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A strategy for trading the S&P 500 futures market

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Abstract

A system for trading the S&P 500 futures market is proposed. The system is applied to S&P 500 futures data during the period from September 14, 1987, to September 27, 1999. The system uses a momentum oscillator for generating entry or exit prices. In addition, the system uses another indicator for predicting the direction of the trend. When only the oscillator is used for selecting trades, the system is not, in general, as good as buy-and-hold. However, when the trend indicator is used as a filter, the trading system is, at least, as good as buy-and-hold.

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References

  • Andrews, D. 1991. “Heteroskedasticity and Autocorrelation Consistent Covariant Matrix Estimation.”Econometrica 59: 817–858.

    Article  Google Scholar 

  • J. Beran. 1994.Statistics for Long Memory Process. New York: Chapman and Hall.

    Google Scholar 

  • Henriksson, R. D., and R. C. Merton. 1981. “On Market Timing and Investment Performance: II. Statistical Procedures for Evaluating Forecasting Skills.”Journal of Business 54: 513–533.

    Article  Google Scholar 

  • Hurst, H. E. 1951. “The Long-Term Storage Capacity of Reservoirs.”Transactions of the American Society of Civil Engineers 116: 770–799.

    Google Scholar 

  • Lo, A. W. 1991. “Long-Term Memory in Stock Market Prices.”Econometrica 59: 1279–1313.

    Article  Google Scholar 

  • Mandelbrot, B. B., and J. R. Wallis. 1969. “Computer Experiments with Fractional Gaussian Noises: Part 1. Averages and Variances.”Water Resources Research 5: 229–241.

    Google Scholar 

  • Mandelbrot, B. B., and J. R. Wallis. 1969. “Computer Experiments with Fractional Gaussian Noises: Part 1. Mathematical Appendix.”Water Resources Research 5: 260.

    Google Scholar 

  • Mandelbrot, B. B., and J. R. Wallis. 1969. “Computer Experiments with Fractional Gaussian Noises: Part 2. Rescaled Ranges and Spectra.”Water Resources Research 5: 260–267.

    Google Scholar 

  • Mandelbrot, B. B., and J. W. Van Ness. 1968. “Fractional Brownian Motions, Fractional Noises and Applications.”SIAM Review 10: 422–437.

    Article  Google Scholar 

  • Merton, R. C. 1981. “On Market Timing and Investment Performance: An Equilibrium Theory of Value for Market Forecasts.”Journal of Business 54: 363–406.

    Article  Google Scholar 

  • Murphy, J. J. 1986.Technical Analysis of the Futures Markets. New York Institute of Finance, New York, NY 10270.

    Google Scholar 

  • Olszewski, E. A.. 1998. “Assessing inefficiency in the futures markets.”The Journal of Futures Markets 18(6): 671–704.

    Article  Google Scholar 

  • Parkinson, M. 1980. “The extreme value method for estimating the variance of the rate of return.Journal of Business 53(1): 61–65.

    Article  Google Scholar 

  • Peters, E. E. 1994.Fractal Market Analysis. New York: John Wiley and Sons, Inc.

    Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Physics, University of North Carolina at Wilmington, 28403, Wilmington, NC

    Edward Olszewski

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  1. Edward Olszewski
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Correspondence to Edward Olszewski.

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Olszewski, E. A strategy for trading the S&P 500 futures market. J Econ Finan 25, 62–79 (2001). https://doi.org/10.1007/BF02759687

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  • DOI: https://doi.org/10.1007/BF02759687

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