Using dynamic mode decomposition to extract cyclic behavior in the stock market

Physica A: Statistical Mechanics and its Applications

Volumn 448, Issue , 2016, Pages 172-180

  Hua, Jia Chen ^a,c   Roy, Sukesh ^b   McCauley, Joseph L ^a   Gunaratne, Gemunu H ^a  

^a University of Houston   (United States)

^b Statistical Research Consultants   (United States)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Business cycle; Complex system; Dynamic mode decomposition; Econophysics; Koopman operator; Stock markets

Indexed keywords

COMMERCE; LARGE SCALE SYSTEMS; STOCHASTIC SYSTEMS;

BUSINESS CYCLES; DYNAMIC MODE DECOMPOSITIONS; ECONOPHYSICSS; INTERVENING PERIOD; KOOPMAN OPERATOR; NATURAL APPROACHES; OSCILLATORY BEHAVIORS; PHASE RELATIONSHIPS;

FINANCIAL MARKETS;

EID: 84954348608     PISSN: 03784371     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.physa.2015.12.059     Document Type: Article

References (29)

1. P.M. Madhani Rebalancing fixed and variable pay in a sales organization: A business cycle perspective Compens. Benefits Rev. 42 2010 179 189
2. J.C.L.S. de Sismondi Nouveaux principes Déconomie Politique, ou De la Richesse dans ses Rapports avec la Population 2 1827 Delaunay Paris
3. C. Juglar Des Crises Commerciales et de leur Retour Periodique en France, en Angleterre, et aux Etats-Unis 1862 Guillaumin Paris
4. M.W. Lee Economic Fluctuations: An Analysis of Business Cycles and Other Economic Fluctuations 1955 R. D. Irwin
5. J. Kitchin Cycles and Trends in Economic Factors Rev. Econ. Stat. 5 1923 10
6. S.S. Kuznets Secular Movements in Production and Prices: Their Nature and their Bearing Upon Cyclical Fluctuations 1967 A. M. Kelley
7. N.D. Kondratieff, and W.F. Stolper The long waves in economic life Rev. Econ. Stat. 17 1935 105
8. J. Poměnková, J. Fidrmuc, I. Korhonen, China and the world economy: Wavelet spectrum analysis of business cycles, Bank of Finland Discussion Papers 5, 2014.
9. S.M. Raihan, Y. Wen, B. Zeng, Wavelet: A new tool for business cycle analysis, Federal Reserve Bank of St. Louis Working Paper Series, 2005.
10. J.L. Lumley The structure of inhomogeneous flow Atmospheric Turbulence and Radio Wave Propagation 1967 Publishing House Nauka Moscow 166 176
11. L. Sirovich Turbulence and the dynamics of Coherent structures. 1. Coherent structures Quart. Appl. Math. 45 1987 561 571
12. L. Sirovich Turbulence and the dynamics of Coherent structures. 2. Symmetries and transformations Quart. Appl. Math. 45 1987 573 582
13. L. Sirovich Turbulence and the dynamics of Coherent structures. 3. Dynamics and scaling Quart. Appl. Math. 45 1987 583 590
14. H. Meng, and et al. Systemic risk and spatiotemporal dynamics of the US housing market Sci. Rep. 4 2014
15. H. Hassani, and D. Thomakos A review on singular spectrum analysis for economic and financial time series Stat. Interface 3 2010 377 397
16. A. Groth, M. Ghil, S. Hallegatte, and P. Dumas Identification and reconstruction of oscillatory modes in US business cycles using multivariate singular spectrum analysis Workshop on Frequency Domain Research in Macroeconomics and Finance 2011 Bank of Finland, Helsinki
17. H. Hassani, A.S. Soofi, and A.A. Zhigljavsky Predicting daily exchange rate with singular spectrum analysis Nonlinear Anal. RWA 11 2010 2023 2034
18. K. Afshar, N. Bigdeli, and H. Shayeghi Singular spectral analysis applied for short term electricity price forecasting Int. J. Tech. Phys. Probl. Eng. 4 2012 32 40
19. F. Wen, J. Xiao, Z. He, and X. Gong Stock Price Prediction based on SSA and SVM Procedia Comput. Sci. 31 2014 625 631
20. M. de Carvalho, P.C. Rodrigues, and A. Rua Tracking the US business cycle with a singular spectrum analysis Econom. Lett. 114 2012 32 35
21. I. Mezic, and A. Banaszuk Comparison of systems with complex behavior Physica D 197 2004 101 133
22. C.W. Rowley, I. Mezic, S. Bagheri, P. Schlatter, and D.S. Henningson Spectral analysis of nonlinear flows J. Fluid Mech. 641 2009 115 127
23. M. Budisic, R. Mohr, and I. Mezic Applied Koopmanism Chaos 22 2012 047510
24. I. Mezic Analysis of fluid flows via spectral properties of the Koopman operator S.H. Davis, P. Moin, Annu. Rev. Fluid Mech. Vol. 45 2013 357 378
25. P.J. Schmid Dynamic mode decomposition of numerical and experimental data J. Fluid Mech. 656 2010 5 28
26. S. Roy, J.-C. Hua, W. Barnhill, G.H. Gunaratne, and J.R. Gord Deconvolution of reacting-flow dynamics using proper orthogonal and dynamic mode decompositions Phys. Rev. E 91 2015 013001
27. K.E. Bassler, J.L. McCauley, and G.H. Gunaratne Nonstationary increments, scaling distributions, and variable diffusion processes in financial markets Proc. Natl. Acad. Sci. USA 104 2007 17287 17290
28. J.-C. Hua, L. Chen, L. Falcon, J.L. McCauley, and G.H. Gunaratne Variable diffusion in stock market fluctuations Physica A 419 2015 221 233
29. C. Heyde, and N. Leonenko Student processes Adv. Appl. Probab. 37 2005 342 365