Estimation of multiple time series with volatility. - Ramos, Mark Louie F. (University of the Philippines, 2015)
Abstract (Volatility episodes in a multiple times series exert influence on the parameter estimates that will significantly reduce model fit for the non-volatile parts. Assuming a multiple time series with common autoregressive parameter, a combination of block bootstrap and forward search algorithm embedded into a backfitting algorithm was used to generate robust estimates when temporary volatility is present in the data. Simulation studies exhibited robustness of the estimates from the hybrid during the non-volatile periods of the time series. While predictive ability deteriorates when the time series are very short or when they are nearly non-stationary, it still provides better estimates than some common modeling strategies).