Escañuela Romana, Ignacio (2011): Empirical Evidence on the Predictability of Stock Market Cycles: the Behaviour of the Dow Jones Index Industrial Average in the Stock Market Crises of 1929, 1987 and 2007.
This is the latest version of this item.

PDF
MPRA_paper_49226.pdf Download (240kB)  Preview 
Abstract
Based on a deterministic hypothesis, this paper aims to verify the regularity of the stock market cycles and, if this regularity is found, the ability to predict major stock market crises. Harmonic analysis, or Fourier series, is applied in order to, decomposing into sinusoids curves, find the constant periodicities hidden under the series of observed data. Starting from the industrial stock market data in the U.S., considering three periods of similar length of 165 months: 1919:01 to 1932:09, 1977:01 to 1999:09 and 1997:03 to 2010:11, I stand in the moment of maximum growth of the Dow Jones Industrial Average and I check if the most significant hidden periodicities allowed to predict the sharp drop in the index that was coming and the subsequent development. The evidence is inconclusive. A small number of theoretical cycles reasonably explain the stock market evolution. In terms of predictive power, in two cases there is this ability, while not in another. The conclusion reached indicates that, due to the regularity in the data, the application of the a deterministic hypothesis is reasonable. However, it is necessary to perform a deeper analysis of the data to be able to describe and predict major stock market cycles, including crises or large declines in stock market prices.
Item Type:  MPRA Paper 

Original Title:  Empirical Evidence on the Predictability of Stock Market Cycles: the Behaviour of the Dow Jones Index Industrial Average in the Stock Market Crises of 1929, 1987 and 2007. 
English Title:  Empirical Evidence on the Predictability of Stock Market Cycles: the Behaviour of the Dow Jones Index Industrial Average in the Stock Market Crises of 1929, 1987 and 2007. 
Language:  English 
Keywords:  Stock Market; Periodogram; Business Cycles Prediction 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C10  General E  Macroeconomics and Monetary Economics > E3  Prices, Business Fluctuations, and Cycles > E32  Business Fluctuations ; Cycles C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes E  Macroeconomics and Monetary Economics > E3  Prices, Business Fluctuations, and Cycles > E37  Forecasting and Simulation: Models and Applications 
Item ID:  49226 
Depositing User:  Ignacio Escañuela Romana 
Date Deposited:  22. Aug 2013 09:14 
Last Modified:  22. Aug 2013 09:37 
References:  Alcaide Inchausti, A. y Álvarez Vázquez, N. J. (1992), Econometría. Modelos Deterministas y Estocásticos. Teoría, Madrid, Ramón Areces. Álvarez Vázquez, N. J. (1998), Econometría ( Addenda), Madrid, UNED. Álvarez Vázquez, N. J., Rodríguez Ruíz, J. y González Salgueiro, C. (2005), “El Papel de la Inferencia Estocástica en Economía Cuantitativa”, Rect@, Actas 131, pp. 113. Álvarez Vázquez, N. J., Pérez Pascual, P. y Alcaide Arenales, A. (2001), “Consideraciones en torno a las Hipótesis Alternativas de Estacionalidad Fijas o Variables”, Rect@, Actas 91, pp. 113. Bachiller Cacho, A. (1992), “Estimación del Ciclo Bursátil en las Bolsas Española y Americana”, Revista Española de Financiación y Contabilidad, vol. XXII, n. 73, pp. 975992. Brooks, C. y Hinich, M. J. (2006), "Detecting intraday periodicities with application to high frequency exchange rates", Journal Of The Royal Statistical Society Series C, vol. 55, n.2, pp. 241259. Chen, P. (1996), “A RandomWalk of ColorChaos on the TimeFrequency Analysis of S&P Indexes”, Studies in Nonlinear Dynamics and Econometrics, vol.I, n.2, pp. 87103. Fama, E.F. (1965), “The Behavior of StockMarket Prices”, The Journal of Business, vol. 38, n. 1, pp.34105. Fama, E. F. (1970), “Efficient Capital Markets: A Review of Theory and Empirircal Work”, The Journal of Finance, vol. 24, n. 2, pp. 383417. Granger, C.W.J. (1996), “The Typical Spectral Shape of an Economic Variable”, Econometrica, vol. 34, n.1, pp. 150161. Granger, C.W.J. y Morgenstern, O. (1963), “Spectral Analysis of New York Stock Market Prices”, Kyklos, Vol. 16, n. 1, pages 1–27 Hellstrom, T. y Holmstrom, K. (1998), “Predicting the Stock Market”, Technical Report Series ImaTOM199707, Malardalen University, 1998. Houthakker, H. S. (1961), “Systematic and Random Elements in ShortTerm Price Movements”, The American Economic Review, vol. 51, n.2, pp. 164172. Kendall, M. G. , Bradford Hill, A. (1953), “The Analysis of Economic Time Series Part I: Prices”, Journal of the Royal Statistical Society , Series A, vol. 116, n. 1, pp. 1134. LeRoy, S. F. (1973), “Risk Aversion and the Martingale Property of Stock Prices”, International Economic Review, vol. 14, n. 2, pp.436446. Lo, A. W. y Mackinlay, A. C. (1988), “Stock Market Prices do not follow Random Walks: Evidence from a Simple Specification Test”, Review of Financial Studies, vol.1, n.1, pp. 4166. Lucas, R.E. (1978), “Asset Prices in an Exchange Economy”, Econometrica, vol. 46, n. 6, pp. 14291445. Malkiel, B. G. (2003), “The Efficient Market Hypothesis and Its Critics”, CEPS Working Paper n. 91, pp. 147. Mandelbrot, B. (1963), “The variation of Certain Speculative Prices”, The Journal of Business, vol. 36, n. 4, pp. 394419. Marcucci, J. (2005), “Forecasting Stock Market Volatility with RegimeSwitching GARCH Models”, Studies in Nonlinear Dynamics & Econometrics, vol. 9, n. 4, pp. 153, Meyers, D. (1999), “The Discrete Fourier Transform Illusion”, http://www.meyersanalytics.com/publications/dft.pdf. Nagel, E. (1961), The Structure of Science, Nueva York, Harcourt. Osborne, M. F. M. (1959), “Brownian Motion in the Stock Market”, Operations Research, vol. 7, n. 2, pp. 145173. Popper, K. (1963), Conjectures and Refutations: The Growth of Scientific Knowledge, New York, Harper Torchbooks. Samuelson, P.A. (1965), “Proof that properly anticipated prices fluctuate randomly”, Industrial Management Review, vol. 6, n. 2, pp. 4149. Selvam, A.M. (2006), “Spectral Analysis of Dow Jones Index and Comparison with Model Predicted Cycles during 19002005”, http://arxiv.org/abs/physics/0603065v1, pp. 115. Sewell, M. (2011), “Characterization of Financial Time Series”, UCL Department of Computer Science, Research Note RN/11/01, pp. 135. Tirole, J. (1982), “On the Possibility of Speculation under Rational Expectations”, Econometrica, vol. 50, n. 5, 1982, pp. 11631181. TurhanSayan, G., Sayan, S. (2011), “Use of TimeFrequency Representations in the Analysis of Stock Market Data”, cap. 22, pp.429453 in Computational Methods in Decisionmaking, Economics and Finance edited by E. Kontoghiorghes, B. Rustem and S. Siokos, Kluwer Applied Optimization Series (Series Editors: P. Pardalos and D.W. Hearn),Kluwer Academic Publishers, 2002. (chapter in book). Uddin, G.S., Khoda, N. (2009), “An Empirical Examination of Random Walk Hypothesis for Dhaka Stock Exchange: Evidence from Pharmaceutical Sector of Bangladesh”, International Research Journal of finance and Economics, n. 33, pp.87100. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/49226 
Available Versions of this Item

Evidencia empírica sobre la predictibilidad de los ciclos bursátiles: el comportamiento del índice Dow Jones Industrial Average en las crisis bursátiles de 1929, 1987 y 2997. (deposited 04. Sep 2011 09:53)
 Empirical Evidence on the Predictability of Stock Market Cycles: the Behaviour of the Dow Jones Index Industrial Average in the Stock Market Crises of 1929, 1987 and 2007. (deposited 22. Aug 2013 09:14) [Currently Displayed]