Modelling and Forecasting Volatility
Modelling and Forecasting Volatility: An Application of GARCH and SV models
|Author:||Mizanur Rahman Bhuiyan|
|Supervisor:||Dr. Md. Israt Rayhan|
Financial market volatility is an important aspect when setting up strategies related to portfolio management, options pricing and market regulation. It is an important indicator of the dynamic fluctuations in stock prices. An understanding of volatility in stock markets is important for determining the cost of capital and for assessing investment and leverage decisions as volatility is synonymous with risk. A number of previous studies have been devoted to investigate properties of volatility in emerging markets. In attempt to contribute to literature, this study examines stock return volatility in Dhaka stock market. The empirical investigation is conducted
by means of ARIMA,SV model and GARCH models including both symmetric and asymmetric models with a data set of GEN-Index over ten years period from January, 2002 to December, 2011. The findings present the inappropriateness of symmetric GARCH in modelling Dhaka stock return volatility. The results also provide evidence of the superiority of EGARCH(1,2) over the other GARCH models. Also Stochastic Volatility (SV) model is found best among other models. Regarding the forecasting capability, the results favor the EGARCH(1,2) and SV models. The findings are evidenced by six different measures used to evaluate the forecasting accuracy.