Seasonalities and cycles in time series: A fresh look with computer experiments
Abstract
Recent advances in the understanding of time series permit to clarify seasonalities and cycles, which might be rather obscure in today's literature. A theorem due to P. Cartier and Y. Perrin, which was published only recently, in 1995, and several time scales yield, perhaps for the first time, a clear-cut definition of seasonalities and cycles. Their detection and their extraction, moreover, become easy to implement. Several computer experiments with concrete data from various fields are presented and discussed. The conclusion suggests the application of this approach to the debatable Kondriatev waves.
Domains
Quantitative Finance [q-fin] Statistical Finance [q-fin.ST] Quantitative Finance [q-fin] Computational Finance [q-fin.CP] Computer Science [cs] Computational Engineering, Finance, and Science [cs.CE] Computer Science [cs] Data Structures and Algorithms [cs.DS] Statistics [stat] Other Statistics [stat.ML] Mathematics [math] Logic [math.LO]
Origin : Files produced by the author(s)
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