Acceso usuarios
David G. McMillan, Mark E. Wohar
Evidence in favour of long memory has recently been questioned by tests that allow for structural breaks. This article tests for periodic breaks in the unconditional variance of stock return data on eight UK sectors, as well as the market index. Using the modified Iterative Cumulative Sum of Squares (ICSS) algorithm, we observe breaks in seven sectors and the index series. The breaks range from two or three for basic materials and industrials, to five and more for financials, technology and the telecoms sector. Hence, the more traditional stocks exhibit fewer breaks than the newer sectors. The implications of such breaks are numerous, in terms of volatility dynamics and forecasting and portfolio management. With respect to volatility dynamics, further analysis reveals that accounting for breaks substantially reduces the degree of persistence over a Generalized Autoregressive Conditional Heteroscedastic (GARCH) model that maintains a constant unconditional variance. Moreover, the mean to which volatility reverts is time varying; as such, failure to account for breaks will lead to severe forecast errors. Regarding portfolio management, there is substantial evidence of sector specific volatility breaks. Hence, estimation of a market model over the whole sample will lead to errors in both the riskiness of individual sectors and the ability to take advantage of possible above market returns.
