Measuring volatility in financial data series

Abstract

This paper analyse relation between expected return and conditional variance, mainly whether it is time-varying or constant (and also linear). It is assumed that for specified period of time investors expect higher returns from assets with higher risk. However there is no agreement whether positive relation between expected returns and variance is 'dynamic'. Investment over short horizons may sometimes be influenced by portfolio balance and transaction cost consideration or by unexpected immediate consumption needs. All these factors may doubtful the risk and return relation in the short horizon. The risk and return relation may also be nonlinear or time varying. The author analyse this relation for 3 assets quoted on the Central Bank of Sri Lanka with the aim to provide additional insight into the nature of return volatility and its relation to expected returns. The GARCH(l,l) models with constant and time varying parameter are implemented. For most assets there are no reasons to reject the hypothesis of no autocorrelation of returns. Observable higher serial correlations in portfolio returns are in agreement with the results of other investigations. According to the estimates of the parameters in the conditional variance, current information remains important for forecasts of the conditional variance for very long horizons.