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10 results for “GARCH models”
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Research ArticleOpen accessPhrase in the titleA Study on the Behavior of Volatility in Saudi Arabia Stock Market Using Symmetric and Asymmetric GARCH ModelsAjab Al Freedi, Ahmed Shamiri, Zaidi IsaProblem statement: This study examines several stylized facts (heavy-tailedness, leverage effect and persistence) in volatility of stock price returns exploiting symmetric and asymmetric GARCH family models for Saudi Arabia. Approach: This study is carried out using closing stock market prices over 15 years covering the period 1 January 1994 to 31 March 2009. The sample period is divided into three … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 7 Feb 2012 · 7,577 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleModelling 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
Research ArticleOpen accessIn the keywordsForecasting the Stock Exchange of Thailand uses Day of the Week Effect and Markov Regime Switching GARCHP. Sattayatham, N. Sopipan, B. PremanodeProblem statement: We forecast return and volatility of the Stock Exchange of Thailand (SET) Index. Approach: In this study, we modeled the SET Index returns using mean equation with day of the week effect and autoregressive moving-average. Next we forecast the volatility of the SET Index by using the GARCH-type model and the Markov Regime Switching GARCH (MRS-GARCH) model. Results: … …American Journal of Economics and Business Administration, Vol. 4, Issue 1 · 15 Mar 2012 · 7,865 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSuitability of Volatility Models for Forecasting Stock Market Returns: A Study on the Indian National Stock ExchangeTrilochan Tripathy, Luis A. Gil-AlanaProblem statement: Measuring volatility is an important issue for stock market traders. Also, volatility has been used as a proxy for riskiness associated with the asset. This study aims to compare the different volatility models based on how well they model the volatility of the India NSE. Approach: The study has made use of five models which are Historical/Rolling Window … …American Journal of Applied Sciences, Vol. 7, Issue 11 · 8 Nov 2010 · 7,851 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModeling 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 abstractA Hybrid Artificial Neural Network Model for Option PricingHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiIn the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Aug 2019 · 7,410 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 abstractInvestigation of Socially Responsible Investment Markets (SRI) Using Dynamic Conditional Correlation (DCC) Method: Implications for DiversificationGurudeo Anand Tularam, Eduardo Roca, Victor Siew Howe WongProblem statement: Over the last ten years there has been a phenomenal growth in the amount of funds placed in SRI globally estimated to be around US$6.5 trillion while around US$55 billion in the Australian market. Accurate knowledge of correlation of the Australian SRI market with other SRI markets overseas is crucially important for Australian (SRI) investors for international portfolio … …Journal of Mathematics and Statistics, Vol. 6, Issue 4 · 4 Nov 2010 · 16,234 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 accessAll words, across the recordFORECASTING 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