MODELING AND FORECASTING THE VOLATILITY OF VIETNAM STOCK MARKET PRICE USING GARCH MODELS

• Main Authors: Le Thi Kim Ngoc, 黎氏金玉
• Other Authors: Song Zan Chiou Wei
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/8233yb

碩士 === 國立高雄應用科技大學 === 製造與管理外國學生碩士專班 === 103 === Volatility in financial markets has gained so much concern by practitioners, and researchers in the past 25 years. Especially, forecasting and modeling is an important issue of research in financial markets. This thesis is to apply Generalized Autogressive Conditional Heteroscedascity model (GARCH), Exponential GARCH (EGARCH), GJR-GARCH model to analysis Vietnam stock market in the last time and modeling a GARCH the volatility of Vietnam stock market daily closing value. After comparing the Root Mean Square Error (RMSE), will choose the best model to predict the conditional variance. This thesis also find clearly what is the main reasons which strongly affected on the volatility of Vietnam stock market index between 2005 and 2015 and from that will have best predicting Vietnam stock market in the future.