نتایج جستجو برای: garch family models

تعداد نتایج: 1304725  

2012
Piotr Jaworski Marcin Pitera

We propose a method for defining and measuring the spatial contagion between two financial markets. Next we investigate which from the large family of multivariate GARCH models is the best tool for modeling spatial contagion.

2011
Taufiq Choudhry Mohammed Hasan

This paper investigates the forecasting ability of five different versions of GARCH models. The five GARCH models applied are bivariate GARCH, GARCH-ECM, BEKK GARCH, GARCH-X and GARCH-GJR. Forecast errors based on four emerging stock futures portfolio return (based on forecasted hedge ratio) forecasts are employed to evaluate out-ofsample forecasting ability of the five GARCH models. Daily data...

Journal: :Journal of Economic Dynamics and Control 2015

  In this study we compare a set of Markov Regime-Switching GARCH models in terms of their ability to forecast the Tehran stock market volatility at different time intervals. SW-GARCH models have been used to avoid the excessive persistence that usually found in GARCH models. In SW-GARCH models all parameters are allowed to switch between a low or high volatility regimes. Both Gaussian and fat-...

Journal: :SSRN Electronic Journal 2008

Journal: :Applied sciences 2022

The frequent and sharp fluctuations in garlic prices seriously affect the sustainable development of industry. Accurate prediction can facilitate correct evaluation scientific decision making by practitioners, thereby avoiding market risks promoting healthy To improve accuracy prices, this paper proposes a garlic-price-prediction method based on combination long short-term memory (LSTM) multipl...

2004
Xiong-Fei Zhuang Lai-Wan Chan

Nowadays many researchers use GARCH models to generate volatility forecasts. However, it is well known that volatility persistence, as indicated by the sum of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH models are based on these two parameters, this may lead to poor volatility forecasts. It has long been argued that this high persist...

Journal: :JCP 2012
Yan Gao Chengjun Zhang Liyan Zhang

Since ARCH and GARCH models are presented, more and more authors are interested in the study of volatilities in financial markets with GARCH models. Method for estimating the coefficients of GARCH models is mainly the maximum likelihood estimation. Now we consider another method—MCMC method to substitute for maximum likelihood estimation method. Then we compare three GARCH models based on it. M...

2014
STEVE S. CHUNG Steve S. Chung Kyle Gallivan Wei Wu

The autoregressive conditional heteroskedasticity (ARCH) and generalized autoregressive conditional heteroskedasticity (GARCH) models take the dependency of the conditional second moments. The idea behind ARCH/GARCH model is quite intuitive. For ARCH models, past squared innovations describes the present squared volatility. For GARCH models, both squared innovations and the past squared volatil...

2004
Xiangdong Long

To capture the missed information in the standardized errors by parametric multivariate generalized autoregressive conditional heteroskedasticity (MV-GARCH) model, we propose a new semiparametric MV-GARCH (SM-GARCH) model. This SM-GARCH model is a twostep model: firstly estimating parametric MV-GARCH model, then using nonparametric skills to model the conditional covariance matrix of the standa...

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