Modelling Long-Run Trends and Cycles in Financial Time Series Data
CESifo, Munich, 2008
CESifo Working Paper No. 2330
![](https://cesifo.org/DocImg/cesifo1_wp2330.jpg?c=1689237062)
This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the spectrum is allowed to contain more than a single pole or singularity, occurring at zero and non-zero (cyclical) frequencies. This model is used to analyse four annual time series with a long span, namely dividends, earnings, interest rates and long-term government bond yields. The results indicate that the four series exhibit fractional integration with one or two poles in the spectrum. A forecasting comparison shows that a model with a non-linear trend along with fractional integration outperforms alternative models over long horizons.
Empirical and Theoretical Methods