Results 181 to 190 of about 13,808,600 (300)

GARCH Diagnosis with Portmanteau Bicorrelation Test: An Application on the Malaysia's Stock Market [PDF]

This study employed the Hinich portmanteau bicorrelation test (Hinich and Patterson, 1995; Hinich, 1996) as a diagnostic tool to determine the adequacy of the GARCH model in describing the returns generating process of Malaysia’s stock market ...
K.P. Lim, M.J. Hinich, K.S. Liew
core  

Robust Estimation and Inference for Time‐Varying Unconditional Volatility

Journal of Time Series Analysis, EarlyView.
ABSTRACT We derive a general and robust estimator of a large class of parametric specifications of time‐varying unconditional volatility of financial returns, both univariate and multivariate, and establish the Consistency and Asymptotic Normality (CAN) of the estimator.
Adam Lee, Rickard Sandberg, Genaro Sucarrat   +2 more
wiley   +1 more source

Selection of the Informative Base in ARMA-GARCH Models [PDF]

In this paper we consider the selection of the information set in ARMA-GARCH models using the methodology proposed in Muñoz et al. (2001) based on ideas of Phillips (1996). To that end, we analyse the performance of some selection criteria asymptotically
Laura Muñoz, Pilar Olave, Manuel Salvador   +2 more
core  

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley   +1 more source

Study of the cross-market effects of Brexit based on the improved symbolic transfer entropy GARCH model-An empirical analysis of stock-bond correlations. [PDF]

PLoS One, 2017
Chen X, Tian Y, Zhao R.
europepmc   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi, Bouchra R. Nasri, Bruno N. Rémillard   +2 more
wiley   +1 more source

Penalized Convex Estimation in Dynamic Location Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley   +1 more source

Moving Aggregate Modified Autoregressive Copula‐Based Time Series Models (MAGMAR‐Copulas)

Journal of Time Series Analysis, EarlyView.
ABSTRACT Copula‐based time series models can model univariate and stationary time series in a flexible way by decomposing the joint distribution of consecutive observations into a copula and the stationary distribution. Implicitly, this approach assumes a finite Markov order. In reality, a time series may not follow the Markov property.
Sven Pappert
wiley   +1 more source

Parametric Time‐Variation in the Unconditional Volatility: Estimation and Inference

Journal of Time Series Analysis, EarlyView.
ABSTRACT We propose modeling time‐variation in the unconditional volatility by augmenting the standard GARCH model by a deterministic time‐varying intercept. The model, called the additive time‐varying (ATV‐)GARCH model, can be interpreted as a reduced form of a model including covariates and can be derived from a multiplicative decomposition of ...
Niklas Ahlgren, Alexander Back, Timo Teräsvirta   +2 more
wiley   +1 more source

Detecting Multiple Change Points in Linear Models With Heteroscedasticity

Journal of Time Series Analysis, EarlyView.
ABSTRACT The problem of detecting change points in the parameters of a linear regression model with errors and covariates exhibiting heteroscedasticity is considered. Asymptotic results for weighted functionals of the cumulative sum (CUSUM) processes of model residuals are established when the model errors are weakly dependent and non‐stationary ...
Lajos Horváth, Gregory Rice, Yuqian Zhao   +2 more
wiley   +1 more source