Date of Award

Spring 1-2014

Document Type


Degree Name

Master of Science in Finance



First Advisor

Dr. John Loughlin

Second Advisor

Dr. Guarango Banerjee

Third Advisor

Dr. Robert Allen


This paper is one of the first research works to examine the stock index volatility in the Mongolian Stock Exchange. The study utilizes the Generalized Autoregressive Conditional Heteroscedasticity (GAR CH) models to estimate volatility of stock market return of the Mongolian Stock Exchange. A number of prior research work demonstrated that ARCH and GARCH models are fruitful models for modeling volatility of time series data. However, they recommend using different versions of GARCH-type models for different distributions (Normal, Student's t, Skewed Student's t and Generalized Error Distribution) for emerging markets or developing markets. This paper compares the GARCH(l, 1) model and EGARCH(l, 1 ), a version of the GAR CH model, in terms of two different conditional distributions of error, normal distribution and student's t distribution by using the daily stock market return from February 2001 to October 2013. Findings show that the EGARCH(l,1) model gives a better explanation than GARCH(l, 1) for the Mongolian Stock Exchange.