A note on state space representations of locally stationary wavelet time series

Triantafyllopoulos, K.; Nason, G. P.

A note on state space representations of locally stationary wavelet time series

Authors

Description

In this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which following a moving average process with time-varying parameters. We then show that such moving average processes are equivalent to state space models with stochastic design components. Using a simple simulation step, we propose a heuristic method of estimating the above state space models and then we apply the methodology to foreign exchange rates data.
8 pages, 3 figures