Results 61 to 70 of about 14,449,980 (201)

Heteroscedasticity effects as component to future stock market predictions using RNN-based models.

PLoS ONE
Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility is a
Aida Nabilah Sadon, Shuhaida Ismail, Azme Khamis, Muhammad Usman Tariq   +3 more
doaj   +1 more source

Multimodality in the GARCH Regression Model [PDF]

Several aspects of GARCH(p,q) models that are relevant for empirical applications are investigated. In particular, it is noted that the inclusion of dummy variables as regressors can lead to multimodality in the GARCH likelihood.
Jurgen A. Doornik, Marius Ooms
core  

A Range-Based GARCH Model for Forecasting Volatility [PDF]

A new variant of the ARCH class of models for forecasting the conditional variance, to be called the Generalized AutoRegressive Conditional Heteroskedasticity Parkinson Range (GARCH-PARK-R) Model, is proposed.
Mapa, Dennis S.
core  

On buffered threshold Garch models

Statistica Sinica, 2016
published_or_final_version
LO, PH, Li, G, Yu, PLH, Li, WK
openaire   +3 more sources

Estimation of tail thickness parameters from GJR-GARCH models [PDF]

, 2009
We propose a method of estimating the Pareto tail thickness parameter of the unconditional distribution of a financial time series by exploiting the implications of a GJR-GARCH volatility model.
Iglesias, Emma M., Linton, Oliver, Iglesias Vázquez, Emma   +2 more
core   +1 more source

Research on time series prediction method of gas data on fully mechanized mining face

Gong-kuang zidonghua, 2019
In view of problems of complex algorithm and short prediction step length of existing gas concentration prediction methods based on time series, a time series prediction method of gas data on fully mechanized mining face based on ARIMA+GARCH combination ...
ZHAO Meicheng, HE Anmin, QU Shijia
doaj   +1 more source

Threshold Network GARCH Model

Journal of Time Series Analysis
Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model and its variations have been widely adopted in the study of financial volatilities, while the extension of GARCH‐type models to high‐dimensional data is always difficult because of over‐parameterization and computational complexity. In this article, we propose a multi‐variate GARCH‐
Pan, Yue, Pan, Jiazhu
openaire   +4 more sources

An integer GARCH model for a Poisson process with time-varying zero-inflation. [PDF]

PLoS One, 2023
Ratnayake IP, Samaranayake VA.
europepmc   +1 more source

A multivariate generalized independent factor GARCH model with an application to financial stock returns [PDF]

We propose a new multivariate factor GARCH model, the GICA-GARCH model , where the data are assumed to be generated by a set of independent components (ICs).
Antonio García-Ferrer, Daniel Peña, Ester González-Prieto   +2 more
core  

HERDING BEHAVIOR IN THE INDONESIAN ISLAMIC STOCK MARKET

Journal of Islamic Monetary Economics and Finance, 2019
Indonesia Stock Exchange provides Islamic stocks for Muslim investors who want to invest, with the first Islamic stock index in Indonesia being Jakarta Islamic Index or JII that consists of thirty of the most liquid Islamic stocks.
Nora Amelda Rizal, Mirta Kartika Damayanti   +1 more
doaj   +1 more source