Non Linear Analysis of S&P Index
DOI:
https://doi.org/10.12775/EQUIL.2013.030Keywords:
exchange rates, time series, chaos theoryAbstract
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.
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References
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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 Dollar\Euro 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.
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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.
