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Markov Switching Beta-skewed-t EGARCH
2019This study extends the work of Harvey and Sucarrat [15] and present Markov regime-switching (MS) Beta-skewed-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model to predict the volatility. To examine the performance of our model, in-sample point forecast precision and AIC and BIC weights are conducted.
Woraphon Yamaka +2 more
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A realized EGARCH-MIDAS model with higher moments
Finance Research Letters, 2021Abstract This paper proposes a realized EGARCH-MIDAS model with higher moments (REGARCH-MIDAS-SK) which combines the REGARCH-MIDAS model by Borup and Jakobsen (2019) and the REGARCH-SK model by Wu et al. (2019) to model volatility. A key feature of the proposed model is the ability to account for the high persistence of volatility and the time ...
Xinyu Wu, Haibin Xie
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Pricing-to-Market Using EGARCH-Error Correction Model
International Journal of Strategic Decision Sciences, 2012In this paper, the authors use an exponential generalized autoregressive conditional heteroscedastic (EGARCH) error-correction model (ECM), that is, EGARCH-ECM, to estimate the pass-through effects of foreign exchange (FX) rates and producers’ prices for 20 U.K. export sectors.
Baoying Lai, Nathan Lael Joseph
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VAD Based on Kernel Smoothed Function of EGARCH Models
Wireless Personal Communications, 2013An algorithm for a voice activity detector (VAD) is proposed. It is based on the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) filter for generalized hyperbolic (GH), Gaussian random variables, adaptive threshold values and autocorrelation coefficients.
Usoph Hamdi Salemi +2 more
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Financial Contagion in South Asia: An EGARCH Approach
SSRN Electronic Journal, 2013This study examines financial contagion in stock markets of India, Sri Lanka and Pakistan during various financial crises. These markets represent a significant part of South Asian economies; therefore, the results obtained can be generalized to the region. The paper employs an Exponential GARCH model in an event study approach.
Syed Kashif Saeed +2 more
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Application of EGARCH-GED model in VaR measurement
2010 International Conference on Financial Theory and Engineering, 2010The GARCH model is used in simulating the volatility and VaR of the financial assets. The paper established an EGARCH-GED model to calculate the time varying VaR. Compared the VaR of the EGARCH-GED model and the GARCH model under the normal distribution and T distribution respectively, The paper checked the anticipated VaR in the previous step by ...
Tianjun Yu, Yang Wang
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Risk Measure of Shibor Based on VAR and EGARCH
2008 International Conference on Computer Science and Software Engineering, 2008There is a great significance to research the interest rate risk based on the method of value at risk on the background of Chinapsilas gradual marketization of interest rates. The paper takes the overnight shibor as the target. First, introduce the calculating method for value at risk.
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Model construction and empirical study of ARMA-EGARCH
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009), 2009This paper establishes an ARMA-EGARCH-M model by combining ARMA model with ARCH group models to study securities market volatility appraisal. The results based on examination of measuring indices for forecasting error using mass samples indicate that ARMA-EGARCH-M model surpasses ARCH group models on Shanghai securities market volatility fitting.
Bo Zhang, Zhong-min Yin
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The North American Journal of Economics and Finance, 2020
Abstract This paper investigates the volatility spillover and dynamic conditional correlation between three types of China’s shares including A, B and H-shares with 12 major emerging and developed markets from 2002 to 2017 using EGARCH and multivariate DCC-EGARCH models. Both models found that Chinese equities are more related with their neighbouring
A. Do, R. Powell, J. Yong, A. Singh
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Abstract This paper investigates the volatility spillover and dynamic conditional correlation between three types of China’s shares including A, B and H-shares with 12 major emerging and developed markets from 2002 to 2017 using EGARCH and multivariate DCC-EGARCH models. Both models found that Chinese equities are more related with their neighbouring
A. Do, R. Powell, J. Yong, A. Singh
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Volatility Forecasting With Range-Based EGARCH Models
Journal of Business & Economic Statistics, 2006We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range. Using Standard and Poor's 500 index data for 1983–2004, we demonstrate the importance of a long-memory specification, based on either a two-factor ...
Brandt, Michael W. +1 more
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