://www.econbiz.de/10013132439

Penalized sieve estimation and inference of semi-nonparametric dynamic models : a selective review

Chen, Xiaohong - 2011

In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and some temporal dependence properties. We then...

Persistent link: https://www.econbiz.de/10009230387

Efficient Semi-Parametric Estimation of Non-Gaussian GARCH Processes

Godin, Frédéric - 2016

Semi-parametric estimators for non-Gaussian GARCH processes based on Feasible Weighted Least Squares (FWLS) are proposed. The estimators are consistent and do not require the specification of the innovations distribution family. The FWLS estimators incorporate information related to the skewness...

Persistent link: https://www.econbiz.de/10012978175