Estimating Volatility Returns Using ARCH Models. An Empirical Case: The Spanish Energy Market

This paper analyzes the most common regularities of daily stock returns time series in the Spanish Energy Market from an empirical point of view. As they are a powerful tool, we fit a selection of developments of Autoregressive Conditional Heteroscedastic (ARCH) processes to the series in order to model their volatility. The paper finds that just two series have a significant and different relationship between the expected conditional stock return and its own conditional variance: Enagas (negative) and Cepsa (positive). It also finds that the electric market has been the most volatile market during the period under analysis.