Modeling the persistence in expected returns

The major contribution of this paper is to explicitly model the persistencein the time series of expected returns. The series of expected returnsis derived from a state space representation of the net present value identityrelating expected returns and expected dividend (earnings) growth tothe observed price dividend (earnings) ratio. The state space model isadjusted in order to include the possibility of expected returns followingan autoregressive fractional integrated (ARFIMA) process which capturesthe persistence of the process. The new ARFIMA model performs moderatelycompared to the simple autoregressive process, which may be dueto the presence of different regimes and structural breaks. The expectedreturns series is applied in three instances namely in predictive regressions,analysing the relationship between consumption and discount rates andalso in a market timing strategy.