Symbolic time series analysis and dynamic regimes

In this paper I describe and apply the methods of Symbolic Time Series Analysis (STSA) to an experimental framework. The idea behind Symbolic Time Series Analysis is simple: the values of a given time series data are transformed into a finite set of symbols obtaining a finite string. Then, we can process the symbolic sequence using tools from information theory and symbolic dynamics. I discuss data symbolization as a tool for identifying temporal patterns in experimental data and use symbol sequence statistics in a model strategy. In this application the data symbolization is based on economic criteria using the notion of economic regime.

[1]  Philip Hans Franses,et al.  Modeling Multiple Regimes in the Business Cycle , 1999, Macroeconomic Dynamics.

[2]  James D. Hamilton A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[3]  C. S. Daw,et al.  Symbolic Time-Series Analysis of Engine Combustion Measurements , 1998 .

[4]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[5]  A. Lavezzi Investment-productivity dynamics and distribution dynamics in a multisector economy: some theory and an application to Italian regions , 2003 .

[6]  A. Lavezzi Structural Instability and Unemployment: Evidence from Italian Regions , 2000 .

[7]  C. Finney,et al.  Observing and modeling nonlinear dynamics in an internal combustion engine , 1998 .

[8]  Steven N. Durlauf,et al.  Multiple regimes and cross‐country growth behaviour , 1995 .

[9]  Young,et al.  Inferring statistical complexity. , 1989, Physical review letters.

[10]  G. Weiss TIME-REVERSIBILITY OF LINEAR STOCHASTIC PROCESSES , 1975 .

[11]  Reggie Brown,et al.  Symbol statistics and spatio-temporal systems , 1997 .

[12]  Cees Diks,et al.  Reversibility as a criterion for discriminating time series , 1995 .

[13]  R. Adler,et al.  SYMBOLIC DYNAMICS AND MARKOV PARTITIONS , 1996 .

[14]  N. Packard,et al.  Symbolic dynamics of noisy chaos , 1983 .

[15]  Bernhard Böhm,et al.  Dynamics of Industrial Sectors and Structural Change in the Austrian and Italian Economies, 1970–1989 , 1994 .

[16]  A. Rechester,et al.  Symbolic Analysis of Chaotic Signals and Turbulent Fluctuations , 1997 .

[17]  W. D. Ray,et al.  The Econometric Analysis of Time Series. , 1981 .

[18]  J. Brida Regime Dynamics in a Model of Inflation and Unemployment Fluctuations , 2000 .

[19]  Juan Gabriel Brida,et al.  Coding economic dynamics to represent regime dynamics. A teach-yourself exercise , 2003 .

[20]  L. Punzo Some Complex Dynamics for a Multisectoral Economy ( , 1995 .

[21]  Claude E. Shannon,et al.  The mathematical theory of communication , 1950 .

[22]  Kiminori Matsuyama,et al.  Growing Through Cycles , 1999 .

[23]  Johney B. Green,et al.  Time Irreversibility of Cycle-by-Cycle Engine Combustion Variations , 1999 .

[24]  X. Z. Tang,et al.  Data compression and information retrieval via symbolization. , 1998, Chaos.

[25]  J. Hicks Capital and Time , 1987 .

[26]  Annette Witt,et al.  Analysis of solar spike events by means of symbolic dynamics methods , 1993 .

[27]  Tang,et al.  Symbol sequence statistics in noisy chaotic signal reconstruction. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[28]  Annette Witt,et al.  Measures of complexity in signal analysis , 1996 .

[29]  C. S. Daw,et al.  Time Irreversibility and Comparison of Cyclic-Variability Models , 1999 .

[30]  Reggie Brown,et al.  Reconstruction of chaotic signals using symbolic data , 1994 .

[31]  J. Kurths,et al.  TEST FOR NONLINEAR DYNAMICAL BEHAVIOR IN SYMBOL SEQUENCES , 1998 .