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8 results for “EGARCH”
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Research ArticleOpen accessEvery word in the titleAsymmetry Effect of Inflation on Inflation Uncertainty in Iran: Using from EGARCH Model, 1959-2009Dahmardeh Nazar, Pourshahabi Farshid, Khani Zade Amiri MojtabaProblem statement: In this study, we tried to examine the relationship between inflation and inflation uncertainty in Iran, because of considerable variation in its inflation rate. Approach: Inflation uncertainty is the major cost of high inflation that can influence the decision making of economic agents. Results: This study constructed a time series of seasonally inflation uncertainty in Iran from 1959-2009 … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 7,679 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Volatility and Asymmetry of Won/Dollar Exchange RateSeok Yoon, Ki Seong LeeThe study on volatility and asymmetry of the exchange rate by applied to the daily Won/Dollar exchange rate shows that past volatility of the exchange rate still has strong persistency at present and asymmetry effect and the leverage effect, which explain that volatility shock has an effect on the uncertainty of the exchange rate, are also existent after the free … …Journal of Social Sciences, Vol. 4, Issue 1 · 31 Mar 2008 · 8,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelling the Error Term of Australia Gross Domestic ProductAyodele Abraham Agboluaje, Suzilah Ismail, Chee Yin YipThe main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 2 Nov 2016 · 6,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling the Error Term by Moving Average and Generalized Autoregressive Conditional Heteroscedasticity ProcessesAyodele Abraham Agboluaje, Suzilah bt Ismail, Chee Yin YipThis study has been able to reveal that the Combine White Noise model outperforms the existing Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Moving Average (MA) models in modeling the errors, that exhibits conditional heteroscedasticity and leverage effect. MA process cannot model the data that reveals conditional heteroscedasticity and GARCH cannot model the leverage effect also. The standardized residuals of GARCH … …American Journal of Applied Sciences, Vol. 12, Issue 11 · 20 Nov 2015 · 6,721 accessesView PDFCite
Research ArticleOpen accessIn the abstractFORECASTING RETURNS FOR THE STOCK EXCHANGE OF THAILAND INDEX USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop Sopipan, Anchalee Sattayatham, Samruam ChongcharoenThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive Moving-Average order p and q (ARMA (p, q)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Afterwards, we forecast the volatility … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 18 Mar 2013 · 7,438 accessesView PDFCite
Research ArticleOpen accessIn the abstractAre There Smaller Leverage Effects in Less-Developed Markets? Evidence from an Oil Exporting CountryMosayeb Phalavani, Parinaz EzzatiProblem statement: This study uses daily data from the Tehran Stock Market (TSM) to illustrate the nature of stock market volatility in an undeveloped and young stock market. Although most studies suggest that a negative shock to stock prices will generate more volatility than a positive shock of equal magnitude but there is no evidence of asymmetric effect in TSM. … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,519 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling and Forecasting Volatility of the Malaysian Stock MarketsAhmed Shamiri, Zaidi IsaProblem statement: One of the main purposes of modeling variance is forecasting, which is crucial in many areas of finance. Despite the burgeoning interest in and evaluation of volatility forecasts, a clear consensus on witch volatility model/or distribution specification to use has not yet been reached. Therefore, the out of-sample forecasting ability should be a natural model selection criterion for … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 7,900 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using Garch ModelsFrimpong Joseph Magnus, Oteng-Abayie Eric FosuThis paper models and forecasts volatility (conditional variance) on the Ghana Stock Exchange using a random walk (RW), GARCH(1,1), EGARCH(1,1), and TGARCH(1,1) models. The unique ‘three days a week’ Databank Stock Index (DSI) was used to study the dynamics of the Ghana stock market volatility over a 10-year period. The competing volatility models were estimated and their specification and forecast … …American Journal of Applied Sciences, Vol. 3, Issue 10 · 31 Oct 2006 · 7,551 accessesView PDFCite