Previous models of monthly CPI inflation time series have focused on possible regime shifts, non-linearities and the feature of long memory. This paper proposes a new time series model, named Adaptive ARFIMA; which appears well suited to describe inflation and potentially other economic time...

A strategy for estimating, ?filtering and forecasting time-varying factor betas is proposed. The approach is based on the multivariate realized regression principle, an omnibus noise ?filter and an adaptive long memory forecasting model. While the multivariate realized regression approach allows...

This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing the intercept to follow a slowly varying...

In the paper a new approach to the modelling of common components in long memory processes is introduced. The approach is based on a two-step procedure relying on Fourier transform methods (firrst step) and principal components analysis (second step), which, differently from previous...

What are the causes of exchange rate volatility? When second moments implications of theories of exchange rates determination are considered, long-term fundamental linkages between macroeconomic and exchange rate volatility can be envisaged. Moreover, as the exchange rate is an important...

We study the time series properties of the Fama-French factor returns volatility processes. Among the original findings of this paper, we point to structural breaks in the volatility of the factors, and strong coincidence between the timing of the breaks in the volatility of the market portfolio...