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

By K. Triantafyllopoulos and G.P. Nason


In this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which follows 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.\ud \u

Publisher: Elsevier
Year: 2009
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