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N-tuple S&P patterns across decades, 1950–2011

Listed author(s):
  • A. Malliaris

    ()

  • Mary Malliaris

    ()

Numerous studies have analyzed the movements of the S&P 500 index using several methodologies such as technical analysis, econometric modeling, time series techniques and theories from behavioral finance. In this paper we take a novel approach. We use daily closing prices for the S&P 500 index for a very long period from 1/3/1950 to 7/19/2011 for a total of 15,488 daily observations. We then investigate the up and down movements and their combinations for 1–7 days giving us multiple possible patterns for over six decades. Some patterns of each type are more dominant across decades. We split the data into training and validation sets and then select the dominant patterns to build conditional forecasts in several ways, including using a decision tree methodology. The best model is correct 51 % of the time on the validation set when forecasting a down day, and 61 % when forecasting an up day. We show that certain conditional forecasts outperform the unconditional random walk model. Copyright Springer-Verlag Berlin Heidelberg 2014

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File URL: http://hdl.handle.net/10.1007/s10100-013-0298-3
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Article provided by Springer & Slovak Society for Operations Research & Hungarian Operational Research Society & Czech Society for Operations Research & Österr. Gesellschaft für Operations Research (ÖGOR) & Slovenian Society Informatika - Section for Operational Research & Croatian Operational Research Society in its journal Central European Journal of Operations Research.

Volume (Year): 22 (2014)
Issue (Month): 2 (June)
Pages: 339-353

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Handle: RePEc:spr:cejnor:v:22:y:2014:i:2:p:339-353
DOI: 10.1007/s10100-013-0298-3
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  1. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-482, May.
  2. Chan, Kalok & Chan, K C & Karolyi, G Andrew, 1991. "Intraday Volatility in the Stock Index and Stock Index Futures Markets," Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 657-684.
  3. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
  4. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
  5. De Long, J. Bradford & Shleifer, Andrei & Summers, Lawrence H. & Waldmann, Robert J., 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Scholarly Articles 27693805, Harvard University Department of Economics.
  6. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tuebingen Working Papers in Economics and Finance 24, University of Tuebingen, Faculty of Economics and Social Sciences.
  7. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
  8. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
  9. McInish, Thomas H & Wood, Robert A, 1992. " An Analysis of Intraday Patterns in Bid/Ask Spreads for NYSE Stocks," Journal of Finance, American Finance Association, vol. 47(2), pages 753-764, June.
  10. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
  11. Culter, D.M. & Poterba, J.M. & Summers, L.H., 1990. "Speculative Dynamics," Working papers 544, Massachusetts Institute of Technology (MIT), Department of Economics.
  12. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, 08.
  13. Nicholas Barberis & Andrei Shleifer & Robert W. Vishny, 1997. "A Model of Investor Sentiment," NBER Working Papers 5926, National Bureau of Economic Research, Inc.
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