Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2013 | 8 | nr 4 | 125--135
Tytuł artykułu

Non Linear Analysis of S&P Index

Treść / Zawartość
Warianty tytułu
Języki publikacji
This paper applies non-linear methods to analyze and predict the daily open S&P index which is one of the most important stock index in the world. The aim of the analysis is to quantitatively show if the corresponding time series is a deterministic chaotic one and if one or more days ahead prediction can be achieved. These results make the present work a valuable tool for traders investors and funds. (original abstract)
Opis fizyczny
  • Kavala Institute of Technology, Greece
  • Kavala Institute of Technology, Greece
  • Kavala Institute of Technology, Greece
  • Abarbanel H.D.I (1996), Analysis of observed chaotic data, Springer, New York.
  • Alexander C. (2002), Market models, John Wiley&Sons Ltd., New York.
  • Alexander C., Giblin I. (1997), Multivariate embedding methods: Forecasting highfrequency data in the INFFC, "Journal of Computational Intelligence in Finance" Vol. 5 No. 6.
  • Coronnello C.M., Tumminello F.L., Micciche S. Mantegna R.N. (2007), Economic Sector Identification in a Set of Stocks Traded at the New York Stock Exchange: A Comparative Analysis, "Noise and Stochastics in Complex Systems and Finance", Vol. 6601.
  • Garas A., Argyrakis P. (2007), Correlation Study of the Athens Stock Exchange, "Physica", Vol. 380.
  • Grassberger P., Procaccia I. ( 1983a), Estimation of the kolmogorov entropy from a chaotic signal, "Physical Review", Vol. 28, No. 4.
  • Grassberger P., Procaccia I. (1983b), Measuring the strangeness of strange attractors, "Physica", Vol. 9.
  • Hanias M.P., Giannaris G., Spyridakis A., Rigas A. (2006), Time series analysis in chaotic diode resonator circuit, "Chaos Solitons and Fractals", Vol. 27, No. 2.
  • Hanias M.P., Magafas L. (2012), DemoscopoPhysics: A New and Interdisciplinary Research Field, "Chaos and Complexity Theory for Management: Nonlinear Dynamics", Vol. 16.
  • Hanias M.P., Curtis G., Thallasinos J.E. (2007), Non-linear dynamics and chaos: The case of the price indicator at the Athens Stock Exchange, "International Research Journal of Finance and Economics", Vol. 11.
  • Hanias M.P., Curtis G., Ozun A. (2008), Chaos theory in predicting the Istanbul Stock Exchange Index, "Empirical Economics Letters", Vol. 7, No. 4.
  • Hanias M.P., Curtis P.G (2008), Time Series Prediction of DollarEuro Exchange Rate Index, "International Research Journal of Finance and Economics", Vol. 15.
  • Kantz H., Schreiber T. (1997), Nonlinear Time Series Analysis, Cambridge University Press, Cambridge.
  • Kodba S., Perc M., Marhl M. (2005), Detecting Chaos from a Time Series, "European Journal of Physics", Vol. 26.
  • Ott E., Sauer T., Yorke J.A. (1994), Coping with chaos, Wiley - Interscience Publication, New York.
  • Ozun A, Hanias M.P., Curtis P.G. (2010), A chaos analysis for Greek and Turkish equity markets, "EuroMed Journal of Business", Vol. 5, No. 1.
  • Peters E.E. (1991), Chaos and order in the capital markets, Wiley Finance Editions, New York.
  • Schouten J.C., Takens F., Bleek C.M. (1994), Estimation of the Dimension of a Noisy Attractor, "Physics Review", Vol. 50, No. 3.
  • Sprott J.C. (2003), Chaos and Time series Analysis, Oxford University Press.
  • Sugihara G., May R.M. (1990), Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series, "Nature", Vol. 344.
  • Takens F. (1981), Detecting strange attractors in turbulence [in:] Rand D. Young L.-S. (eds.), Dynamical Systems and Turbulence, Lecture Notes in Mathematics, Warwick.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.