Volatility of Futures Contract in Iran Mercantile Market

Most financial theories are relying on estimation of volatility. Volatility is not directly observable and must be estimated. In this research we investigate the volatility of gold, trading as a futures contract on the Iran Mercantile Exchange (IME) using intraday (high frequency) data from 5 January 2009 to May 2012. This paper uses several models for the calculation of volatility based on range prices. The results show that a simple measure of volatility (defined as the first logarithmic difference between the high and low prices) overestimates the other three measures. Comparing values of RMSE, MSE, MAD and MAPE we find out that Garman-Klass and Rogers-Satchell Models are more accurate estimator of volatility. Keywords: volatility, range-based models, futures contract

Modeling the Dynamics of Correlations Between International Equity Volatility Indices

I show that volatility indices are more volatile than equity indices, and correlation is higher during periods of high market uncertainty. In this thesis, I consider correlation between volatility markets around the world. This thesis introduces a one-factor model to examine the correlations between volatility markets. I show that for markets where there is a higher level of stock market integration, there is a correspondingly higher degree of volatility market integration. My findings suggest that investors’ expectations about future uncertainty are highly integrated. Applying the dynamic conditional correlation model developed by Engle (2002) to 10 volatility indices across different countries, I show that there is a positive and time-varying correlation between all volatility indices and that the correlation with the underlying equity market index is one factor associated with volatility market integration. I document some evidence of regional integration in volatility markets which suggests that macroeconomic factors should be examined further in future research

Modeling the Dynamics of Correlations Between International Equity Volatility Indices

I show that volatility indices are more volatile than equity indices, and correlation is higher during periods of high market uncertainty. In this thesis, I consider correlation between volatility markets around the world. This thesis introduces a one-factor model to examine the correlations between volatility markets. I show that for markets where there is a higher level of stock market integration, there is a correspondingly higher degree of volatility market integration. My findings suggest that investors’ expectations about future uncertainty are highly integrated. Applying the dynamic conditional correlation model developed by Engle (2002) to 10 volatility indices across different countries, I show that there is a positive and time-varying correlation between all volatility indices and that the correlation with the underlying equity market index is one factor associated with volatility market integration. I document some evidence of regional integration in volatility markets which suggests that macroeconomic factors should be examined further in future research