Results 51 to 60 of about 14,449,980 (201)

Examining the Effect of Ramazan and Muharram on the Risk and Return of Mutual Funds in Iran Capital Market [PDF]

تحقیقات مالی, 2017
Risk and return of active mutual funds in Iran capital market. We apply multiple regression analysis, correlogram tests and GARCH model between 2008 – 2014 years to test the data.
Seyed Ali Hosseini, Mohammad Salehifar, Moslem Nilchi   +2 more
doaj   +1 more source

Enhancing the Efficiency of Time Series Forecasting by Hybrid Univariate Box Jenkins–GARCH Models [PDF]

The Egyptian Statistical Journal
Due to the high non-linearity and volatility of the data, financial time series forecasting has been classified as a standard problem. The current study presents a method for modeling stationary, non-stationary, non-linear, and high volatility time ...
Mona Abdel Bary
doaj   +1 more source

Long memory with Markov-Switching GARCH [PDF]

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su?cient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation
Krämer, Walter
core   +2 more sources

Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models

East Asian Economic Review, 2009
We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast.
Hojin Lee
doaj   +1 more source

Estimation and tests for power-transformed and threshold GARCH models [PDF]

, 2008
Consider a class of power transformed and threshold GARCH(p,q) (PTTGRACH(p,q)) model, which is a natural generalization of power-transformed and threshold GARCH(1,1) model in Hwang and Basawa (2004) and includes the standard GARCH model and many other ...
Tong, H., Wang, H., Pan, J.
core   +3 more sources

Stability of Nonlinear Ar-Garch Models [PDF]

Journal of Time Series Analysis, 2006
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model.
MEITZ, Mika, SAIKKONEN, Pentti
openaire   +8 more sources

Asymptotics for Parametric GARCH-in-Mean Models [PDF]

SSRN Electronic Journal, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Conrad, Christian, Mammen , Enno
openaire   +3 more sources

A Mixture Integer-Valued Garch Model

Revstat Statistical Journal, 2016
In this paper, we generalize the mixture integer-valued ARCH model (MINARCH) introduced by Zhu et al. (2010) (F. Zhu, Q. Li, D. Wang. A mixture integer-valued ARCH model, J. Statist. Plann.
Mamadou Lamine Diop , Aliou Diop , Abdou Kâ Diongue   +2 more
doaj   +1 more source

Analysis of Factors Influencing Stock Market Volatility Based on GARCH-MIDAS Model

Complexity, 2022
This paper further extends the existing GARCH-MIDAS model to deal with the effect of microstructure noise in mixed frequency data. This paper has two highlights. First, according to the estimation of the long-term volatility components of the GARCH-MIDAS
Dan Ma, Tianxing Yang, Liping Liu, Yi He
doaj   +1 more source

Assessing Efficiency of D-Vine Copula ARMA-GARCH Method in Value at Risk Forecasting: Evidence from PSE Listed Companies

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2015
The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014.
Václav Klepáč, David Hampel
doaj   +1 more source