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

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

2008-07-19

arxiv.org/abs/0807.3113v1

Statistics and Probability Letters (2009), 79, pp. 50-54.

Statistics

Methodology

8 pages, 3 figures

Scientific paper

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.

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