This paper examines the performance of alternative models in estimating systematic risk in the oil industry, considering the traditional market model, three time-varying models, and some combination methods of individual models. This study uses the world's top 10 oil firms’ data series to find...

This study looks at the time-varying nature of systematic risk in the Greater China equity markets. The Shanghai and Shenzhen markets both have a low average systematic risk when measured against the world market. The short outbursts in systematic risk for these two markets seem to be directly...

This study looks at the time-varying nature of systematic risk in the Greater China equity markets. The Shanghai and Shenzhen markets both have a low average systematic risk when measured against the world market. The short outbursts in systematic risk for these two markets seem to be directly...

What explains the cross section of expected returns for the 25 size/value Fama-French portfolios? It is found that modelling time-varying betas is important to explain the cross-section of expected returns, as well as to comply with the time series restriction on Jensen-alpha. Support for a...

This paper investigates the time-varying behavior of systematic risk for 18 pan-European sectors. Using weekly data over the period 1987-2005, six different modeling techniques in addition to the standard constant coefficient model are employed: a bivariate t-GARCH(1,1) model, two Kalman filter...

This study estimates the systematic for the listed companies on the Stock Exchange of Mauritius using the capital asset pricing model and the market model. We then correct for thin trading. Finally, the Schwert and Seguin (1990) model is used to estimate the time variation in beta. The results...

This paper investigates the time-varying behavior of systematic risk for eighteen pan-European industry portfolios. Using weekly data over the period 1987-2005, three different modeling techniques in addition to the standard constant coefficient model are employed: a bivariate t- GARCH(1,1)...

This paper investigates the time-varying behavior of systematic risk for eighteen pan-European sectors. Using weekly data over the period 1987- 2005, four different modeling techniques in addition to the standard constant coefficient model are employed: a bivariate t-GARCH(1,1) model, two Kalman...