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Bootstrap forecast intervals for asymmetric volatilities via EGARCH model
Communications in Statistics - Theory and Methods, 2017 Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore ...
Dong Wan Shin
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Full Bayesian Inference for GARCH and EGARCH Models
Journal of Business & Economic Statistics, 2000A full Bayesian analysis of GARCH and EGARCH models is proposed consisting of parameter estimation, model selection, and volatility prediction. The Bayesian paradigm is implemented via Markov-chain Monte Carlo methodologies. We provide implementation details and illustrations using the General Index of the Athens stock exchange.
Vrontos, Ioannis D. +5 more
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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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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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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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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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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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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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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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